Sunday, September 20, 2009

Gender Empowerment in India: Concepts and Measurements


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.


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 (; 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 ( 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.


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.


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.


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 ( 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.


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).


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.


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.


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.


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Saturday, September 5, 2009

What can we learn from India’s Mass Employment Scheme?

I. Introduction
Countries with large rural populations that include high shares of landless laborers typically require formal safety nets to reduce vulnerability and sustain people’s livelihoods. India already has several large, universal safety net programs, including the Public Distribution System (PDS) for food and the Integrated Child Development Services (ICDS) scheme, and in 2006, it launched another. The National Rural Employment Guarantee Scheme (NREGS) emanated from India’s commitment to a legal right to work. Adopted in the wake of persistent public demand, the NREGS is a mass ‘public works program’ (PWP) based on the country’s experience in reducing human distress in recent decades in rural Maharashtra state. It promises to sustain the incomes of rural people while creating physical infrastructure that will benefit the country in the long run. Although the program is relatively new and thus has not been subject to a comprehensive assessment, early indicators point to areas of success and failure, highlighting where improvements can be made and lessons learned in a public employment program of this size.

II. The National Rural Employment Guarantee Act/Scheme (NREGA/S)
The ‘right to work’ is a ‘directive principle’ in Indian Constitution which was formalized through the enactment of NREGA (2005) . It is seen as a mechanism of income transfer, infrastructure development and promoting rural production and consumption markets - a multifarious strategy indeed. NREGA has found priority policy attention in India’s 11th five year plan (2007-12) under a broader objective of ‘Bharat Nirman’ aiming for resurgence in rural areas. Some consider nrega a natural response to non-inclusive growth that occurred during reforms process of last about two decades. The format of nrega and its nationwide implementation was a result of persistence by civil society and activists which is a common mechanism to influence policy in India. NREGS is unique, being large in size , intended to cover long periods, disburse huge funds and be dynamically responsive to climatic and rainfall conditions and above all open to any adult intending to work for wages often lower than local causal wages. Since self-targeting is inherent to scheme, besides chronic poverty manifest for example in food inadequacy, it also intends to mitigate idiosyncratic risks and shocks faced by households due to being differently-abled or death of earning member. NREGS can attract the unemployed or underemployed rural youth; because of immediate cash availability and 100 days of assured work which functions as a short-term relief objective. Indian policy appears confident that nregs can be important normally, even in the absence of price or income shocks and that it can smoothen seasonal fluctuations in labor demand and, therefore, wage rates in rural areas where rainfall patterns and insufficient irrigation preclude year-round crop cultivation (see also Barrett, et. al, 2004). Other objectives include, generation of productive assets, empowering rural women, reducing rural-urban migration, fostering social equity and environmental protection. Box 1 summarized the multiple nrega goals which can be categorized as protective, preventive and promotive in nature.

Multiple Goals of NREGS

Protective : assistance ensuring consumption smoothening and immediate welfare

Preventive : insurance facilitating risk taking such as investment in agriculture

Promotive : economic stimulus, through cash accumulation, local production and enhancing markets
- harmonize labor market, promote rural nonfarm employment (RNFE) and equalize wage rates;
- create durable physical assets impacting local eco-system and climate change;
- facilitate human capital formation through skill development; and
- alleviate poverty, effect equity, reduce distress migration and empower women.

The listed issues, however, are yet to be thoroughly investigated in the context of nrega.

How was the NREGS formulated: The format of nrega/s draws upon positive experiences of reducing human distress by Maharashtra ‘employment guarantee scheme’ (MEGS). The MEGS was first of its kind effort in India, to address high levels of rural distress caused by a severe drought in 1973-74. The MEGS created 3,597 million person days of work on minor irrigation, soil and water conservation, reforestation and local roads since inception until 2004. In its peak year in 1980 about one fifth of capital spending of Maharashtra was spent on EGS. MEGS thus became a model of sorts in which all aspects of governance, political commitment, bureaucratic efficiency, equity objective and concerns to sustain local environment and so on came into play, although at the heart of the issues was clearly the push and pulls of electoral politics. This scheme had central focus on drought proofing activities that led to measurable tangible results. Land holders were direct beneficiaries and the scheme also established a participatory process in the local governance (Moore and Jadhav 2006).

While the MEGS was a prototype and used as a benchmark, before the launch of nrega a plethora of PWPs were tried out all over India. National rural employment program (NREP) was initiated in 1980 followed by rural landless employment guarantee program (RLEGP), and in 1989 they were merged to form Jawahar rozgar youjana (JRY) with a focus on unemployed and creating rural assets. Employment assurance scheme (EAS) introduced in 1993 became universal by 1997-98. Jawahar gram samridhi yojana (JGSY) introduced in 1999 restructured the JRY and made it a central scheme. Sampoorna grameen rozgar yojana (SGRY) was launched in 2001 and in 2002 EAS and JGSY were also merged, aiming at providing rural wage employment as a mechanism to ensure food security, along with the creation of durable community, social and economic assets. The ‘national rural employment guarantee act (NREGA)’ thus is the most resent version of PWP, which for the first time has a legal sanctity inbuilt into the scheme.

Coverage of the program: The national level rural development ministry and associated departments are responsible for implementing nrega across the whole country. They also appropriate financial allocations from national budgetary mechanism and facilitate states to draw respective shares to execute work projects. The nrega coverage during first year of implementation (2006-7) was only to 200 poorest districts, followed by an additional 130 district during 2007-8; and by 2008-9 all the 610 districts across India were brought under nrega. A review of data published biannually through official website suggests that in the year 2007-8 , overall 33.7 million households were provided with 1.43 billion man days of nrega employment and distributed close to Rs. 86 billion. These absolute numbers which account for about 45% of all rural households, suggest a vibrant and highly efficient program implementation and matches with the stated policy and the targets.

Budgetary allocations: Before formalizing the Act, government agencies estimated that full coverage of nregs will cost Rs. 400 billion (about US$ 9-10 billion) which was about 1% of GDP. Some empirical assessments suggest that nrega could help reduce rural poverty to 23 per cent during lean season, at annual cost of 1.7 per cent of GDP (Murgai and Ravallion 2005). Others based on simple average minimum wage aggregates of all states estimated the national annual cost to be 1.3% of GDP; and a case was made that nrega will be sensitive to prevailing minimum wages in respective states (Shariff, 2004).

The allocation and expenditure on nregs during first two years of implementation were low due to staggered implementation; yet even after covering all 610 districts in 2008-9, only Rs. 160 billion (0.37% GDP) were allocated. The allocation for the year 2009-10 is Rs. 780 billion or 0.66 % of GDP, but the actual expenditure is expected to much less. NREGA expenditure for 2007-8 although 0.23 % of GDP compares well with other national programs namely targeted ‘public distribution system (PDS)’ of food products (0.13% GDP) and ICDS (0.10% GDP) respectively. However, a cost-benefit estimate for erstwhile MEGS compared with PDS suggested a ratio of 21.6 % for the former and meager 11.2% for the latter (Parikh et. al. 2007). Although there are substantial improvements lately, the relative efficiency differentials are likely to prevail. The Indian safety net programs appear huge in terms of allocations and coverage but reach a small proportion of poor and only nominal benefits are received by them.

Given both low allocation and under-utilization of funds, further financial expansion of nrega are not expected to impact national level fiscal deficits adversely even if no additional tax or levy is imposed; nor does one expect that nregs proceeds would cause inflation in the local economy. An increased cash flow amongst wage workers will pushup local demand and prices, but a simultaneous accelerating effect on local product market associated with broad based income growth will dampen the inflationary impact. However, nregs appear good in reducing risks and vulnerability, but not sufficient to eliminate poverty in India.

III. Strong Performance in Some States

Given a vast expanse one expects interstate differentials in nrega performance, some due to staggered and lagged universalization others because of administrative bottlenecks unique to each state (CAG, 2007). Corruption, leakage and dominance of private agents are other notable hurdles which are insurmountable where panchayats are nonexistent. Some appreciate self-targeting strategy inherent in nrega, but cautions social welfare losses caused by miss-targeting (Banerjee, 2008). Overall all, Rajasthan, Madhya Pradesh and Chhattisgarh stand out as better performing states. The relative coverage of households is better and average wage accruals are reasonable due to better provisioning of employment days. Given relatively higher poverty it is reasonable to assume that relatively vulnerable households do benefit in these states.

In case of Rajasthan, there are satisfactory assessments as to who benefits from nregs. Wage accruals have helped smoothening of household income (Scandizzo, et al., 2007) and there are large favorable gender impacts (Chandrasekhar and Ghosh, 2009). A silver lining thus has emerged from state of Rajasthan (Shivakumar 2006, Dreze, et al. 2007) which indeed provide much needed confidence to strive for improvement and continuity of nregs. Although vibrant panchayat raj administration is essential, but it is not a sufficient condition for better nrega; for example, Kerala with well developed panchayats is suffering from high leakage of funds. The success story of Rajasthan is due to a fair balance between functioning of panchayats and other enabling factors such as open and transparent monitoring and public audit mechanisms.

IV. Poor Performance in Most States

States which host large number of the poor but doing poorly in nrega are Bihar and Uttar Pradesh. Other states utilizing meager expenditures are Haryana, Gujarat, Karnataka, Kerala, Maharashtra and West Bengal. Another backward state, Jharkhand suffers from absence of panchayat institutions (Bhatia and Dreze 2006). Orissa’s problem is attributed to systemic bureaucratic failure to put in place transparent implementation of nregs. Large scale leakages and corruption are rampant due to absence of documentation system amenable for crosschecks for accuracy of record keeping (Dreze, et al. 2007), and the situation in Bihar is not encouraging either (Pankaj or Sharma 2006).

While nregs suffers from large exclusion errors due to poor coverage, one finds some hope due to greater access that it gives to women, the Scheduled Castes and the Scheduled Tribes (Chandrasekhar and Ghosh, 2009). A recent field study of vulnerable rural households in seven north Indian states (Shariff, 2008) suggests that community participation; information sharing and formulation of an opinion of program stand out as dominating factors that enhance maximization of receipts from nrega. Such attributes are normally prevalent amongst ‘rural middle class’ and therefore poorest of the poor within a micro locality are most likely to face entry barrier to nregs. Mechanisms to overcome such anomalies are available, for example, beneficiary participation and partnerships with local civil society and NGOs are known to have helped in ensuring transparency, equity, timeliness, financial prudence and quality assurance in delivery of public services. Such partnership also strengthens institutional capacity at the grassroots. The future reforms or nregs-course correction must address such anomalies, lest the program is held ransom to middle class values.

V. What determines access to NREGA and maximization of employment days?

A perceptions survey of 3200 poor households about government’s safety net programs in sixteen selected most deprived districts in northern parts of India provides some rare data that are amenable for econometric analysis in identifying factors supporting access and use of the nregs. These data evaluates both nregs accessibility/enrollment and number of days of employment received per household form such employment. Qualitative information on participation of households in village level institutions (of local governance), frequency and transparency of panchayat meetings are also available. The data were subjected to the ‘correction for the selectivity bias econometric model’; which assessed in its first stage, determinants of enrolment and factored a computed lambda value in the second stage to find out characteristics supporting maximization of the number of days of employment from amongst those enrolled. The survey was conducted across seven states in north India, the results do present a close to accurate status of the nregs of this region and the main findings are highlighted below .

Accessing NREGS: The econometric analysis suggests that social variables have influence nrega enrollment in expected direction, for example the casual labor and illiterate households have easy enrollment into the scheme. However, the scheme is accessible to households belonging to all caste and religious communities suggesting the fact that the scheme is adequately broad-based although one expects the Scheduled Castes and Scheduled Tribes to show greater access. Important is that fact that governance variables such as participation in panchayat meetings and having an opinion about transparency in nrega meeting have favorable impact on choice of nrega work. View on ‘transparency’ was categorized as yes, no and no opinion. Both divergent views - that nrega meetings were ‘transparent’ and that they were ‘not-transparent’- show a large and significant positive effect on nregs as opposed to those households who did not have a opinion at all or the fact that they were truly not interested in having a view on local panchayat meetings. Given this strong and important relationship additional tests were performed using interactive terms with transparency but did not find significant additional advantage. This analysis suggests that program information and having-a-view on institutions that promote participation are important to determine enrolments. This finding provides a strong signal to program managers that to enhance reach and efficacy of nregs and similar other programs people’s participation is essential irrespective of whether such participants approve or disapprove of a program. There are a few studies which have discovered the importance of participation for example, Krishna (2006, 2001); Weinberger (2000); and Cohen and Norman (1980) in promoting access to program in developing economies and in rural areas.

To understand whether the scheme is accessible to the poor a comprehensive index (using a combination of productive assets such as animals, implements and durables) which captured economic standing was used in the model. It was puzzling to find that relatively better-offs have high accessibility to the scheme; and the evidence challenge the program expectation that nregs is designed to benefit the poorest of the poor through self targeting mechanism. Since nregs-wage in a number of states is higher than local wage rates the beneficiaries are the regular wage workers, and not necessary those abject poor whose reservation wages can be low. Although, by law all those who approach for work must be provided with jobs, there are many constrains that limits creation of all the desired / demanded / needed employment days. Such limits emerge from limited supply of funds, seasonal factors, non-availability of useful projects and local level idiosyncratic factors as well. Given such limitations, many nregs jobs will be appropriated by those who have a better bargaining capacity (can also be the better off within the group), thus inhibiting the poorest of the poor benefiting from the program.

Maximizing Days of Employment: The selection bias correction model used evacuated the mean number of days of employment conditional upon a household getting enrolled. Information on ownership and size of land was used as distinguishing variable which also reflect relative economic condition of the household. Limited numbers of variables show significant effects; for example, even after controlling for land asset variable with no impact, the ownership of pukka (good quality) house shows independent positive impact at less than 5% level. That is labor force living in pukka homes maximize netting nregs employment days. Another dominant effect emerge from a community level factor namely, institutional participation of woman in the village; followed by significant (less than 5%) and unexpected effect from those reporting fair food adequacy. Finally, households having a migrant family member show high degree of incapacity to maximize nregs employment days, although as we found above they were successful in enrolling into the program, however.

It appears that the inner story of who gets to work more number of employment days depends upon one crucial fact that shows little influence on whether one gets to work or not; but once one gets enrolled in to the scheme derives maximum benefit. This crucial fact is women’s formal participation (from within households or own community) in local self governance such as the panchayat, school committees, mahila mandlas and so on which has shown the most dominant impact suggesting the fact that household gets its employment days maximized when a woman from the household or even from own community participates in the panchayati raj linked village level institutions. Strategies to improve program efficiency must be undertaken jointly and concurrently by strengthening local self governance with clear distinctions made between political, administrative and fiscal decentralization (von Braun and Grote, 2002). Best results can accrue if political and administrative decentralization precede the financial but it appears that in case of nregs this step wise transition has not taken a clear shape yet. This finding is highly significant both to the national goal of democratic decentralization on the one hand and favorable implementation of nregs on the other.

An unexpected finding is that even households reporting fair food adequacy have recorded a large positive effect that gives credence to the fact, that even those households who do not feel the pinch of food inadequacy make efforts to hang on to nregs employment for maximum number of days and this effect is prominent even after controlling for other social and economic factors makes it puzzling . Given a vast array of mechanisms through which leakages and discrimination works, it appears that those who manage to show endurance can hang on to more employment through various partnerships that may develop with the managers of muster rolls and payments in this program. In case of the migrant households, what appeared to be a reflection of distress while seeking work turns out to be worse as they are not able to maximize upon wage receipts through higher number of days of employment. In fact such people seem to get penalized and factors that lead to such a situation are not yet clearly documented.

VI. Policy Implications

India’s experience so far suggests lessons for its own implementation of the NREGS as well as for other countries that implement large-scale employment schemes and a few are summarized below:

Lesson 1. Be sure that local institutions exist that are capable of implementing large PWPs. This Indian model depends entirely on the 3rd tier of government identified as the local panchayats which are in principal locally elected bodies reflecting not only people’s participation but also people’s interaction with such institutions on a daily basis. However, panchayat system is essential but not sufficient condition for the success of nregs.

Lesson 2. Make implementation transparent to all stakeholders. Transparency is a trait which is not well factored in program implementation in India. Number of welfare programs therefore suffers from lack of scope for monitoring and mid-course correction if necessary. In built monitoring through a transparent documentation and audit mechanism enables reductions in leakages, better targeting and cost efficient delivery. NREGA has responded well when there is transparency in implementation.

Lesson 3. Monitoring through social audits can help ensure accountability. A social audit is a process in which the people work with the government to monitor and evaluate the planning and implementation of a scheme or indeed of a policy. NREGA social audit can examine local records such as the muster roles, work requisitions and monetary transactions, by nregs-workers and civil society. Such social audits will benefit from use of modern information technology (IT) and banking networks. NREGA has immensely benefitted both by the IT, and the banking and post office networks across India resulting in reduction in corruption, leakage and improvements in timely payments to the enrolled participants.

Lesson 4. Reducing ‘exclusion’ and ‘inclusion’ errors; the former being highly anti-poor and the latter reflecting program inefficiency are essential to register success for such a large scheme. It is ideal, therefore, that political and administrative decentralization precedes the financial one so as to enhance coverage and make nregs inclusive. Sustaining nregs-wages below the minimum wage seems essential so as to eliminate the crowing-out effect adversely impacting self-targeting, thereby causing exclusion.

Lesson 5. A larger policy issue relates to nregs promoting labor market distortions and impacting upon the natural process of migration (see also World Bank 2009). NREGS can inhibit rural to urban and rural to rural migration affecting employment and wages in both place of origin and place of destination across the country. Such a possibility arises when the nregs wage is arbitrarily fixed higher than the reservation wage of the poorest amongst the rural communities. Higher wages will deepen the exclusionary and wrong inclusionary process thus defeating the very purpose of large PWPs. Besides, if nregs create basic public service infrastructure in rural areas it may in fact inhibit migration of the poor in search of such services.

In conclusions it is useful to emphasize, that future of nregs, which is a legal entitlement for the deprived living in rural areas, is securely tied with functioning of the panchayati raj institutions in India. To some this scheme is a consolidation of democratic process and appears revolutionary. But test of the success of such a large scheme is in its ability to carry vulnerable and the poor on board and keep them there for extended period of time. Further mechanism for an exit from nregs is a useful policy to think about. Due to deepening effects on farming and increase in land productivity the household incomes can rise above poverty line or at a level when reservation-wage will be more than nregs-wage, in which case many marginal and small farmers, may not further nregs work. This aspect is not recognized and no policy guide lines exist as ‘exit strategy’. It is useful to document the processes which provide leads to nregs’s relevance for poverty alleviation through improvement in agriculture.

In spite of powerful demands from the monitoring agencies, academics and activists, one finds lack of coordinated government level initiative, innovation and interventions to improve the program. In the end it must be stated that nregs has potential to provide social security to the masses only if its implementation is efficient and synergies are exploited. India should not miss another opportunity to demonstrate that world’s largest democracy also cares for its people especially the deprived and vulnerable, and that it truly is marching ahead to become a welfare state.