Friday, September 17, 2010
Friday, September 10, 2010
Recent Articles/Book Review
OPED in Indian Express: 23rd August 2010
http://www.indianexpress.com/news/casting-the-caste-net/663820/
Invited Article in Outlook Magazine: 28th August 2010
http://www.outlookindia.com/article.aspx?266661
Economic and Political Weekly, Book Review
http://beta.epw.in/newsItem/comment/188683/
http://www.indianexpress.com/news/casting-the-caste-net/663820/
Invited Article in Outlook Magazine: 28th August 2010
http://www.outlookindia.com/article.aspx?266661
Economic and Political Weekly, Book Review
http://beta.epw.in/newsItem/comment/188683/
Monday, August 30, 2010
Big League India! Should we Celebrate?
Yes and NO !
The world is jubilant after a recovery, albeit meek, from the global gloom of economic meltdown of 2008-10 rivaling only the depression of the 1930’s. This recovery seems to have occurred by resilient growth in China and India and large bailout and economic restructuring packages offered by the US and European economies. While China has pushed down Japan to take second place next only to the US, India has also found a place in the top ten or trillion dollar economies and poised to take 5th position much before 2030.
India indeed has come a long way to create a niche for itself in the global economic space. The world foresee a demographic advantage that India can harness, given young age structure and a fast and consistent pace of income growth in GDP which is propelling shifts in consumption classes generating huge domestic demand for practically all types of modern goods and services. The markets for such products in the west are close to saturation and at the most meager. The investors world over, look into India as the power house to manufacture and export goods and services at cost effective contracts as well. There is also an expectation that India during the next 20-30 years will continue to provide trained manpower to the firms and business in the western world due to its relatively higher fertility levels and larger young age population.
There are credible predictions of large shifts in consumption behavior from the basic necessities to discretionary items and services. Indians are now being recognized as being the “maharajas of the technological type across the world”! Yet the fallacy of the growing economy gets highlighted only when one looks in to disparities of income. Although as measured by Gini coefficients the disparity of income/ consumption in India is about one half the level of China; it is interesting to watch the income disparities across the emerging markets during the next decade or so especially in India and China.
India produces close to 200 million tons of food grains including pulses and is self-sufficient so far as agricultural output is concerned. Yet one finds extremely high levels of malnutrition amongst the children and even the expectant and lactating mothers in India. The puzzling fact is that the level of malnourishment is even more than a number of countries in Sub-Saharan Africa which is so well known as the poorest part of the world.
The demographic dividends are expected out of labour supply potential that India has over other emerging economics of the world. However, it is also important to note that India’s population will also generates domestic demand in such a way that a substantial labour and skill pool is required to sustain domestic markets thus thrusting a considerable pressure on the global demand for labour either through fewer leaving India for other greener pastures; or though increase in exports of manufactured goods and services.
Both India and China are already facing shortage in a number of high skilled professions. The income growth is fueling air travel, while capital is aplenty to purchase/lease carriers both are facing serious shortage of aircraft pilots. Similarly, physicians, doctors, surgeons will be short of demand in both the economics especially when medical tourism is booming already in India. India so well known in having supplied software engineers all over the world will itself face serious shortage at home. While India is not at the verge of declining workforce as is the case with China; India has huge demerit in having a low educated and unskilled manpower which will be of hardly any use in the growing sectors of the economy. This means it is surely meant to increase wage bills not far from now in which case the labour and wage advantage that India had in the globalizing competitive environment will be lost, thus exposing the economy to risk of stagnation. Growing mismatch between the type of education skilled manpower that these countries have and the demand in the markets by the newly established companies and industries are going to cause a serious challenge within the next decade or so.
The structure of global competitive economy is such that India was the seventh largest in terms of volume of output at the time of its Independence; but in spite of the apparent high growth trajectory it is no where closer to that ranking presently. However, at the beginning of the 21st century the world is taking India seriously, mostly due to the imminent demographic advantage that this country is demonstrating to the world. India has always been a brain trust and exporter of highly educated manpower especially to the western world and to undertake business to countries such as the south-east Asia. Besides, considerable number of skilled (even at lower levels) labour force was attracted towards the west Asian economies right from the 1970s and this trend not yet reversed. While it would be fare that India would made all efforts to ensure that the newly developed production and distribution markets are sustained using the available labour and skills; it would be somewhat over ambitious to say that the Indian labour force will indeed be available to meet the requirement of the outside economies. On the contrary however, a noticeable number of professionals are returning back to India to seek employment in high growth sectors such as the Information Technology, Research and Development in pharmaceuticals and medicine and other high technology sectors. India needs large investments in education and technological training so as to skill growing labour force and meet the expectations at least partially.
India has many puzzles and dualisms: for example the debates over ‘India’ versus ‘Bharat’ or the urban rural divide; the unorganized versus organized workforce; continuance of abject poverty and hunger when the growth rates are best in the world; and issues revolving around social and income poverty. These debates will be explored in the subsequent chunks of articles to follow.
The world is jubilant after a recovery, albeit meek, from the global gloom of economic meltdown of 2008-10 rivaling only the depression of the 1930’s. This recovery seems to have occurred by resilient growth in China and India and large bailout and economic restructuring packages offered by the US and European economies. While China has pushed down Japan to take second place next only to the US, India has also found a place in the top ten or trillion dollar economies and poised to take 5th position much before 2030.
India indeed has come a long way to create a niche for itself in the global economic space. The world foresee a demographic advantage that India can harness, given young age structure and a fast and consistent pace of income growth in GDP which is propelling shifts in consumption classes generating huge domestic demand for practically all types of modern goods and services. The markets for such products in the west are close to saturation and at the most meager. The investors world over, look into India as the power house to manufacture and export goods and services at cost effective contracts as well. There is also an expectation that India during the next 20-30 years will continue to provide trained manpower to the firms and business in the western world due to its relatively higher fertility levels and larger young age population.
There are credible predictions of large shifts in consumption behavior from the basic necessities to discretionary items and services. Indians are now being recognized as being the “maharajas of the technological type across the world”! Yet the fallacy of the growing economy gets highlighted only when one looks in to disparities of income. Although as measured by Gini coefficients the disparity of income/ consumption in India is about one half the level of China; it is interesting to watch the income disparities across the emerging markets during the next decade or so especially in India and China.
India produces close to 200 million tons of food grains including pulses and is self-sufficient so far as agricultural output is concerned. Yet one finds extremely high levels of malnutrition amongst the children and even the expectant and lactating mothers in India. The puzzling fact is that the level of malnourishment is even more than a number of countries in Sub-Saharan Africa which is so well known as the poorest part of the world.
The demographic dividends are expected out of labour supply potential that India has over other emerging economics of the world. However, it is also important to note that India’s population will also generates domestic demand in such a way that a substantial labour and skill pool is required to sustain domestic markets thus thrusting a considerable pressure on the global demand for labour either through fewer leaving India for other greener pastures; or though increase in exports of manufactured goods and services.
Both India and China are already facing shortage in a number of high skilled professions. The income growth is fueling air travel, while capital is aplenty to purchase/lease carriers both are facing serious shortage of aircraft pilots. Similarly, physicians, doctors, surgeons will be short of demand in both the economics especially when medical tourism is booming already in India. India so well known in having supplied software engineers all over the world will itself face serious shortage at home. While India is not at the verge of declining workforce as is the case with China; India has huge demerit in having a low educated and unskilled manpower which will be of hardly any use in the growing sectors of the economy. This means it is surely meant to increase wage bills not far from now in which case the labour and wage advantage that India had in the globalizing competitive environment will be lost, thus exposing the economy to risk of stagnation. Growing mismatch between the type of education skilled manpower that these countries have and the demand in the markets by the newly established companies and industries are going to cause a serious challenge within the next decade or so.
The structure of global competitive economy is such that India was the seventh largest in terms of volume of output at the time of its Independence; but in spite of the apparent high growth trajectory it is no where closer to that ranking presently. However, at the beginning of the 21st century the world is taking India seriously, mostly due to the imminent demographic advantage that this country is demonstrating to the world. India has always been a brain trust and exporter of highly educated manpower especially to the western world and to undertake business to countries such as the south-east Asia. Besides, considerable number of skilled (even at lower levels) labour force was attracted towards the west Asian economies right from the 1970s and this trend not yet reversed. While it would be fare that India would made all efforts to ensure that the newly developed production and distribution markets are sustained using the available labour and skills; it would be somewhat over ambitious to say that the Indian labour force will indeed be available to meet the requirement of the outside economies. On the contrary however, a noticeable number of professionals are returning back to India to seek employment in high growth sectors such as the Information Technology, Research and Development in pharmaceuticals and medicine and other high technology sectors. India needs large investments in education and technological training so as to skill growing labour force and meet the expectations at least partially.
India has many puzzles and dualisms: for example the debates over ‘India’ versus ‘Bharat’ or the urban rural divide; the unorganized versus organized workforce; continuance of abject poverty and hunger when the growth rates are best in the world; and issues revolving around social and income poverty. These debates will be explored in the subsequent chunks of articles to follow.
Four Years after Sachar? Are Muslims better off in India?
An article published in OUTLOOK INDIA Magazine, Special Independice day Issue, 23rd August 2010. http://www.outlookindia.com/article.aspx?266661
The Lamb's Share
It is essential to begin this essay by emphasizing the fact that the minorities including the Muslims maintain aspirations and seek opportunities for development similar to any other community in India. Yet an empirical review suggests Muslims lagging practically in all spheres of development including education, employment, income and assets and so on. There are some efforts from both the centre and state governments to overcome deprivation amongst the Muslims across India, but a quick review of outcomes suggest little improvements. There is a need for durable changes, firstly a recognition that deprivation amongst the minorities /
Muslims exists due to systemic causes which can be set right only through broad based public policy initiatives, not entirely through special purpose vehicles such as the minority/Muslim oriented programs; rather assisting them to strive to access their share within the mainstream line ministries, departments and programs.
India through the 73rd and 74th constitutional amendment has made a strong socio-political statement of its arrival as a matured democracy, championing multi-layer decentralized governance, sharing substantial powers and national pool of resources with the States. Further, the enduring cannons of governance and economic development are grounded in principals of socialism, inclusiveness and secularism and fully conscious of regional imbalance given a large expanse of the Indian nation. India probably is a rare example of pluralism, with multi-dimensional cultural and social groupings, language, race, region and not the least religion; in short rich in diversity.
Like other main communities of India, the Muslims should be able to pursue social, economic and educational aspirations within the frame and support of government provided infrastructure, opportunities and political awakening. Thus one expect ‘diversity’ - the diversity natural to our population should get reflected in the public spheres such as in educational institutions, public and organized sector employment, political system and governance structures at all levels. Yet, in spite of the fact that practically all social, educational and economic spheres of living are governed, regulated and implemented by the States; one would find substantial (often unacceptable level) differences between varied social groups and across states. Such differentials are prominent in spite of special constitutional provisions bestowed upon the minorities since the Independence.
Over 150 million citizens, just about 14% of all Indians profess Islam as their religion and reside across all parts of India. Muslims are the largest (80%) of all identified minorities of India. They reside in substantial numbers and proportions in states such as Assam, West Bengal, Kerala, UP and Bihar, Gujarat, Maharashtra and so on. There are examples and best practices found within India. Consider the states of Kerala, Karnataka, Andhra Pradesh and Tamil Nadu, all have devised policies favoring Muslims at two levels. (a) Along with all others, the Muslims have relatively better access to quality mass education (both elementary and higher level) and employment; and (b) given the history of relative deprivation of the Muslims the state policy have extended the benefit of reservations in a certain measure of fractional-proportions linked to their size and share in population. Such quotas are enabling the Muslim girls and boys to catch up with their peers amongst the Hindus and Christians, both in education and employment. Similar provisions will enable Muslims to participate even in the political spaces; and Andhra Pradesh has made a beginning by promoting a system of ‘co-option’ or ‘nomination’ system to the Mandals (sub-taluka), Zila Parishads and Municipalities/Naga Panchayets (AP Panchayat Act 2006).
Thus maintaining diversity in public spheres is essential. When this does not happen naturally, it has to be made to happen through government intervention. Legislation can be one way; and the mechanism is to remind the government and the institutions that ensuring diversity is their responsibility; the state should have done it in the first place. Diversity can be assured in India by offering incentives/credits to government departments, institutions, universities, panchayats, PSU and so on.
Another mechanism is to provide institutional access to any one of the citizens (including religious minorities) to ensure ‘Equity’ in public sphere. An ‘Equal Opportunity Commission’ will go a long way both to ensure diversity as a key state objective, and it can also function as an institution to enforce redressal.
The national government has made some efforts during the past 3-4 years to address various aspects of Muslim deprivation. Broadly under the revised 15-point programme, a special investment program in about 100 minority (includes substantial Christian and Muslim populations) concentration districts (MCD); exclusive scholarships are announced for the first time to cover minorities both in elementary and higher levels of education. The RBI is consistently sending memos to the public sector banks to increase funding to the applicants from the minorities and so on. However, a review of all the above programs suggest, that the MCD program has not even made presence in many states such as West Bengal, Assam, Bihar, Jharkhand and Gujarat. The overall utilization is less than 20% of the total funds earmarked to this program since inception. Similarly the scholarship program although very popular is able to cover only a fraction of total applicants; and it appears that the public sector banks have not even taken a note of the repeated requests make by the RBI which is a matter to utmost concern.
The larger malice of exclusion has to be fought unitedly by all ‘regular-line departments’ and Ministries at the national and State levels. It also needs collaboration and partnership with civil society and private institutional structures. How will a separate Ministry ensure the implementation of more than 300 programs that aim to alleviate poverty and improve human development which will promote inclusiveness of the excluded, whether they be Scheduled Castes, Scheduled Tribes or Muslims?
In the absence of any time-line, program-specific implementative strategy and clarity with respect to monitoring tools and mechanisms, no results will be forthcoming. It is important to mention that a flat policy of earmarking 15 per cent of budgetary allocations to favor the minorities is not implementable. Rather, the service delivery procedures must use population shares at the “program specified operational levels” such as the district, taluka and block levels so as to ensure maximum coverage and provide a sense of equity. The early euphoria and expectations are dying out. The UPA -1 took many initiatives to dissect and diagnose the problem, and UPA -2 must ensure that inclusive policies are actually implemented before the people at large become disappointed. I only hope this does not lead to frustration.
The Lamb's Share
It is essential to begin this essay by emphasizing the fact that the minorities including the Muslims maintain aspirations and seek opportunities for development similar to any other community in India. Yet an empirical review suggests Muslims lagging practically in all spheres of development including education, employment, income and assets and so on. There are some efforts from both the centre and state governments to overcome deprivation amongst the Muslims across India, but a quick review of outcomes suggest little improvements. There is a need for durable changes, firstly a recognition that deprivation amongst the minorities /
Muslims exists due to systemic causes which can be set right only through broad based public policy initiatives, not entirely through special purpose vehicles such as the minority/Muslim oriented programs; rather assisting them to strive to access their share within the mainstream line ministries, departments and programs.
India through the 73rd and 74th constitutional amendment has made a strong socio-political statement of its arrival as a matured democracy, championing multi-layer decentralized governance, sharing substantial powers and national pool of resources with the States. Further, the enduring cannons of governance and economic development are grounded in principals of socialism, inclusiveness and secularism and fully conscious of regional imbalance given a large expanse of the Indian nation. India probably is a rare example of pluralism, with multi-dimensional cultural and social groupings, language, race, region and not the least religion; in short rich in diversity.
Like other main communities of India, the Muslims should be able to pursue social, economic and educational aspirations within the frame and support of government provided infrastructure, opportunities and political awakening. Thus one expect ‘diversity’ - the diversity natural to our population should get reflected in the public spheres such as in educational institutions, public and organized sector employment, political system and governance structures at all levels. Yet, in spite of the fact that practically all social, educational and economic spheres of living are governed, regulated and implemented by the States; one would find substantial (often unacceptable level) differences between varied social groups and across states. Such differentials are prominent in spite of special constitutional provisions bestowed upon the minorities since the Independence.
Over 150 million citizens, just about 14% of all Indians profess Islam as their religion and reside across all parts of India. Muslims are the largest (80%) of all identified minorities of India. They reside in substantial numbers and proportions in states such as Assam, West Bengal, Kerala, UP and Bihar, Gujarat, Maharashtra and so on. There are examples and best practices found within India. Consider the states of Kerala, Karnataka, Andhra Pradesh and Tamil Nadu, all have devised policies favoring Muslims at two levels. (a) Along with all others, the Muslims have relatively better access to quality mass education (both elementary and higher level) and employment; and (b) given the history of relative deprivation of the Muslims the state policy have extended the benefit of reservations in a certain measure of fractional-proportions linked to their size and share in population. Such quotas are enabling the Muslim girls and boys to catch up with their peers amongst the Hindus and Christians, both in education and employment. Similar provisions will enable Muslims to participate even in the political spaces; and Andhra Pradesh has made a beginning by promoting a system of ‘co-option’ or ‘nomination’ system to the Mandals (sub-taluka), Zila Parishads and Municipalities/Naga Panchayets (AP Panchayat Act 2006).
Thus maintaining diversity in public spheres is essential. When this does not happen naturally, it has to be made to happen through government intervention. Legislation can be one way; and the mechanism is to remind the government and the institutions that ensuring diversity is their responsibility; the state should have done it in the first place. Diversity can be assured in India by offering incentives/credits to government departments, institutions, universities, panchayats, PSU and so on.
Another mechanism is to provide institutional access to any one of the citizens (including religious minorities) to ensure ‘Equity’ in public sphere. An ‘Equal Opportunity Commission’ will go a long way both to ensure diversity as a key state objective, and it can also function as an institution to enforce redressal.
The national government has made some efforts during the past 3-4 years to address various aspects of Muslim deprivation. Broadly under the revised 15-point programme, a special investment program in about 100 minority (includes substantial Christian and Muslim populations) concentration districts (MCD); exclusive scholarships are announced for the first time to cover minorities both in elementary and higher levels of education. The RBI is consistently sending memos to the public sector banks to increase funding to the applicants from the minorities and so on. However, a review of all the above programs suggest, that the MCD program has not even made presence in many states such as West Bengal, Assam, Bihar, Jharkhand and Gujarat. The overall utilization is less than 20% of the total funds earmarked to this program since inception. Similarly the scholarship program although very popular is able to cover only a fraction of total applicants; and it appears that the public sector banks have not even taken a note of the repeated requests make by the RBI which is a matter to utmost concern.
The larger malice of exclusion has to be fought unitedly by all ‘regular-line departments’ and Ministries at the national and State levels. It also needs collaboration and partnership with civil society and private institutional structures. How will a separate Ministry ensure the implementation of more than 300 programs that aim to alleviate poverty and improve human development which will promote inclusiveness of the excluded, whether they be Scheduled Castes, Scheduled Tribes or Muslims?
In the absence of any time-line, program-specific implementative strategy and clarity with respect to monitoring tools and mechanisms, no results will be forthcoming. It is important to mention that a flat policy of earmarking 15 per cent of budgetary allocations to favor the minorities is not implementable. Rather, the service delivery procedures must use population shares at the “program specified operational levels” such as the district, taluka and block levels so as to ensure maximum coverage and provide a sense of equity. The early euphoria and expectations are dying out. The UPA -1 took many initiatives to dissect and diagnose the problem, and UPA -2 must ensure that inclusive policies are actually implemented before the people at large become disappointed. I only hope this does not lead to frustration.
How will Caste Census affect the Muslims in India?
Published as an editorial article in the Indian Express, 23rd August, 2010
http://www.indianexpress.com/news/casting-the-caste-net/663820/
Casting the Caste Net
The GoM under Shri Pranab Mukherjee’s chairmanship has approved collecting Caste information in Census 2011. Although Muslims are considered a casteless community, it is a diverse society and practically all are experiencing deep levels of deprivation in various social, educational and economic facets of life. In the following I discuss alternatives for collecting caste data and also highlight implications to the Muslim community within the context of inclusive development agenda of the UPA government.
Open ended question method: Given a large number of castes and caste like identities in India; whatever ‘caste name’ the informants’ report can be filled-in and codified later. A pre-coded list of castes that enumerators normally carry to ascertain the SC/ST identity will continue; and for all others it can be open ended caste reporting. Such a method will reveal the actual numbers, but from these numbers it is not possible to declare a particular caste as backward or forward. The information on socio, economic and educational indicators which will be collected in the Census 2011may not be adequate to compute the backwardness or forwardness of castes. The Muslim community will participate in this process of data collection of the open ended caste identities along with all other community groups in India. But it appears that such an open method will not be used in the 2011 census operation although the demand of cast collection of data is of this nature.
Matching of reported caste with the pre-coded Caste/Class Lists: As mentioned above the SCs and STs are so identified using a pre-coded list which is matched at the time of census taking itself. Thus, only two coded categories are extracted from the Census which are used to estimate the SCs and STs for any geographic or administrative area. Now since the demand for the caste census has been made mostly by the castes which can be grouped as the OBCs (other backward classes); it is but expected that similar procedure is used to collect the share of OBCs in the 2011 census.
Unlike in case for the SCs/STs for whom the respective lists are being compiled and updated since last six censuses in Independent India; the case for OBCs is to be undertaken for the first time in 2011. The most likely benchmark will be a list of OBCs from the Mandal Commission. It is puzzling to note that as per the Mandal Commission, ‘OBC list’ is considered a ‘class category with little sociological, cultural or economic basis to designate as such. Besides, the OBC list was prepared almost 30 years ago and that too in the absence of any dependable data. The communities were identified using some sketchy data from 1931 census of India and in many cases even by the Mandal Commission’s own view are ‘best guesses’. I am of the opinion that using the OBC list during the 2011 census to identify the size and share of OBC will be highly problematic, and it will make devising inclusive policies difficult both at the national and state level.
The Mandal Commission has guessed the percentages of both the Hindu and non-Hindu OBCs based on assumptions. For example, one notices wide variation in identifying the ‘castes’ and their shares to qualify as OBCs both in State and Central lists. For example, in case of Muslims, while almost all Muslims in Kerala are listed as OBCs, almost none (very small proportion) in West Bengal are listed as such in the Mandal Commission document. About 40% of Muslims are counted as the OBCs in Uttar Pradesh and such OBCs in Karnataka are about 5-7%. The OBC listing for the Muslims for all the respective states is just ‘guestimates’ and are not true estimates. Using such lists will do more harm to the cause of Muslims especially because a large number or proportion of Muslims will be counted as those belonging to the ‘high castes/class’ and therefore will be excluded from any scheme of affirmative action (for example, if government considers implementation of Ranganath Mishra Commission recommendations or other similar inclusive policies).
It could be seen from the statement below that only about 25% of all Hindus are considered as the High Castes or socio-economically better offs; whereas, about 50% of Muslims are classified as High Castes or socio-economically better offs. This is because none from the Muslims are classified under the SCs/STs category and all such Muslims with the SC / ST identity are actually listed as the High Castes/Class which is unacceptable. This is a serious anomaly in estimates of OBCs by Mandal commission in case of Muslim community.
Mandal Commission Caste/Class Classification and Proportions of
Hindus and Muslims in India
Religion SCs+STs OBCs All Others (High Caste/Class)
Hindus 23 52 25
Muslims 0 52 48
Source: Extracts from the Mandal Commission
In view of these facts it is essential that correct estimates with respect to (a) ‘SCs/STs type Muslims’, (b) ‘OBC Muslims’ and (c) ‘all other Muslims’ are undertaken with care and sensitivity. Even if the SC/ST type of Muslims are not so listed due to certain procedural hurdles even when legally and constitutionally appropriate; such Muslims must be listed as OBCs in which case upto 80% of all Muslims will be so classified. Note that, practically all Muslims in India are converts and hardly any original Muslims who migrated from out of erstwhile Indian territory now reside in India. Further, it is historically documented that most of those converted to Islam belong to low castes such as the dalits and the tribes. The ‘Sachar Committee’ (2006) on status of Muslims in India has also clearly revealed the distressing socio-economic and educational conditions of Muslims of India.
I will be almost impossible to prepare a list of Muslim caste/class for classifying them as Muslim-OBCs. Therefore, I suggest that ‘list of exclusion’ can be prepared so as to determine the social forwardness or backwardness of a large section of Muslims in India. Such list of exclusion can be prepared for each state separately after consultations with the state level Muslim intellectuals and religious bodies. Thus, once a list of exclusion is prepared, all other Muslims who do not match with the list of exclusion can be identified as the “Muslim OBCs”.
Given the UPA governments resolve to ensure inclusive development of India, it is necessary a serious anomaly with respect to identification of the Muslims OBCs is removed before the conduct of the 2011 census, lest the discrimination so far faced by the Muslims continue for ever after.
[A rejoinder to this article can be found in this link: http://www.pasmandamuslims.com/2010/08/caste-census-and-indian-muslims_28.html]
http://www.indianexpress.com/news/casting-the-caste-net/663820/
Casting the Caste Net
The GoM under Shri Pranab Mukherjee’s chairmanship has approved collecting Caste information in Census 2011. Although Muslims are considered a casteless community, it is a diverse society and practically all are experiencing deep levels of deprivation in various social, educational and economic facets of life. In the following I discuss alternatives for collecting caste data and also highlight implications to the Muslim community within the context of inclusive development agenda of the UPA government.
Open ended question method: Given a large number of castes and caste like identities in India; whatever ‘caste name’ the informants’ report can be filled-in and codified later. A pre-coded list of castes that enumerators normally carry to ascertain the SC/ST identity will continue; and for all others it can be open ended caste reporting. Such a method will reveal the actual numbers, but from these numbers it is not possible to declare a particular caste as backward or forward. The information on socio, economic and educational indicators which will be collected in the Census 2011may not be adequate to compute the backwardness or forwardness of castes. The Muslim community will participate in this process of data collection of the open ended caste identities along with all other community groups in India. But it appears that such an open method will not be used in the 2011 census operation although the demand of cast collection of data is of this nature.
Matching of reported caste with the pre-coded Caste/Class Lists: As mentioned above the SCs and STs are so identified using a pre-coded list which is matched at the time of census taking itself. Thus, only two coded categories are extracted from the Census which are used to estimate the SCs and STs for any geographic or administrative area. Now since the demand for the caste census has been made mostly by the castes which can be grouped as the OBCs (other backward classes); it is but expected that similar procedure is used to collect the share of OBCs in the 2011 census.
Unlike in case for the SCs/STs for whom the respective lists are being compiled and updated since last six censuses in Independent India; the case for OBCs is to be undertaken for the first time in 2011. The most likely benchmark will be a list of OBCs from the Mandal Commission. It is puzzling to note that as per the Mandal Commission, ‘OBC list’ is considered a ‘class category with little sociological, cultural or economic basis to designate as such. Besides, the OBC list was prepared almost 30 years ago and that too in the absence of any dependable data. The communities were identified using some sketchy data from 1931 census of India and in many cases even by the Mandal Commission’s own view are ‘best guesses’. I am of the opinion that using the OBC list during the 2011 census to identify the size and share of OBC will be highly problematic, and it will make devising inclusive policies difficult both at the national and state level.
The Mandal Commission has guessed the percentages of both the Hindu and non-Hindu OBCs based on assumptions. For example, one notices wide variation in identifying the ‘castes’ and their shares to qualify as OBCs both in State and Central lists. For example, in case of Muslims, while almost all Muslims in Kerala are listed as OBCs, almost none (very small proportion) in West Bengal are listed as such in the Mandal Commission document. About 40% of Muslims are counted as the OBCs in Uttar Pradesh and such OBCs in Karnataka are about 5-7%. The OBC listing for the Muslims for all the respective states is just ‘guestimates’ and are not true estimates. Using such lists will do more harm to the cause of Muslims especially because a large number or proportion of Muslims will be counted as those belonging to the ‘high castes/class’ and therefore will be excluded from any scheme of affirmative action (for example, if government considers implementation of Ranganath Mishra Commission recommendations or other similar inclusive policies).
It could be seen from the statement below that only about 25% of all Hindus are considered as the High Castes or socio-economically better offs; whereas, about 50% of Muslims are classified as High Castes or socio-economically better offs. This is because none from the Muslims are classified under the SCs/STs category and all such Muslims with the SC / ST identity are actually listed as the High Castes/Class which is unacceptable. This is a serious anomaly in estimates of OBCs by Mandal commission in case of Muslim community.
Mandal Commission Caste/Class Classification and Proportions of
Hindus and Muslims in India
Religion SCs+STs OBCs All Others (High Caste/Class)
Hindus 23 52 25
Muslims 0 52 48
Source: Extracts from the Mandal Commission
In view of these facts it is essential that correct estimates with respect to (a) ‘SCs/STs type Muslims’, (b) ‘OBC Muslims’ and (c) ‘all other Muslims’ are undertaken with care and sensitivity. Even if the SC/ST type of Muslims are not so listed due to certain procedural hurdles even when legally and constitutionally appropriate; such Muslims must be listed as OBCs in which case upto 80% of all Muslims will be so classified. Note that, practically all Muslims in India are converts and hardly any original Muslims who migrated from out of erstwhile Indian territory now reside in India. Further, it is historically documented that most of those converted to Islam belong to low castes such as the dalits and the tribes. The ‘Sachar Committee’ (2006) on status of Muslims in India has also clearly revealed the distressing socio-economic and educational conditions of Muslims of India.
I will be almost impossible to prepare a list of Muslim caste/class for classifying them as Muslim-OBCs. Therefore, I suggest that ‘list of exclusion’ can be prepared so as to determine the social forwardness or backwardness of a large section of Muslims in India. Such list of exclusion can be prepared for each state separately after consultations with the state level Muslim intellectuals and religious bodies. Thus, once a list of exclusion is prepared, all other Muslims who do not match with the list of exclusion can be identified as the “Muslim OBCs”.
Given the UPA governments resolve to ensure inclusive development of India, it is necessary a serious anomaly with respect to identification of the Muslims OBCs is removed before the conduct of the 2011 census, lest the discrimination so far faced by the Muslims continue for ever after.
[A rejoinder to this article can be found in this link: http://www.pasmandamuslims.com/2010/08/caste-census-and-indian-muslims_28.html]
Thursday, May 27, 2010
Proposed Caste Census 2011 in India
There is a renewed demand from many corners, especially a segment of political leadership to collect a citizen’s caste affiliation during the 2011 census of India. The GOI in principle has agreed to collect information on caste in 2011 census; but what is not clear is as to what kind of information on caste will be collected; will it be collected during the house listing operation or during the population census. It appears the whole process of ‘upward social mobility’ will get up-side-down to ‘downward social mobility’ or what we can call as Competitive Backwardness. In the following, however, I identify the difficulties in collecting caste data through the ongoing operations relating to census 2011.
1. Operational Difficulties in Collecting Caste in Census 2011:
Census Operation
The census is undertaken in two phases. A house listing operation (Phase 1) precedes the population enumeration (phase 2) usually scheduled during months of February and March of the census years. The house listing for census 2011 is already in progress.
House Listing Operation collects information on SCs & STs (see item 15 in the attached proforma):
Item 15: If SC* (1) or ST* (2) Other (3)
* Note: Scheduled Caste can be only from Hindus, Sikhs and Buddhists and not from other religion. Schedule Tribe can be from any religion.
However, information on Religion is not collected during house listing operations. Since information on the SCs and STs are collected using a list provided by the government as a check list similar arrangement can be made to collect information on other castes but all clubbed in an additional category OBC (other backward classes). There is some logical problem in such an effort as it is the caste identity (not class) which will be used to classify them as ‘Other Backward Class’. Yet this is an easier process to compile OBC information provided there is a checklist of OBC castes provided by government of India.
OPTION 1:
Suggested format of the new Item 15 in the ‘house listing proforma:
if SC* (1) or ST* (2) OBC (3) Other (4)
However, this is not feasible now; due to the fact that the phase 1 or the house listing operation is already on all over India and it is too late to incorporate this information. Further according to news paper announcements, the caste data will be collected as an additional question – “what is your cast”. This question now can be asked only in phase 2 which is known as Population Enumeration Operation undertaken during March-April 2011. Since there is no ready list of OBCs for cross checking during the data collection stage itself, it has to be an open question asked immediacy after the questions on religion (Q. 7), SC (Q.8) and ST (Q.9) as follows:
Phase II : Population Enumeration| February –March 2011
Q. 7: Religion (Write name of the religion in full)
Q. 8: If Scheduled Caste, Write name of the SC from the list supplied
Q .9: If Scheduled Tribe, write name of the ST from the list supplied
OPTION 2:
Proposed Q.10: What is your Caste? _____________________
Such a question will generate a lot of caste reporting exclusive to each state and regions within state. Often the same caste is identified/pronounced and spelled differently and also the same caste has different status in different states. Collating such information subsequent to conclusion of Census will be a herculean effort and can be the basis for controversies. Therefore one needs to be clear and careful as to what kind of caste data have to be collected in Q.10 of the population enumeration proforma using the currently proposed question ‘what is your caste?’.
OPTION 3:
Another option is to consider collecting information only on ‘as to whether the individual belongs to a OBC category? As discussed earlier (see Option 1above) this can be done only if there is an approved list of OBCs provided apriori by Government of India. In the absence of approved OBC list, self-reported categorization will generate huge errors. Since, eliciting OBC information during enumeration will have to be done as an additional question after the question on religion there can be errors due to misreporting and confounding effects. Thus self-reporting of the OBC status will be affected considerably by the religious affiliation. Note that if the OBC information is collected during the house listing such errors would be low as no question on religion precedes. The recent debates on extension of ‘reservation’ benefits to individuals belonging to religions other than Hindus have indeed generated anxiety and also expectations especially amongst the minorities.
2. Possible Contamination of Census Information
India has a long uninterrupted history of undertaking census every 10 years since the late 19th century and certainly a regular pan-Indian census since the Independence. Indian Census is respected across the world for its quality and academic content. A lot of debates and research has fed the number and type of question to be included in the ‘house listing’ and ‘population enumeration’ exercises. It is useful to note that the last time caste information was collected was during census 1931.
Further, the concepts, definitions and questions are standardized in such a way that the inter-censal comparisons are possible. Such comparisons are the basis to evaluate a number of economic, social, educational and work/employment parameters for India and its many states and even districts. Therefore, any addition or alteration and even change in placement of a question, both in the listing and enumeration proforme can cause changes in the quality of data in other words can contaminate census information.
(a) For example, the errors in self-reported SCs/STs and OBCs category can be enormous by boosting the respective population shares which can prompt increase in the quota shares. This can happen because – those not SCs/STs may get motivated to report themselves as such; so will be the case for OBCs. Since the OBC reservation debate is in its peak one can expect an extra caution amongst the OBCs to ensure reporting; while there can also be misreporting thus boosting the share of OBCs in the population. Even communities with no caste identities may innovate or identify a caste for themselves.
(b) Distorted Occupations: It is likely that caste question can affect the reporting of occupations. The possibility is large due to expected gains offered by the government based on caste/occupation linked targeting such as programs for ‘weavers’ and so on. There can many other distortions or contamination of data.
3. What we know about OBC Identity? What can be Done?
‘Mid-Term Census’ (MTC)
There are two types of demands in the recent past with respect to additional data to be collected from the Indian decennial census. (a) The caste data with a focus on identifying correct share of OBCs since the Mandal commission linked reservations are based on old data from 1931 and not so valid local level surveys. (b) Another demand has been to collect information so as to assess the accessibility to the human capital enhancing government investments and provisioning of social services/safety nets.
It is therefore conceived that time is ripe for a ‘Mid-Term Census (MTC)’ say every five years after the main Census which can collected data on caste as well as on social parameters and other qualitative variables. The mega programs such as the MG-NREGA, PDS and ICDS have not been evaluated so as to find out the efficacy of the program and undertake cost benefit estimates. Further delinking such data collection through a MTC will help in keeping the comprehensive nature of the main census that too with no contamination which is essential in inter-censal comparisons. There are many other countries around the world who conduct census with 5 year interval. However, cost considerations will be important aspects in such a decision making, which is not enunciated in this note.
Special Surveys by Independent Agencies / National Sample Surveys
The other possibility is to commission special surveys and improve the scope and coverage of the National Sample Surveys. The current sample size in the NSSO is around two hundred thousand if both the central and state samples are merged. The NSSO in its 55th and 61st round have collected OBC data, so are a few other independent surveys such as the National Council of Applied Economic Research’s (NCAER) human development surveys, and the National Health and Family Surveys. The state specific distribution of population according to broad caste categories are presented in the following table and graphs. One notices a large disparity between states especially Kerala and West Bengal which needs further discussion.
1. Operational Difficulties in Collecting Caste in Census 2011:
Census Operation
The census is undertaken in two phases. A house listing operation (Phase 1) precedes the population enumeration (phase 2) usually scheduled during months of February and March of the census years. The house listing for census 2011 is already in progress.
House Listing Operation collects information on SCs & STs (see item 15 in the attached proforma):
Item 15: If SC* (1) or ST* (2) Other (3)
* Note: Scheduled Caste can be only from Hindus, Sikhs and Buddhists and not from other religion. Schedule Tribe can be from any religion.
However, information on Religion is not collected during house listing operations. Since information on the SCs and STs are collected using a list provided by the government as a check list similar arrangement can be made to collect information on other castes but all clubbed in an additional category OBC (other backward classes). There is some logical problem in such an effort as it is the caste identity (not class) which will be used to classify them as ‘Other Backward Class’. Yet this is an easier process to compile OBC information provided there is a checklist of OBC castes provided by government of India.
OPTION 1:
Suggested format of the new Item 15 in the ‘house listing proforma:
if SC* (1) or ST* (2) OBC (3) Other (4)
However, this is not feasible now; due to the fact that the phase 1 or the house listing operation is already on all over India and it is too late to incorporate this information. Further according to news paper announcements, the caste data will be collected as an additional question – “what is your cast”. This question now can be asked only in phase 2 which is known as Population Enumeration Operation undertaken during March-April 2011. Since there is no ready list of OBCs for cross checking during the data collection stage itself, it has to be an open question asked immediacy after the questions on religion (Q. 7), SC (Q.8) and ST (Q.9) as follows:
Phase II : Population Enumeration| February –March 2011
Q. 7: Religion (Write name of the religion in full)
Q. 8: If Scheduled Caste, Write name of the SC from the list supplied
Q .9: If Scheduled Tribe, write name of the ST from the list supplied
OPTION 2:
Proposed Q.10: What is your Caste? _____________________
Such a question will generate a lot of caste reporting exclusive to each state and regions within state. Often the same caste is identified/pronounced and spelled differently and also the same caste has different status in different states. Collating such information subsequent to conclusion of Census will be a herculean effort and can be the basis for controversies. Therefore one needs to be clear and careful as to what kind of caste data have to be collected in Q.10 of the population enumeration proforma using the currently proposed question ‘what is your caste?’.
OPTION 3:
Another option is to consider collecting information only on ‘as to whether the individual belongs to a OBC category? As discussed earlier (see Option 1above) this can be done only if there is an approved list of OBCs provided apriori by Government of India. In the absence of approved OBC list, self-reported categorization will generate huge errors. Since, eliciting OBC information during enumeration will have to be done as an additional question after the question on religion there can be errors due to misreporting and confounding effects. Thus self-reporting of the OBC status will be affected considerably by the religious affiliation. Note that if the OBC information is collected during the house listing such errors would be low as no question on religion precedes. The recent debates on extension of ‘reservation’ benefits to individuals belonging to religions other than Hindus have indeed generated anxiety and also expectations especially amongst the minorities.
2. Possible Contamination of Census Information
India has a long uninterrupted history of undertaking census every 10 years since the late 19th century and certainly a regular pan-Indian census since the Independence. Indian Census is respected across the world for its quality and academic content. A lot of debates and research has fed the number and type of question to be included in the ‘house listing’ and ‘population enumeration’ exercises. It is useful to note that the last time caste information was collected was during census 1931.
Further, the concepts, definitions and questions are standardized in such a way that the inter-censal comparisons are possible. Such comparisons are the basis to evaluate a number of economic, social, educational and work/employment parameters for India and its many states and even districts. Therefore, any addition or alteration and even change in placement of a question, both in the listing and enumeration proforme can cause changes in the quality of data in other words can contaminate census information.
(a) For example, the errors in self-reported SCs/STs and OBCs category can be enormous by boosting the respective population shares which can prompt increase in the quota shares. This can happen because – those not SCs/STs may get motivated to report themselves as such; so will be the case for OBCs. Since the OBC reservation debate is in its peak one can expect an extra caution amongst the OBCs to ensure reporting; while there can also be misreporting thus boosting the share of OBCs in the population. Even communities with no caste identities may innovate or identify a caste for themselves.
(b) Distorted Occupations: It is likely that caste question can affect the reporting of occupations. The possibility is large due to expected gains offered by the government based on caste/occupation linked targeting such as programs for ‘weavers’ and so on. There can many other distortions or contamination of data.
3. What we know about OBC Identity? What can be Done?
‘Mid-Term Census’ (MTC)
There are two types of demands in the recent past with respect to additional data to be collected from the Indian decennial census. (a) The caste data with a focus on identifying correct share of OBCs since the Mandal commission linked reservations are based on old data from 1931 and not so valid local level surveys. (b) Another demand has been to collect information so as to assess the accessibility to the human capital enhancing government investments and provisioning of social services/safety nets.
It is therefore conceived that time is ripe for a ‘Mid-Term Census (MTC)’ say every five years after the main Census which can collected data on caste as well as on social parameters and other qualitative variables. The mega programs such as the MG-NREGA, PDS and ICDS have not been evaluated so as to find out the efficacy of the program and undertake cost benefit estimates. Further delinking such data collection through a MTC will help in keeping the comprehensive nature of the main census that too with no contamination which is essential in inter-censal comparisons. There are many other countries around the world who conduct census with 5 year interval. However, cost considerations will be important aspects in such a decision making, which is not enunciated in this note.
Special Surveys by Independent Agencies / National Sample Surveys
The other possibility is to commission special surveys and improve the scope and coverage of the National Sample Surveys. The current sample size in the NSSO is around two hundred thousand if both the central and state samples are merged. The NSSO in its 55th and 61st round have collected OBC data, so are a few other independent surveys such as the National Council of Applied Economic Research’s (NCAER) human development surveys, and the National Health and Family Surveys. The state specific distribution of population according to broad caste categories are presented in the following table and graphs. One notices a large disparity between states especially Kerala and West Bengal which needs further discussion.
Ways to accurately estimate the OBCs in India
There is a renewed demand from many corners, especially a segment of political leadership to collect a citizen’s caste affiliation during the 2011 census of India. The GOI in principle has agreed to collect information on caste in 2011 census; but what is not clear is as to what kind of information on caste will be collected; will it be collected during the house listing operation or during the population census.
Operational Difficulties in Collecting Caste in Census 2011: The census is undertaken in two phases. A house listing operation (Phase 1) precedes the population enumeration (phase 2) usually scheduled during months of February and March of the census years. The house listing for census 2011 is already in progress. House Listing Operation collects information on SCs & STs - item 15 in the proforma. Once can expand this question by providing an addition option ‘OBC (3) and changing code of ‘Other’ to (4). Note also that information on Scheduled Caste is collected only from Hindus, Sikhs and Buddhists and not from other religion; whereas Schedule Tribe can be from any religion. Since religion is not collected in this phase the OBC reporting will be free of divergent influences and overall this approach can work if the OBC check list is provided to enumerators in advance. But since the listing operation is already on all over India and it is too to collect caste/OBC information during the house listing operation.
According to news paper reports, it appears, that data on caste will be collected by asking a simple question “what is your cast?” during the census operations. This now can be done only in phase 2 known as Population Enumeration undertaken during March-April 2011. This kind of open question can be asked immediacy after the following questions:
Q. 7: Religion (Write name of the religion in full)
Q. 8: If Scheduled Caste, Write name of the SC from the list supplied
Q .9: If Scheduled Tribe, write name of the ST from the list supplied
Proposed Q.10: What is your Caste? _____________________
Such a question will generate a lot of caste reporting exclusive to each state and regions within state. Often a given caste is identified, pronounced and spelled differently; and sometimes same cast can assume differential status in other states. Collating such information subsequent to conclusion of Census will be a herculean effort and also cause for controversies. Therefore one needs to be clear and careful as to what kind of caste data to be collected during the population enumeration.
Therefore it is suggested that the Proposed Q.10 during enumeration phase should collect information only on ‘as to whether the individual belongs to a OBC category? This is best done if an approved list of OBCs is provided in advance. In the absence of approved OBC list, self-reported post enumeration categorization will be controversial. Yet eliciting OBC information during enumeration will have to be done as an additional question after the question on religion there can be errors due to misreporting and confounding effects. Recent debates on extension of ‘reservation’ benefits to individuals belonging to religions other than Hindus have generated anxiety and also expectations especially amongst the minorities.
Possible Contamination of Census Information : India has a long uninterrupted history of undertaking census every 10 years since the late 19th century and certainly a regular pan-Indian census since the Independence. Indian Census is respected across the world for its quality and academic content. A lot of debates and research has fed the number and type of question to be included in the ‘house listing’ and ‘population enumeration’ exercises. It is useful to note that the last time caste information was collected was during census 1931.
The concepts, definitions and questions are standardized in such a way that the inter-censal comparisons are possible. Such comparisons are the basis to evaluate a number of economic, social, educational and work/employment parameters for India and its many states and even districts. Therefore, any addition or alteration and even change in placement of a question, both in the listing and enumeration proforme can cause changes in the quality of data in other words can contaminate census information. For example, (a) the errors in self-reported SCs/STs and OBCs category can be enormous by boosting the respective population shares which can prompt increase in the quota shares. This can happen because – those not SCs/STs may get motivated to report themselves as such; so will be the case for OBCs. Since the OBC reservation debate is in its peak one can expect an extra caution amongst the OBCs to ensure reporting; while there can also be misreporting thus boosting the share of OBCs in the population. Even communities with no caste identities may innovate or identify a caste for themselves. (b) It is likely that caste question can affect the reporting of occupations. The possibility is large due to expected gains offered by the government based on caste/occupation linked targeting such as programs for ‘weavers’ and so on. There can many other distortions or contamination of data.
What can be Done? It appears the demand for caste census emerges from the need to know the accurate size of the OBC communities. Since data on the SCs and STs are regularly collected since 1951 census, there is no issue relating to these categories. Thus the focus should be on identifying correct size and share of OBCs, since the Mandal commission linked reservations are based on old data from 1931 and not so valid local level surveys. The quinnqunnel National Sample Surveys are undertaken about five years apart and they are most respected for quality and consistency of data. Current sample size is over one hundred and fifty thousand households rural and urban households. Fortunately, India also hosts independent survey research organizations such as the National Council of Applied Economic Research which can execute such surveys with ease and accuracy. Should there is a need one can devise a multi-level multi-stratum sample sizes so as to provide the estimates of the religion specific size and share of OBCs in each of the Indian state and regions within the larger states of India. Such estimates will keep the chastity of the Indian census intact while proving accurate data for devising pro-poor social policies in India.
Operational Difficulties in Collecting Caste in Census 2011: The census is undertaken in two phases. A house listing operation (Phase 1) precedes the population enumeration (phase 2) usually scheduled during months of February and March of the census years. The house listing for census 2011 is already in progress. House Listing Operation collects information on SCs & STs - item 15 in the proforma. Once can expand this question by providing an addition option ‘OBC (3) and changing code of ‘Other’ to (4). Note also that information on Scheduled Caste is collected only from Hindus, Sikhs and Buddhists and not from other religion; whereas Schedule Tribe can be from any religion. Since religion is not collected in this phase the OBC reporting will be free of divergent influences and overall this approach can work if the OBC check list is provided to enumerators in advance. But since the listing operation is already on all over India and it is too to collect caste/OBC information during the house listing operation.
According to news paper reports, it appears, that data on caste will be collected by asking a simple question “what is your cast?” during the census operations. This now can be done only in phase 2 known as Population Enumeration undertaken during March-April 2011. This kind of open question can be asked immediacy after the following questions:
Q. 7: Religion (Write name of the religion in full)
Q. 8: If Scheduled Caste, Write name of the SC from the list supplied
Q .9: If Scheduled Tribe, write name of the ST from the list supplied
Proposed Q.10: What is your Caste? _____________________
Such a question will generate a lot of caste reporting exclusive to each state and regions within state. Often a given caste is identified, pronounced and spelled differently; and sometimes same cast can assume differential status in other states. Collating such information subsequent to conclusion of Census will be a herculean effort and also cause for controversies. Therefore one needs to be clear and careful as to what kind of caste data to be collected during the population enumeration.
Therefore it is suggested that the Proposed Q.10 during enumeration phase should collect information only on ‘as to whether the individual belongs to a OBC category? This is best done if an approved list of OBCs is provided in advance. In the absence of approved OBC list, self-reported post enumeration categorization will be controversial. Yet eliciting OBC information during enumeration will have to be done as an additional question after the question on religion there can be errors due to misreporting and confounding effects. Recent debates on extension of ‘reservation’ benefits to individuals belonging to religions other than Hindus have generated anxiety and also expectations especially amongst the minorities.
Possible Contamination of Census Information : India has a long uninterrupted history of undertaking census every 10 years since the late 19th century and certainly a regular pan-Indian census since the Independence. Indian Census is respected across the world for its quality and academic content. A lot of debates and research has fed the number and type of question to be included in the ‘house listing’ and ‘population enumeration’ exercises. It is useful to note that the last time caste information was collected was during census 1931.
The concepts, definitions and questions are standardized in such a way that the inter-censal comparisons are possible. Such comparisons are the basis to evaluate a number of economic, social, educational and work/employment parameters for India and its many states and even districts. Therefore, any addition or alteration and even change in placement of a question, both in the listing and enumeration proforme can cause changes in the quality of data in other words can contaminate census information. For example, (a) the errors in self-reported SCs/STs and OBCs category can be enormous by boosting the respective population shares which can prompt increase in the quota shares. This can happen because – those not SCs/STs may get motivated to report themselves as such; so will be the case for OBCs. Since the OBC reservation debate is in its peak one can expect an extra caution amongst the OBCs to ensure reporting; while there can also be misreporting thus boosting the share of OBCs in the population. Even communities with no caste identities may innovate or identify a caste for themselves. (b) It is likely that caste question can affect the reporting of occupations. The possibility is large due to expected gains offered by the government based on caste/occupation linked targeting such as programs for ‘weavers’ and so on. There can many other distortions or contamination of data.
What can be Done? It appears the demand for caste census emerges from the need to know the accurate size of the OBC communities. Since data on the SCs and STs are regularly collected since 1951 census, there is no issue relating to these categories. Thus the focus should be on identifying correct size and share of OBCs, since the Mandal commission linked reservations are based on old data from 1931 and not so valid local level surveys. The quinnqunnel National Sample Surveys are undertaken about five years apart and they are most respected for quality and consistency of data. Current sample size is over one hundred and fifty thousand households rural and urban households. Fortunately, India also hosts independent survey research organizations such as the National Council of Applied Economic Research which can execute such surveys with ease and accuracy. Should there is a need one can devise a multi-level multi-stratum sample sizes so as to provide the estimates of the religion specific size and share of OBCs in each of the Indian state and regions within the larger states of India. Such estimates will keep the chastity of the Indian census intact while proving accurate data for devising pro-poor social policies in India.
Tuesday, April 6, 2010
Monday, April 5, 2010
NEWS Report | http://beta.thehindu.com/news/national/article381832.ece
Sachar member laments low spending on Muslims' welfare
Vidya Subrahmaniam | The Hindu | April 3, 2010
Keywords: Sachar Committee, Muslims, Ministry of Minority Affairs
Abusaleh Shariff, member-secretary of the Rajinder Sachar Committee on the status of Muslims, is angry and upset. He thinks the United Progressive Alliance government has not done enough to push the cause of Muslims' welfare.
Talking to The Hindu, Dr. Shariff said: “It is more than three years since the Committee's report established the pitiable socio-economic status of Indian Muslims. I am saddened and depressed that in all this time there has been more talk about Sachar than action.”
As a case in point, he refers to the Ministry of Minority Affairs' Minority Concentration Districts (MCDs) programme. The largest of the Ministry's schemes, the MCD programme gets the lion's share of the Ministry's budgetary allocation. In the current budget, the Ministry's overall allocation went up from Rs. 1,740 crore to Rs. 2,600 crore. The MCD programme's share correspondingly went up from Rs. 889.50 crore to Rs. 1,204.20 crore.
Dr. Shariff maintains that this increase is eyewash. “This is deceiving people” he says, because so far hardly any of the MCD amount has been spent by the States. The Ministry's own figures establish “the dismal state of affairs.” Only five States reported spending any of the MCD money. The rest did not even bother to send a progress report.
The five States in turn picked up only tiny amounts, averaging an expenditure of just 8 per cent of the funding approved for them. The total cost of MCD projects approved by the Ministry as of December 31, 2009 was Rs.1,821.50 crore. Against this, the Ministry's account books show an expenditure of only Rs. 142.40 crore. The highest MCD spender was Uttar Pradesh which lifted 14.3 per cent of the total approved cost of Rs. 582.30 crore. Haryana followed with 12.8 per cent and West Bengal with 6 per cent.
Initiated in 2007, the MCD programme identified 90 districts in 20 States for targeted focus, based on parameters of backwardness and a minority population criterion of at least 25 per cent. Most MCDs are expectedly Muslim-dominated.
Mr. Shariff accepts that a lot of government schemes suffer from underutilisation of funds. However, when underutilisation touches 92 per cent, then “I would think that the lapse is intentional.” He gives the counter example of the Sarva Shiksha Abhiyan, where the fund utilisation averages around 70 per cent.
In an interview to The Hindu in September 2009, Minority Affairs Minister Salman Khursheed lamented that his Ministry was not able to touch the lives of ordinary Muslims. To be effective, the Ministry needed to have greater powers, he said.
Vidya Subrahmaniam | The Hindu | April 3, 2010
Keywords: Sachar Committee, Muslims, Ministry of Minority Affairs
Abusaleh Shariff, member-secretary of the Rajinder Sachar Committee on the status of Muslims, is angry and upset. He thinks the United Progressive Alliance government has not done enough to push the cause of Muslims' welfare.
Talking to The Hindu, Dr. Shariff said: “It is more than three years since the Committee's report established the pitiable socio-economic status of Indian Muslims. I am saddened and depressed that in all this time there has been more talk about Sachar than action.”
As a case in point, he refers to the Ministry of Minority Affairs' Minority Concentration Districts (MCDs) programme. The largest of the Ministry's schemes, the MCD programme gets the lion's share of the Ministry's budgetary allocation. In the current budget, the Ministry's overall allocation went up from Rs. 1,740 crore to Rs. 2,600 crore. The MCD programme's share correspondingly went up from Rs. 889.50 crore to Rs. 1,204.20 crore.
Dr. Shariff maintains that this increase is eyewash. “This is deceiving people” he says, because so far hardly any of the MCD amount has been spent by the States. The Ministry's own figures establish “the dismal state of affairs.” Only five States reported spending any of the MCD money. The rest did not even bother to send a progress report.
The five States in turn picked up only tiny amounts, averaging an expenditure of just 8 per cent of the funding approved for them. The total cost of MCD projects approved by the Ministry as of December 31, 2009 was Rs.1,821.50 crore. Against this, the Ministry's account books show an expenditure of only Rs. 142.40 crore. The highest MCD spender was Uttar Pradesh which lifted 14.3 per cent of the total approved cost of Rs. 582.30 crore. Haryana followed with 12.8 per cent and West Bengal with 6 per cent.
Initiated in 2007, the MCD programme identified 90 districts in 20 States for targeted focus, based on parameters of backwardness and a minority population criterion of at least 25 per cent. Most MCDs are expectedly Muslim-dominated.
Mr. Shariff accepts that a lot of government schemes suffer from underutilisation of funds. However, when underutilisation touches 92 per cent, then “I would think that the lapse is intentional.” He gives the counter example of the Sarva Shiksha Abhiyan, where the fund utilisation averages around 70 per cent.
In an interview to The Hindu in September 2009, Minority Affairs Minister Salman Khursheed lamented that his Ministry was not able to touch the lives of ordinary Muslims. To be effective, the Ministry needed to have greater powers, he said.
Thursday, April 1, 2010
Structure of Food Crisis in Rural India
It is generally believed that since cultivation is undertaken in rural areas, the rural households do not face food stress and food price increase is not any issue. Surely, food production is a rural phenomenon but since upto one half of rural households are either land less or hold small and unproductive land, such households are subjected to sever food shortages. During the visits to rural areas in three states of Uttar Pradesh, Madhya Pradesh and Karnataka, it was possible to find out the barest minimum amount of income needed for a typical family to ensure food consumption (the kind of food which is normally consumed in rural areas) and meet other expenditures on minimum needs. This amount works out to be Rs. 31, 600 per annum; but a large number of rural households are unable to earn this sum, and there is a shortage ranging from Rs. 7,400 in MP, 6,400 in UP and 4,300 in Karnataka. The shortfall of Rs. 7,400 for a family of 5 members, for example, in MP is despite income accruing to the family from agriculture of Rs. 5,600, from wages of Rs. 7,500, sale of agricultural by products worth Rs. 2,000, from cattle Rs. 4,000, a total of 4,220 subsidy / cash transfers received from a number of public programs such as PDS, NREGA, ICDS, MMD and pension schemes, and also Rs.900 on average received in remittances. The multiplicity in source of income itself is a strategy to ensure adequate income receipts but the cost of living even rural areas is higher for over one third of households, if not more.
We also measured food eaten by all the family members a day before the date of visit to the households. Overall all the daily consumption of cereal per person is estimated to be 540 gm in urban and 462 gm in rural areas. As expected individuals in the working ages of 15-49 years large amounts with the exception of urban areas in UP and MP where those aged 50 + consume largest quantities. In urban areas, older men and women consume 219 grams of vegetable per capita and in rural areas all adults consume just about 162 grams. Although milk consumption is relatively high in urban areas, and amongst the older ages the amount consumed is a meagerly 75-85 ml and the average is around 55 ml in rural areas. It is only in Karnataka we found that children less than 14 year old are give relatively larger amounts of milk compared to adults which is encouraging. Further, we found that adult males who consume more, but female children consume relatively more than the boys is all states. There is no differential in consumption of food items amongst men and women in the working age group. However, again female children are found to consume more vegetables compared to the boys. It is only in case of milk that boys have better consumption compared with girls, and this can also be a reason for relatively lower intake of cereals and vegetables amongst boys.
Food Consumption a day previous to interview
by place of residence and age of individual
State All cereals (gm) All Vegetables (gm) Milk (ml)
0 to 14 15 to 49 50 + 0 to 14 15 to 49 50 + 0 to 14 15 to 49 50 +
Rural
All 347 493 462 117 163 162 61 53 71
UP 335 478 477 103 144 153 63 40 67
MP 376 587 548 111 159 151 55 56 77
Karnataka 310 396 392 155 188 178 71 64 71
Urban
All 314 487 540 137 190 219 85 75 77
UP 367 562 750 124 163 166 56 67 86
MP 373 580 635 135 176 209 60 78 78
Karnataka 292 420 407 158 218 261 98 55 55
Delhi 260 460 458 132 184 194 111 105 127
Source: Author’s estimates - food quantities are measured from 559 deprived households of UP, MP, Karnataka and Delhi
during September to November 2009.
In the following we narrate typologies which help in explaining behavioral differentials and other characteristics of residents with respect of response to food price increase. Broadly, people’s responses can be differentiated based on ‘perceptions’, ‘opportunities’, idiosyncratic shocks’, ‘social networks’ and ‘safety nets’ one experiences with.
Perception: The way quality of life is understood differ considerably between rural and urban areas, reflecting the exposure to the level of modernization, for example in urban areas which broadly vary according to size of town, and intensity and quality of public infrastructure and governance. Rural life style is sedentary and the one anchored upon contentment with limited demands if any. Such behavioral variation is both a virtue and a curse. ‘Virtue’ to the extent that it makes their limited life style manageable and perceptible desire to lead a content life; where as a ‘Curse’ when households are unable to benchmark or even understand the mechanisms to improve standard of life at a minimum or comfortable level as recognized by modern standards; for example minimum levels of schooling, basic levels of nutrition, health and hygienic conditions, housing and so on. Therefore, the food price response differs considerably as to variation in food habits and extent to which communities and households depend upon non-local markets to access culturally appropriate food products when not self-produced.
Opportunities: Large variations are noticed in terms of opportunities that the communities and households have not only for earning income but also to interact with markets. Rudimentary nature of local labor market often sustained based one exchange labor and non-monetized considerations at least in rural areas is causing labor mobility which can be characterized as migrant labor. One finds a considerable economic prosperity amongst households having at least one member as a labor migrant, but often one finds the whole families migrating out for short periods of 4-8 months, but also for much longer time periods. Most of the households in the urban periphery are migrants from rural out backs, and it appears they are pushed out of rural life both by expectations as well as economic stress, while some are able to capitalize upon their skills and education, most have fallen deeper in to poverty trap due to confrontation with urban monetized and somewhat standardized life and their inability to meet those expectations. What is clearly evident is a complex urban sociology and economy which in some places provides for a living and for a few others opportunities do not exist. Such situations are highly local but it would be possible to profile urban living standards through further research which is not common in the context of south Asia, especially India. Generally the poor both in rural and urban areas are afraid of market dependence to ensure supply of cereals and other basic food products.
Amongst the poorer rural households, average land holding is very low so is the land productivity; further they own few productive assets and lack irrigation. Over and above the drought caused during July-August 2009 have made all of such households vulnerable to food stress. The SC-families have smaller land holdings and land owned is of lower productivity which in fact was allotted by government agencies under different schemes. The net (of seeds) yield of the main crops of paddy and wheat was found to be around 6 quintals per acre, but due to draught paddy got damaged. The local wage work opportunities are far too low and wage rates range between Rs. 50 and Rs. 60/- per day of work.
Idiosyncratic Shocks: Households with deep food stress do have highly specified situations which differ as per the household situations, for example inability to sustain livestock due to sheer poverty, or inaccessibility to common property resource such as grazing lands or even lack of a member who can take care of cattle and so on. Female headed households do face difficulty in undertaking cultivation and therefore lease out land with low home grown food access which increase vulnerability. In both rural and urban areas ill-health causes extreme degree of idiosyncratic shocks causing conditions of food deficit and malnutrition. Strict adherence to cultural values in case of marriage, birth and death related ceremonies can push households into penury and in many cases irreversible thus exposing such households for extreme food stress.
Social Networks: Informal social networks are some of the most durable extensions of India family values which provide considerable amounts of safety nets. Rural areas across India are in advantageous situations where social networks do work in support to sustain food smoothening; but the situation in the urban peripheries is different due to unclear linkages, rather a breakdown of social networks. Lack of social environment in towns can be attributed to peripheral societies build upon migration often from rural areas. But another fact which accentuates the urban-anonymity and lack of networks is the fact that households in specified urban localities face situations which are equally stressful thus making social networks redundant. Such differential social typologies are crucial for withstanding extreme food related stress in India.
Safety nets: Often it is argued that since urban areas by definition have higher concentration of social, economic and market institutions the urban households do not require targeted safety nets. We do find that the rural areas have a relatively better coverage of safety nets of various kinds although; the efficacy and utilization vary between villages and also different types of households. But one finds absence of such safety net schemes in urban locales. On the other hand urban areas do have concentration of both social and physical infrastructure managed both by the public and private initiatives; but the poor living in fringes in towns and cities have limited access to them due to lack of their integration into the urban system. Often such families do not hold for example PDS cards, nor will they be listed as eligible beneficiaries for social protection schemes due to unclear domiciliary conditions. Such a situation was clearly noticeable in case of Delhi, but also in other larger towns/cities such as Kanpur in UP and Kolar in Karnataka.
Any reform in the public polices in India are affected not so much as to what and why but HOW to identify the right household, group of households, villages and communities. The above profiling of the poor will help policy makers to devise better methodologies for targeting the poverty alleviation programs.
We also measured food eaten by all the family members a day before the date of visit to the households. Overall all the daily consumption of cereal per person is estimated to be 540 gm in urban and 462 gm in rural areas. As expected individuals in the working ages of 15-49 years large amounts with the exception of urban areas in UP and MP where those aged 50 + consume largest quantities. In urban areas, older men and women consume 219 grams of vegetable per capita and in rural areas all adults consume just about 162 grams. Although milk consumption is relatively high in urban areas, and amongst the older ages the amount consumed is a meagerly 75-85 ml and the average is around 55 ml in rural areas. It is only in Karnataka we found that children less than 14 year old are give relatively larger amounts of milk compared to adults which is encouraging. Further, we found that adult males who consume more, but female children consume relatively more than the boys is all states. There is no differential in consumption of food items amongst men and women in the working age group. However, again female children are found to consume more vegetables compared to the boys. It is only in case of milk that boys have better consumption compared with girls, and this can also be a reason for relatively lower intake of cereals and vegetables amongst boys.
Food Consumption a day previous to interview
by place of residence and age of individual
State All cereals (gm) All Vegetables (gm) Milk (ml)
0 to 14 15 to 49 50 + 0 to 14 15 to 49 50 + 0 to 14 15 to 49 50 +
Rural
All 347 493 462 117 163 162 61 53 71
UP 335 478 477 103 144 153 63 40 67
MP 376 587 548 111 159 151 55 56 77
Karnataka 310 396 392 155 188 178 71 64 71
Urban
All 314 487 540 137 190 219 85 75 77
UP 367 562 750 124 163 166 56 67 86
MP 373 580 635 135 176 209 60 78 78
Karnataka 292 420 407 158 218 261 98 55 55
Delhi 260 460 458 132 184 194 111 105 127
Source: Author’s estimates - food quantities are measured from 559 deprived households of UP, MP, Karnataka and Delhi
during September to November 2009.
In the following we narrate typologies which help in explaining behavioral differentials and other characteristics of residents with respect of response to food price increase. Broadly, people’s responses can be differentiated based on ‘perceptions’, ‘opportunities’, idiosyncratic shocks’, ‘social networks’ and ‘safety nets’ one experiences with.
Perception: The way quality of life is understood differ considerably between rural and urban areas, reflecting the exposure to the level of modernization, for example in urban areas which broadly vary according to size of town, and intensity and quality of public infrastructure and governance. Rural life style is sedentary and the one anchored upon contentment with limited demands if any. Such behavioral variation is both a virtue and a curse. ‘Virtue’ to the extent that it makes their limited life style manageable and perceptible desire to lead a content life; where as a ‘Curse’ when households are unable to benchmark or even understand the mechanisms to improve standard of life at a minimum or comfortable level as recognized by modern standards; for example minimum levels of schooling, basic levels of nutrition, health and hygienic conditions, housing and so on. Therefore, the food price response differs considerably as to variation in food habits and extent to which communities and households depend upon non-local markets to access culturally appropriate food products when not self-produced.
Opportunities: Large variations are noticed in terms of opportunities that the communities and households have not only for earning income but also to interact with markets. Rudimentary nature of local labor market often sustained based one exchange labor and non-monetized considerations at least in rural areas is causing labor mobility which can be characterized as migrant labor. One finds a considerable economic prosperity amongst households having at least one member as a labor migrant, but often one finds the whole families migrating out for short periods of 4-8 months, but also for much longer time periods. Most of the households in the urban periphery are migrants from rural out backs, and it appears they are pushed out of rural life both by expectations as well as economic stress, while some are able to capitalize upon their skills and education, most have fallen deeper in to poverty trap due to confrontation with urban monetized and somewhat standardized life and their inability to meet those expectations. What is clearly evident is a complex urban sociology and economy which in some places provides for a living and for a few others opportunities do not exist. Such situations are highly local but it would be possible to profile urban living standards through further research which is not common in the context of south Asia, especially India. Generally the poor both in rural and urban areas are afraid of market dependence to ensure supply of cereals and other basic food products.
Amongst the poorer rural households, average land holding is very low so is the land productivity; further they own few productive assets and lack irrigation. Over and above the drought caused during July-August 2009 have made all of such households vulnerable to food stress. The SC-families have smaller land holdings and land owned is of lower productivity which in fact was allotted by government agencies under different schemes. The net (of seeds) yield of the main crops of paddy and wheat was found to be around 6 quintals per acre, but due to draught paddy got damaged. The local wage work opportunities are far too low and wage rates range between Rs. 50 and Rs. 60/- per day of work.
Idiosyncratic Shocks: Households with deep food stress do have highly specified situations which differ as per the household situations, for example inability to sustain livestock due to sheer poverty, or inaccessibility to common property resource such as grazing lands or even lack of a member who can take care of cattle and so on. Female headed households do face difficulty in undertaking cultivation and therefore lease out land with low home grown food access which increase vulnerability. In both rural and urban areas ill-health causes extreme degree of idiosyncratic shocks causing conditions of food deficit and malnutrition. Strict adherence to cultural values in case of marriage, birth and death related ceremonies can push households into penury and in many cases irreversible thus exposing such households for extreme food stress.
Social Networks: Informal social networks are some of the most durable extensions of India family values which provide considerable amounts of safety nets. Rural areas across India are in advantageous situations where social networks do work in support to sustain food smoothening; but the situation in the urban peripheries is different due to unclear linkages, rather a breakdown of social networks. Lack of social environment in towns can be attributed to peripheral societies build upon migration often from rural areas. But another fact which accentuates the urban-anonymity and lack of networks is the fact that households in specified urban localities face situations which are equally stressful thus making social networks redundant. Such differential social typologies are crucial for withstanding extreme food related stress in India.
Safety nets: Often it is argued that since urban areas by definition have higher concentration of social, economic and market institutions the urban households do not require targeted safety nets. We do find that the rural areas have a relatively better coverage of safety nets of various kinds although; the efficacy and utilization vary between villages and also different types of households. But one finds absence of such safety net schemes in urban locales. On the other hand urban areas do have concentration of both social and physical infrastructure managed both by the public and private initiatives; but the poor living in fringes in towns and cities have limited access to them due to lack of their integration into the urban system. Often such families do not hold for example PDS cards, nor will they be listed as eligible beneficiaries for social protection schemes due to unclear domiciliary conditions. Such a situation was clearly noticeable in case of Delhi, but also in other larger towns/cities such as Kanpur in UP and Kolar in Karnataka.
Any reform in the public polices in India are affected not so much as to what and why but HOW to identify the right household, group of households, villages and communities. The above profiling of the poor will help policy makers to devise better methodologies for targeting the poverty alleviation programs.
Saturday, February 27, 2010
Food prices and coping mechanism in India
Debates abound, in the recent months, as to the steep increase in inflation in India and a substantial contribution from the primary food articles. This obviously is a matter of great concern to the government, the civil society and consumers alike. Since food is consumed on a daily basis and most households undertake daily purchases, it is imperative to find out how poorer households cope with high food inflation and sustain their food consumption.
In the following we investigate: (1) whether the food inflation is accurately captured through the WPI- inflation monitoring; and (2) how do the households in rural and urban areas cope, so as to smoothen food consumption.
Prices: Inflation which is benchmarked on the wholesale price index underestimates the impact of food prices due to low weightage attached to the group of food products, for example, the food group as a whole has a weight of just over a quarter, and food grains have only a 5 % weight. In reality (estimated from household survey) these proportions are 51% and 19.2% in rural and 41% and 16% in urban areas. Therefore, food price increase is not adequately factored in inflation figures provided by government agencies. Given this situation, if the government claims that food price increase indeed is one of the factors for high inflation, it should mean an unprecedented and very high price increase in food articles indeed.
Further citizens normally take newspaper reporting seriously to make judgments about the food inflation. Often the retail market prices collected from urban neighborhoods do not correctly reflect prices due to large discrepancy with the wholesale market prices of the same food items. Further, for food items other than vegetables and fruits it is essential to take a short to medium (as opposed to immediate) term view by tracking prices say on a weekly, monthly and seasonal basis. This article gleams over monthly data for over 25 food items from 78 towns and cities spread all over India since April 2006 to October 2009 period. The size of the town/city is a good proxy for size of market as well as proximity to the source of supply, normally the rural areas. An interesting pattern emerges. Small town having less than one lakh population are the cheapest for unprocessed food items such as whole wheat, paddy and rice, unprocessed milk and so on. The processed food items such as wheat atta, polished rice and packed milk are found to be priced high in large towns above 25 lakh population. But the contrast is in wheat and atta. While wheat prices are least in small towns, wheat atta is priced highest in small towns compared with the larger ones. The wheat flour is priced between 40% to 50% higher than the whole wheat prices in small towns. Other processed food items also cost exorbitantly high in small towns and rural areas. However, towns with 1-5 lakh population are the cheapest for both rice and wheat in India suggesting that they maximize gains from nearness to source of supply, as well as possible scale economics in business and also because of location of processing industries. Rice price increases as size of town/city increase and thus affects the poor living in larger towns and cities the most. The price of pulses and sugar has recorded unprecedented increase during the 2009-10 periods and affects both rural and urban areas equally. There is a broad based increase in prices of food items in India and the momentum of this increase has built up during 2007-8 and is continuing during the 2010.
Coping Mechanisms: There are noteworthy rural-urban consumption differentials in India – rural households consume more of cereals so is the case for poorer households. Consumption of quality and value added foods are high in urban areas and amongst the richer households. Price wield large and dominant impact even on consumption of rice and wheat, generally considered price inelastic. Therefore, self production of these cereals has considerably strong impact on sustaining consumption. It is instructive to note that 36 % of wheat and 32% of rice requirement are met through self-grown agriculture. Another 11% of wheat and 14% of rice requirement is met by the Public Distribution System. Thus even in the rural areas one half of the all wheat and rice requirement is met by open market purchases. As expected 92% of wheat and 84 per cent of rice requirement of urban households is met by open markets, and only about 5 % wheat and 11% rice requirement is met of PDS in urban area.
Relatively poorer households try to depend less on markets but they fall short of home grown food at least in rural areas, consequently their dependence upon the PDS supply is large. One finds that PDS has reached rural areas and there is also a great demand for supplies. However, the PDS supply is irregular and insufficient due to state specific bureaucratic failure, leakage and large exclusion and inclusion errors in targeting. Urban areas show unfair distribution of BPL cards compared with rural parts although the mismatch is considerable in both place of residences. Further the targeted PDS program is poor in states where poverty is high such as Jharkhand, Uttar Pradesh, Bihar and Chhattisgarh.
It is essential to find out the share of expenditure on cereals to total food so as to find out how relative prices impact the poor. Cereal shares are about 35% in rural and 27 % in urban areas; but a disturbing fact is that relatively poor spend substantial higher shares on cereals compared to relatively richer. Therefore, any cereal price increase is going to impact the poor the most. Therefore, it is absolutely essential to keep a check on unusually high price rise of cereals from the consumers’ point of view, yet it is imperative that incentives are built so as to directly benefit the farmers who will sustain cultivation of cereals. Another aspect which provides deeper understanding is the fact that bottom 20 % (poorest) households spend almost all their disposable income in urban and 72 % higher than the disposable income in rural areas on food. This suggests that there is an urgent need to build food security for the rural poor much more than the urban poor although at the outset it appears that it is the urban poor who gets affected by the food price inflation.
In conclusion, it is essential to emphasize, that there has to be a prudent price management scheme for both wheat and rice in India. Further it is imperative that appropriate amount of income transfer is effected either through the PDS or food / cash vouchers schemes. The key is in the ability of the state to identify the poor dispassionately and through a systematic methodology. Keeping a close watch on market price of food items must become inherent part of public policy. It appears India is not yet amenable for free market in food products although experiments in crafting exclusive agricultural markets for exports and strengthening supply chains to organized and supermarkets can continue.
In the following we investigate: (1) whether the food inflation is accurately captured through the WPI- inflation monitoring; and (2) how do the households in rural and urban areas cope, so as to smoothen food consumption.
Prices: Inflation which is benchmarked on the wholesale price index underestimates the impact of food prices due to low weightage attached to the group of food products, for example, the food group as a whole has a weight of just over a quarter, and food grains have only a 5 % weight. In reality (estimated from household survey) these proportions are 51% and 19.2% in rural and 41% and 16% in urban areas. Therefore, food price increase is not adequately factored in inflation figures provided by government agencies. Given this situation, if the government claims that food price increase indeed is one of the factors for high inflation, it should mean an unprecedented and very high price increase in food articles indeed.
Further citizens normally take newspaper reporting seriously to make judgments about the food inflation. Often the retail market prices collected from urban neighborhoods do not correctly reflect prices due to large discrepancy with the wholesale market prices of the same food items. Further, for food items other than vegetables and fruits it is essential to take a short to medium (as opposed to immediate) term view by tracking prices say on a weekly, monthly and seasonal basis. This article gleams over monthly data for over 25 food items from 78 towns and cities spread all over India since April 2006 to October 2009 period. The size of the town/city is a good proxy for size of market as well as proximity to the source of supply, normally the rural areas. An interesting pattern emerges. Small town having less than one lakh population are the cheapest for unprocessed food items such as whole wheat, paddy and rice, unprocessed milk and so on. The processed food items such as wheat atta, polished rice and packed milk are found to be priced high in large towns above 25 lakh population. But the contrast is in wheat and atta. While wheat prices are least in small towns, wheat atta is priced highest in small towns compared with the larger ones. The wheat flour is priced between 40% to 50% higher than the whole wheat prices in small towns. Other processed food items also cost exorbitantly high in small towns and rural areas. However, towns with 1-5 lakh population are the cheapest for both rice and wheat in India suggesting that they maximize gains from nearness to source of supply, as well as possible scale economics in business and also because of location of processing industries. Rice price increases as size of town/city increase and thus affects the poor living in larger towns and cities the most. The price of pulses and sugar has recorded unprecedented increase during the 2009-10 periods and affects both rural and urban areas equally. There is a broad based increase in prices of food items in India and the momentum of this increase has built up during 2007-8 and is continuing during the 2010.
Coping Mechanisms: There are noteworthy rural-urban consumption differentials in India – rural households consume more of cereals so is the case for poorer households. Consumption of quality and value added foods are high in urban areas and amongst the richer households. Price wield large and dominant impact even on consumption of rice and wheat, generally considered price inelastic. Therefore, self production of these cereals has considerably strong impact on sustaining consumption. It is instructive to note that 36 % of wheat and 32% of rice requirement are met through self-grown agriculture. Another 11% of wheat and 14% of rice requirement is met by the Public Distribution System. Thus even in the rural areas one half of the all wheat and rice requirement is met by open market purchases. As expected 92% of wheat and 84 per cent of rice requirement of urban households is met by open markets, and only about 5 % wheat and 11% rice requirement is met of PDS in urban area.
Relatively poorer households try to depend less on markets but they fall short of home grown food at least in rural areas, consequently their dependence upon the PDS supply is large. One finds that PDS has reached rural areas and there is also a great demand for supplies. However, the PDS supply is irregular and insufficient due to state specific bureaucratic failure, leakage and large exclusion and inclusion errors in targeting. Urban areas show unfair distribution of BPL cards compared with rural parts although the mismatch is considerable in both place of residences. Further the targeted PDS program is poor in states where poverty is high such as Jharkhand, Uttar Pradesh, Bihar and Chhattisgarh.
It is essential to find out the share of expenditure on cereals to total food so as to find out how relative prices impact the poor. Cereal shares are about 35% in rural and 27 % in urban areas; but a disturbing fact is that relatively poor spend substantial higher shares on cereals compared to relatively richer. Therefore, any cereal price increase is going to impact the poor the most. Therefore, it is absolutely essential to keep a check on unusually high price rise of cereals from the consumers’ point of view, yet it is imperative that incentives are built so as to directly benefit the farmers who will sustain cultivation of cereals. Another aspect which provides deeper understanding is the fact that bottom 20 % (poorest) households spend almost all their disposable income in urban and 72 % higher than the disposable income in rural areas on food. This suggests that there is an urgent need to build food security for the rural poor much more than the urban poor although at the outset it appears that it is the urban poor who gets affected by the food price inflation.
In conclusion, it is essential to emphasize, that there has to be a prudent price management scheme for both wheat and rice in India. Further it is imperative that appropriate amount of income transfer is effected either through the PDS or food / cash vouchers schemes. The key is in the ability of the state to identify the poor dispassionately and through a systematic methodology. Keeping a close watch on market price of food items must become inherent part of public policy. It appears India is not yet amenable for free market in food products although experiments in crafting exclusive agricultural markets for exports and strengthening supply chains to organized and supermarkets can continue.
Monday, January 25, 2010
Friday, January 15, 2010
Poverty Reduction and Poverty Creation in India
Do they happen concurrently and for what reason?
Summary of a recent paper entitled 'The Irrelevance of National Strategies:
Rural Poverty Creation and Reduction in States of India' jointly written with
Anirudh Krishna of the Duke University, USA
There are only a few controversial and somewhat puzzling economic dimensions which are academically unresolved and subject to serious debates. While there is recognition about the speed and direction of growth scenario suggesting India’s arrival on the global economic scene, what is puzzling at the same time is not only the continued prevalence of poverty but also a possible increase over the past decade, at least in the rural hinterland. Poverty measurement is an unsettled issue, both conceptually and methodologically. In fact, since poverty is a process as well as an outcome; many come out of it while others may be falling into it. The net effect of these two parallel processes is a proportion commonly identified as the ’head count ratio’, but these ratios hide the fundamental dynamism that characterizes poverty in practice. Note that the most recent poverty re-estimates using a supposedly refined methodology by a Government of India expert group has also missed this crucial dynamism (Report of the Expert Group to Review the Methodology for Estimation of Poverty, 2009. New Delhi: Government of India, Planning Commission). Studies carried out by one of the authors of this article, in parts of Andhra Pradesh, Gujarat, and Rajasthan have, however, helped bring to light the essential fact of poverty dynamics: which is simultaneously both created and reduced. Some households fall into poverty, becoming the new poor; other households concurrently escape from poverty.
Following up on these insights, we examined, for the first time in India, a nationally-representative panel data set for more than 13,000 households studied in 1993-94 and re-interviewed in 2004-05. We found that while 18.2 percent of the rural population moved out of poverty, another 22.1 per cent fell into it over this twelve-year period. This net increase of four percentage points was found to have a considerable variation across states and regions. In states, such as Himachal Pradesh, Kerala, Rajasthan and West Bengal, where more people moved out of poverty than fell into poverty, there has been an overall decline in rural poverty. Conversely, rural poverty increased in Andhra Pradesh, Bihar, Gujarat, Haryana, Maharashtra, Madhya Pradesh, Orissa, Tamil Nadu, and Uttar Pradesh, where descents into poverty were more numerous than escapes from poverty.
States – as well as regions within states – differ from one another. Some have high descent rates but low escape rates; in a few other states, both descent and escape rates are low. Different combinations of poverty policies will be required in states that are characterized by different patterns of escaping poverty and falling into poverty. A typology emerging from our analysis is presented below:
Consider the upper-left cell which lists regions that have most successfully reduced poverty over the 12-year reference period, because a high escape rate went together with a low descent rate. Two small states, Kerala and Himachal Pradesh, and another group of states (Assam and the Northeast) fall within this high-performing group. A poor person in India is best-off living within some region of this cell: the probability is highest that her circumstances will improve over time. For a contrasting situation, consider the bottom-right cell, characterized by low escape rates and high descent rates. Compared to other regions in India, the prospect for poor people in these regions is bleak; chances for further impoverishment are the highest. Future efforts in this region will do well to concentrate, first, on lowering the high rate of descent, and second, on ramping up the low escape rate.
A more nuanced prognosis emerges for regions included within the off-diagonal cells. Consider, for example, the two regions belonging to the bottom-left cell (Karnataka- Inland Southern, and Madhya Pradesh-Vindhya). A high escape rate within these regions has been compromised by a concurrently high descent rate. Future poverty reduction efforts in these regions should focus primarily on reducing the high rate of descent into poverty. It makes greater sense to raise the escape rate only after the high risk of falling into poverty has been brought under control. The opposite policy prescription seems appropriate for regions of the top-right cell. In Maharashtra-Eastern and Haryana-Western, additional resources should be deployed primarily for raising poor people’s chances of escape.
Thus, different policy mixes, combining different elements of prevention (against descents into poverty) and support (for escaping poverty), are required in diverse regions and states. A uniform national poverty policy will not be effective for entire states, far less for the entire country.
A Typology of Poverty of States and Regions in India
Escape Rate
High (43.0-21.3) Medium (21.2-15.9) Low (15.8-4.4)
Descent Rate Low (18.7-9.1) Assam & Northeast AP-Coastal Maharashtra -Eastern
Karnataka - Coastal, Ghats, & Inland Eastern Punjab-Northern Haryana-Western
Kerala AP-Inland Southern
WB-Himalayan
WB-Central Plains
Himachal Pradesh
Rajasthan-Western
Rajasthan-North-Eastern
Bihar-Jharkhand
West Bengal-Eastern Plains
Medium (24.7-18.8) Gujarat-Plains Northern UP-Western MP-South Western
TN-Coastal & Coastal Northern TN-Southern Orissa-Coastal & Southern
Rajasthan-Southern & South-Eastern UP-Uttaranchal Gujarat-Saurashtra & Dry areas
Bihar-Central Maharashtra-Inland Western & Coastal
MP-Chhattisgarh
Punjab-Southern
MP-South
Gujarat-Eastern & Plains Southern
Haryana-Eastern
High (47.4-24.8) Karnataka -Inland Southern UP-Eastern & Central Orissa-Northern
MP-Vindhya Maharashtra-Inland Eastern Maharashtra-Inland Central
Bihar-Northern TN-Inland
Karnataka-Inland Northern AP-Inland Northern
MP-Malwa
Maharashtra-Inland Northern
MP-Northern
AP-South Western
MP-Central
What kinds of policies and programs will help prevent descents into poverty? And what kinds of programs and policies are required to promote escapes from poverty? We examined the escapes and the descents that have occurred in rural India between 1993 and 2005, and we identified the factors that mattered for each of these trends. A few factors are involved with both escapes and descents, but there is also another group of factors that affect only escape or only descent.
Factors significantly associated both with escape and descent : Age of household head, household size, household composition (reflected by the variable “male advantage”), households with telephones (land lines or mobile), change in the share of rural non-farm income (RNFY), remittances, women’s media exposure, and loan taken in last five years.
Factors associated with escape but not with descent: A few other factors influence escapes but do not matter much for descents. These factors include being a member of ‘minority other than Muslim’, presence of adult son during the previous period (1993), and that the household was located within 5 km of nearest town with the availability of bus stop. Sickness within households had an adverse effect.
Factors associated with descent but not with escape: A household belonging to SC, ST or OBC faced a significantly greater risk of descent into poverty, whereas having the head of the household educated to secondary level or higher reduced the risk of descent. Possession of land and other assets reduced the risk of descent. Significantly, such rural assets were not germane to escapes from poverty.
States with high and low growth rates have variously experienced high and low rates of escape and descent. No clear correlation exists at the level of states and regions between high growth rates and higher poverty reduction. Thus, to claim that “growth of aggregate consumption/income is a sufficient condition for poverty reduction,” as one influential government document does, is hardly an appropriate or adequate policy prescription. Rather than waiting for growth to occur and work its putative magic, direct actions to reduce poverty are necessary.
Action along two fronts is simultaneously required: descents into poverty must be prevented using context-specific measures even as escapes from poverty are promoted vigorously. Different escape and descent rates characterize diverse states and separate regions within states. The reasons that matter for escape and descent also differ considerably across and within states. Considering only the aggregate results obscures these important differences. Diverse policy designs are required in order to deal with these different trends. Any uniform national policy does not, therefore, represent the best use of resources. State- and region-specific threats and opportunities must be separately identified and directly addressed.
Summary of a recent paper entitled 'The Irrelevance of National Strategies:
Rural Poverty Creation and Reduction in States of India' jointly written with
Anirudh Krishna of the Duke University, USA
There are only a few controversial and somewhat puzzling economic dimensions which are academically unresolved and subject to serious debates. While there is recognition about the speed and direction of growth scenario suggesting India’s arrival on the global economic scene, what is puzzling at the same time is not only the continued prevalence of poverty but also a possible increase over the past decade, at least in the rural hinterland. Poverty measurement is an unsettled issue, both conceptually and methodologically. In fact, since poverty is a process as well as an outcome; many come out of it while others may be falling into it. The net effect of these two parallel processes is a proportion commonly identified as the ’head count ratio’, but these ratios hide the fundamental dynamism that characterizes poverty in practice. Note that the most recent poverty re-estimates using a supposedly refined methodology by a Government of India expert group has also missed this crucial dynamism (Report of the Expert Group to Review the Methodology for Estimation of Poverty, 2009. New Delhi: Government of India, Planning Commission). Studies carried out by one of the authors of this article, in parts of Andhra Pradesh, Gujarat, and Rajasthan have, however, helped bring to light the essential fact of poverty dynamics: which is simultaneously both created and reduced. Some households fall into poverty, becoming the new poor; other households concurrently escape from poverty.
Following up on these insights, we examined, for the first time in India, a nationally-representative panel data set for more than 13,000 households studied in 1993-94 and re-interviewed in 2004-05. We found that while 18.2 percent of the rural population moved out of poverty, another 22.1 per cent fell into it over this twelve-year period. This net increase of four percentage points was found to have a considerable variation across states and regions. In states, such as Himachal Pradesh, Kerala, Rajasthan and West Bengal, where more people moved out of poverty than fell into poverty, there has been an overall decline in rural poverty. Conversely, rural poverty increased in Andhra Pradesh, Bihar, Gujarat, Haryana, Maharashtra, Madhya Pradesh, Orissa, Tamil Nadu, and Uttar Pradesh, where descents into poverty were more numerous than escapes from poverty.
States – as well as regions within states – differ from one another. Some have high descent rates but low escape rates; in a few other states, both descent and escape rates are low. Different combinations of poverty policies will be required in states that are characterized by different patterns of escaping poverty and falling into poverty. A typology emerging from our analysis is presented below:
Consider the upper-left cell which lists regions that have most successfully reduced poverty over the 12-year reference period, because a high escape rate went together with a low descent rate. Two small states, Kerala and Himachal Pradesh, and another group of states (Assam and the Northeast) fall within this high-performing group. A poor person in India is best-off living within some region of this cell: the probability is highest that her circumstances will improve over time. For a contrasting situation, consider the bottom-right cell, characterized by low escape rates and high descent rates. Compared to other regions in India, the prospect for poor people in these regions is bleak; chances for further impoverishment are the highest. Future efforts in this region will do well to concentrate, first, on lowering the high rate of descent, and second, on ramping up the low escape rate.
A more nuanced prognosis emerges for regions included within the off-diagonal cells. Consider, for example, the two regions belonging to the bottom-left cell (Karnataka- Inland Southern, and Madhya Pradesh-Vindhya). A high escape rate within these regions has been compromised by a concurrently high descent rate. Future poverty reduction efforts in these regions should focus primarily on reducing the high rate of descent into poverty. It makes greater sense to raise the escape rate only after the high risk of falling into poverty has been brought under control. The opposite policy prescription seems appropriate for regions of the top-right cell. In Maharashtra-Eastern and Haryana-Western, additional resources should be deployed primarily for raising poor people’s chances of escape.
Thus, different policy mixes, combining different elements of prevention (against descents into poverty) and support (for escaping poverty), are required in diverse regions and states. A uniform national poverty policy will not be effective for entire states, far less for the entire country.
A Typology of Poverty of States and Regions in India
Escape Rate
High (43.0-21.3) Medium (21.2-15.9) Low (15.8-4.4)
Descent Rate Low (18.7-9.1) Assam & Northeast AP-Coastal Maharashtra -Eastern
Karnataka - Coastal, Ghats, & Inland Eastern Punjab-Northern Haryana-Western
Kerala AP-Inland Southern
WB-Himalayan
WB-Central Plains
Himachal Pradesh
Rajasthan-Western
Rajasthan-North-Eastern
Bihar-Jharkhand
West Bengal-Eastern Plains
Medium (24.7-18.8) Gujarat-Plains Northern UP-Western MP-South Western
TN-Coastal & Coastal Northern TN-Southern Orissa-Coastal & Southern
Rajasthan-Southern & South-Eastern UP-Uttaranchal Gujarat-Saurashtra & Dry areas
Bihar-Central Maharashtra-Inland Western & Coastal
MP-Chhattisgarh
Punjab-Southern
MP-South
Gujarat-Eastern & Plains Southern
Haryana-Eastern
High (47.4-24.8) Karnataka -Inland Southern UP-Eastern & Central Orissa-Northern
MP-Vindhya Maharashtra-Inland Eastern Maharashtra-Inland Central
Bihar-Northern TN-Inland
Karnataka-Inland Northern AP-Inland Northern
MP-Malwa
Maharashtra-Inland Northern
MP-Northern
AP-South Western
MP-Central
What kinds of policies and programs will help prevent descents into poverty? And what kinds of programs and policies are required to promote escapes from poverty? We examined the escapes and the descents that have occurred in rural India between 1993 and 2005, and we identified the factors that mattered for each of these trends. A few factors are involved with both escapes and descents, but there is also another group of factors that affect only escape or only descent.
Factors significantly associated both with escape and descent : Age of household head, household size, household composition (reflected by the variable “male advantage”), households with telephones (land lines or mobile), change in the share of rural non-farm income (RNFY), remittances, women’s media exposure, and loan taken in last five years.
Factors associated with escape but not with descent: A few other factors influence escapes but do not matter much for descents. These factors include being a member of ‘minority other than Muslim’, presence of adult son during the previous period (1993), and that the household was located within 5 km of nearest town with the availability of bus stop. Sickness within households had an adverse effect.
Factors associated with descent but not with escape: A household belonging to SC, ST or OBC faced a significantly greater risk of descent into poverty, whereas having the head of the household educated to secondary level or higher reduced the risk of descent. Possession of land and other assets reduced the risk of descent. Significantly, such rural assets were not germane to escapes from poverty.
States with high and low growth rates have variously experienced high and low rates of escape and descent. No clear correlation exists at the level of states and regions between high growth rates and higher poverty reduction. Thus, to claim that “growth of aggregate consumption/income is a sufficient condition for poverty reduction,” as one influential government document does, is hardly an appropriate or adequate policy prescription. Rather than waiting for growth to occur and work its putative magic, direct actions to reduce poverty are necessary.
Action along two fronts is simultaneously required: descents into poverty must be prevented using context-specific measures even as escapes from poverty are promoted vigorously. Different escape and descent rates characterize diverse states and separate regions within states. The reasons that matter for escape and descent also differ considerably across and within states. Considering only the aggregate results obscures these important differences. Diverse policy designs are required in order to deal with these different trends. Any uniform national policy does not, therefore, represent the best use of resources. State- and region-specific threats and opportunities must be separately identified and directly addressed.
Tuesday, December 15, 2009
Publications of Interest
Recent Publications:
‘Assessment of Outreach and Benefits of National Rural Employment Guarantee Scheme of India’ accepted for publication in Indian Journal of Labor Economics, 52 (2): June 2009.
On Shelves
Handbook of Muslims in India: Empirical and Policy Perspectives; Edited jointly with Rakesh Basant; New Delhi: Oxford University Press (ISBN13: 9780198062059 | ISBN10: 0198062052) December 2009.
Rural Income and Employment Diversity in India during 1994 and 2005
‘Rural Income and Employment Diversity in India during 1994 and 2005’, Journal of Developing Societies, 25(2): June 2009.
Summary: – This paper assesses the structure of rural income and employment according to source in India. It probes the size and role of ‘rural nonfarm employment’ in poverty alleviation. Data from two nationally representative rural sample surveys (33230 and 27010 households respectively) with reference years 1993-4 and 2004-5 are subjected to multinomial logit and CLAD regressions to explore importance of diversity of income sources across states and regions. These are rare data on direct household income estimates in the multi-model survey context having advantage of many household and village level determinants suitable for advanced analysis. Evidence suggests considerable income diversification over the reference decade, but distribution of shares suggests that top most quintile draw almost all of the benefits of recent economic growth in India. The economic linkage between the RNFE and rural wage rates has reduced and almost not existent during the later reference year in analysis.
Key Words: rural nonfarm employment (RNFE), Labor shares, changeover 1993-4 and 2004-5, income productivity, wage determination, Rural India
Summary: – This paper assesses the structure of rural income and employment according to source in India. It probes the size and role of ‘rural nonfarm employment’ in poverty alleviation. Data from two nationally representative rural sample surveys (33230 and 27010 households respectively) with reference years 1993-4 and 2004-5 are subjected to multinomial logit and CLAD regressions to explore importance of diversity of income sources across states and regions. These are rare data on direct household income estimates in the multi-model survey context having advantage of many household and village level determinants suitable for advanced analysis. Evidence suggests considerable income diversification over the reference decade, but distribution of shares suggests that top most quintile draw almost all of the benefits of recent economic growth in India. The economic linkage between the RNFE and rural wage rates has reduced and almost not existent during the later reference year in analysis.
Key Words: rural nonfarm employment (RNFE), Labor shares, changeover 1993-4 and 2004-5, income productivity, wage determination, Rural India
Tuesday, December 8, 2009
The Future Shock Revisited: India should Lead not Plead Climate Change Negotiations
It was 1970 when Alvin Toffler’s book Future Shock shook the imagination of millions in developing countries as to how the western way of life and markets threatened the future of humanity. His shock was emanated not only from the western ‘waste’ or ‘greed’ but also from the ‘pace of change that took place’ since the second war and great depression – in other words the miracle of the free market. It is the same free market that we are now after to seek solutions for mitigating the impact of climate change; while the same western economies are contemplating ‘punitive’ carbon tariffs and taxes which can threaten the very development of the developing societies. Market disorientation and not just a psychological one, is round the corner which threatens the very development of emerging India.
At the turn of 21st century we are at the verge of another ‘Shock’ that will be felt directly not by us but our progeny. The scientists say that the current CO_2 emission concentration has reached 430 parts per million in 2008 which is 17% higher than 280 ppm before the industrial revolution. Such a fast change and given much larger and faster industrialization process it is likely to cross over 1200 ppm by the end of this century which can lead to 50C increase in global temperature. Note that the world have experienced about as much, 50C increase in temperature since the ice age which was long-long ago. Thus we are at the verge of another ‘Future Shock’ that too with ‘the pace of change that we have never ever experienced in the past’.
India’s position in global climate change can be gauged through two well researched numbers:
Comparative Energy Use Criteria: It is estimated that in 2005 India needed 201 Kgs per capita of coal equivalent to sustain its overall economy. Compare this with the USA which expended 60 time more coal equivalent energy per capita than India; The UK, Germany and USSR did about 30 times more; and , Brazil, China and Turkey about 3 time more compared with what India used.
The second comparison is of the direct CO_2 Emissions: India contributes just about 2 tonnes of CO_2 equivalent per person, compared with Australia and USA which contributes over 12 times more; Japan and the EU about 5 times, and China and Brazil about 3 times more than India. Even in such an outcome measure India stands out to be inconsequential. A good comparison however is between China and USA. While China, being most populous in the world, adds a total of 7.2 billion tonnes of CO_2 in absolute terms, and the USA adds 7.1 billion tonnes due to very high per capita use. India with least amount of percapita emissions does add 1.9 billion tonnes of CO_2 in absolute measure due to the second highest population size. On the other hand Australia which has the highest per capita amount contributes just about one half of a billion tonnes.
The evidence that India is not a delinquent yet and its contribution to the global pollution is probably the least measured through both the ‘use’ and ‘outcome per capita’ terms gets somewhat dented when absolute contribution is looked into. This absolute contribution is what makes India an important player in the game of climate change, and it should use this as an opportunity. Although India is an economy which is trapped between the first wave (agricultural revolution) and the second wave (industrial revolution); it has shown its mark even in the third wave (IT based super industrialization) of economic growth. India appears unique where two-thirds labor force is trapped in farming and unorganized sector employment; but has fairly large industrial and manufacturing base (notwithstanding cars and steel) yet also in the forefront of services sector growth which now contributes closer to 60 % of GDP. No country on the earth faces all these three different economic growth phases that too at the same time! Large number of households follows sedentary agrarian lifestyle, burning wood, consumption of barely processed cereals; self produced food and other local items and so on; while at the same time India is now considered one of the largest market for modern goods and services. Indian enigma and puzzle continue in this modern age as well.
Now the Dharma Sankat is who should share the burden of global warming. It appears fair and logical that the per capita basis should be the benchmark; but there is danger lurking that Lord Brahma can get annihilated sooner than later. Since the Copenhagen Summit is more likely to put some acceptable benchmarks for the future policies, it is important for India to be leading rather than pleading. It is neither a matter of national shame nor will it mean abrogating national sovereignty to take a proactive role in international negotiations by announcing a willingness to do our bit to the World unilaterally. While doing so it is common and often needed to seek partners and promote coalitions and in this case it appears it is India, China, Brazil, USA and possibly Russia. Note that India has done well by partnering with both erstwhile superpowers – (USA and Russia notwithstanding continuing rivalry between the two) through respective nuclear deals which are complimentary and benefitting India. In my view it is the farsightedness and firmness of Dr. Manmohan Singh that has prevailed in these missions not only to withstand the domestic opposition, but also negotiating with the outside world while keeping the interest of the poor and industry at the same time. If this is not a cleaver tight rope walking success then what else can it be? It would be fair to ask the opposition voices within the Indian Parliament not to behave like sulking kids while unaware of the pressures of future energy needs and responsible global partnerships in issues as sensitive as climate change.
Note that not far ago, it was India who took a firm stand against opening of the Indian Agriculture almost stalling the relevance of Doha round of WTO negotiations. It is difficult to judge whether this stand is good or bad, but a stand was taken which has maintained the statusquo with respect to the subsistence agriculture. But the weakness of India is in its ignorance - we have little if at all research and knowledge about our own way of life including way of production, consumption and sustenance of life. This can also be said about as to how we are drawing upon resources to meet the energy needs. India must take a lead in generating knowledge through research on as to how to mitigate and arrest the adverse impacts of global warming. India indeed can be a laboratory for assessing climate change impact on a range of agro-climatic and geographical regions since it is one of most diverse country on earth so far as natural formations are concerned.
There is a growing debate that large climate changes are already underway through global warming, and that it adversely affects agriculture, food security and sustainability of long term growth in India and other parts of South Asia. The evidence is an increase in levels of temperatures which could cause havoc in physical systems for example, by disappearing glaciers in the Himalayan mountain range which could flood large tracks of cultivable lands in the foot hills and indo-gangetic plains of northern India. The warming on the other hand can be increasing the occurrence of drought and depletion of arable land in the Deccan plateau. Besides, the global causes which are increasing average temperatures even in South Asia, common practices such as increasing use of fossil fuels, burning of wood and biomass for domestic use, and also fast pace of deforestation is enhancing adverse effect of climate change in both physical and biological systems in this region. Indiscriminate overexploitation of ground water for cultivation has become one of the major problems facing Indian agriculture during the recent years. It is therefore important to find out if there are processes or programs which are intended to mitigate the impact of climate change or identify parameters which will help devise adaptation strategies to overcome adverse impact of climate change.
There is a need to conceptualize and devise a comprehensive ‘natural resources framework (NRF)’ which will encompass both exogenous and endogenous relationships and facilitate assessment of the net effects between economic activities and climate change. The literature consists of a number of approaches to measure the forward link namely economic impacts of climate change but not the endogenous association of climate change due to enhanced economic activity. Climate change resulting from human causes has been increasing during the past few decades (United Nations Environment Program, 2007), especially due to human and animal activity, and change in land use patterns such as multiple cropping, alternative use of land such as deforestation for crop cultivation, and urbanization and so on. Further, there are factors known as ‘feedbacks’ that amplify or reduce effects on climate change; for example conflicting role of ‘water vapor’ on agricultural production. It would be appropriate in this context to assess the role of mega government work program namely the National Rural Employment Guarantee Scheme. The nregs linked manual labor inputs are being used to sustain and create for example small water bodies, undertake rain water harvesting and appropriately mend the water flow of streams and brooks so as to improve the micro-water sheds across rural India.
In this connection we can further explore if we have a record of practices that promote pollution and ill health; either due to our cultural practices or sheer poverty, and lack of modern knowledge including limited infrastructure and so on. Practically all our energy (electricity) needs are met by burning cheap and bad quality coal, our hearths are warmed up burning wood and agricultural residue, inefficient technologies are used to drain the ground water table causing desertification of large tracks of farming land and also causing salination in the coastal areas. We already are experiencing pressures on access to potable water even in such places which hitherto considered easy sources in our forest areas. Whether, all these cause and effects are due to climate change or not is not what we need to be debating about, but as to how to address these issues for our own good, lest climate change accentuates already prevailing adverse effects.
It is important also to know that we are not alone in this world of 7 billion and growing. The El Nino/La Nina effect of southern Pacific can reach as far as India and this natural phenomenon has been scientifically validated. There is no reason to suspect that ‘climate change’ is not going to affect us Indians in a global context. Then let us build upon the national pride and economic might that India has acquired during last two decades, and be a change agent and leader in the context of Copenhagen not be apologetic about it.
At the turn of 21st century we are at the verge of another ‘Shock’ that will be felt directly not by us but our progeny. The scientists say that the current CO_2 emission concentration has reached 430 parts per million in 2008 which is 17% higher than 280 ppm before the industrial revolution. Such a fast change and given much larger and faster industrialization process it is likely to cross over 1200 ppm by the end of this century which can lead to 50C increase in global temperature. Note that the world have experienced about as much, 50C increase in temperature since the ice age which was long-long ago. Thus we are at the verge of another ‘Future Shock’ that too with ‘the pace of change that we have never ever experienced in the past’.
India’s position in global climate change can be gauged through two well researched numbers:
Comparative Energy Use Criteria: It is estimated that in 2005 India needed 201 Kgs per capita of coal equivalent to sustain its overall economy. Compare this with the USA which expended 60 time more coal equivalent energy per capita than India; The UK, Germany and USSR did about 30 times more; and , Brazil, China and Turkey about 3 time more compared with what India used.
The second comparison is of the direct CO_2 Emissions: India contributes just about 2 tonnes of CO_2 equivalent per person, compared with Australia and USA which contributes over 12 times more; Japan and the EU about 5 times, and China and Brazil about 3 times more than India. Even in such an outcome measure India stands out to be inconsequential. A good comparison however is between China and USA. While China, being most populous in the world, adds a total of 7.2 billion tonnes of CO_2 in absolute terms, and the USA adds 7.1 billion tonnes due to very high per capita use. India with least amount of percapita emissions does add 1.9 billion tonnes of CO_2 in absolute measure due to the second highest population size. On the other hand Australia which has the highest per capita amount contributes just about one half of a billion tonnes.
The evidence that India is not a delinquent yet and its contribution to the global pollution is probably the least measured through both the ‘use’ and ‘outcome per capita’ terms gets somewhat dented when absolute contribution is looked into. This absolute contribution is what makes India an important player in the game of climate change, and it should use this as an opportunity. Although India is an economy which is trapped between the first wave (agricultural revolution) and the second wave (industrial revolution); it has shown its mark even in the third wave (IT based super industrialization) of economic growth. India appears unique where two-thirds labor force is trapped in farming and unorganized sector employment; but has fairly large industrial and manufacturing base (notwithstanding cars and steel) yet also in the forefront of services sector growth which now contributes closer to 60 % of GDP. No country on the earth faces all these three different economic growth phases that too at the same time! Large number of households follows sedentary agrarian lifestyle, burning wood, consumption of barely processed cereals; self produced food and other local items and so on; while at the same time India is now considered one of the largest market for modern goods and services. Indian enigma and puzzle continue in this modern age as well.
Now the Dharma Sankat is who should share the burden of global warming. It appears fair and logical that the per capita basis should be the benchmark; but there is danger lurking that Lord Brahma can get annihilated sooner than later. Since the Copenhagen Summit is more likely to put some acceptable benchmarks for the future policies, it is important for India to be leading rather than pleading. It is neither a matter of national shame nor will it mean abrogating national sovereignty to take a proactive role in international negotiations by announcing a willingness to do our bit to the World unilaterally. While doing so it is common and often needed to seek partners and promote coalitions and in this case it appears it is India, China, Brazil, USA and possibly Russia. Note that India has done well by partnering with both erstwhile superpowers – (USA and Russia notwithstanding continuing rivalry between the two) through respective nuclear deals which are complimentary and benefitting India. In my view it is the farsightedness and firmness of Dr. Manmohan Singh that has prevailed in these missions not only to withstand the domestic opposition, but also negotiating with the outside world while keeping the interest of the poor and industry at the same time. If this is not a cleaver tight rope walking success then what else can it be? It would be fair to ask the opposition voices within the Indian Parliament not to behave like sulking kids while unaware of the pressures of future energy needs and responsible global partnerships in issues as sensitive as climate change.
Note that not far ago, it was India who took a firm stand against opening of the Indian Agriculture almost stalling the relevance of Doha round of WTO negotiations. It is difficult to judge whether this stand is good or bad, but a stand was taken which has maintained the statusquo with respect to the subsistence agriculture. But the weakness of India is in its ignorance - we have little if at all research and knowledge about our own way of life including way of production, consumption and sustenance of life. This can also be said about as to how we are drawing upon resources to meet the energy needs. India must take a lead in generating knowledge through research on as to how to mitigate and arrest the adverse impacts of global warming. India indeed can be a laboratory for assessing climate change impact on a range of agro-climatic and geographical regions since it is one of most diverse country on earth so far as natural formations are concerned.
There is a growing debate that large climate changes are already underway through global warming, and that it adversely affects agriculture, food security and sustainability of long term growth in India and other parts of South Asia. The evidence is an increase in levels of temperatures which could cause havoc in physical systems for example, by disappearing glaciers in the Himalayan mountain range which could flood large tracks of cultivable lands in the foot hills and indo-gangetic plains of northern India. The warming on the other hand can be increasing the occurrence of drought and depletion of arable land in the Deccan plateau. Besides, the global causes which are increasing average temperatures even in South Asia, common practices such as increasing use of fossil fuels, burning of wood and biomass for domestic use, and also fast pace of deforestation is enhancing adverse effect of climate change in both physical and biological systems in this region. Indiscriminate overexploitation of ground water for cultivation has become one of the major problems facing Indian agriculture during the recent years. It is therefore important to find out if there are processes or programs which are intended to mitigate the impact of climate change or identify parameters which will help devise adaptation strategies to overcome adverse impact of climate change.
There is a need to conceptualize and devise a comprehensive ‘natural resources framework (NRF)’ which will encompass both exogenous and endogenous relationships and facilitate assessment of the net effects between economic activities and climate change. The literature consists of a number of approaches to measure the forward link namely economic impacts of climate change but not the endogenous association of climate change due to enhanced economic activity. Climate change resulting from human causes has been increasing during the past few decades (United Nations Environment Program, 2007), especially due to human and animal activity, and change in land use patterns such as multiple cropping, alternative use of land such as deforestation for crop cultivation, and urbanization and so on. Further, there are factors known as ‘feedbacks’ that amplify or reduce effects on climate change; for example conflicting role of ‘water vapor’ on agricultural production. It would be appropriate in this context to assess the role of mega government work program namely the National Rural Employment Guarantee Scheme. The nregs linked manual labor inputs are being used to sustain and create for example small water bodies, undertake rain water harvesting and appropriately mend the water flow of streams and brooks so as to improve the micro-water sheds across rural India.
In this connection we can further explore if we have a record of practices that promote pollution and ill health; either due to our cultural practices or sheer poverty, and lack of modern knowledge including limited infrastructure and so on. Practically all our energy (electricity) needs are met by burning cheap and bad quality coal, our hearths are warmed up burning wood and agricultural residue, inefficient technologies are used to drain the ground water table causing desertification of large tracks of farming land and also causing salination in the coastal areas. We already are experiencing pressures on access to potable water even in such places which hitherto considered easy sources in our forest areas. Whether, all these cause and effects are due to climate change or not is not what we need to be debating about, but as to how to address these issues for our own good, lest climate change accentuates already prevailing adverse effects.
It is important also to know that we are not alone in this world of 7 billion and growing. The El Nino/La Nina effect of southern Pacific can reach as far as India and this natural phenomenon has been scientifically validated. There is no reason to suspect that ‘climate change’ is not going to affect us Indians in a global context. Then let us build upon the national pride and economic might that India has acquired during last two decades, and be a change agent and leader in the context of Copenhagen not be apologetic about it.
Sunday, September 20, 2009
Gender Empowerment in India: Concepts and Measurements
I: INTRODUCTION
A lot is now spoken and written about the need for gender sensitive inclusive development in developing economies such as India (GOI, 11th plan document, GOI, 2009). The gender sensitivity was heralded to be essential in assessing social and economic development by the UNDP which computes a ‘human’ and another ‘gender (adjusted) development’ index, and presents a conceptual scheme on ‘gender empowerment measure’ (HDR 1995). In the following we present a set of variables which integrate both the ‘gender adjustment’ and ‘empowerment measures’ and compute a single ‘gender empowerment index (GEI)’. The GEI further eliminates three constraints the UNDP concepts face, firstly that the GEI aggregates multi-dimensional concepts and dimensions of empowerment; secondly the variables are socio-culturally sensitive to India; and that the new index can be estimated not only at the level of a nation but also at the level of states and lower level of geographic units within a country.
Practically all countries in the world that are identified as ‘developed’ are in unison for having provided equality of opportunity and access to women in all spheres of economy, society and polity. Such inclusiveness was possible not only through formal legal provisions but also as a matter of democratization of political system. Further, the process of inclusiveness of women in development was concurrent to increase in real incomes of households which was controlled and managed by women themselves; often such income was individually earned by them. In the context of developing societies such as the democratic India, where patriarchal social values are still in vogue, understanding women’s empowerment is somewhat complicated. Given a large canvas of social, economic, political and household level dimensions, empirically measuring women’s contributions across India and many States is not easy. This paper identifies the core concepts that are socio-culturally relevant and uses the empirical measures to compute a Gender Empowerment Index (GEI) for the mid-period of first decade in 21st century. The variables identified are those which capture the essence of the six main dimensions which together define gender empowerment efficiently, namely; (i) women’s level of human capital formation, (ii) women work participation, (iii) women’s capacity for household decision making, (iv) women’s control over resource and self assertion, (v) women’s control over reproduction, and (vi) woman’s political participation.
What follows in section 2 is a description of the generic concepts relating to empowerment found in literature; the gender relevance in the Indian context or a conceptual framework within which gender empowerment is articulated in section 3. Section 4 introduces the dimensions which encompass gender empowerment and the variables which help measure them; and estimates of the index values and state ranks as well as ranks according to social and economic characteristics are discussed in section 5. Section 6 concludes and discusses policy implications.
II: GENERIC CONCEPTS AND EMPOWERMENT
International literature on gender often highlights an important facet of societal decision making namely agency which is a desire and ability of the society and households to delegate responsibility to woman so that they take decisions independent of men and traditional- institutional support. The role of women's agency in the expansion of social opportunities for both women and men is considered to eliminate gender inequality (Dreze and Sen, 1999, 2000). Empirical research has found out that household decision attributed to women especially when interacted with education yield better human capital formation through investments in children’s education and health and also reduce gender bias (Schultz 1995, Shariff 1995. Another evidence has been feminization of agriculture, in the Indian context the skeptics use this as an evidence of distress but one can look at this phenomenon as empowerment of women instead (see Duvvury 1998, Shariff 2009). A related issue is of control - over resources (http://www.un.org/womenwatch/); for example, women normally use number of resources but they do not own or have control over them. For example, research highlights as to how little control women have over resources; none at all in case of land and only limited control over food crops for example in Uganda (FAO, 2008). The situation in India is not be any better in this regard since the rules of asset ownership is governed by complicated patriarchic system of inheritance and also because women move over husband’s place of co-residence after marriage . In its first ever gender gap study covering 58 nations, the World Economic Forum (http://www.weforum.org/) ranked India a lowly 53. Titled 'The Women's Empowerment: Measuring the Global Gender Gap', the report measures the gap between women and men in five critical areas namely economic participation, economic opportunity, political empowerment, access to education and access to reproductive health care.
Since the gender dimensions are far too many and condition of women varies according to different social, economic and political settings, it is not ordinarily possible to standardize the number and type of variables, measurements and framework of analysis to be used. The UNDP methodology of international comparisons chose variables that are easy to collect and but at high levels of aggregation such as a country. Although many countries are adopting the UNDP method to create disaggregated measures at lower geographic units, it is argued in this paper that these efforts do not adequately capture the socio-cultural context of the gender empowerment within a nation. Any adaptation therefore should take the conceptual relevance and application inherent in choice of variables and its national level appropriateness in to account.
The framework of analysis and choice of variables in this paper are guided by the evolving ideas on gender deprivation over time (more below) as well as availability of dependable data to empirically estimate gender empowerment at the level of the states. The six gender dimensions identified broadly conform to the generalized gender empowerment framework for India enunciated below. The choice of variables and measures are compatible for similar estimation even at lower levels of geographic/ administrative units such as the districts within a state in India. In this regard it is important to state that since the UNDP considers elected representatives in the parliamentary and assembly levels as the proxy for gender empowerment, these indicators are not suitable benchmarks if one is considering disaggregated level analysis. In the Indian case, appropriate indicator is intensity of participation of women in local level institutions such as the panchayats and nagrpalikas; and since over 17 years of democratic decentralization through the 73rd and 74th Indian Constitutional amendments, such data are available to academic use. Since August 2009 it is mandatory to compulsorily elect women for fifty per cent of the panchayat membership posts in India. Unlike all other variables in this paper which are extracted from unit level records, information on political participation is accessed from relevant departments of the government of India.
Alternative Analytical Frameworks
A number of analytical frameworks are in vogue for undertaking a gender enriched analysis; the prominent are identified below . The frameworks are not mutually exclusive and there is ample scope for academics to formulate new analytical models so as to contextualize the country specificity and / or incorporate socio-culturally relevant new data. The following listing is arranged in a broad chronological order although the refinements in the concepts and frameworks are a continuous process.
UNDP’s Gender Empowerment Measure: Assessments and measures to evaluate bias based on sex of individual was in vogue in research amongst the applied economists, sociologists and demographers since long, yet what made the gender discrimination prominent knowledge was the UNDP’s human development index which brought sex-differentials to fore in parameters such as literacy and health outcomes through the Human Development Reports, the first of its kind published in 1991. Subsequently in 1995 the UNDP formalized the gender dimension by computing a separate ‘gender adjusted index’ and expanded the scope not only to understand gender bias in common parameters but also to assess ‘gender empowerment’ using the political, economic and societal factors of highest order. But the UNDP’s choice of variables capture empowerment at a high level of geographic aggregation and less conducive for disaggregated measures at states, districts and other social and economic criteria.
Gender Roles Framework: An analytical framework developed by the Harvard Institute of Development, is a grid for collecting data at the micro-level, mapping the productive and reproductive work of men and women in a community, and highlighting the differences between them. This approach utilizes a number of tools such as, an activity profile, an access and control profile of resources and benefits, and lists influencing factors. This framework :-
• argues for an economic case for allocating resources to women as well as men, what is known as the efficiency approach to gender and development;
• resources, not power relations, are central to this approach;
• adapts well to an analysis of agriculture or other rural production systems; and
• relies on micro-level analysis and data collection at the household/individual level.
Gender Planning Framework: Developed by Moser (1994) this framework links the examination of women’s roles to the larger development process and questions the assumption that planning is a purely technical task. It employs three main concepts; women’s triple role of productive, reproductive, and community work; and practical and strategic gender needs. This approach:-
• disaggregates control of resources and decision-making within the household;
• uses concept of triple role and analyzes linkages between them; and
• conceptually focus on emancipation of women from their subordination.
Social Relations Approach: Developed by Kabeer (1994), this approach uses concepts instead of tools to concentrate on the relationships between people, their relationship to resources and activities, and how these are re-worked through the institutions of state, market, community, and family. More recently the institutional linkages for gender empowerment are well argues in global context for example in Roy et. al., (2008). one finds The framework helps to examine social institutional parameters that explain how gender inequality is formed and reproduced at the individual level leading to inequalities. This approach utilizes qualitative and contextual information which is often difficult to quantify.
• The framework concentrates on institutions and challenges the ideological neutrality and independence of institutions;
• links institutional analysis at all levels;
• views development as a process for increasing human well-being; and
• employs a holistic analysis of poverty, recognizing the cross-cutting inequalities of class, race, ethnicity and so on.
Gender Analysis Matrix: Developed by Parker (1998), this method attempts to determine the differential impact development interventions have on women and men, by providing a community-based technique for identifying and analyzing gender differences. It supports -
• participatory approach/fosters bottom-up analysis and qualitative in nature;
• use community for self-identification of problems and solutions;
• excludes macro-and institutional analysis; and
• capture change over time but through repetition of the analysis.
Since the UNDP’s efforts to sensitize the gender issues has been commendable and also the one with very high reach and visibility, it is quite normal to benchmark any further work on it. However, this present paper is aligned more with the other frameworks enunciated above, since it focus on empirical measurements within in social and economic contexts, and suitability of variables for disaggregated assessment.
The UNDP spearheaded the concept of human development and undertook gender oriented empirical adjustments to create a parallel index known as Gender-related Development Index (GDI) (HDR 1991). Further, in 1995 it also gave a methodology to compute a ‘gender empowerment measure’ (GEM). The GEM uses a set of variables namely, (1) seats in parliament held by women (% of total), (2) female legislators, senior officials and managers (% of total), (3) female professional and technical workers (% of total), (4) estimated earned income of women, and (5) women’s share of population (Human Development Report, 2004). Thus GEM attempts to capture women’s participation in higher political office (political empowerment), employment in high offices (economic empowerment), and macro-economic participation. Both the GDI and GEM indices, therefore, fail to capture socially and culturally sensitive factors which are relevant to assess gender empowerment amongst the masses in India. In fact the UN is unable to compute the GEM even for the all India level let alone for its many states due to want of appropriate data (HDR,????). The adaptation and recasting of the India GEM methodology undertaken by the ‘ministry of woman and child development’, Government of India could not eliminate these deficiencies in spite of efforts to rationalize the variables and data inputs in computation of GEM (GOI, 2009).
There are other critiques of the UNDP’s GEM as well. For example, Beteta (2006) argues that the UNDP concept do not account non-economic dimensions of decision-making and appear to measure empowerment only of the better-offs. Another critique argues that while normally the GDI & GEM are being used to highlight gender discrimination, but these measures do not reflect discrimination per se (Schuler, 2006), rather the GDI measures only the objective gender inequality when compared with the HDI. The GDI is not an independent and stand alone measure as it has to be interpreted always in conjunction of the HDI. There are also methodological issues relating to the estimations as found in Bhardan and Klasen (2000).
At the India level the report of the ministry of woman and child welfare, (GOI, 2009) do not isolate the socio-culturally sensitive factors that ideally measure woman’s empowerment amongst the Indian population. Rather it carries forwarded the UNDP suggested variables which are rather topical in nature and only captures very high and idealistic level of empowerment. Further the measures do not reflect the status linked to a specified state, for example, in India the national level services such as the IAS, IPS, the Judges and so on do not generally belong to the state of birth as matter of policy. Similarly, due to skewed prevalence of educational infrastructure, the professional women need not necessary belong to the state of their birth for practicing their services, rather they move over to places of higher demand and to megacities.
III: GENDER RELAVANCE IN THE INDIAN GROWTH CONTEXT
Establishing interlinks between economic growth, reduction of poverty and profiling livelihood opportunities is topical given the progressive context of ongoing economic reforms and global integration of economies. Drawing a gender perspective is essential as women stand at the cross road of economic growth and human development burdened with multiple activities in both reproductive and remunerative roles. Gender poverty is far bigger a challenge that confronts developing societies as much as the issues of equity. It is essential to recognize that although women and men are born equal, the changing social and agrarian structure, development policies and growth trajectories impact them differently. The socio economic dynamics reveal that while impact of growth processes have not been completely gender neutral, that of poverty and its deepening has had its worst impact upon women. It is well documented and acknowledged that women suffer most in conditions of deepening poverty and unless existing inequalities in opportunities, capabilities and differential rights are eliminated, the agenda of poverty reduction cannot be achieved. Female disadvantage reflected in unequal access to household resources, economic opportunities, household decision-making power and lack of control over reproduction or child care have large perpetuating intergenerational implications.
It is, therefore, essential to discuss gender disadvantage in a holistic framework, tracing the various facets of inequality and how poverty renders women doubly disadvantaged and vulnerable to economic shocks and adjustments. Refer to a diagrammatic presentation (Figure 1) of a ‘generalized framework’ explaining the factors which render women poor and the manifestation of it. These linkages may have substantial variation depending upon which state or region one lives in. It is well understood that inequalities originate from the household at very early stages of lifecycle continues to reflect in several social and economic spheres. The discussion therefore should revolve around the multiple dimensions of inequality and how poverty worsens the situation from a gender disaggregated perspective.
FIGURE 1 ABOUT HERE
Normally, since men being the sole breadwinners of the household had to go out and earn their living; they also have control over all resources and assets and the right to better nutrition, healthcare and education. Men, therefore, both at the household and community at large emerged as the decision makers and exhibit strong bargaining powers, favoring their own interests. Gradually this logical following of things matured and because of males’ supreme command over assets, particularly land and other economic resources resulted in increasing gender inequality. Women all along derived their identity through their kinship and household relationships. There is a vicious circle where things originated and went wrong because of the influence of socio cultural stereotypes and poverty has had a compounding impact.
With the passage of time, when women increasingly took to education and economic activities, such participation stood in conflict with the dominant socio cultural practices. Subsequently, all growth and adjustment processes have neglected the issue of gender or rather touched upon marginally and failed to recognize women as potential partners. Whereby, in conditions of inequality and deepening poverty, women have had to bear the brunt of it, balancing both reproductive and remunerative activities. Gradually what was considered a way of living took different forms and some of these inequalities; unequal access to food, nutrition, healthcare, market seclusion and voicelessness of women has become resilient to change.
Household and Market Gender Relationships: In examining the gender relationships at the household level, it is observed that nutrition biases are in favor of men and boys in the family. This pattern is aggravated in conditions of scarcity arising out of cyclical seasonal effects and differential entitlements wherein women and girls eat less and last as a coping devise. Although women are responsible for ensuring food security of the family, they themselves are the most food insecure. This results in under nourishment of women in their reproductive age and young girls. For women, poor nutrition, severe anemia levels and poor quality or nonexistent reproductive health services contribute to high maternal mortality and low child survival.
Such biases are observed in healthcare systems as well. Women have lesser access to healthcare services. They rarely seek health services during sickness or ill health compared to men. This is yet another expenditure saving mechanism. Health seeking behavior of females is also guided by their educational levels whereby they are informed and understand the necessity to be healthy. Women in rural areas are more vulnerable to respiratory disease owing to their prolonged exposure to harmful and toxic fuels and gases. Women are at greater risk of disease and morbidity living in unhygienic conditions, which lack sanitation and access to pure drinking water, as observed in growing urban slums.
There has been a lot of advocacy in ensuring female education and employment is considered critical means of liberation. Although reducing female illiteracy has been part of every development agenda, there exist strong biases against female education and more so continuation in school. It is also true that although girls are sent to school at an early age, their continuation rates are poor compared to boys. Often it is the poor penetration of schools in rural areas that deter parents from sending their daughters to schools at far off distance. Again given the restricted opportunities in the labor market, the alternative is better to save upon the resources spent in educating a girl for marriage. When poverty strikes, girls are withdrawn from school such that their male siblings can continue. Also in families where the mother is engaged is some wage work to eke out a living, young girls are kept at home to take care and nurse their younger sibling or else join their mothers to contribute to the family pot.
Division of labor is highly skewed to the disadvantage of female and more so poor women are caught in a double whammy; balancing both reproductive and productive activities. Although globalization had broadened employment opportunities in most of the developing countries, it has set in trends of informalisation and women have been increasingly a part of it. Although women form a large part of the labor force, most of them are tied to the lower rungs. There is an increasing trend of feminisation of informalisation of the labor force. The informal sector is characterized by low wages, no contract and no fixed workplace. Women who are not educated enough and lack skills form part of this informal workforce. This has added to their workload, the returns from which are not at all remunerative. Often it is the economic distress that compels them to join the labor force and does not help them in enhancing their well being. As found in rural agrarian communities, women work either as unpaid family laborers or agricultural laborers as opposed to men who enjoy ownership rights. Despite the fact that the agrarian structure is undergoing enormous diversification and the role of women in dairying, fishing, horticulture can be improved; the efforts lack the appropriate gender sensitiveness. Although empirical evidences suggest that women through self help groups and community management approaches can lead in some of these spheres, the progress is too slow.
It is common practice that women have less access to ownership of land, credit and other productive resources. The law of inheritance in a south Asia study found men’s supreme command over land rights. Women derive their land rights by virtue of their relationship with men and have barely any role in using it as a resource. In agricultural communities, men are the landlords and own the assets as well as revenue accruing from land based activities. Women mostly work as wage or family labor and do not enjoy entrepreneurial rights. Differential access to credit has its roots in land ownership, wherein land is used as a mortgage for loans and it is only men who have the benefit of using it to access credit facilities. Hence women have very little access to credit which impedes their participation in any kind of technological innovation critical for agricultural growth. The self-help group approach to micro credit has mixed results in India unlike its roaring success in Bangladesh. Unequal access to resources has resulted in limited and restricted participation of women in both farm and non-farm activities.
Gender gaps in education, health care and employment opportunities have resulted in the voiceless of women in decision making and bargaining for a better livelihood. This has rendered women poorer and more vulnerable to shocks and adjustment processes. Inequality and poverty are two reinforcing elements and is seen as aggravating one another. In other words, unequal access to resources and opportunities is the major obstacle to women’s economic liberation and opportunity to break free from the poverty trap. Similarly, poverty aggravates inequality wherein female in early stages of their life cycle adopt expenditure saving mechanisms such as eat less, drop out of schools and live unhealthily life and as women take to income earning measures by taking up any low paid insecure odd jobs.
Modern economic reforms and associated dynamics with respect to work and income earning mechanisms are promoting empowerment of women even in rural areas of India. Besides remittances promote participation of women in agriculture which in turn improves agriculture productivity and household income. The new evidence suggests considerable increase in rural income from remittances (Shariff, 2009) due to an increase in rural-rural and rural-rural migration within India (WDR, 2009). Gender empowerment has received strong empirical support across the globe since it further enhances investments in education, health and nutrition that build stock of physical capital formation, thereby yielding durable poverty alleviating effects. Therefore, it is important to bring to fore the fact, that even in India the formative abilities of women are being enhanced due to higher education, participation in workforce, democratic participation and learning from programs such as micro-credit and national rural employment guarantee scheme. It is imperative, therefore, that women demand a rightful place in household and societal level decision making. Figure 2 below provides a pictorial depiction of gender empowered economy in India.
IV: GENDER EMPOWERING CHARACTERISTICS AND MEASURES
After an understanding of the multi-dimensional general framework within which one need to understand gender issues and a number of approaches that are in vogue enunciated above; in the following we identify selected measurable characteristics which all together will form a comprehensive and wholesome ‘gender empowerment measure’. Since these entire variable set are empirically measurable, an index derived out of them is described as ‘gender empowerment index’, which will be a useful policy instrument to governments and civil society alike. Note that this index is a mix of the gender adjustment which UNDP’s GDI performs as well the gender empowerment measure; and conceptually measures empowerment of masses as opposed to a measure of higher order which is inherent in UNDP’s gender empowerment measure.
Conceptually the selected indicators measure empowerment within the contemporary Indian socio-economic outlook and compatible with the debate on mechanisms to reduce gender bias in society and political decision making. Note that the dimensions and factors used in this paper are very different from those identified by the Government of India (2009) which is aligned with the UNDP concept but weak data support of suspicious quality.
An empowered Indian woman is the one who is literate, works (often outside home) and contributes measurable household income, independently decides for example, as to what kind of food needs to prepared and ingredients to be purchased; do not wait for husband to seek paid care for a sick child, owns some property by herself and also manages a bank account. Above all she decides as to how many children she can bear as well as ensure full immunization of all her children. She executes her right to vote and also participates in local panchayats and committees.
Compare this with a concept in which she is an IAS/IPS officer or a judge in a High Court, or can also be doctor or an engineer, or someone who can borrow at least Rs. 2 lakhs from a bank, or an MP, MLA or a Panchayat president, have immovable property and so on. In such a measure the focus is on individual instead of societal achievements and therefore can be aggregated only at national level. On the other hand the multi-dimensional attributes can be created at lower geographic levels and they reflect empowerment of all women in specified locales.
There are also serious data problems in case of the UNDP linked GOI approach; for example, in India the top level services including judiciary have national relevance. At the level of the state, a women born and education elsewhere will normally be posted in a specified state, thus her empowerment do not reflect empowerment of women of that state. Similarly, a large number of professional for example get education in states where educational infrastructure is better and often begin to reside and work in that state. Under such circumstance the gender measures will over estimate the true level of empowerment and may go inimical to women in that state/district. Another measurement issue is that all the measures are to be accessed from secondary sources often of poor and questionable quality. On the other hand the alternative variables proposed are extracted from unit level records of large household surveys which are known to be dependable data for measurements of societal dynamics at least in India. Further the proposed concepts and method can estimate a ‘gender empowerment value/index’ at any level of disaggregation even upto a village level and also estimated can be separately provided for the rural and urban areas separately. The data occurrence and coverage of the universe is almost all women in a defined areas in case of the alternative set of variables; where as in case of the GOI recasted method only a miniscule proportion of women may be covered, for example, even at the state level women in top level services, judiciary and polity can be only a handful countable in single digits and s on.
Statement 1
Measuring Gender Employment in a Socio-Cultural Framework:
Multi-Dimensions and Variable Measures
Choice of Dimensions and Variable measurements
Dimensions Measures Source and Quality of Variables
Human Capital Adult (7+) literacy Estimated from a nationally representative survey of 41,554 households namely the Human Development (HDPI) 2004-05, undertaken by NCAER New Delhi.
Gender gap in literacy
Work Participation Work Participation Rate (15‐64 Year) Estimated from a nationally representative survey of 1,24,680 households namely the National Sample Survey (NSSO) of Employment and Unemployment, 2004-05.
Gender gap in WPR
Household Decision Making Capacity to decide matters alone relating to daily household purchases Estimated from a nationally representative survey of 1,09,041 households namely National Family health Survey (NFHS)–3 of 2005-06.
Capacity to independently undertake the decision for own health care NFHS- 3 (2005-06)
Eco. Resources /Assets Individual/shared ownership of immovable assets HDPI (2004-05)
Manage independent bank accounts NFHS-3 (2005-06)
Earned Cash wages as a regular salaried/wage employee NSS (2004-05)
Gender gap in wages as a regular salaried/wage employee
Earned Cash wages as a casual wage labor NSS (2004-05)
Gender gap in wages as a casual wage labor
Reproduction and Child Care Use of modern contraceptives NFHS-3 (2005-06)
Women having fully immunized children in ages 12-23 months NFHS-3 (2005-06)
Political Participation Cast their vote in the last general election Statistical Report on General Elections, 2004 (14th Lok Sabha) – Vol. I, Election Commission of India.
Gender Gap in the vote casting
Panchayat members Ministry of Panchayati Raj, Government of India: Number of women elected representatives in the three tiers of panchayats as on 31.03.2008 are available in the Annexure 1(A).
Thus, in the Indian context a comprehensive measure of gender advantage needs to incorporate indicators that capture culture-specific dimensions of agency and control over resources, through measures having relevance at the level of individual, household and society. Since aspects of gender empowerment are complex and multidimensional the variables and data needs are diverse and needs to be debated as to their appropriateness. Ideally the variables that measure a social situation and dimension should have the following qualities – (a) robust outcome indicators are the best; but since such indicators are difficult to gather and also as they change slowly, indicators highlighting the process and proximate to the concept of the index measure, in this case ‘gender empowerment’ can be used; (b) that the indicators are easy to collect and that they are collected from independent survey data rather than from service statistics which often lack quality; (c) easy to update frequently such as annually or at the most once in two years, for example, the NSSO undertake annual surveys and required data can therefore be collected, and (d) as much possible relevant to whole or majority of population.
We have identified six dimensions of which five dimensions extracts data directly from large sample surveys using the primary unit level records at the level of individual and households. A gender empowering dimension namely ‘political participation’ uses data from the government records since sample surveys so far have not collected information on these issues. All dimensions are aggregates of multiple measures and wherever appropriate incorporates gender gaps as well. The national sample surveys (NSS), national family health surveys (NFHS) and human development Surveys of the national council of applied economic research (NCAER) are well known data source in India.
(i) Human Capital (Education): Most commonly used human capital indicator, along with its gender gap captures human capital formation, namely, literacy. Absolute measures of female literacy amongst the population ages 7 years and above in percentage and the gender gap ratio are used to capture this dimension. Data from the human development survey of NCAER for reference year 2004-5 supplies data to measure literacy.
(ii) Female work participation: Female work participation rate and associated gender gap for adults 15-64 year was assessed using the ‘usual principal activity status’ (UPS) over a reference period of one year. Further the gender gap in work participation is also incorporated into the computation. A woman is classified as a participant in labor force, if she had been either working or looking for work during a longer part of 365 days preceding the survey. The UPS measure excludes from the labor force all those female who are unemployed and employed for a period of less than six months. The data are drawn from the 61st round employment and unemployment survey of the NSSO for the reference year 2004-05.
(iii) Household Decision Making: This is an aggregation of two variables namely, (a) women’s capacity of ‘making purchases for daily household needs’ and (b) women's participation in decision making for own health care, both extracted from NFHS-3 survey 2005-06 (www.measuredhs.com). The variables together measure women’s participation in decision making; those who usually make specified decisions on their own or independently. Those reporting joint decision making along with men or husbands are excluded from these measures. These variables selected to reflect woman’s capacity for independent decision making in the domain of household are well recognized even in studies undertaken in other developing economies around the world.
(iv) Economic Resources and Assets: Aggregates of two variables namely, women’s ownership of (a) immovable assets and (b) bank account are used to reflect her control over resources. The first variable is measured as the proportion of women who have their name on immovable properties owned or rented. Normally such names are incorporated on to the contract or registered property documents. For the first time such data have become available for all India and many states from the NCAER’s Human Development Survey -2004-5. Women having a bank / savings account are drawn from the NFHS-3 data set. Give that these data have longer-term relevance and are important aspects of households, both individually owned and jointly owned (along with husbands/other household members) are considered appropriate to reflect control of respective resources.
It is useful to state both these variables have become prominent in the Indian context in reflecting the independent nature of women and their empowerment. Besides a number of states in India have passed laws which favor joint (registration) ownership of land or properties which are rented. Often properties jointly owned are given tax concessions by law. So far as the ownership of bank accounts we bring the attention of the readers to the fact that the microfinance programs in India are over two decades old and upto 25 million households are enrolled into such program through the self-help group formations; and they are in a way enrolled in to a informal banking scheme. Further since about a year millions of bank accounts are opened in the names of women across India through a wage employment program known as ‘national employment guarantee scheme’. Thus there is a revolution of sorts which is enabling women even in rural areas to open and operate their own bank account. However the data used to assess these variable have the reference year 2004-5, and conditions during recent years are expected to more women friendly. Given this background these variables are India specific and they capture a dominant part of women’s empowerment.
(v) Reproduction and Care: This dimension is an aggregation of two variables, (a) one reflecting women’s capacity to choose and use a modern contraceptive method which is a reflection of control over reproduction; and (b) her capacity to ensure that her own children are completed with all essential dozes of immunizations. This second variable is constructed linking all children aged 12-36 months with the respondent women and identifying the completeness of all immunizations.
(vi) Political Participation: Participation of women in political sphere is indeed a dominant evidence of empowerment. For example, Indian historically has been in the forefront in this benchmark as it has had considerable world recognition when Mrs. Indira Gandhi was the Prime Minister of India. Contemporary situation has enabled Smt. Pratibha Patel to be the President of India, and another high position of the ‘Speaker’ of the Loksabha (lower house of parliament) is occupied by a woman. The list of world’s powerful women contains many more entries from India. In spite of such feat one finds the condition of women in India is deplorable, mostly due to strong patriarchy and men favoring social and public policies. Therefore, we believe what is relevant to capture the political empowerment of women in India is their participation in Indian democratic system. We capture these traits by using two variables whose data are available from government sources. Percentage of women exercising franchise during the last general election is one variable used and dependable data are available from the Election Commission of India. Another positive woman favoring policy in India has been the democratic decentralization of governance to a third tier identified as the Panchayats in rural areas and nagar palikas (municipalities) in urban areas. Percentage of women members in the panchayat councils is used to represent political participation in this indexing exercise.
V: GENDER EMPOWERMENT INDEX: Values and Rankings
This is an exercise to cumulate the multi-dimensionality of gender empowerment inherent in the six identified dimensions enunciated in the previous section and create an index at the level of the Indian states, economic standing and social identities, and place of residence. All six dimensions are considered equally important; for example literacy and work are two equally important attributes expressing pedagogy and economic independence. Similarly, control over physical assets, using banking services, independently taking routine household decisions as well as control over her own reproduction and take decision about child care are all equally important in expressing the power a women exercise so as to change her immediate environment to benefit her own welfare, and the derived welfare of the household. So is the ability of women to participate in political system especially in the modern context of decentralized democratization process especially in India. Therefore, we believe assigning equal weights to each of the six dimensions should be noncontroversial, also because one expects systematic improvements occurring concurrently across all these dimensions over a period of time. The variables chosen to reflect the above aspects of empowerment are carefully selected from across the multiple sources of data, and wherever necessary gender differentials are also factored in the computations. Normally the index values and rankings are created for over the time comparisons; it should not matter much as to what the definitions, measurements and weights (implied) are so far as they remain constant over time. Even assign equal weights, however, care must be taken by making all variables and dimensions scale free so that the level difference between selected variables do no influence the values and subsequent rankings. A comprehensive discussion about the scaling, normalization, weighing and indexing in the Indian context can be found in Kundu et. al (2007).
Gender Empowerment Index for Major Indian States:
The gender empowerment values/index and associated ranks for all six identified components/dimensions according to major sates of India can be found in Table 1 and the last column assigns a GEI ranking.. The upper and lower benchmarks for comparisons are taken from within the state distributions and therefore the absolute values are not comparable with other international benchmarks. Measuring empowerment requires country specific qualitative variables as described above and therefore no effort is made to undertake international comparisons although such indices can be crafter should a situation demands.
The GEI index values reflect the levels of achievement to the maximum possible of 1 and the least value being 0. Thus if a state takes the maximum value of 1 in six dimensions then the aggregated index value will be 1 which is the perfectly women empowered situation and if it is 0 then it is the worst scenario. At the All India level the overall GEI value has worked out to be 0.424 which is less than even the half of the level mark, and in the inter-state comparisons show the bottom most value is 0.238 recorded in Uttar Pradesh and the top most value is 0.646 for Kerala. We have categorized states in four segments taking the mean of all states as the first dividing line and further the mean of each segment as the other dividing line to distribute states in all four segments. This method of ordering states in segments provides useful analytical advantage. One can find that states with relatively better or ‘high GEI’ besides Kerala are Tamil Nadu, Maharashtra and Karnataka in that order, followed by Gujarat, Punjab, Andhra Pradesh, Haryana and West Bengal which can be considered as states with ‘moderate GEI’. States which have ‘low’ index are Orissa, Chhattisgarh and Madhya Pradesh; followed by the ‘very low GEI’ states namely, Jharkhand, Assam, Rajasthan, Bihar and Uttar Pradesh (refer Table 1). Refer also to a composite map (Map 1) and six other maps one each of the specified dimensions of empowerment identified in this empirical exercise (Maps 2- 7).
TABLE 1, 2 AND MAPS ABOUT HERE
In case of Gujarat while it ranks as low as 8th in human capital formation, it is on the top on ‘control over assets, and second on ‘capacity for household decision making’; but it ranks too low at 16th of the 17 states in political participation. On the other hand Kerala which is on top on human capital formation, but as low as 8th in household decision making as well as woman’s work participation and 6th in political participation.
Gender Empowerment Index according to Socio-Economic Categories:
The type of the data used allows estimating the GEI using the first five dimensions, since disaggregated data for woman’s political participation is not available, according to place of residence (rural or urban residence), socio-religious categories and economic groups based on per capita income quintiles (Table 2). It is surprising to note lack of GEI differential according to place of residence, namely the rural and urban areas; although we are aware that there are noteworthy gender differentials if only an absolute level of a particular variable is evaluated. Thus while there may be huge level differentials in the measurement of variables in absolute terms, when one takes the relative gender differentials it does not matter whether one resides in rural or urban areas, the gender bias seems as strong. This is a very important empirical finding.
Further the values and rankings are evaluated for economic classification and socio-religious groups and one notices some perfect association. The GEI index has a perfect match with the per capita income quintiles in such a way that relative economic prosperity indeed promotes gender empowerment. The only dimension which has inverse relationship from within the six considered is women’s work participation suggesting that poorer women work relatively more so as to supplement household income; yet overall economic prosperity promotes ‘gender empowerment’.
The data bases used, namely the national sample surveys, the NCAER’s human development survey and the national family health surveys contain variables that are amenable to create exclusive socio-religious categories which are generally so identified in day-to-day discourses in India. One finds considerable variations in the GEI according to the socio-religious categories as well. For example, it is residual others (minority religions other than Muslims but less than 5 % of population) category which has the highest value of 0.763 followed by the high caste Hindus with 0.675 and these two communities are class apart and reflect large inequity in society. The subsequent values are far too low at 0.410 for OBCs, 0.366 for SCs, 0.281 for the STs and least for Muslims at 0.276. There is a notion that the tribal communities offer fairly egalitarian social system which, but such common understanding and does not stand the empirical test, thus making ST women extremely vulnerable as well along with the SCs and the Muslims. The socio-religious exercise provides excellent leads for public policy formulation in the area of effecting group-equity in India.
VI: CONCLUSIONS AND POLICY IMPLICATIONS
It is common knowledge that the UNDP promoted the concept of human development index which is now widely used all over India. One finds that many states in India have brought out human development reports highlighting district level variations as well. We consider it useful to compare the state HDI ranks with the GEI estimated by us (see Table 3). There are a few unexpected relationships between the two in a few states. For example Assam and Uttar Pradesh have recorded relatively better HDI ranking compared with the GEI which are far too low. Other states with higher ranking differentials and having lower GEIs are Bihar, Haryana and Punjab. On the other hand state which have improved over their HDI rankings considerably are Maharashtra, Karnataka, Orissa, Jharkhand and Chhattisgarh. However, it will be instructive to know as to what factors have pulled the state of Assam and Uttar Pradesh considerably low in the GEI measures.
TABLE 3 ABOUT HERE
The correlation between the GHI and HDI rankings has worked out to be only 0.58 suggesting that HDI do not reflect the true gender vulnerability and therefore it is essential to create a separate series of data that reflect women’s empowerment. As mentioned earlier, we have used six dimensions and associated measures for which dependable data are available from sample surveys and government records. Although we believe that dimensions and variables chosen for this exercise are excettent and effecnint in capturing empowerment of women in India, one can add other concepts provided quality data are available so as to contextualize indexing to local situation and needs. Tt is most appropriate to create the gender indices as the level of districts, and according to socio-religions communities within the state for a better understanding of the problem of gender discrimination.
A number of policy implications will emerge from this research and a few of them are listed below:
• Enable policy makers to understand the process that facilitate empowerment of women.
• This research will enable recognition of the significant role gender empowerment play in improving incomes especially in rural areas and thereby poverty alleviation.
• Help formulate policy support to sustain empowerment of women, for example, through strategies to establish and sustain ownership rights, enhance participation in local governance and undertake market based activities.
• Promote fiscal and financial products which suits formation of household capital, assets and insurance against risks in rural areas of India.
• Effective policies can be designed to so that economic resources transferred through micro-credit programs can promote micro-enterprises and local markets.
• Promotes regionally balanced economic growth through wage and labor market effects especially factoring increased female participation in labor force.
We believe that this paper raises a major issue of appropriateness of the factors and measures that reflect gender empowerment and hope that the methodology presented will help generate an informed debate on the topic in India and other developing societies.
References:
Beteta, K. C (2006). ‘What is missing in measures of women’s empowerment?’, Journal of Human Development and Capabilities, 7 (2):221-241.
Bhardan, Kalpana and Stephan Klasen (2000). On UNDP’s revision of Gender-Related Development Index; Journal of Human Development, 1(2):191-195.
Dreze, J and A. Sen (2000): India Development and Participation (New York: Oxford University Press).
---- (1999): India Economic Development and Social Opportunity (New York: Oxford University Press)
Duvvury, Nata. (1998). ‘Women and Agriculture in the New Economic Regime’, in M. Krishnaraj, R. M. Sudarshan and A. Shariff (eds.), Gender, Population and Development, New Delhi: Oxford University Press.
Food and Agricultural Organization (FAO) (2008). ‘Women quantify lack of control over work resources’ UNEP/GRID-Arendal Maps and Graphics Library. (www.fao.org/) ( http://maps.grida.no/go/graphic/ women-quantify-lack-of-control-over-work-resources)
Government of India, (2009). Gendering Human Development Indices: Recasting the Gender Development Index and Gender Empowerment Measure for India; a summary report; New Delhi: Ministry of Woman and Child Welfare.
Kabeer, Naila (1994). Reversed Realities: Gender Hierarchies in Development Thought. Verso books.
Roy, Kartik, Hans Blomqvist and Cal Clark (2008). Institutions and Gender Empowerment in Global Economy, London: World Scientific Publishing Co. ltd., pp308.
Kundu, A., A. Shariff and P.K. Ghosh, (2007): ‘Indexing Human Development in India: Indicators, scaling and composition’ in A. Shariff and M. Krishnaraj (ed.), State, Markets and Inequalities: Human Development in Rural India, New Delhi: Orient Longman, pp44-89.
March, Candida., Ines, Smyth and Maitrayee Mukhopadhyay (1999). A Guide to Gender-Analysis Frameworks. UK: Oxfam.
Moser, Caroline O.N. (1993). Gender Planning and Development: Theory, Practice, and Training., London: Routledge.
Parker, Rani (1998).Gender Relations Analysis: A Guide for Trainers. Save the Children, USA.
Schluer, Dana (2006). ‘The use and misuse of gender related development index and gender empowerment measures: a review of the literature, Journal of Human Development and Capabilities. 7 (2):161-181.
Schultz, P (1995). Investment in Women’s Capital, Chicago: University of Chicago Press, pp641.
Shariff, Abusaleh (2009). Income and Employment Diversity in India: changes in rural nonfarm share between 1995 and 2005. Mimio, International Food Policy Research Institute, New Delhi.
Shariff, A and Namkee Ahn (1995). ‘Mother's Education Effect on Child Health: An Econometric Analysis of Child Anthropometry in Uganda’, The Indian Economic Review, 30(2):203-222.
UNDP (United Nations Development Programme). 2007. Human Development Report 2007/2008: Fighting Climate Change, New York: Oxford University Press.
Woman’s Watch, (http://www.un.org/womenwatch/);
World Development Report, 2009 (http://www.worldbank.org/wdr2009)
World Economic Forum (http://www.weforum.org/)
A lot is now spoken and written about the need for gender sensitive inclusive development in developing economies such as India (GOI, 11th plan document, GOI, 2009). The gender sensitivity was heralded to be essential in assessing social and economic development by the UNDP which computes a ‘human’ and another ‘gender (adjusted) development’ index, and presents a conceptual scheme on ‘gender empowerment measure’ (HDR 1995). In the following we present a set of variables which integrate both the ‘gender adjustment’ and ‘empowerment measures’ and compute a single ‘gender empowerment index (GEI)’. The GEI further eliminates three constraints the UNDP concepts face, firstly that the GEI aggregates multi-dimensional concepts and dimensions of empowerment; secondly the variables are socio-culturally sensitive to India; and that the new index can be estimated not only at the level of a nation but also at the level of states and lower level of geographic units within a country.
Practically all countries in the world that are identified as ‘developed’ are in unison for having provided equality of opportunity and access to women in all spheres of economy, society and polity. Such inclusiveness was possible not only through formal legal provisions but also as a matter of democratization of political system. Further, the process of inclusiveness of women in development was concurrent to increase in real incomes of households which was controlled and managed by women themselves; often such income was individually earned by them. In the context of developing societies such as the democratic India, where patriarchal social values are still in vogue, understanding women’s empowerment is somewhat complicated. Given a large canvas of social, economic, political and household level dimensions, empirically measuring women’s contributions across India and many States is not easy. This paper identifies the core concepts that are socio-culturally relevant and uses the empirical measures to compute a Gender Empowerment Index (GEI) for the mid-period of first decade in 21st century. The variables identified are those which capture the essence of the six main dimensions which together define gender empowerment efficiently, namely; (i) women’s level of human capital formation, (ii) women work participation, (iii) women’s capacity for household decision making, (iv) women’s control over resource and self assertion, (v) women’s control over reproduction, and (vi) woman’s political participation.
What follows in section 2 is a description of the generic concepts relating to empowerment found in literature; the gender relevance in the Indian context or a conceptual framework within which gender empowerment is articulated in section 3. Section 4 introduces the dimensions which encompass gender empowerment and the variables which help measure them; and estimates of the index values and state ranks as well as ranks according to social and economic characteristics are discussed in section 5. Section 6 concludes and discusses policy implications.
II: GENERIC CONCEPTS AND EMPOWERMENT
International literature on gender often highlights an important facet of societal decision making namely agency which is a desire and ability of the society and households to delegate responsibility to woman so that they take decisions independent of men and traditional- institutional support. The role of women's agency in the expansion of social opportunities for both women and men is considered to eliminate gender inequality (Dreze and Sen, 1999, 2000). Empirical research has found out that household decision attributed to women especially when interacted with education yield better human capital formation through investments in children’s education and health and also reduce gender bias (Schultz 1995, Shariff 1995. Another evidence has been feminization of agriculture, in the Indian context the skeptics use this as an evidence of distress but one can look at this phenomenon as empowerment of women instead (see Duvvury 1998, Shariff 2009). A related issue is of control - over resources (http://www.un.org/womenwatch/); for example, women normally use number of resources but they do not own or have control over them. For example, research highlights as to how little control women have over resources; none at all in case of land and only limited control over food crops for example in Uganda (FAO, 2008). The situation in India is not be any better in this regard since the rules of asset ownership is governed by complicated patriarchic system of inheritance and also because women move over husband’s place of co-residence after marriage . In its first ever gender gap study covering 58 nations, the World Economic Forum (http://www.weforum.org/) ranked India a lowly 53. Titled 'The Women's Empowerment: Measuring the Global Gender Gap', the report measures the gap between women and men in five critical areas namely economic participation, economic opportunity, political empowerment, access to education and access to reproductive health care.
Since the gender dimensions are far too many and condition of women varies according to different social, economic and political settings, it is not ordinarily possible to standardize the number and type of variables, measurements and framework of analysis to be used. The UNDP methodology of international comparisons chose variables that are easy to collect and but at high levels of aggregation such as a country. Although many countries are adopting the UNDP method to create disaggregated measures at lower geographic units, it is argued in this paper that these efforts do not adequately capture the socio-cultural context of the gender empowerment within a nation. Any adaptation therefore should take the conceptual relevance and application inherent in choice of variables and its national level appropriateness in to account.
The framework of analysis and choice of variables in this paper are guided by the evolving ideas on gender deprivation over time (more below) as well as availability of dependable data to empirically estimate gender empowerment at the level of the states. The six gender dimensions identified broadly conform to the generalized gender empowerment framework for India enunciated below. The choice of variables and measures are compatible for similar estimation even at lower levels of geographic/ administrative units such as the districts within a state in India. In this regard it is important to state that since the UNDP considers elected representatives in the parliamentary and assembly levels as the proxy for gender empowerment, these indicators are not suitable benchmarks if one is considering disaggregated level analysis. In the Indian case, appropriate indicator is intensity of participation of women in local level institutions such as the panchayats and nagrpalikas; and since over 17 years of democratic decentralization through the 73rd and 74th Indian Constitutional amendments, such data are available to academic use. Since August 2009 it is mandatory to compulsorily elect women for fifty per cent of the panchayat membership posts in India. Unlike all other variables in this paper which are extracted from unit level records, information on political participation is accessed from relevant departments of the government of India.
Alternative Analytical Frameworks
A number of analytical frameworks are in vogue for undertaking a gender enriched analysis; the prominent are identified below . The frameworks are not mutually exclusive and there is ample scope for academics to formulate new analytical models so as to contextualize the country specificity and / or incorporate socio-culturally relevant new data. The following listing is arranged in a broad chronological order although the refinements in the concepts and frameworks are a continuous process.
UNDP’s Gender Empowerment Measure: Assessments and measures to evaluate bias based on sex of individual was in vogue in research amongst the applied economists, sociologists and demographers since long, yet what made the gender discrimination prominent knowledge was the UNDP’s human development index which brought sex-differentials to fore in parameters such as literacy and health outcomes through the Human Development Reports, the first of its kind published in 1991. Subsequently in 1995 the UNDP formalized the gender dimension by computing a separate ‘gender adjusted index’ and expanded the scope not only to understand gender bias in common parameters but also to assess ‘gender empowerment’ using the political, economic and societal factors of highest order. But the UNDP’s choice of variables capture empowerment at a high level of geographic aggregation and less conducive for disaggregated measures at states, districts and other social and economic criteria.
Gender Roles Framework: An analytical framework developed by the Harvard Institute of Development, is a grid for collecting data at the micro-level, mapping the productive and reproductive work of men and women in a community, and highlighting the differences between them. This approach utilizes a number of tools such as, an activity profile, an access and control profile of resources and benefits, and lists influencing factors. This framework :-
• argues for an economic case for allocating resources to women as well as men, what is known as the efficiency approach to gender and development;
• resources, not power relations, are central to this approach;
• adapts well to an analysis of agriculture or other rural production systems; and
• relies on micro-level analysis and data collection at the household/individual level.
Gender Planning Framework: Developed by Moser (1994) this framework links the examination of women’s roles to the larger development process and questions the assumption that planning is a purely technical task. It employs three main concepts; women’s triple role of productive, reproductive, and community work; and practical and strategic gender needs. This approach:-
• disaggregates control of resources and decision-making within the household;
• uses concept of triple role and analyzes linkages between them; and
• conceptually focus on emancipation of women from their subordination.
Social Relations Approach: Developed by Kabeer (1994), this approach uses concepts instead of tools to concentrate on the relationships between people, their relationship to resources and activities, and how these are re-worked through the institutions of state, market, community, and family. More recently the institutional linkages for gender empowerment are well argues in global context for example in Roy et. al., (2008). one finds The framework helps to examine social institutional parameters that explain how gender inequality is formed and reproduced at the individual level leading to inequalities. This approach utilizes qualitative and contextual information which is often difficult to quantify.
• The framework concentrates on institutions and challenges the ideological neutrality and independence of institutions;
• links institutional analysis at all levels;
• views development as a process for increasing human well-being; and
• employs a holistic analysis of poverty, recognizing the cross-cutting inequalities of class, race, ethnicity and so on.
Gender Analysis Matrix: Developed by Parker (1998), this method attempts to determine the differential impact development interventions have on women and men, by providing a community-based technique for identifying and analyzing gender differences. It supports -
• participatory approach/fosters bottom-up analysis and qualitative in nature;
• use community for self-identification of problems and solutions;
• excludes macro-and institutional analysis; and
• capture change over time but through repetition of the analysis.
Since the UNDP’s efforts to sensitize the gender issues has been commendable and also the one with very high reach and visibility, it is quite normal to benchmark any further work on it. However, this present paper is aligned more with the other frameworks enunciated above, since it focus on empirical measurements within in social and economic contexts, and suitability of variables for disaggregated assessment.
The UNDP spearheaded the concept of human development and undertook gender oriented empirical adjustments to create a parallel index known as Gender-related Development Index (GDI) (HDR 1991). Further, in 1995 it also gave a methodology to compute a ‘gender empowerment measure’ (GEM). The GEM uses a set of variables namely, (1) seats in parliament held by women (% of total), (2) female legislators, senior officials and managers (% of total), (3) female professional and technical workers (% of total), (4) estimated earned income of women, and (5) women’s share of population (Human Development Report, 2004). Thus GEM attempts to capture women’s participation in higher political office (political empowerment), employment in high offices (economic empowerment), and macro-economic participation. Both the GDI and GEM indices, therefore, fail to capture socially and culturally sensitive factors which are relevant to assess gender empowerment amongst the masses in India. In fact the UN is unable to compute the GEM even for the all India level let alone for its many states due to want of appropriate data (HDR,????). The adaptation and recasting of the India GEM methodology undertaken by the ‘ministry of woman and child development’, Government of India could not eliminate these deficiencies in spite of efforts to rationalize the variables and data inputs in computation of GEM (GOI, 2009).
There are other critiques of the UNDP’s GEM as well. For example, Beteta (2006) argues that the UNDP concept do not account non-economic dimensions of decision-making and appear to measure empowerment only of the better-offs. Another critique argues that while normally the GDI & GEM are being used to highlight gender discrimination, but these measures do not reflect discrimination per se (Schuler, 2006), rather the GDI measures only the objective gender inequality when compared with the HDI. The GDI is not an independent and stand alone measure as it has to be interpreted always in conjunction of the HDI. There are also methodological issues relating to the estimations as found in Bhardan and Klasen (2000).
At the India level the report of the ministry of woman and child welfare, (GOI, 2009) do not isolate the socio-culturally sensitive factors that ideally measure woman’s empowerment amongst the Indian population. Rather it carries forwarded the UNDP suggested variables which are rather topical in nature and only captures very high and idealistic level of empowerment. Further the measures do not reflect the status linked to a specified state, for example, in India the national level services such as the IAS, IPS, the Judges and so on do not generally belong to the state of birth as matter of policy. Similarly, due to skewed prevalence of educational infrastructure, the professional women need not necessary belong to the state of their birth for practicing their services, rather they move over to places of higher demand and to megacities.
III: GENDER RELAVANCE IN THE INDIAN GROWTH CONTEXT
Establishing interlinks between economic growth, reduction of poverty and profiling livelihood opportunities is topical given the progressive context of ongoing economic reforms and global integration of economies. Drawing a gender perspective is essential as women stand at the cross road of economic growth and human development burdened with multiple activities in both reproductive and remunerative roles. Gender poverty is far bigger a challenge that confronts developing societies as much as the issues of equity. It is essential to recognize that although women and men are born equal, the changing social and agrarian structure, development policies and growth trajectories impact them differently. The socio economic dynamics reveal that while impact of growth processes have not been completely gender neutral, that of poverty and its deepening has had its worst impact upon women. It is well documented and acknowledged that women suffer most in conditions of deepening poverty and unless existing inequalities in opportunities, capabilities and differential rights are eliminated, the agenda of poverty reduction cannot be achieved. Female disadvantage reflected in unequal access to household resources, economic opportunities, household decision-making power and lack of control over reproduction or child care have large perpetuating intergenerational implications.
It is, therefore, essential to discuss gender disadvantage in a holistic framework, tracing the various facets of inequality and how poverty renders women doubly disadvantaged and vulnerable to economic shocks and adjustments. Refer to a diagrammatic presentation (Figure 1) of a ‘generalized framework’ explaining the factors which render women poor and the manifestation of it. These linkages may have substantial variation depending upon which state or region one lives in. It is well understood that inequalities originate from the household at very early stages of lifecycle continues to reflect in several social and economic spheres. The discussion therefore should revolve around the multiple dimensions of inequality and how poverty worsens the situation from a gender disaggregated perspective.
FIGURE 1 ABOUT HERE
Normally, since men being the sole breadwinners of the household had to go out and earn their living; they also have control over all resources and assets and the right to better nutrition, healthcare and education. Men, therefore, both at the household and community at large emerged as the decision makers and exhibit strong bargaining powers, favoring their own interests. Gradually this logical following of things matured and because of males’ supreme command over assets, particularly land and other economic resources resulted in increasing gender inequality. Women all along derived their identity through their kinship and household relationships. There is a vicious circle where things originated and went wrong because of the influence of socio cultural stereotypes and poverty has had a compounding impact.
With the passage of time, when women increasingly took to education and economic activities, such participation stood in conflict with the dominant socio cultural practices. Subsequently, all growth and adjustment processes have neglected the issue of gender or rather touched upon marginally and failed to recognize women as potential partners. Whereby, in conditions of inequality and deepening poverty, women have had to bear the brunt of it, balancing both reproductive and remunerative activities. Gradually what was considered a way of living took different forms and some of these inequalities; unequal access to food, nutrition, healthcare, market seclusion and voicelessness of women has become resilient to change.
Household and Market Gender Relationships: In examining the gender relationships at the household level, it is observed that nutrition biases are in favor of men and boys in the family. This pattern is aggravated in conditions of scarcity arising out of cyclical seasonal effects and differential entitlements wherein women and girls eat less and last as a coping devise. Although women are responsible for ensuring food security of the family, they themselves are the most food insecure. This results in under nourishment of women in their reproductive age and young girls. For women, poor nutrition, severe anemia levels and poor quality or nonexistent reproductive health services contribute to high maternal mortality and low child survival.
Such biases are observed in healthcare systems as well. Women have lesser access to healthcare services. They rarely seek health services during sickness or ill health compared to men. This is yet another expenditure saving mechanism. Health seeking behavior of females is also guided by their educational levels whereby they are informed and understand the necessity to be healthy. Women in rural areas are more vulnerable to respiratory disease owing to their prolonged exposure to harmful and toxic fuels and gases. Women are at greater risk of disease and morbidity living in unhygienic conditions, which lack sanitation and access to pure drinking water, as observed in growing urban slums.
There has been a lot of advocacy in ensuring female education and employment is considered critical means of liberation. Although reducing female illiteracy has been part of every development agenda, there exist strong biases against female education and more so continuation in school. It is also true that although girls are sent to school at an early age, their continuation rates are poor compared to boys. Often it is the poor penetration of schools in rural areas that deter parents from sending their daughters to schools at far off distance. Again given the restricted opportunities in the labor market, the alternative is better to save upon the resources spent in educating a girl for marriage. When poverty strikes, girls are withdrawn from school such that their male siblings can continue. Also in families where the mother is engaged is some wage work to eke out a living, young girls are kept at home to take care and nurse their younger sibling or else join their mothers to contribute to the family pot.
Division of labor is highly skewed to the disadvantage of female and more so poor women are caught in a double whammy; balancing both reproductive and productive activities. Although globalization had broadened employment opportunities in most of the developing countries, it has set in trends of informalisation and women have been increasingly a part of it. Although women form a large part of the labor force, most of them are tied to the lower rungs. There is an increasing trend of feminisation of informalisation of the labor force. The informal sector is characterized by low wages, no contract and no fixed workplace. Women who are not educated enough and lack skills form part of this informal workforce. This has added to their workload, the returns from which are not at all remunerative. Often it is the economic distress that compels them to join the labor force and does not help them in enhancing their well being. As found in rural agrarian communities, women work either as unpaid family laborers or agricultural laborers as opposed to men who enjoy ownership rights. Despite the fact that the agrarian structure is undergoing enormous diversification and the role of women in dairying, fishing, horticulture can be improved; the efforts lack the appropriate gender sensitiveness. Although empirical evidences suggest that women through self help groups and community management approaches can lead in some of these spheres, the progress is too slow.
It is common practice that women have less access to ownership of land, credit and other productive resources. The law of inheritance in a south Asia study found men’s supreme command over land rights. Women derive their land rights by virtue of their relationship with men and have barely any role in using it as a resource. In agricultural communities, men are the landlords and own the assets as well as revenue accruing from land based activities. Women mostly work as wage or family labor and do not enjoy entrepreneurial rights. Differential access to credit has its roots in land ownership, wherein land is used as a mortgage for loans and it is only men who have the benefit of using it to access credit facilities. Hence women have very little access to credit which impedes their participation in any kind of technological innovation critical for agricultural growth. The self-help group approach to micro credit has mixed results in India unlike its roaring success in Bangladesh. Unequal access to resources has resulted in limited and restricted participation of women in both farm and non-farm activities.
Gender gaps in education, health care and employment opportunities have resulted in the voiceless of women in decision making and bargaining for a better livelihood. This has rendered women poorer and more vulnerable to shocks and adjustment processes. Inequality and poverty are two reinforcing elements and is seen as aggravating one another. In other words, unequal access to resources and opportunities is the major obstacle to women’s economic liberation and opportunity to break free from the poverty trap. Similarly, poverty aggravates inequality wherein female in early stages of their life cycle adopt expenditure saving mechanisms such as eat less, drop out of schools and live unhealthily life and as women take to income earning measures by taking up any low paid insecure odd jobs.
Modern economic reforms and associated dynamics with respect to work and income earning mechanisms are promoting empowerment of women even in rural areas of India. Besides remittances promote participation of women in agriculture which in turn improves agriculture productivity and household income. The new evidence suggests considerable increase in rural income from remittances (Shariff, 2009) due to an increase in rural-rural and rural-rural migration within India (WDR, 2009). Gender empowerment has received strong empirical support across the globe since it further enhances investments in education, health and nutrition that build stock of physical capital formation, thereby yielding durable poverty alleviating effects. Therefore, it is important to bring to fore the fact, that even in India the formative abilities of women are being enhanced due to higher education, participation in workforce, democratic participation and learning from programs such as micro-credit and national rural employment guarantee scheme. It is imperative, therefore, that women demand a rightful place in household and societal level decision making. Figure 2 below provides a pictorial depiction of gender empowered economy in India.
IV: GENDER EMPOWERING CHARACTERISTICS AND MEASURES
After an understanding of the multi-dimensional general framework within which one need to understand gender issues and a number of approaches that are in vogue enunciated above; in the following we identify selected measurable characteristics which all together will form a comprehensive and wholesome ‘gender empowerment measure’. Since these entire variable set are empirically measurable, an index derived out of them is described as ‘gender empowerment index’, which will be a useful policy instrument to governments and civil society alike. Note that this index is a mix of the gender adjustment which UNDP’s GDI performs as well the gender empowerment measure; and conceptually measures empowerment of masses as opposed to a measure of higher order which is inherent in UNDP’s gender empowerment measure.
Conceptually the selected indicators measure empowerment within the contemporary Indian socio-economic outlook and compatible with the debate on mechanisms to reduce gender bias in society and political decision making. Note that the dimensions and factors used in this paper are very different from those identified by the Government of India (2009) which is aligned with the UNDP concept but weak data support of suspicious quality.
An empowered Indian woman is the one who is literate, works (often outside home) and contributes measurable household income, independently decides for example, as to what kind of food needs to prepared and ingredients to be purchased; do not wait for husband to seek paid care for a sick child, owns some property by herself and also manages a bank account. Above all she decides as to how many children she can bear as well as ensure full immunization of all her children. She executes her right to vote and also participates in local panchayats and committees.
Compare this with a concept in which she is an IAS/IPS officer or a judge in a High Court, or can also be doctor or an engineer, or someone who can borrow at least Rs. 2 lakhs from a bank, or an MP, MLA or a Panchayat president, have immovable property and so on. In such a measure the focus is on individual instead of societal achievements and therefore can be aggregated only at national level. On the other hand the multi-dimensional attributes can be created at lower geographic levels and they reflect empowerment of all women in specified locales.
There are also serious data problems in case of the UNDP linked GOI approach; for example, in India the top level services including judiciary have national relevance. At the level of the state, a women born and education elsewhere will normally be posted in a specified state, thus her empowerment do not reflect empowerment of women of that state. Similarly, a large number of professional for example get education in states where educational infrastructure is better and often begin to reside and work in that state. Under such circumstance the gender measures will over estimate the true level of empowerment and may go inimical to women in that state/district. Another measurement issue is that all the measures are to be accessed from secondary sources often of poor and questionable quality. On the other hand the alternative variables proposed are extracted from unit level records of large household surveys which are known to be dependable data for measurements of societal dynamics at least in India. Further the proposed concepts and method can estimate a ‘gender empowerment value/index’ at any level of disaggregation even upto a village level and also estimated can be separately provided for the rural and urban areas separately. The data occurrence and coverage of the universe is almost all women in a defined areas in case of the alternative set of variables; where as in case of the GOI recasted method only a miniscule proportion of women may be covered, for example, even at the state level women in top level services, judiciary and polity can be only a handful countable in single digits and s on.
Statement 1
Measuring Gender Employment in a Socio-Cultural Framework:
Multi-Dimensions and Variable Measures
Choice of Dimensions and Variable measurements
Dimensions Measures Source and Quality of Variables
Human Capital Adult (7+) literacy Estimated from a nationally representative survey of 41,554 households namely the Human Development (HDPI) 2004-05, undertaken by NCAER New Delhi.
Gender gap in literacy
Work Participation Work Participation Rate (15‐64 Year) Estimated from a nationally representative survey of 1,24,680 households namely the National Sample Survey (NSSO) of Employment and Unemployment, 2004-05.
Gender gap in WPR
Household Decision Making Capacity to decide matters alone relating to daily household purchases Estimated from a nationally representative survey of 1,09,041 households namely National Family health Survey (NFHS)–3 of 2005-06.
Capacity to independently undertake the decision for own health care NFHS- 3 (2005-06)
Eco. Resources /Assets Individual/shared ownership of immovable assets HDPI (2004-05)
Manage independent bank accounts NFHS-3 (2005-06)
Earned Cash wages as a regular salaried/wage employee NSS (2004-05)
Gender gap in wages as a regular salaried/wage employee
Earned Cash wages as a casual wage labor NSS (2004-05)
Gender gap in wages as a casual wage labor
Reproduction and Child Care Use of modern contraceptives NFHS-3 (2005-06)
Women having fully immunized children in ages 12-23 months NFHS-3 (2005-06)
Political Participation Cast their vote in the last general election Statistical Report on General Elections, 2004 (14th Lok Sabha) – Vol. I, Election Commission of India.
Gender Gap in the vote casting
Panchayat members Ministry of Panchayati Raj, Government of India: Number of women elected representatives in the three tiers of panchayats as on 31.03.2008 are available in the Annexure 1(A).
Thus, in the Indian context a comprehensive measure of gender advantage needs to incorporate indicators that capture culture-specific dimensions of agency and control over resources, through measures having relevance at the level of individual, household and society. Since aspects of gender empowerment are complex and multidimensional the variables and data needs are diverse and needs to be debated as to their appropriateness. Ideally the variables that measure a social situation and dimension should have the following qualities – (a) robust outcome indicators are the best; but since such indicators are difficult to gather and also as they change slowly, indicators highlighting the process and proximate to the concept of the index measure, in this case ‘gender empowerment’ can be used; (b) that the indicators are easy to collect and that they are collected from independent survey data rather than from service statistics which often lack quality; (c) easy to update frequently such as annually or at the most once in two years, for example, the NSSO undertake annual surveys and required data can therefore be collected, and (d) as much possible relevant to whole or majority of population.
We have identified six dimensions of which five dimensions extracts data directly from large sample surveys using the primary unit level records at the level of individual and households. A gender empowering dimension namely ‘political participation’ uses data from the government records since sample surveys so far have not collected information on these issues. All dimensions are aggregates of multiple measures and wherever appropriate incorporates gender gaps as well. The national sample surveys (NSS), national family health surveys (NFHS) and human development Surveys of the national council of applied economic research (NCAER) are well known data source in India.
(i) Human Capital (Education): Most commonly used human capital indicator, along with its gender gap captures human capital formation, namely, literacy. Absolute measures of female literacy amongst the population ages 7 years and above in percentage and the gender gap ratio are used to capture this dimension. Data from the human development survey of NCAER for reference year 2004-5 supplies data to measure literacy.
(ii) Female work participation: Female work participation rate and associated gender gap for adults 15-64 year was assessed using the ‘usual principal activity status’ (UPS) over a reference period of one year. Further the gender gap in work participation is also incorporated into the computation. A woman is classified as a participant in labor force, if she had been either working or looking for work during a longer part of 365 days preceding the survey. The UPS measure excludes from the labor force all those female who are unemployed and employed for a period of less than six months. The data are drawn from the 61st round employment and unemployment survey of the NSSO for the reference year 2004-05.
(iii) Household Decision Making: This is an aggregation of two variables namely, (a) women’s capacity of ‘making purchases for daily household needs’ and (b) women's participation in decision making for own health care, both extracted from NFHS-3 survey 2005-06 (www.measuredhs.com). The variables together measure women’s participation in decision making; those who usually make specified decisions on their own or independently. Those reporting joint decision making along with men or husbands are excluded from these measures. These variables selected to reflect woman’s capacity for independent decision making in the domain of household are well recognized even in studies undertaken in other developing economies around the world.
(iv) Economic Resources and Assets: Aggregates of two variables namely, women’s ownership of (a) immovable assets and (b) bank account are used to reflect her control over resources. The first variable is measured as the proportion of women who have their name on immovable properties owned or rented. Normally such names are incorporated on to the contract or registered property documents. For the first time such data have become available for all India and many states from the NCAER’s Human Development Survey -2004-5. Women having a bank / savings account are drawn from the NFHS-3 data set. Give that these data have longer-term relevance and are important aspects of households, both individually owned and jointly owned (along with husbands/other household members) are considered appropriate to reflect control of respective resources.
It is useful to state both these variables have become prominent in the Indian context in reflecting the independent nature of women and their empowerment. Besides a number of states in India have passed laws which favor joint (registration) ownership of land or properties which are rented. Often properties jointly owned are given tax concessions by law. So far as the ownership of bank accounts we bring the attention of the readers to the fact that the microfinance programs in India are over two decades old and upto 25 million households are enrolled into such program through the self-help group formations; and they are in a way enrolled in to a informal banking scheme. Further since about a year millions of bank accounts are opened in the names of women across India through a wage employment program known as ‘national employment guarantee scheme’. Thus there is a revolution of sorts which is enabling women even in rural areas to open and operate their own bank account. However the data used to assess these variable have the reference year 2004-5, and conditions during recent years are expected to more women friendly. Given this background these variables are India specific and they capture a dominant part of women’s empowerment.
(v) Reproduction and Care: This dimension is an aggregation of two variables, (a) one reflecting women’s capacity to choose and use a modern contraceptive method which is a reflection of control over reproduction; and (b) her capacity to ensure that her own children are completed with all essential dozes of immunizations. This second variable is constructed linking all children aged 12-36 months with the respondent women and identifying the completeness of all immunizations.
(vi) Political Participation: Participation of women in political sphere is indeed a dominant evidence of empowerment. For example, Indian historically has been in the forefront in this benchmark as it has had considerable world recognition when Mrs. Indira Gandhi was the Prime Minister of India. Contemporary situation has enabled Smt. Pratibha Patel to be the President of India, and another high position of the ‘Speaker’ of the Loksabha (lower house of parliament) is occupied by a woman. The list of world’s powerful women contains many more entries from India. In spite of such feat one finds the condition of women in India is deplorable, mostly due to strong patriarchy and men favoring social and public policies. Therefore, we believe what is relevant to capture the political empowerment of women in India is their participation in Indian democratic system. We capture these traits by using two variables whose data are available from government sources. Percentage of women exercising franchise during the last general election is one variable used and dependable data are available from the Election Commission of India. Another positive woman favoring policy in India has been the democratic decentralization of governance to a third tier identified as the Panchayats in rural areas and nagar palikas (municipalities) in urban areas. Percentage of women members in the panchayat councils is used to represent political participation in this indexing exercise.
V: GENDER EMPOWERMENT INDEX: Values and Rankings
This is an exercise to cumulate the multi-dimensionality of gender empowerment inherent in the six identified dimensions enunciated in the previous section and create an index at the level of the Indian states, economic standing and social identities, and place of residence. All six dimensions are considered equally important; for example literacy and work are two equally important attributes expressing pedagogy and economic independence. Similarly, control over physical assets, using banking services, independently taking routine household decisions as well as control over her own reproduction and take decision about child care are all equally important in expressing the power a women exercise so as to change her immediate environment to benefit her own welfare, and the derived welfare of the household. So is the ability of women to participate in political system especially in the modern context of decentralized democratization process especially in India. Therefore, we believe assigning equal weights to each of the six dimensions should be noncontroversial, also because one expects systematic improvements occurring concurrently across all these dimensions over a period of time. The variables chosen to reflect the above aspects of empowerment are carefully selected from across the multiple sources of data, and wherever necessary gender differentials are also factored in the computations. Normally the index values and rankings are created for over the time comparisons; it should not matter much as to what the definitions, measurements and weights (implied) are so far as they remain constant over time. Even assign equal weights, however, care must be taken by making all variables and dimensions scale free so that the level difference between selected variables do no influence the values and subsequent rankings. A comprehensive discussion about the scaling, normalization, weighing and indexing in the Indian context can be found in Kundu et. al (2007).
Gender Empowerment Index for Major Indian States:
The gender empowerment values/index and associated ranks for all six identified components/dimensions according to major sates of India can be found in Table 1 and the last column assigns a GEI ranking.. The upper and lower benchmarks for comparisons are taken from within the state distributions and therefore the absolute values are not comparable with other international benchmarks. Measuring empowerment requires country specific qualitative variables as described above and therefore no effort is made to undertake international comparisons although such indices can be crafter should a situation demands.
The GEI index values reflect the levels of achievement to the maximum possible of 1 and the least value being 0. Thus if a state takes the maximum value of 1 in six dimensions then the aggregated index value will be 1 which is the perfectly women empowered situation and if it is 0 then it is the worst scenario. At the All India level the overall GEI value has worked out to be 0.424 which is less than even the half of the level mark, and in the inter-state comparisons show the bottom most value is 0.238 recorded in Uttar Pradesh and the top most value is 0.646 for Kerala. We have categorized states in four segments taking the mean of all states as the first dividing line and further the mean of each segment as the other dividing line to distribute states in all four segments. This method of ordering states in segments provides useful analytical advantage. One can find that states with relatively better or ‘high GEI’ besides Kerala are Tamil Nadu, Maharashtra and Karnataka in that order, followed by Gujarat, Punjab, Andhra Pradesh, Haryana and West Bengal which can be considered as states with ‘moderate GEI’. States which have ‘low’ index are Orissa, Chhattisgarh and Madhya Pradesh; followed by the ‘very low GEI’ states namely, Jharkhand, Assam, Rajasthan, Bihar and Uttar Pradesh (refer Table 1). Refer also to a composite map (Map 1) and six other maps one each of the specified dimensions of empowerment identified in this empirical exercise (Maps 2- 7).
TABLE 1, 2 AND MAPS ABOUT HERE
In case of Gujarat while it ranks as low as 8th in human capital formation, it is on the top on ‘control over assets, and second on ‘capacity for household decision making’; but it ranks too low at 16th of the 17 states in political participation. On the other hand Kerala which is on top on human capital formation, but as low as 8th in household decision making as well as woman’s work participation and 6th in political participation.
Gender Empowerment Index according to Socio-Economic Categories:
The type of the data used allows estimating the GEI using the first five dimensions, since disaggregated data for woman’s political participation is not available, according to place of residence (rural or urban residence), socio-religious categories and economic groups based on per capita income quintiles (Table 2). It is surprising to note lack of GEI differential according to place of residence, namely the rural and urban areas; although we are aware that there are noteworthy gender differentials if only an absolute level of a particular variable is evaluated. Thus while there may be huge level differentials in the measurement of variables in absolute terms, when one takes the relative gender differentials it does not matter whether one resides in rural or urban areas, the gender bias seems as strong. This is a very important empirical finding.
Further the values and rankings are evaluated for economic classification and socio-religious groups and one notices some perfect association. The GEI index has a perfect match with the per capita income quintiles in such a way that relative economic prosperity indeed promotes gender empowerment. The only dimension which has inverse relationship from within the six considered is women’s work participation suggesting that poorer women work relatively more so as to supplement household income; yet overall economic prosperity promotes ‘gender empowerment’.
The data bases used, namely the national sample surveys, the NCAER’s human development survey and the national family health surveys contain variables that are amenable to create exclusive socio-religious categories which are generally so identified in day-to-day discourses in India. One finds considerable variations in the GEI according to the socio-religious categories as well. For example, it is residual others (minority religions other than Muslims but less than 5 % of population) category which has the highest value of 0.763 followed by the high caste Hindus with 0.675 and these two communities are class apart and reflect large inequity in society. The subsequent values are far too low at 0.410 for OBCs, 0.366 for SCs, 0.281 for the STs and least for Muslims at 0.276. There is a notion that the tribal communities offer fairly egalitarian social system which, but such common understanding and does not stand the empirical test, thus making ST women extremely vulnerable as well along with the SCs and the Muslims. The socio-religious exercise provides excellent leads for public policy formulation in the area of effecting group-equity in India.
VI: CONCLUSIONS AND POLICY IMPLICATIONS
It is common knowledge that the UNDP promoted the concept of human development index which is now widely used all over India. One finds that many states in India have brought out human development reports highlighting district level variations as well. We consider it useful to compare the state HDI ranks with the GEI estimated by us (see Table 3). There are a few unexpected relationships between the two in a few states. For example Assam and Uttar Pradesh have recorded relatively better HDI ranking compared with the GEI which are far too low. Other states with higher ranking differentials and having lower GEIs are Bihar, Haryana and Punjab. On the other hand state which have improved over their HDI rankings considerably are Maharashtra, Karnataka, Orissa, Jharkhand and Chhattisgarh. However, it will be instructive to know as to what factors have pulled the state of Assam and Uttar Pradesh considerably low in the GEI measures.
TABLE 3 ABOUT HERE
The correlation between the GHI and HDI rankings has worked out to be only 0.58 suggesting that HDI do not reflect the true gender vulnerability and therefore it is essential to create a separate series of data that reflect women’s empowerment. As mentioned earlier, we have used six dimensions and associated measures for which dependable data are available from sample surveys and government records. Although we believe that dimensions and variables chosen for this exercise are excettent and effecnint in capturing empowerment of women in India, one can add other concepts provided quality data are available so as to contextualize indexing to local situation and needs. Tt is most appropriate to create the gender indices as the level of districts, and according to socio-religions communities within the state for a better understanding of the problem of gender discrimination.
A number of policy implications will emerge from this research and a few of them are listed below:
• Enable policy makers to understand the process that facilitate empowerment of women.
• This research will enable recognition of the significant role gender empowerment play in improving incomes especially in rural areas and thereby poverty alleviation.
• Help formulate policy support to sustain empowerment of women, for example, through strategies to establish and sustain ownership rights, enhance participation in local governance and undertake market based activities.
• Promote fiscal and financial products which suits formation of household capital, assets and insurance against risks in rural areas of India.
• Effective policies can be designed to so that economic resources transferred through micro-credit programs can promote micro-enterprises and local markets.
• Promotes regionally balanced economic growth through wage and labor market effects especially factoring increased female participation in labor force.
We believe that this paper raises a major issue of appropriateness of the factors and measures that reflect gender empowerment and hope that the methodology presented will help generate an informed debate on the topic in India and other developing societies.
References:
Beteta, K. C (2006). ‘What is missing in measures of women’s empowerment?’, Journal of Human Development and Capabilities, 7 (2):221-241.
Bhardan, Kalpana and Stephan Klasen (2000). On UNDP’s revision of Gender-Related Development Index; Journal of Human Development, 1(2):191-195.
Dreze, J and A. Sen (2000): India Development and Participation (New York: Oxford University Press).
---- (1999): India Economic Development and Social Opportunity (New York: Oxford University Press)
Duvvury, Nata. (1998). ‘Women and Agriculture in the New Economic Regime’, in M. Krishnaraj, R. M. Sudarshan and A. Shariff (eds.), Gender, Population and Development, New Delhi: Oxford University Press.
Food and Agricultural Organization (FAO) (2008). ‘Women quantify lack of control over work resources’ UNEP/GRID-Arendal Maps and Graphics Library. (www.fao.org/) ( http://maps.grida.no/go/graphic/ women-quantify-lack-of-control-over-work-resources)
Government of India, (2009). Gendering Human Development Indices: Recasting the Gender Development Index and Gender Empowerment Measure for India; a summary report; New Delhi: Ministry of Woman and Child Welfare.
Kabeer, Naila (1994). Reversed Realities: Gender Hierarchies in Development Thought. Verso books.
Roy, Kartik, Hans Blomqvist and Cal Clark (2008). Institutions and Gender Empowerment in Global Economy, London: World Scientific Publishing Co. ltd., pp308.
Kundu, A., A. Shariff and P.K. Ghosh, (2007): ‘Indexing Human Development in India: Indicators, scaling and composition’ in A. Shariff and M. Krishnaraj (ed.), State, Markets and Inequalities: Human Development in Rural India, New Delhi: Orient Longman, pp44-89.
March, Candida., Ines, Smyth and Maitrayee Mukhopadhyay (1999). A Guide to Gender-Analysis Frameworks. UK: Oxfam.
Moser, Caroline O.N. (1993). Gender Planning and Development: Theory, Practice, and Training., London: Routledge.
Parker, Rani (1998).Gender Relations Analysis: A Guide for Trainers. Save the Children, USA.
Schluer, Dana (2006). ‘The use and misuse of gender related development index and gender empowerment measures: a review of the literature, Journal of Human Development and Capabilities. 7 (2):161-181.
Schultz, P (1995). Investment in Women’s Capital, Chicago: University of Chicago Press, pp641.
Shariff, Abusaleh (2009). Income and Employment Diversity in India: changes in rural nonfarm share between 1995 and 2005. Mimio, International Food Policy Research Institute, New Delhi.
Shariff, A and Namkee Ahn (1995). ‘Mother's Education Effect on Child Health: An Econometric Analysis of Child Anthropometry in Uganda’, The Indian Economic Review, 30(2):203-222.
UNDP (United Nations Development Programme). 2007. Human Development Report 2007/2008: Fighting Climate Change, New York: Oxford University Press.
Woman’s Watch, (http://www.un.org/womenwatch/);
World Development Report, 2009 (http://www.worldbank.org/wdr2009)
World Economic Forum (http://www.weforum.org/)
Subscribe to:
Posts (Atom)