Incidence of Public Expenditure on Education: Viewing ...



Incidence of Public Expenditure on Education: Viewing Through a Gender Lens

Protiva Kundu

Abstract

Gender is not synonymous with women, nor is it a zero-sum game implying loss for men; rather, it refers to both women and men, and to their status, relative to each other. Persistent disparities between women and men not only have negative implications for women themselves, but for the society as a whole. Education plays the most important link in achievement of development goals through promotion of gender equality.

There has been a long standing concern in economics on how to measure the benefits of publicly provided goods to individuals in society.

This study makes an attempt to analyze the gender and expenditure class disaggregated Benefit Incidence Analysis (BIA), to examine the disparity in the incidence of Government expenditure on education across socio-economic groups.

The analysis is based on the household level data from National Sample Survey (NSS), 55th Round, Report no. 473 on ‘literacy level of India’ for 1999-2000. This survey includes area wise and sex disaggregated data on educational attainment of persons aged 7 and above according to Household’s Marginal Per Capita Consumption Expenditure class across states.

The results of ‘benefit incidence analysis’ powerfully explains which expenditure group actually benefited from the government’s subsidized education and how this benefit is distributed between males and females in India across states and regions. This helps to understand the root causes of gender disparity in India and helped in provide a guideline for developing a gender sensitized education policy.

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JNU

Women have an enormous impact on the well-being of their families and societies – yet their potential is not realized because of discriminatory social norms, incentives, and legal institutions. And while their status has improved in recent decades, gender inequalities remain pervasive.

Govt. subsidies are a very powerful instrument of fiscal policy used to improve the welfare of the people. In most of the countries public subsidization of social and economic services is a common feature. Every nation identifies education as public good. Where education is not publicly provided, it is subsidised by states.

There has been a long standing concern in economics is how to measure the benefits of publicly provided goods to individuals in society. The pure public goods are considered as freely provided and benefiting communities as a whole but when government spending subsidizes the provision of private goods (e.g., health, education services) ,it is no longer valid to use the price paid as a measure of the good in question to the individual consumers. To combat this problem , the concept of ‘Benefit Incidence Analysis’ emerges, which combines the cost of providing public services with information on their use in order to illustrate the way in which the benefits of government spending are distributed. The "benefit incidence" approach, also called the classic or the non-behavioral approach, was pioneered by twin World Bank studies by Selowsky (1979) for Colombia and Meerman (1979) for Malaysia. The main goal of benefit incidence analysis is to identify who benefits from public spending and by how much.

Government subsidizes services in order to improve certain critical outcomes among the population. There are many links in the chain between govt. spending and the outcomes sought. Using the example of health spending, given by Filmer, Hammer and Pritchett (1998) a framework of public spending and education links in the chain is constructed.

Figure: Public Spending and Outcomes-links in the Chain

[pic]

The framework distinguishes four basic links. The first link is between total public spending on education and composition of spending. If he education budget is devoted mainly to activities which have little impact on population at large, the link will be weakened. For example, spending on tertiary level of education will not benefit the population at large; as such facilities are used mainly by better-off people. The second link translates the budget into effective education services. If the sector is inefficient, the level of spending will be a poor indicator of service provision. The third link shows how the total provision of effective services is affected by public spending. The final link is between the provision of education services and outcomes at the individual level.

Benefit Incidence Analysis focuses mainly on these links, addressing the question: to what extent do government spending on education used by poor households and how much they are benefited from this service?

Methodology of BIA

Benefit incidence analysis is a powerful technique for assessing how efficiently public spending is targeted to the poor. It identifies who benefits from public expenditure on education in different group.

BIA involves a five-step process:

1. Obtain the average unit cost of providing a public service by dividing government

Spending on the service (net of any cost-recovery fees and out-of-pocket expenses by the Users) by the total number of users of the service.

2. Define the average benefit from government spending on a service as the average unit cost of providing the service, which is derived from the previous step.

This assumption “attributes” or “imputes” benefits from government in-kind transfers to

individuals’ welfare as measured by their income or consumption. This is a strong

assumption; the alternative is the more complicated task of estimating a demand curve for a public service and deriving benefits from users’ willingness to pay as summarized in the demand curve.

3. Rank the population of users from poorest to richest using a welfare measure and

aggregate them into groups with equal numbers of users.

4. Fourth, derive the distribution of benefits by multiplying the average benefit derived from the previous step by the number of users of the service in each income or consumption group.

The first four steps can now be illustrated by some simple algebra as applied to the case of education spending. Total benefits from government spending on “all” education (i.e., the combined primary, secondary and tertiary spending) accrued to group j is estimated as

[pic]

[pic][pic] where j=1,2,3,4,5.

Where Xj is the benefit incidence in local currency accrued to income or consumption group j from (net) government spending on level i (primary, secondary, or tertiary education) denoted as Si, also measured in local currency; Eij represents number of students enrolled in level i from group j where each group is a quintile; and Si / Ei is the unit cost of providing education at level i. Groups are typically ordered from lowest to highest with respect to the Classifying variable. If desired, the groups in the middle of the distribution can be aggregated to define a “middle class”.

By dividing both sides of expression (1) by total (net) government education spending, S, one obtains the share of benefits accrued to quintile j from total government spending on education:

[pic], where j=1,2,3,4,5

Where,[pic]

; eij is the quintile j share of total students enrolled at primary, secondary and tertiary level;si is the share of government spending for a given level I in total education spending and[pic]

5. Compare the resulting distribution of benefits with a number of benchmark distributions.

Data:

The analysis is based on the household level data from National Sample Survey (NSS), 55th Round, Report no. 473 on ‘literacy level of India’ for 1999-2000. This survey includes area wise and sex disaggregated data on educational attainment of persons aged 7 and above according to Household’s Marginal Per Capita Consumption Expenditure class across states. In this survey total numbers of sample households surveyed are divided in 12 MPCE classes. The MPCE classes are formed from a table giving estimated cumulative percentage frequency distribution of persons by MPCE for each sector separately. The MPCE classes have been assigned to the households on the basis of data with reference period of ‘365 days’ for education.

In this analysis, for sake of simplicity in calculation I have converted the 12 MPCE classes into 4 MPCE classes. The classes are defined as follows:

Rural area:

0-300 = Poor;

300-420 = Lower Middle Class;

420-615 = Upper Middle Class;

615-950+ = Rich.

These classes are defined over the entire rural population getting education at all level, with an equal number of users in each class.

Urban area:

0-425 = Poor;

425-665 = Lowe Middle Class;

665-1120 = Upper Middle Class;

1120-1925+ = Rich.

The data on total enrolment at each level of education is given by Selected Educational statistics, Ministry of Human Resource Development for the year 1999-2000. The data on public spending on education is taken from the Analysis of Budgeted expenditure on Education, Revenue account, 1999-2000. Finally the data on cost recovery is taken from Finance Accounts, 1999-2000 for each respective state.

The first step in Benefit Incidence Analysis is enumeration of amount of per student subsidy.

Unit Subsidy in Education for 1999-2000

Table 3.1: Unit Subsidy in Elementary level of education

|States |Gross Expd. (lakhs) |Cost Recovery (Lakhs) |Total Amount of |Subsidy Per Student |

| | | |Subsidy.(lakhs) |(Rs./annum) |

|Andhra Pradesh |128479 |21190.3976 |107288 |1080.8425 |

|Assam |78479 |0 |78479 |1812.3708 |

|Bihar |167689 |69.94526 |167619 |2013.0672 |

|Gujarat |171357 |896.45934 |170461 |2014.2283 |

|Haryana |54277 |1904.07745 |52373 |1812.0794 |

|Karnataka |130379 |0.15499 |130379 |1729.0666 |

|Kerala |90521 |44.44204 |90476 |2838.803 |

|Madhya Pradesh |169044 |138.40784 |168905 |1181.3257 |

|Maharashtra |234622 |387.51631 |234235 |1299.5979 |

|Orissa |80438 |828.0092 |79610 |2043.1987 |

|Punjab |50684 |297.2666 |50387 |1648.1271 |

|Rajasthan |150127 |111.50314 |150015 |1590.8287 |

|Tamil Nadu |183152 |34.56343 |183117 |2087.2753 |

|Uttar Pradesh |322879 |2000.32353 |320879 |1643.0753 |

|West Bengal |96434 |1.31302 |96432 |1091.8817 |

Source: Analysis of Budgeted Expenditure on Education, Various years, MHRD, GOI

Finance accounts of different states, 1999-2000 Ministry of Finance, GOI

* Recovery data is not available. Hence gross expenditure assumed to be the total subsidy.

The table above presents the result of state wise estimates of subsidy per student/unit subsidies in elementary education. Second column of the table represents state wise gross public budgeted expenditure on elementary education. Third column is simply the difference of column 2 and 3. It represents the cost recovery by govt. fourth column corresponds to net expenditure by government which is the total subsidy given by government on the basis of assumption that average benefit from government spending on a service is the average Cost of providing the service. Finally the last column represents the unit subsidies in elementary education for all states calculated as total subsidy given by govt.on elementary education divided by total number of students enrolled in the corresponding state for elementary level.

The table shows the regional disparities in unit subsidy in elementary level of education. It is found from the table that the subsidy per student is he highest for Kerala followed by Tamil Nadu, Orissa, Gujarat and Bihar. States with low level of subsidies are Andhra Pradesh, West Bengal and Madhya Pradesh. However, this does not imply that Kerala spends the highest amount among the 15 states, because, the unit subsidy is a combination of two factors: demand of public education and total public expenditure on elementary education incurred by state.

Table 3.2: Unit Subsidy in Secondary Level of education

|States |Gross Expd. (lakhs) |Cost Recovery (Lakhs) |Total Amount of |Subsidy Per Student |

| | | |Subsidy.(lakhs) |(Rs./annum) |

|Andhra Pradesh |76030 |1698.5926 |74332 |7568 |

|Assam |35494 |186.15 |35308 |6410 |

|Bihar |49768 |786.55709 |48981 |6958 |

|Gujarat |101691 |420.9606 |101270 |7862 |

|Haryana |49774 |62.89995 |49711 |5867 |

|Karnataka |78068 |1802.8502 |76265 |4762 |

|Kerala |60247 |1811.6728 |58435 |7029 |

|Madhya Pradesh |54519 |5.84694 |54513 |3320 |

|Maharashtra |198952 |67.02645 |198885 |12297 |

|Orissa |41669 |0.08954 |41669 |5946 |

|Punjab |94085 |560.49917 |93525 |11220 |

|Rajasthan |97627 |243.09954 |97384 |8723 |

|Tamil Nadu |146251 |2592.8335 |143658 |7104 |

|Uttar Pradesh |181722 |8128.3643 |173594 |5041 |

|West Bengal |148548 |6.90751 |148541 |13675 |

Source: Analysis of Budgeted Expenditure on Education, Various years, MHRD, GOI

Finance accounts of different states, 1999-2000 Ministry of Finance, GOI

Similar to the previous table the table above presents the result of state wise estimates of unit subsidies in secondary education. Same methodology is applied here for calculating unit level subsidy in secondary education. In case of secondary education the amount of unit subsidy is highest in west Bengal, followed by Maharashtra and Punjab. Madhya Pradesh gets minimum amount of subsidy. However, here also this does not imply that West Bengal spends the highest amount among the 15 states.

Table 3.3: Unit Subsidy in Tertiary Level of Education

|States |Gross Expd. (lakhs) |Cost Recovery (Lakhs) |Total Amount of |Subsidy Per Student |

| | | |Subsidy.(lakhs) |(Rs./annum) |

|Andhra Pradesh |49963.83 |229.9141 |49733.916 |10045 |

|Assam* |11718 | |11718 |6042 |

|Bihar |31427.15 |11.0328 |31416.117 |6269 |

|Gujarat |24087.05 |599.023 |23488.027 |7824 |

|Haryana |11566.5 |63.54969 |11502.95 |6728 |

|Karnataka |30878.75 |0 |30878.75 |3871 |

|Kerala |31062.87 |882.6055 |30180.265 |16442 |

|Madhya Pradesh |23560.39 |690.52909 |22869.861 |9189 |

|Maharashtra |49363.47 |184.53238 |49178.938 |6431 |

|Orissa |19510.87 |101.39 |19409.48 |12119 |

|Punjab |16528.17 |165.26361 |16362.906 |10699 |

|Rajasthan |19414.11 |143.48832 |19270.622 |7319 |

|Tamil Nadu |29533.2 |688.90166 |28844.298 |11575 |

|Uttar Pradesh |40876.23 |424.07519 |40452.155 |4979 |

|West Bengal |36230.54 |12.27635 |36218.264 |8596 |

Source: Analysis of Budgeted Expenditure on Education, Various years, MHRD, GOI.

Finance accounts of different states, 1999-2000 Ministry of Finance, GOI

* Recovery data is not available. Hence gross expenditure assumed to be the total subsidy.

The table above presents the result of state wise estimates of unit subsidies in tertiary level of education. States with high level of subsidies are Kerala, Orissa, Punjab and Andhra Pradesh. Karnataka spends substantially low amount of subsidies compare to other states. It is also found that the amount of unit subsidy is highest in tertiary level of education than elementary and secondary level.

In this part an attempt is made to analyze the gender disparity in education for all educational level by MPCE class and for both rural and urban area across states.

Here, gender disparity is highlighted across educational attainment among household surveyed for each MPCE group and each education level.

Table 3.4: Percentage of Educational Attainment by Gender, MPCE Class, Area and States (1999-2000)

|MPCE Class/States |Rural |Urban |

| |Male |Female |Male |Female |

|Andhra Pradesh |

|Poor |18% |10% |25.0% |17.2% |

|Lower Middle |22% |12% |29.8% |29.1% |

|Upper Middle |24% |16% |29.0% |32.5% |

|Rich |27% |25% |11.7% |27.0% |

|Assam |

|Poor |28% |22% |35.0% |26.7% |

|Lower Middle |39% |28% |49.5% |39.5% |

|Upper Middle |44% |33% |35.4% |40.5% |

|Rich |41% |41% |14.9% |26.8% |

|Bihar |

|Poor |16% |4% |25.0% |16.4% |

|Lower Middle |22% |10% |30.5% |24.9% |

|Upper Middle |27% |15% |22.9% |27.3% |

|Rich |25% |21% |15.6% |19.0% |

|Gujarat |

|Poor |31% |11% |34.3% |18.3% |

|Lower Middle |28% |15% |42.7% |32.9% |

|Upper Middle |35% |21% |40.2% |37.2% |

|Rich |35% |29% |22.1% |23.2% |

|Haryana |

|Poor |15% |5% |21.3% |7.2% |

|Lower Middle |21% |12% |34.0% |21.9% |

|Upper Middle |29% |21% |32.6% |29.1% |

|Rich |32% |26% |20.8% |20.9% |

|Karnataka |

|Poor |21.5% |9.3% |36.7% |28.8% |

|Lower Middle |30.4% |18.5% |35.6% |33.7% |

|Upper Middle |35.2% |25.1% |37.4% |34.3% |

|Rich |36.4% |31.0% |18.3% |22.9% |

|Kerala |

|Poor |46.0% |41.6% |59.5% |58.3% |

|Lower Middle |57.1% |43.2% |63.1% |51.0% |

|Upper Middle |56.6% |49.4% |50.2% |47.7% |

|Rich |50.4% |48.1% |33.2% |33.7% |

|Madhya Pradesh |

|Poor |18.8% |9.4% |26.4% |18.3% |

|Lower Middle |27.0% |13.4% |36.8% |28.2% |

|Upper Middle |33.1% |15.9% |29.0% |28.8% |

|Rich |34.4% |26.1% |16.9% |18.6% |

|Maharashtra |

|Poor |34.8% |24.9% |44.9% |38.1% |

|Lower Middle |40.3% |30.6% |45.9% |41.3% |

|Upper Middle |43.7% |33.4% |40.8% |41.5% |

|Rich |37.7% |36.7% |24.8% |26.5% |

|Orissa |

|Poor |17.0% |8.7% |29.1% |20.1% |

|Lower Middle |29.0% |20.3% |36.6% |26.6% |

|Upper Middle |36.4% |25.5% |25.9% |31.1% |

|Rich |33.5% |32.8% |11.8% |26.4% |

|Punjab |

|Poor |1.7% |3.7% |27.8% |20.4% |

|Lower Middle |23.0% |11.0% |31.7% |26.4% |

|Upper Middle |26.0% |21.6% |30.2% |26.7% |

|Rich |28.9% |27.5% |20.2% |17.8% |

|Rajasthan |

|Poor |17.8% |3.3% |28.9% |12.6% |

| |26.1% |6.1% |36.7% |25.0% |

|Lower Middle | | | | |

|Upper Middle |31.0% |10.5% |30.3% |28.1% |

|Rich |32.7% |16.4% |22.5% |25.1% |

|Tamil Nadu |

|Poor |29.1% |19.7% |43.0% |33.9% |

|Lower Middle |36.6% |26.1% |46.2% |38.9% |

|Upper Middle |38.8% |28.9% |40.8% |37.3% |

|Rich |39.5% |31.8% |20.9% |24.0% |

|Uttar Pradesh |

|Poor |23.2% |8.7% |25.9% |15.9% |

|Lower Middle |25.9% |12.7% |33.6% |22.4% |

|Upper Middle |29.2% |17.1% |27.1% |25.8% |

|Rich |33.2% |24.0% |19.6% |23.1% |

|West Bengal |

|Poor |26.2% |14.2% |31.3% |21.8% |

|Lower Middle |30.8% |19.8% |43.7% |36.8% |

|Upper Middle |40.4% |33.0% |34.1% |43.6% |

|Rich |39.7% |40.7% |18.6% |24.3% |

Source: NSSO, 55th Round, report no. 473 Literacy and Levels of Education in India, 1999-2000

Attainment rates rise with household expenditures per capita nationally and in all states, and they tend to be higher for boys than for girls. (Lanjouw and Ravallion ,1998 .)

We begin with primary school enrollment for person aged 7 and above. The calculated attainment rates from the NSS are appreciably lower than those obtained from schools themselves, on which official enrollment rates are based.

The table above presents the state wise percentage of educational attainment for elementary level of education by MPCE class, gender and area. The percentage shows typical biases in attainment behaviour, with males having more attainment than girls. The bias is more noticeable for poor income class. In all states the attainment is increasing with increase in MPCE for both male and female and also the disparity is lowering. Another important feature is educational attainment is more in urban area compare to rural area for both sex and gender disparity is also less for all MPCE classes. In both areas gender disparity is decreasing with increase in MPCE.

In Andhra Pradesh, female attainment is more than male in middle and rich MPCE class, which is a welcome sign of gender development. Kerala shows even distribution of attainment between male and female.

|Secondary Level |

|MPCE Class/States |Rural |Urban |

| |Male |Female |Male |Female |

|Andhra Pradesh |

|Poor |4% |2% |8.7% |3.9% |

|Lower Middle |8% |3% |21.3% |12.0% |

|Upper Middle |11% |4% |34.3% |23.7% |

|Rich |23% |13% |38.1% |35.1% |

|Assam |

|Poor |4% |2% |5.4% |1.6% |

|Lower Middle |8% |5% |22.5% |17.1% |

|Upper Middle |16% |10% |31.2% |30.7% |

|Rich |28% |25% |33.3% |28.0% |

|Bihar |

|Poor |4% |1% |9.3% |4.2% |

|Lower Middle |10% |2% |22.7% |14.6% |

|Upper Middle |16% |5% |34.1% |32.9% |

|Rich |26% |13% |27.4% |38.1% |

|Gujarat |

|Poor |8% |3% |7.7% |1.8% |

|Lower Middle |9% |2% |17.9% |9.3% |

|Upper Middle |11% |5% |31.2% |23.1% |

|Rich |25% |16% |32.4% |33.8% |

|Haryana* |

|Poor | |0.1% |4.4% |0.9% |

|Lower Middle |9.0% |2.2% |11.5% |9.5% |

|Upper Middle |14.6% |3.5% |28.3% |23.8% |

|Rich |25.1% |13.8% |39.7% |32.8% |

|Karnataka |

|Poor |6.4% |1.9% |11.9% |5.9% |

|Lower Middle |10.5% |3.0% |22.1% |15.6% |

|Upper Middle |13.4% |6.7% |32.8% |28.6% |

|Rich |27.2% |18.2% |39.5% |41.3% |

|Kerala |

|Poor |7.9% |6.3% |10.7% |13.9% |

|Lower Middle |7.7% |11.2% |15.6% |18.4% |

|Upper Middle |13.7% |14.4% |29.2% |26.0% |

|Rich |25.3% |22.8% |35.5% |40.4% |

|Madhya Pradesh |

|Poor |4.2% |0.6% |10.7% |4.3% |

|Lower Middle |6.6% |1.8% |20.8% |12.2% |

|Upper Middle |11.6% |2.7% |30.4% |24.0% |

|Rich |19.9% |7.7% |28.9% |26.5% |

|Maharashtra |

|Poor |6.9% |2.1% |10.9% |5.3% |

|Lower Middle |11.0% |3.8% |21.1% |11.9% |

|Upper Middle |17.7% |8.2% |31.7% |21.3% |

|Rich |30.6% |16.7% |36.3% |32.7% |

|Orissa | | | | |

|Poor |3.5% |1.0% |7.9% |3.1% |

|Lower Middle |9.1% |3.1% |20.2% |17.1% |

|Upper Middle |14.1% |7.8% |37.2% |30.3% |

|Rich |29.3% |20.2% |21.5% |28.9% |

|Punjab |

|Poor |1.7% |1.7% |10.0% |7.1% |

|Lower Middle |8.9% |3.6% |16.6% |14.5% |

|Upper Middle |11.7% |8.9% |30.9% |26.9% |

|Rich |23.9% |17.2% |34.4% |35.6% |

|Rajasthan |

|Poor |4.6% |0.2% |9.2% |1.6% |

|Lower Middle |5.9% |0.7% |18.2% |8.5% |

|Upper Middle |7.6% |1.2% |29.2% |17.5% |

|Rich |15.5% |4.0% |31.8% |29.4% |

|Tamil Nadu |

|Poor |5.4% |2.4% |9.7% |7.3% |

|Lower Middle |10.1% |6.0% |19.3% |13.1% |

|Upper Middle |12.8% |7.1% |32.0% |23.7% |

|Rich |24.0% |17.6% |37.8% |35.8% |

|Uttar Pradesh |

|Poor |4.8% |1.0% |9.6% |4.9% |

|Lower Middle |9.6% |2.3% |16.5% |14.9% |

|Upper Middle |13.6% |5.3% |32.3% |22.2% |

|Rich |21.7% |10.8% |31.5% |24.6% |

|West Bengal |

|Poor |2.5% |1.4% |5.0% |1.8% |

|Lower Middle |3.8% |1.1% |13.9% |8.7% |

|Upper Middle |10.5% |4.1% |27.6% |22.7% |

|Rich |22.2% |12.8% |28.5% |30.4% |

* Data for poor MPCE class not available

The table above presents the state wise percentage of educational attainment for secondary level of education by MPCE class, gender and area. Same pattern is observed for secondary level of attainment similar to elementary level. In this level, for all states male attainment is higher than female that is gender disparity is typically present. Another noticeable feature is with increase in MPCE class gender disparity is increasing. The disparity is more in rural area compare to urban area irrespective of states.

|Tertiary Level |

|MPCE Class/States |Rural |Urban |

| |Male |Female |Male |Female |

|Andhra Pradesh |

|Poor |0.4% |0.0% |0.7% |0.3% |

|Lower Middle |0.7% |0.1% |5.2% |2.0% |

|Upper Middle |1.5% |0.3% |16.5% |6.4% |

|Rich |7.6% |2.6% |39.8% |21.5% |

|Assam |

|Poor |0.0% |0.2% |0.2% |0.0% |

|Lower Middle |1.5% |0.4% |5.9% |4.2% |

|Upper Middle |2.2% |0.5% |16.8% |5.3% |

|Rich |9.6% |2.6% |41.4% |34.6% |

|Bihar |

|Poor |0.7% |0.1% |1.7% |0.1% |

|Lower Middle |1.6% |0.2% |11.2% |5.7% |

|Upper Middle |4.0% |0.6% |26.9% |8.0% |

|Rich |11.8% |4.4% |43.6% |32.4% |

|Gujarat |

|Poor |0.0% |0.4% |1.5% |0.7% |

|Lower Middle |1.2% |0.4% |1.8% |1.3% |

|Upper Middle |1.4% |0.4% |8.3% |5.7% |

|Rich |5.9% |2.7% |35.2% |29.2% |

|Haryana |

|Poor |0.0% |0.0% |0.1% |0.2% |

|Lower Middle |0.7% |0.0% |1.8% |1.9% |

|Upper Middle |1.0% |0.2% |8.8% |7.8% |

|Rich |5.2% |1.3% |25.1% |24.4% |

|Karnataka |

|Poor |0.5% |0.0% |1.0% |0.6% |

|Lower Middle |1.2% |0.0% |5.5% |2.3% |

|Upper Middle |1.7% |3.0% |13.0% |5.9% |

|Rich |7.9% |0.6% |33.3% |21.2% |

|Kerala |

|Poor |0.0% |0.0% |1.2% |0.6% |

|Lower Middle |0.4% |0.9% |2.0% |2.0% |

|Upper Middle |1.5% |1.0% |5.9% |5.3% |

|Rich |6.3% |5.0% |22.9% |15.3% |

|Madhya Pradesh |

|Poor |0.3% |0.0% |2.7% |1.1% |

|Lower Middle |1.1% |0.1% |5.7% |3.5% |

|Upper Middle |2.0% |0.4% |20.3% |10.6% |

|Rich |6.6% |1.8% |44.2% |33.8% |

|Maharashtra |

|Poor |0.8% |0.0% |0.9% |0.3% |

|Lower Middle |1.2% |0.3% |3.2% |1.4% |

|Upper Middle |1.8% |0.2% |8.3% |5.4% |

|Rich |9.8% |3.8% |27.9% |26.5% |

|Orissa |

|Poor |0.3% |0.2% |0.9% |1.3% |

|Lower Middle |1.7% |0.5% |5.0% |1.9% |

|Upper Middle |4.1% |1.2% |16.7% |6.6% |

|Rich |11.3% |3.8% |50.2% |35.1% |

|Punjab |

|Poor |0.9% |0.0% |0.0% |0.2% |

|Lower Middle |0.5% |0.0% |1.3% |1.8% |

|Upper Middle |0.2% |0.3% |6.9% |7.5% |

|Rich |2.4% |1.7% |28.5% |31.1% |

|Rajasthan |

|Poor |0.4% |0.0% |1.0% |0.6% |

|Lower Middle |0.6% |0.0% |4.6% |1.3% |

|Upper Middle |1.1% |0.1% |14.1% |8.5% |

|Rich |4.2% |0.4% |35.8% |24.4% |

|Tamil Nadu |

|Poor |0.8% |0.0% |1.1% |0.6% |

|Lower Middle |1.2% |0.3% |2.5% |1.6% |

|Upper Middle |1.8% |0.2% |8.9% |5.5% |

|Rich |9.8% |3.8% |32.3% |24.7% |

|Uttar Pradesh |

|Poor |0.8% |0.0% |2.9% |2.0% |

|Lower Middle |1.2% |0.3% |5.7% |3.9% |

|Upper Middle |1.8% |0.2% |16.1% |12.4% |

|Rich |9.8% |3.8% |33.6% |33.2% |

|West Bengal |

|Poor |0.7% |0.2% |0.4% |0.5% |

|Lower Middle |0.4% |0.2% |4.7% |2.0% |

|Upper Middle |2.2% |0.3% |16.3% |8.0% |

|Rich |10.9% |3.6% |44.3% |31.9% |

The table above presents the state wise percentage of educational attainment for tertiary level of education by MPCE class, gender and area. In tertiary level of education, the attainment is very low for poor and middle MPCE class. In rural area percentage of female attainment is insignificant compare to urban female. Except some states like Assam, Bihar, Gujarat, Orissa and west Bengal in all other states female attainment is nil in poor MPCE class. Middle class also fail to achieve a significant amount of attainment for both male and female in rural area. The total tertiary attainment is prorich and mostly urban people can avail it. But in urban area also the gender disparity is significant in rich MPCE class. Only exception is Punjab where female attainment is higher than male.

Gender Disaggregated Benefit Incidence of Public Spending:

By combining the unit subsidy to the public education system with the educational attainment avail by household, we can estimate the benefit estimates of government spending on education. The levels of education wise results of this exercise are presented in three tables.

Four types of disaggregation are reported. First, the subsidy is distributed across the four MPCE class. Second, the estimates are disaggregated by region, third by state and finally, it is reported by gender.

In all the exercise, first it is calculated how the subsidy of each state is distributed between rural and urban area by gender group in all MPCE classes and then the pattern of distribution of this subsidy for each MPCE class.

Table 3.5: Percentage of Subsidy Received by, Gender, MPCE Class, area and States in Elementary level of Education

|MPCE Class/States |Rural |Urban |

| |Male |Female |Male |Female |

|Andhra Pradesh |

|Poor |11.7 |6.5 |12.4 |8.5 |

|Lower Middle |14.4 |8.0 |14.8 |14.5 |

|Upper Middle |15.6 |10.5 |14.4 |16.1 |

|Rich |17.6 |15.7 |5.8 |13.4 |

|All |59.2 |40.8 |47.5 |52.5 |

|Assam |

|Poor |10.2 |7.8 |13.1 |10.0 |

|Lower Middle |14.0 |10.2 |18.4 |14.7 |

|Upper Middle |16.0 |12.0 |13.2 |15.1 |

|Rich |14.8 |15.0 |5.5 |10.0 |

|All |55.0 |45.0 |50.2 |49.8 |

|Bihar |

|Poor |11.1 |3.1 |13.7 |9.0 |

|Lower Middle |15.9 |6.9 |16.8 |13.7 |

|Upper Middle |19.1 |10.8 |12.6 |15.0 |

|Rich |18.2 |14.8 |8.6 |10.5 |

|All |64.4 |35.6 |51.7 |48.3 |

|Gujarat |

|Poor |15.3 |5.3 |13.7 |7.3 |

|Lower Middle |13.7 |7.2 |17.0 |13.1 |

|Upper Middle |17.1 |10.2 |16.0 |14.8 |

|Rich |17.2 |14.1 |8.8 |9.2 |

|All |63.3 |36.7 |55.5 |44.5 |

|Haryana |

|Poor |9.2 |2.9 |11.4 |3.8 |

|Lower Middle |12.8 |7.8 |18.1 |11.7 |

|Upper Middle |17.8 |13.2 |17.4 |15.5 |

|Rich |20.1 |16.3 |11.1 |11.1 |

|All |59.8 |40.2 |57.9 |42.1 |

|Karnataka |

|Poor |10.4 |4.5 |14.8 |11.6 |

|Lower Middle |14.6 |8.9 |14.4 |13.6 |

|Upper Middle |17.0 |12.1 |15.1 |13.8 |

|Rich |17.6 |14.9 |7.4 |9.3 |

|All |59.5 |40.5 |51.7 |48.3 |

|Kerala |

|Poor |11.7 |10.6 |15.0 |14.7 |

|Lower Middle |14.6 |11.0 |15.9 |12.9 |

|Upper Middle |14.4 |12.6 |12.7 |12.0 |

|Rich |12.8 |12.3 |8.4 |8.5 |

|All |53.5 |46.5 |51.9 |48.1 |

|Madhya Pradesh |

|Poor |10.6 |5.3 |13.0 |9.0 |

|Lower Middle |15.2 |7.5 |18.1 |13.9 |

|Upper Middle |18.6 |8.9 |14.3 |14.2 |

|Rich |19.3 |14.6 |8.3 |9.2 |

|All |63.6 |36.4 |53.7 |46.3 |

|Maharashtra |

|Poor |12.3 |8.8 |14.8 |12.6 |

|Lower Middle |14.3 |10.8 |15.1 |13.6 |

|Upper Middle |15.5 |11.8 |13.4 |13.6 |

|Rich |13.4 |13.0 |8.2 |8.7 |

|All |55.5 |44.5 |51.5 |48.5 |

|Orissa |

|Poor |8.4 |4.3 |14.0 |9.7 |

|Lower Middle |14.3 |10.0 |17.6 |12.8 |

|Upper Middle |17.9 |12.5 |12.5 |15.0 |

|Rich |16.5 |16.1 |5.7 |12.7 |

|All |57.1 |42.9 |49.8 |50.2 |

|Punjab |

|Poor |1.2 |2.6 |13.8 |10.1 |

|Lower Middle |16.0 |7.7 |15.7 |13.1 |

|Upper Middle |18.1 |15.1 |15.0 |13.3 |

|Rich |20.1 |19.2 |10.1 |8.8 |

|All |55.5 |44.5 |54.6 |45.4 |

|Rajasthan |

|Poor |12.4 |2.3 |13.8 |6.0 |

|Lower Middle |18.1 |4.3 |17.5 |12.0 |

|Upper Middle |21.6 |7.3 |14.5 |13.4 |

|Rich |22.7 |11.4 |10.8 |12.0 |

|All |74.8 |25.2 |56.6 |43.4 |

|Tamil Nadu |

|Poor |11.6 |7.9 |15.1 |11.9 |

|Lower Middle |14.6 |10.4 |16.2 |13.7 |

|Upper Middle |15.5 |11.5 |14.3 |13.1 |

|Rich |15.8 |12.7 |7.3 |8.4 |

|All |57.5 |42.5 |52.9 |47.1 |

|Uttar Pradesh |

|Poor |13.3 |5.0 |13.4 |8.2 |

|Lower Middle |14.9 |7.3 |17.4 |11.6 |

|Upper Middle |16.8 |9.8 |14.0 |13.3 |

|Rich |19.1 |13.8 |10.1 |12.0 |

|All |64.0 |36.0 |54.9 |45.1 |

|West Bengal |

|Poor |10.7 |5.8 |12.3 |8.6 |

|Lower Middle |12.6 |8.1 |17.2 |14.5 |

|Upper Middle |16.5 |13.5 |13.4 |17.1 |

|Rich |16.2 |16.6 |7.3 |9.6 |

|All |56.0 |44.0 |50.2 |49.8 |

The table shows that the advantage of subsidy in elementary level is much more grasped by rural people than urban people irrespective of sex and MPCE class. The distribution of subsidy is relatively more pro poor. Though there is gender difference in use of public subsidy in each MPCE class and in each state also but the difference is not that much significant. It is also found that the relative disadvantage of female is greater in poor household. One interesting feature is that except Punjab and Haryana, in most of the states in upper middle class and in all states in the rich MPCE class the urban females are capturing more public subsidy compare to urban males and in Andhra Pradesh and Orissa the picture prevails for overall urban educational attainment also. Where the urban males are getting 47.5% of the subsidy, this is 52.5% for the urban female. That implies a progressivism in the elementary education among people of Andhra Pradesh. The highest gender disparity persists in rural area of Rajasthan where females get just one –third of subsidy that of male. Rajasthan is followed by Uttar Pradesh and Madhya Pradesh rural regions. In urban area, the level of subsidy is more than rural area in all states with increase in MPCE class. In both region subsidy is increasing with increase in per capita expenditure but the gender difference is getting lesser in urban area with this increase compare to rural area.

Table 3.6: Percentage of Subsidy Received by, Gender, MPCE Class, area and States in secondary level of Education

|MPCE Class/States |Rural |Urban |

| |Male |Female |Male |Female |

|Andhra Pradesh |

|Poor |5.4 |3.0 |4.9 |2.2 |

|Lower Middle |11.2 |3.7 |12.0 |6.8 |

|Upper Middle |16.5 |6.0 |19.4 |13.4 |

|Rich |34.7 |19.5 |21.5 |19.8 |

|All |67.7 |32.3 |57.8 |42.2 |

|Assam |

|Poor |3.8 |2.1 |3.2 |0.9 |

|Lower Middle |7.9 |5.4 |13.3 |10.1 |

|Upper Middle |16.2 |10.0 |18.4 |18.1 |

|Rich |28.7 |25.8 |19.6 |16.5 |

|All |56.6 |43.4 |54.4 |45.6 |

|Bihar |

|Poor |5.9 |1.0 |5.1 |2.3 |

|Lower Middle |12.6 |2.8 |12.4 |8.0 |

|Upper Middle |20.7 |6.7 |18.6 |18.0 |

|Rich |33.5 |16.9 |14.9 |20.8 |

|All |72.6 |27.4 |51.0 |49.0 |

|Gujarat |

|Poor |9.6 |3.5 |4.9 |1.1 |

|Lower Middle |12.0 |2.9 |11.4 |5.9 |

|Upper Middle |13.4 |6.4 |19.9 |14.7 |

|Rich |31.9 |20.2 |20.6 |21.5 |

|All |67.0 |33.0 |56.8 |43.2 |

|Haryana* |

|Poor |0.0 |0.1 |2.9 |0.6 |

|Lower Middle |13.1 |3.3 |7.6 |6.3 |

|Upper Middle |21.3 |5.2 |18.8 |15.8 |

|Rich |36.8 |20.2 |26.3 |21.7 |

|All |71.2 |28.8 |55.6 |44.4 |

|Karnataka |

|Poor |7.3 |2.2 |6.0 |3.0 |

|Lower Middle |12.1 |3.4 |11.2 |7.9 |

|Upper Middle |15.3 |7.7 |16.6 |14.5 |

|Rich |31.1 |20.9 |20.0 |20.9 |

|All |65.8 |34.2 |53.8 |46.2 |

|Kerala |

|Poor |7.2 |5.8 |5.6 |7.3 |

|Lower Middle |7.0 |10.2 |8.2 |9.7 |

|Upper Middle |12.5 |13.2 |15.4 |13.7 |

|Rich |23.1 |20.8 |18.7 |21.3 |

|All |49.9 |50.1 |48.0 |52.0 |

|Madhya Pradesh |

|Poor |7.7 |1.0 |6.8 |2.7 |

|Lower Middle |11.9 |3.2 |13.2 |7.8 |

|Upper Middle |21.0 |5.0 |19.3 |15.2 |

|Rich |36.1 |13.9 |18.3 |16.8 |

|All |76.8 |23.2 |57.6 |42.4 |

|Maharashtra |

|Poor |7.1 |2.1 |6.4 |3.1 |

|Lower Middle |11.4 |3.9 |12.3 |7.0 |

|Upper Middle |18.2 |8.5 |18.5 |12.4 |

|Rich |31.5 |17.2 |21.2 |19.1 |

|All |68.2 |31.8 |58.4 |41.6 |

|Orissa |

|Poor |4.0 |1.1 |4.8 |1.9 |

|Lower Middle |10.3 |3.5 |12.1 |10.3 |

|Upper Middle |16.0 |8.8 |22.3 |18.2 |

|Rich |33.3 |23.0 |12.9 |17.4 |

|All |63.6 |36.4 |52.2 |47.8 |

|Punjab |

|Poor |2.2 |2.1 |5.7 |4.0 |

|Lower Middle |11.5 |4.7 |9.5 |8.2 |

|Upper Middle |15.1 |11.4 |17.5 |15.3 |

|Rich |30.8 |22.1 |19.6 |20.2 |

|All |59.6 |40.4 |52.2 |47.8 |

|Rajasthan |

|Poor |11.5 |0.4 |6.3 |1.1 |

|Lower Middle |14.8 |1.9 |12.5 |5.9 |

|Upper Middle |19.1 |3.1 |20.1 |12.0 |

|Rich |39.1 |10.0 |21.8 |20.2 |

|All |84.6 |15.4 |60.8 |39.2 |

|Tamil Nadu |

|Poor |6.3 |2.8 |5.4 |4.1 |

|Lower Middle |11.8 |7.0 |10.8 |7.3 |

|Upper Middle |15.0 |8.3 |17.9 |13.3 |

|Rich |28.1 |20.6 |21.2 |20.0 |

|All |61.2 |38.8 |55.3 |44.7 |

|Uttar Pradesh |

|Poor |6.9 |1.4 |6.2 |3.1 |

|Lower Middle |14.0 |3.3 |10.5 |9.5 |

|Upper Middle |19.7 |7.6 |20.6 |14.2 |

|Rich |31.4 |15.7 |20.1 |15.7 |

|All |71.9 |28.1 |57.5 |42.5 |

|West Bengal |

|Poor |4.3 |2.4 |3.6 |1.3 |

|Lower Middle |6.5 |1.9 |10.0 |6.3 |

|Upper Middle |17.9 |7.0 |19.9 |16.4 |

|Rich |38.1 |21.9 |20.5 |22.0 |

|All |66.9 |33.1 |54.1 |45.9 |

* Data for poor MPCE class not available

Government spending on secondary education primarily benefits the non poor. It is evident from the table that the gender disparity is increasing with increase in education level. Karnataka, Kerala, Orissa, Punjab, and Gujarat –in all these states females acquire more subsidy than male in urban rich MPCE class. Kerala shows gender equity in subsidy distribution for all expenditure class in both rural and urban areas. In each of the state irrespective of expenditure class the distribution is in favour of male attendance. The gender disparity is quite huge in rural area compare to urban area. Some states with a high gender difference in subsidy distribution are Rajasthan, Uttar Pradesh, Madhya Pradesh, Haryana and Bihar. In all these states the percentage of subsidy to female is 1/3rd that of male whereas in Rajasthan it is more than 14th of what male gets. However a similar pattern exists at secondary level as elementary level. With increase in household expenditure the gender disparity is decreasing.

Table 3.7: Percentage of Subsidy Received by, Gender, MPCE Class, area and States in Tertiary level of Education

|MPCE Class/States |Rural |Urban |

| |Male |Female |Male |Female |

|Andhra Pradesh |

|Poor |2.8 |0.0 |0.8 |0.3 |

|Lower Middle |5.1 |1.0 |5.7 |2.2 |

|Upper Middle |11.4 |2.3 |17.9 |7.0 |

|Rich |57.6 |19.9 |43.0 |23.2 |

|All |76.8 |23.2 |67.3 |32.7 |

|Assam |

|Poor |0.0 |1.2 |0.2 |0.0 |

|Lower Middle |8.6 |2.5 |5.4 |3.9 |

|Upper Middle |12.9 |3.1 |15.5 |4.9 |

|Rich |56.3 |15.4 |38.2 |31.9 |

|All |77.7 |22.3 |59.3 |40.7 |

|Bihar |

|Poor |2.9 |0.3 |1.3 |0.1 |

|Lower Middle |6.8 |0.7 |8.7 |4.4 |

|Upper Middle |17.2 |2.6 |20.7 |6.2 |

|Rich |50.7 |18.8 |33.6 |25.0 |

|All |77.6 |22.4 |64.3 |35.7 |

|Gujarat |

|Poor |0.0 |3.0 |1.8 |0.8 |

|Lower Middle |9.4 |3.2 |2.2 |1.5 |

|Upper Middle |11.3 |3.5 |10.0 |6.8 |

|Rich |47.7 |21.8 |42.1 |35.0 |

|All |68.5 |31.5 |55.9 |44.1 |

|Haryana |

|Poor |0.4 |0.0 |0.2 |0.2 |

|Lower Middle |8.3 |0.0 |2.6 |2.7 |

|Upper Middle |11.5 |2.0 |12.5 |11.2 |

|Rich |62.1 |15.8 |35.7 |34.8 |

|All |82.2 |17.8 |51.1 |48.9 |

|Karnataka |

|Poor |3.4 |0.2 |1.2 |0.7 |

|Lower Middle |8.3 |0.0 |6.6 |2.7 |

|Upper Middle |11.4 |20.0 |15.8 |7.1 |

|Rich |52.9 |3.8 |40.2 |25.6 |

|All |76.0 |24.0 |63.8 |36.2 |

|Kerala |

|Poor |0.0 |0.0 |2.2 |1.1 |

|Lower Middle |2.4 |5.8 |3.6 |3.6 |

|Upper Middle |10.0 |6.7 |10.7 |9.6 |

|Rich |41.9 |33.3 |41.5 |27.7 |

|All |54.3 |45.7 |57.9 |42.1 |

|Madhya Pradesh |

|Poor |2.4 |0.0 |2.2 |0.9 |

|Lower Middle |8.9 |1.1 |4.7 |2.8 |

|Upper Middle |15.9 |3.2 |16.7 |8.7 |

|Rich |53.5 |14.9 |36.3 |27.7 |

|All |80.8 |19.2 |59.9 |40.1 |

|Maharashtra |

|Poor |4.6 |0.0 |1.2 |0.4 |

|Lower Middle |6.9 |1.7 |4.3 |1.9 |

|Upper Middle |9.8 |1.1 |11.3 |7.3 |

|Rich |54.7 |21.2 |37.8 |35.9 |

|All |76.1 |23.9 |54.6 |45.4 |

|Orissa |

|Poor |1.2 |0.7 |0.8 |1.1 |

|Lower Middle |7.5 |2.2 |4.2 |1.6 |

|Upper Middle |17.9 |5.3 |14.2 |5.6 |

|Rich |48.8 |16.3 |42.7 |29.9 |

|All |75.4 |24.6 |61.9 |38.1 |

|Punjab |

|Poor |14.5 |0.0 |0.0 |0.2 |

|Lower Middle |7.8 |0.0 |1.7 |2.4 |

|Upper Middle |3.9 |4.5 |8.9 |9.7 |

|Rich |40.8 |28.5 |36.8 |40.2 |

|All |67.0 |33.0 |47.5 |52.5 |

|Rajasthan |

|Poor |5.9 |0.5 |1.1 |0.7 |

|Lower Middle |9.3 |0.0 |5.1 |1.4 |

|Upper Middle |16.1 |1.0 |15.6 |9.4 |

|Rich |62.0 |5.4 |39.6 |27.0 |

|All |93.2 |6.8 |61.5 |38.5 |

|Tamil Nadu |

|Poor |4.6 |0.0 |1.4 |0.7 |

|Lower Middle |6.9 |1.7 |3.3 |2.0 |

|Upper Middle |9.8 |1.1 |11.5 |7.2 |

|Rich |54.7 |21.2 |41.9 |32.0 |

|All |76.1 |23.9 |58.0 |42.0 |

|Uttar Pradesh |

|Poor |4.6 |0.0 |2.6 |1.8 |

|Lower Middle |6.9 |1.7 |5.2 |3.5 |

|Upper Middle |9.8 |1.1 |14.6 |11.3 |

|Rich |54.7 |21.2 |30.7 |30.3 |

|All |76.1 |23.9 |53.1 |46.9 |

|West Bengal |

|Poor |3.9 |0.9 |0.4 |0.4 |

|Lower Middle |2.3 |1.3 |4.3 |1.9 |

|Upper Middle |12.0 |1.8 |15.1 |7.4 |

|Rich |58.5 |19.2 |41.0 |29.5 |

|All |76.8 |23.2 |60.8 |39.2 |

The finding from the table confirms that widely held belief that higher education always benefits the non-poor. The relative disadvantage of females with respect to access to education is greatest at the tertiary level. Female receives lower subsidies in each expenditure groups and the disparity is more prominent in rural sector. The most shameless picture is portrayed by Rajasthan rural area. Where irrespective of expenditure class male attendance gets 93% subsidy and the rest 7% is captured by female. For all states except Kerala, the male subsidy is 65% and more than that in rural area. In Madhya Pradesh and Haryana it is more than 80%. For urban areas similar pattern exists at the tertiary level with slight change in magnitude. With increase in per capita expenditure the disparity in subsidy distribution decreases Punjab shows an example for rest of the states in minimizing gender disparity. Here, in urban areas female receives more subsidy than mal in upper middle and rich expenditure class.

Conclusion:

The results of ‘benefit incidence analysis’ powerfully explains which expenditure group actually benefited from the government’s subsidized education and how this benefit is distributed between males and females in India across states and regions. This helps to understand the root causes of gender disparity in India and helped in provide a guideline for developing a gender sensitized education policy.

Gender disaggregated benefit incidence analysis of government spending on education is able to give the answer why the poorest expenditure class has less accessibility to public education specially at the higher level of education. The main reason behind this is greater gender enrolment bias among the poor people in the society.

Attainment rates rise with household expenditure per capita nationally and in all states. They tend to be higher for boys than for girls. But there are marked difference among states. From the benefit incidence analysis it is found that subsidies in elementary level of education mildly favour rich compare to other MPCE classes since we cannot split the public and private schooling in the data, it is expected that public school enrolment may be lower for the rich. Spending in elementary education is on average pro poor and progressive. Elementary education is often regarded as an important tool for ensuring (universal) access to a formal education system, building human capital, and fighting poverty. For primary education to play such a role, it is imperative that the Poor’s share be higher. Although, it is important to note, this does not require propoor spending in the targeting sense.

At the elementary level of education the main beneficiaries are middle income group. Spending on secondary and tertiary education primarily benefits the rich expenditure class and there is strong evidence of middle class subsidy capture. This finding confirms that widely held belief that higher education always benefits the non-poor.The analysis shows that there is region wise disparity also in subsidy distribution. Urban people are more benefited than rural and among the urban the male parts achieve more educational subsidies in all level of education. The result varies only for few states.

Relative disadvantage of female is least at the elementary level. It is also observed that the relative disadvantage of female is correlated with household expenditure. With increase in level of per capita expenditure, the gain of subsidy for female also increases.

These results show that public spending on education benefited males more than females in 1999-2000 in India and all its states. This can be explained in two ways. First, households choose to enroll males more than females at all levels of education, so, despite higher public spending, a gender bias always persists in the benefit incidence of such spending. Secondly, public spending is not properly targeted to the regions of higher gender disparities. The result is failure of public spending in reducing gender disparity.

Based on Benefit Incidence Analysis some policy measures can be recommended to improve gender inequality in the society.

First, the poorest segment of the population receives the lowest subsidy in education, so policies related to public spending on education should be targeted towards the region with higher level of poverty.

Second, region specific education policy should be taken care of. Specially, public spending on rural female should be increased.

Third, instead of national policies state wise policies related to gender equality would be more appropriate in reducing gender disparity.

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Public Spending on Education

Composition of Spending

Public Provision of Effective Education Services

Total Consumption of Effective Education Services vicesSerService

Education Outcomes

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