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  • Fiscal Policy, Demographic Transition and Public Spending on Education: New Macroeconomic Evidence for Higher Education from India
abstract

This paper establishes the empirical relationship between the fiscal policy, demographic transition and public spending or expenditure on education in India with special reference to higher education. Public higher education spending is shown to be related to fiscal policy, if such expenditure is budgeted by the General Government and financed by general taxation and/or public debt. Demographic transition is analysed by population age structure transition and shown to impact on decline in enrollment in education through transition in Education Dependency Ratio. A forward-looking economic-demography model is used to forecast up to 2050 the interactive effects of demographic transition and public higher education expenditure within the framework of fiscal policy in 2011–12. Overall results indicate that, other things being equal including public expenditure commitment to education, demographic transition results in (a) additional budgetary resources for higher education without additional taxation, cut in expenditure benefits and new public debt and (b) decline in public education expenditure generosity by all levels of education in general and higher education in particular. This offers a new macroeconomic evidence for innovative public financing of higher education in India and lessons for other developing countries.

introduction

Fiscal policy is a deliberate formulation and change in design and implementation of budgets of General Government (comprising Union, State and Local levels) to attain the objectives of macroeconomic policy, such as, economic growth, stabilization and income distribution. In addition, the policy aims to integrate [End Page 405] the budget with Government’s socio-economic-political objectives and focuses on short and long run effects of budgetary policies on the entire economy. All expenditures (comprising revenue and capital expenditures) within the budgets of the General Government refer to the aggregate public expenditure. In general, these expenditures are financed by aggregate receipts (comprising revenue and capital receipts) through general taxation and/or borrowings. Aggregate public expenditure is equal to aggregate demand for budgetary resource and aggregate receipts is equal to aggregate supply of budgetary resources. Management of fiscal policy refers to balancing of aggregate supply of and demand for budgetary resources to attain the macroeconomic objectives. In the context of this paper, public spending on education refers to public expenditure on education (comprising all types and levels of education in public sector) within the budgets of the General Government and higher education refers to post-secondary education. Thus, public spending on higher education and its method of financing is an essential component of fiscal policy in India.

India’s higher education may be distinguished by levels and types. Levels include university education (Central, State, Deemed, Private, Open/Distance), autonomous institutes of higher learning (affiliated or not) and collegiate education (affiliated and autonomous). Types include general, technical, medical, agricultural, management and legal education. Institutions in these types and levels may be distinguished by their ownership (public or private), management (public or private or public-private) and financing. Financing of higher education may broadly include all those sources of financial and non-financial resources for institutional provisioning of educational services. In fact, institutions in higher education may be distinguished by their main source/s of financing, such as, public universities, Government colleges and private aided colleges funded by the Central and/or State governments, and private unaided universities and colleges. Own and non-own sources of private financing include management funds, students’ fees (including differential fee charged for management quota), industry contributions including through Corporate Social Responsibility, alumni associations, foreign direct investment, asset income (including interest income from corpus), affiliation fees, voluntary and tax-exempted philanthropy and donations. However, financing issues are important for ensuring affordability and social justice, and have important implications for quantity and quality of provisioning of sustained higher educational services to attain the objectives of higher education policy and employability of graduates for long term socioeconomic growth. However, fiscal policy formulation and management, as they are related to education sector, is a challenging policy task in India due to complexity of interactions between (a) economic structure characterized by the federal system of government and mixed and openness of the economic system; [End Page 406] (b) diversified fiscal policy objectives including economic growth, income distribution, fiscal sustainability, allocative efficiency and internal stabilization; (c) multiple fiscal policy instruments, such as, taxation, inter-governmental fiscal transfers, public expenditure and public debt; and (d) institutional (comprising Constitutional and non-Constitutional) arrangements for vertical and horizontal fiscal relationships and regulatory powers.

An important stakeholder in higher education is consumer of educational services provisioned by the institutions. Students are the direct consumers of higher educational services. They do incur expenditure to access and utilize the services. This expenditure is equal to their consumption of services. Given the provisioning or supply of services, variations in consumption or demand for services determine the current and future provisioning of services. For instance, a decline in enrollment of pre-secondary education for public institutions results in less public spending on it for the current and future years. Other things being the same, this decline may result in savings of public resources which can be reallocated to higher education. An important demographic determinant of changes in consumption of educational services is age structure transition of population. Age structure refers to distribution of total population by individual ages or age groups and its changes over time is called age structure transition.

This paper aims at economic analysis of linkages between the fiscal policy, demographic transition and public spending on higher education in India. This linkage is long term and dynamic in nature because demographic transition is a process over a period of time. Analysis of this linkage is useful to answer the following policy-relevant questions. Will a demographically-induced decline in enrollment impact on budgetary allocation for higher education? If yes, how does fiscal policy account for demographic transition in allocation of public higher education resources? Will a demographically-induced decline in enrollment in higher education impact on attainment of targeted Gross Enrollment Ratio in higher education? If yes, how to quantity such impacts? Will demographic transition offer new challenges and opportunities to finance higher education in India? What are the potential impacts of demographically-induced changes in financing higher education on quality, equity and employability of students in India’s higher education system? To our knowledge, available literature on financing higher education in India does not seem to provide with answers to these questions. This gap is evident in the recent survey of literature on financing education in the context of demographic transition, human capital and economic growth in India by Narayana (2018a) and papers in Varghese and Panigrahi (2019) and NIEPA (2017). However, this paper fills in this gap.

Analyses to answer the above questions are based on benchmark data in 2011–12 and projected population up to 2050. A simple economic-demography [End Page 407] model is used to forecast the interactive effects of demographic transition and public higher education expenditure within the framework of fiscal policy in the benchmark year. Overall results show that fiscal policy, demographic transition and public education expenditure on higher are inter-related and additional budgetary resources can be provided to the higher education in future, notwithstanding the fixed public education commitment at the benchmark year, due to the predicted demographic transition. This offers a new macroeconomic evidence for India’s public financing of higher education and lesson for other developing countries.

Rest of the paper is organized as follows. Section 2 describes the basic numbers and broad implications of current and projected demographic transition on India’s education up to 2100. Section 3 presents an economic-demographic model to forecast the impact of demographic transition on public education spending through economic growth. Data and variables descriptions are given in section 4. Analyses of results are given in section 5. Major conclusion and implications are summarized in section 6.

demographic transition and education

India’s total population, as per the Census of India 2011, is equal to 1.21 billion. This population is projected to increase up to 1.68 billion in 2061 and, subsequently, decline up to 1.52 billion in 2100 (United Nations, 2017). However, relative to population size in 2011, population size in 2061 would be bigger by 38.73% and 25.34% in 2100. These trends in population size will be characterized by remarkable age structure transition (Figure 1). That is, long term decline in young and youth population, rise in elderly population and highest share of working-age population. If higher educated, skillful, healthy and gainfully employed, a higher working age population is contributory to national income, savings, investments and higher economic growth. This attainment of economic growth is called Demographic Dividend.

Demographic (through age structure) transition impacts on financing of higher education in three ways. First, decline in younger population may reduce investment on instructional and non-instructional requirements in pre-secondary education. Other things being equal, this results in saving of resources within the education budget and may be a new way of financing of higher education by reallocation of resources from pre-secondary to higher education. Second, increase in working age population with higher education may increase the size of demographic dividends and fiscal resources (i.e. revenue receipts in general and revenue from Education Cess in particular) through fiscal dividends. Third, population ageing may create a huge pension wealth which can be an additional source of financial resources through borrowings for public investment on higher [End Page 408] education. Analyses of these impacts may provide with unambiguous results to explain and predict the implications of demographic transition on financing of higher education in India if age structure transition may lead to more investible resources for higher education without additional taxation, cut in public expenditure and without raising new public debt for current and future working age population. Thus, introduction of age structure transition have important and urgent fiscal implications to uncover potential sources and innovative methods of India’s financing of higher education, at present and in future.

Figure 1. Demographic (or age structure) transition, India, 2011–2100 Source: Author’s calculation using basic data in and .
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Figure 1.

Demographic (or age structure) transition, India, 2011–2100

Source: Author’s calculation using basic data in Census of India (2011) and United Nations (2017).

Education Dependency Ratio

A decline in young and youth population implies a decline in elementary school going children (6–13 years), secondary school going children (14–17 years) and college going (or higher education) population (18–24 years). This demographic transition impacts on education through a decline in Education Dependency Ratio (EDR). This is measured by a ratio of school-age or college-age population to total population in active/working ages (25–60 years) or potential workers. Figure 2 shows the transition in EDR by levels of education and all levels of education from 2011 through 2100.

The EDR declines throughout and implies that, other things being equal, the number of students by all levels of education falls for every 100 potential workers. In particular, the highest decline in EDR is evident for the elementary school education. For instance, the EDR for the elementary (or higher) education falls from about 40 (or 31) in 2011 to 21 (or 20) in 2050 and 19 (or 17) in 2100. During the same period, total EDR falls from about 90 to 51 and 46. Other things [End Page 409] being the same, the above transition in EDR has implications on current and future public education spending through fiscal policy because the beneficiaries of this spending are projected to decline over the period up to 2100. This is called potential savings in the education system as a result of demographic changes which are investable in educational attainments by programmes aimed at improvement in quality, equity and employability of students.

Figure 2. Education dependency transition, India, 2011–2100 Source: Author’s calculation using basic data in and .
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Figure 2.

Education dependency transition, India, 2011–2100

Source: Author’s calculation using basic data in Census of India (2011) and United Nations (2017).

Importance of Public Education by Enrollment

Demographic transition may have a decisive impact on public education expenditure if enrollment in public education institutions is high. For the benchmark year (2011–12), select indicators of India’s enrollment by levels of education and types of management of educational institutions are summarised in Table 1.

Total enrollment of students in the entire education (251.42 million) has largest composition of students in elementary education (primary and upper primary schools) by about 71%. This is followed by secondary school enrollment (about 17%) and the rest (12%) by enrollment in higher education. Public education institutions share more than 50% of total enrollment by all levels of education and types of management of institutions. That is, enrollment in public education institutions in elementary education is about 80%, secondary education is about 75% and higher education is about 62%. At the same time, Gross Enrollment Ratio (GER) declines from lower to higher levels of education from about 94 percent in primary education to about 54% in secondary education and about 18% in higher education. Thus, public expenditure matters for India’s education in general and for lower levels of education in particular. Consequently, [End Page 410] demographic transition may be expected to have higher impact on public education expenditure, if the transition affects the size of school going children.

Table 1. Select indicators of enrollment by levels of education and types of institutions, India, 2011
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Table 1.

Select indicators of enrollment by levels of education and types of institutions, India, 2011

The above description of relationships between fiscal policy, demographic transition and public education spending looks overly simplistic because it assumes away changes in socio-economic and political contexts of education policy. However, these changes are hard to foresee as compared to more predicable demographic transition. From this perspective, our emphasis on demographic transition when designing and predicting the education spending within the fiscal policy framework looks plausible.

demographic transition and aggregate education expenditure

A simple economic-demographic model is adopted below to forecast the impact of demographic transition on aggregate public education expenditure in India. The benchmark year is 2011–12 and forecasting is up to 2050.

Following Miller (2006), aggregate public expenditure on education is forecast by using a fixed age profile of public education consumption expenditure [E(x,t0)], which shift upward over time at the growth of nominal labour productivity (ρ), combined with a forecast of population by age (x), P(x, t). The nominal labour productivity (ρ) is equal to sum of growth rate of real labour productivity and inflation. Thus, aggregate public expenditure on education in time-t, E(t), is equal to:

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[End Page 411]

Where E(x,t0) = [EX0{EC(x, t0)/∑EC(x,t0)}]/P(x,t0), is age profile of per capita public education expendidture in the benchmark year (t0), where EX0 is total public expenditure on education, EC(x,t0) is total education consumption at age-x, and ∑EC(x,t0) is sum of public education consumption over all age in the benchmark year. Thus, E(t) in (1) is age-specific and population-adjusted forecast of aggregate public education expenditure. Given E(t) from (1), public education expenditure ratio can be calculated if GDP forecast is available.1 Long term official GDP forecast is not available from India’s Central Statistical Office and, hence, the following methodology is used from Miller (2006) to forecast GDP. That is, GDP is forecast by assuming a fixed ratio of GDP to aggregate labour income in the benchmark year (t0).

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Aggregate labor income in (2) is forecast by using a fixed age shape of per capita labor income, L(x, t0), which shifts upward over time at the growth rate of nominal labour productivity (ρ) combined with a forecast of population by age P(x,t). The fixed shape means that the age profile of labour income is constant throughout the forecasting period or labour income profile varies over years by levels but share of each age (or shape of the profile) remains fixed at the benchmark level.

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The forecasting of public education expenditure in equation (1) is determined by (a) age profile of public education consumption expenditure, (b) aggregate public education expenditure and (c) age structure of population. Given the age profile, aggregate public education expenditure in the benchmark year, and assumptions on growth of aggregate public expenditure and GDP from equation (1) through equation (3), forecast values of the aggregate and per capita public education expenditure by age is calculated by using the single year age distribution of population from 2011 through 2050.

Generosity of Public Education Benefits

As before, we assume that all benefits of public expenditure are targeted to persons between the ages 6–24, and they vary by age. In this case, aggregate public education expenditure as a share of GDP can be expressed as a product of two scalar factors. [End Page 412]

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Where P(t) is eligible school or college age population; B(t) is public education expenditure or benefits; and P(t, 25–60) is working age population in year-t. The first factor is economic, [{B(t)/P(t)}/{(Y(t)/P(t, 25–60)}], which is the average public education expenditure relative to GDP per working age adult. The second factor is demographic, {(P(t)/P(t, 25–60)}, which is education dependency ratio or size of school or college age population relative to working age population. The first factor is generally called education benefit generosity ratio (Miller and Castanheira, 2009). We denote this ratio by EBGR.2

A higher EBGR does not imply a more generous public education transfer per beneficiary unless the coverage (or Gross Enrollment Ratio) is equal to 1. In this case, P(t) is equal to eligible beneficiary. To see this point, equation (4) can be rewritten as follows.

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Where Z(t) is size of beneficiary. Thus, equations (4) and (5) are equal if the coverage is full or Z(t) = P(t).

variables and data descriptions

Table 2 gives a description of variables and parameters in the forecasting model (equations 1 to 3) and data for their measurements by sources.

results and analyses

Age Profile of Public Education Expenditure

Figure 3 shows the age profiles of per capita public education expenditure in 2011–12. The profiles are distinguished by per student expenditure by survey data in NSSO (2010) and per capita expenditure [i.e. up-scaled data by using aggregate public education expenditure (Government of India, 2015) and single year age distribution of India’s total population (Census of India, 2011)]. Per student as well as per capita expenditure increase from the elementary education ages to secondary education ages and to higher education ages. For instance, the [End Page 413]

Table 2. Variable and parameter descriptions and data sources
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Table 2.

Variable and parameter descriptions and data sources

[End Page 414]

Figure 3. Per student and per capita public education expenditure by age, India, 2011–12 Source: Author’s calculations using basis data in , and .
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Figure 3.

Per student and per capita public education expenditure by age, India, 2011–12

Source: Author’s calculations using basis data in NSSO (2010), Census of India (2011) and Government of India (2015).

level of per student (or per capita) expenditure increases from Rs.615 (Rs.2621) at age 6 to Rs.1122 (or Rs.4781) at age 13; from Rs.1197 (or Rs.5102) from age 14 to Rs.1632 (or Rs.6953) at age 17; and from Rs.1817 (or Rs.6953) at age 18 to Rs.4074 (or Rs.17357) at age 24. This shows a jump in expenditure (i.e. between entry level age to completion level age) by 82.45% at the elementary education, 26.61% at secondary education and 124.20% at higher education ages.)

Impact of Demographic Transition on Aggregate Public Education

Other things being same, the impact of demographic transition on public education spending has remarkable patterns at the aggregate and by levels of education. This is shown in Figure 4. Over the period 2011 to 2050, the forecast values on size of aggregate public education expenditure increases from about Rs.3039 billion in 2011 to Rs.14798 billion in 2025 and to Rs.178259 billion in 2050. At the same time, expenditure by levels of education shows an upward trend with a remarkable difference between higher, secondary and elementary education. That is, the highest increase in forecast expenditure for the higher education and lowest for secondary education. The upward trends in expenditure of elementary education is more similar to secondary than higher education. These education expenditure forecast results must be qualified because they are calculated by using a fixed age profile of per capita education expenditure in Figure 3.

Demographic Transition and Economic Growth-Linked Aggregate Public Education Expenditure

In absolute terms, demographic transition per se does not lead to decline in aggregate public education expenditure (Figure 4) because the projected population [End Page 415] size from age 6 years through 24 years does not fall below 2011 level. However, in relation to economic growth (or size or growth of GDP) or as a measure public expenditure commitment to education (i.e. aggregate public education as a percentage of GDP), aggregate education expenditure shows a different trend along the path of demographic transition. This is shown in Figure 5. Aggregate public education expenditure as a percentage of GDP declines from 3.82% in 2011 to 2.79% in 2030 and to 2.18% in 2050. During this period, the share of education expenditure by levels of education shows remarkable differences. First, the decline for elementary (or secondary) education is from 0.88% (or 0.65%) to 0.59% (or 0.45%) and to 0.45% (or 0.36%). Or, the decline is about 0.43 (or 0.29) percentage points between 2011 and 2050. In contrast, the share of expenditure on higher education in total GDP declines from 2.30% in 2011 to 1.75% in 2030 and to 1.37% in 2050. This is equivalent to a decline of about 0.93 percentage points between 2011 and 2050. Consequently, the highest decline in public education expenditure as a percentage of GDP is forecast to be in higher education.

Figure 4. Impact of demographic transition on aggregate public education expenditure, India, 2011–2050 Source: Author’s calculation using .
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Figure 4.

Impact of demographic transition on aggregate public education expenditure, India, 2011–2050

Source: Author’s calculation using equation (1).

Implications for Potential Savings in Public Education Expenditure

Given that, all else remain the same and fiscal policy or public expenditure commitment to education remains at benchmark level (i.e. share of aggregate education expenditure as a percentage of GDP at 3.82 in 2011–12 remains the same throughout), the potential savings in aggregate education expenditure (AEE) due to demographic transition is calculated as follows.

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[End Page 416]

Figure 5. Impact of demographic transition on economic-growth adjusted aggregate public education expenditure, India, 2011–2050 Source: Author’s calculations using to .
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Figure 5.

Impact of demographic transition on economic-growth adjusted aggregate public education expenditure, India, 2011–2050

Source: Author’s calculations using equation (1) to (3).

The numerator is the additional budgetary resources to education in terms of current GDP which is the difference in public education commitment in benchmark year (t0) and current year (t) multiplied by GDPt. The denominator is the AEEt. Thus, equation (4) measures the potential savings rate in education in terms of additional budgetary resource as a ratio of AEE.

Figure 6 shows the forecast values of the potential savings rate in public education expenditure from 2011 to 2050. The rate increases from 1.58% in 2012 to 37.20% in 2030 and to 75.62% in 2050 as a result of demographic transition. These savings are spendable on new programmes for improvements in access, quality, equity and employability by levels of education in general and higher education in particular.

Most importantly, the above potential savings rates in education are attainable without fiscal policy changes in terms of additional taxation, cut in expenditure in other sectors and raising new public debt. Thus, other things being the same, management of fiscal policy remains intact throughout and current fiscal policy is sustainable in long run, notwithstanding the demographic transition effects on public education expenditure.

Public Education Benefit Generosity

The results of public education benefit generosity (EBGR) are summarised in Table 2. The value of EBDR for all levels of education and total education rises from 2011 to 2030 and declines from 2030 to 2050. However, over the period 2015–2050, the EBDR declines by 0.17 percentage points for elementary education, 0.27 percentage points for secondary education, 0.53 percentage points for higher education, and 0.18 percentage points for total education. Thus, the highest [End Page 417] (or lowest) decline in EBDR is evident for higher (or elementary) education.

Figure 6. Potential savings in education expenditure due to demographic transition, India, 2011–2050 Source: Author’s calculations using .
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Figure 6.

Potential savings in education expenditure due to demographic transition, India, 2011–2050

Source: Author’s calculations using equation (4).

Overall, the basic results shows that demographic transition impacts on increasing public education spending by all levels of education, declining share public education expenditure as a percentage of GDP, increasing size of potential savings as a percentage of aggregate public education expenditure, and a declining public education expenditure generosity.

GER-adjusted Public Education Expenditure

The results and analyses above are modified by adjusting the per capita public education expenditure to Gross Enrollment Ratio by levels of education and, accordingly, the potential savings are recalculated. These results are presented below.

Table 3. Public education benefit generosity ratio, India, 2011–2050
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Table 3.

Public education benefit generosity ratio, India, 2011–2050

First, GER adjusted per capita education expenditure by age in 2011–12 is shown in Figure 7. Per capita education expenditure is highest for the elementary school ages and declines in secondary and higher education ages. This is in contrast with the GER unadjusted per capita education expenditure in Figure 3 above. This result is mainly attributable to lower GER at secondary and higher education level, although per student education expenditure in higher at these [End Page 418] levels of education.

Figure 7. GER-adjusted per capita public education expenditure by age, India, 2011–12 Source: Author’s calculations
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Figure 7.

GER-adjusted per capita public education expenditure by age, India, 2011–12

Source: Author’s calculations

Second, if GER adjusted per capita education expenditure by age is used to assess the impact of demographic transition, the resultant potential savings in budgetary resources in education is shown in Figure 8. This calculation is based on GER adjusted per capita education expenditure in elementary education where the size of public spending is higher and GER is close to 100. The potential savings from this adjustment is calculated by the following.

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Where TEE is total education expenditure on elementary education (6–13 years) and all other notations are the same as defined earlier. Thus, other things being equal, the potential savings rate in (5) is equal to additional budgetary resources in elementary education in terms of GDP, resulting from the demographic transition, as a ratio of total education expenditure on elementary education in the benchmark year (2011–12). This savings ratio is equal to 0.2 in 2012 and rises to 2.37 in 2030, 9.59 in 2040 and to 33.30 in 2050. This amount of additional budgetary resources is spendable on expansion of coverage in secondary and higher education, quality improvements, attainment of equity and programmes on employability of students.3

conclusion and implications

This paper provides an economic-demographic framework to analyze the empirical [End Page 419] relationships between fiscal policy, demographic transition and public education expenditure in India. The framework is useful to forecast the relationships on long term up to 2050, given the benchmark values on variables and parameters in 2011–12. The analyses are based on data from the recent surveys, census reports and administrative data at the national level. The major conclusions and implications from within these analyses are as follows.

Figure 8. GER-adjusted potential savings in elementary education due to demographic transition, India, 2011–2050
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Figure 8.

GER-adjusted potential savings in elementary education due to demographic transition, India, 2011–2050

The current fiscal policy in regard to allocation of budgetary for education does not explicitly accounts for long term demographic transition effects. However, these fiscal effects of age structure transition need to be accounted for they have important implications on current and future public education expenditure with the current fiscal policy framework.

The results of this paper offer unambiguous empirical evidence for long term decline in public education expenditure due to demographic transition. If public education expenditure commitment in terms of GDP is held constant at the benchmark level, additional budgetary resource would be available for increase in coverage in education and improvements in quality, equity and employability programmes in secondary and higher education. At present, GER in higher education is less than 25% and there is a great opportunity to expand the coverage programmes in higher education, especially to meet the needs of India’s knowledge economy. However, the above additional resource are a form of potential savings in the education budget due to demographic transition without affecting fiscal policy in terms of higher taxes, cut in other expenditure and raising new public debt. Thus, demographic transition effects may be a new and bigger source of financing India’s higher education in future.

Thus, the main conclusion of this paper is that fiscal policy, demographic transition and public education expenditure on education is inter-related. Additional [End Page 420] budgetary resources can be provided to the higher education in future due to combined effects of the fixed public education commitment at the benchmark year and predicted demographic transition. However, public education expenditure generosity decline for all levels of education with highest (or lowest) decline in higher (or elementary) education.

The results, conclusions and implications of this paper are based on assumptions of budget forecasting model and data limitations. However, at present, they may be qualified to be indicative. Availability of more refined data may help to concretize them in future.

A long term reduction in child population may also have a negative implication on public spending in terms of decline in public expenditure on health and family welfare including nutritional programmes, social welfare including child poverty alleviation programme and other child-centric programmes. A reduction in thesenon-education related public expenditure may be contributory to a larger public savings and may have essential implications on management of fiscal policy at national and state levels. A detailed analysis of these fiscal policy management issues in an important extension of this paper.

M. R. Narayana

M.R. Narayana is a Consultant (Academic and Research) at the Fiscal Policy Institute, Government of Karnataka, and a former Professor of Economics at Institute for Social and Economic Change, Bengaluru, India.

references

APU, Azim Premji University. (2018). State of Working India 2018. Centre for Sustainable Employment (Bengaluru).
Census of India. (2011). Single Year Age Data –C13 Table (India/States/UTs). Office of Registrar General & Census Commissioner, Ministry of Home Affairs (New Delhi).
CSO, Central Statistical Office. (2018a). National Accounts Statistics 2018. Ministry of Statistics and Programme Implementation, Government of India (New Delhi).
CSO, Central Statistical Office. (2018b). Consumer Price Index Numbers on Base 2012=100 for Rural, Urban and Combined for the Month of October 2018. Ministry of Statistics and Programme Implementation, Government of India (New Delhi).
Government of India. (2016). Eighth All India School Education Survey (as on 30th September 2009). National Council of Educational Research and Training (New Delhi).
Government of India. (2015). Analysis of Budgeted Expenditure on Education 201112 to 201314. Ministry of Human Resource Development, Department of Higher Education (New Delhi).
Government of India.(2014). All India Survey on Higher Education 201112. Department of Higher Education. Ministry of Human Resource Development (New Delhi).
Miller, T. (2006).Demographic Models for Projections of Social Sector Demand, Latin American and Caribbean. Demographic Centre (CELADE), Population Division, Santiago.
Miller, Tim., and Castanheira, Helena Cruz. (2013). The fiscal impact of population aging in Brazil: 2005–2050. Revista Brasileira de Estudos de População (Brazilian Journal of Population Studies), Vol.30 (Supplement): S5–S23
Narayana, M.R. (2018a). “Accounting for age structure transition through public education expenditure: New macro evidence from India”. South Asia Journal of Macroeconomics and Public Finance. 7(2), 2018: 171–211
Narayana, M.R. (2018b). “Inter-generational equity, poverty and inequality for elderly: Evidence from India”, International Conference on Opportunities and Challenges of the Demographic Transition for Meeting the 2030 Agenda and the Sustainable Development Goals, 12th Global Meeting of the National Transfer Accounts Network: July 23–27, 2018: Mexico City (Mexico). http://ntaccounts.org/doc/repository/Intergenerational%20equity,%20poverty,%20and%20inequality%20for%20the%20elderly.%20Evidence%20from%20India.pdf (accessed on July 5, 2019).
NIEPA. (2017). Papers presented for International Seminar on Innovations in Financing of Higher Education. Jointly organized by CPRHE at NIEPA and British Council, India Habitat Centre (New Delhi): 16–17 February 2017.
NSSO, National Sample Survey Office. (2010). Education in India: 200708. Participation and Expenditure. NSS 64th Round (July 2007June 2008).Ministry of Statistics and Programme Implementation, Government of India (New Delhi).
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Varghese, N.V., and Panigrahi, Jinusha. Eds (2019). India Higher Education Report 2018: Financing of Higher Education. Sage Publishing (New Delhi).

Footnotes

1. Public education expenditure ratio is ratio of aggregate public education expenditure to GDP. It is a variant of public expenditure ratio in UNDP (1990).

2. Implicitly, EBGR assumes that each rupee of public education expenditure creates education benefits which are uniformly available for each student, or at constant per capita, at each stage by levels of education. For instance, students in first year of elementary education receives equal per capita public education benefits equivalent to per capita public education expenditure but these benefits are different for students in second, third and so on in elementary education. In the same way, public education benefits are assumed different at each stage in secondary and higher education levels. This implies that per capita public education benefits vary by each age from 6 years to 24 years. Thus, marginal benefits vary between stages in each level of education and between levels of education.

3. Consumption poverty and inequality are important considerations for equity-based interventions in education sector. Narayana (2018b) shows that consumption poverty is higher for school and pre-school age population (0–14 years) and consumption inequality is higher for college-going population (15–25). Thus, equity-based interventions in education need to be focused by levels of education.

Additional Information

ISSN
1944-6470
Print ISSN
0098-9495
Pages
405-422
Launched on MUSE
2019-11-03
Open Access
No
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