Public expenditure and national income of India: investigating Wagnerian law

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This study tried to empirically test the causal relationship and the direction of causality between public expenditure and GDP in India, using annual data from 1966-67 to 2015-16.

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International Journal of Management (IJM) Volume 9, Issue 5, September–October 2018, pp. 1–9, Article ID: IJM_09_05_001 Available online at http://www.iaeme.com/ijm/issues.asp?JType=IJM&VType=9&IType=5 Journal Impact Factor (2016): 8.1920 (Calculated by GISI) www.jifactor.com ISSN Print: 0976-6502 and ISSN Online: 0976-6510 © IAEME Publication PUBLIC EXPENDITURE AND NATIONAL INCOME OF INDIA: INVESTIGATING WAGNERIAN LAW Dhyani Mehta Assistant Professor, Economics and Finance, Institute of Management, Nirma University, India ABSTRACT This study tried to empirically test the causal relationship and the direction of causality between public expenditure and GDP in India, using annual data from 1966- 67 to 2015-16. The methodology employed was econometric model of the cointegration and the Granger Causality test. The estimates shows that the variables are stationary at first difference and follows I(1) order of integrations. Causality test estimates shows bidirectional causal relationship running from GDP to Revenue Expenditure and from Capital Expenditure to GDP. The estimates do not support the existence of Keynesian hypothesis and Wagner’s Law at the disaggregate level in India. Key words: Public Expenditure, Wagner’s law, Keynesian hypothesis, Cointegration, Granger Causality. Cite this Article: Dhyani Mehta, Public Expenditure and National Income of India: Investigating Wagnerian Law. International Journal of Management, 9 (5), 2018, pp. 1–9. http://www.iaeme.com/IJM/issues.asp?JType=IJM&VType=9&IType=5 1. INTRODUCTION Can increase in public expenditure influence economic growth? What evidence exists on the direct relationship between public expenditure and economic growth? There is lot of debate in public finance literatures based on views of different school of thoughts in economics. There are both theoretical and empirical evidence on the relationship between public expenditure and Gross domestic product (GDP) growth (Blanchard, 2008). If public expenditure negatively influences economic growth then policymakers need to be aware of these relationships when formulating and implementing macroeconomic policy; and if public expenditure enhances economic growth, or at a minimum does not present obstacles to growth. However, it is important for policy makers to manage the debt, which arises due to increased public expenditure and its impact on economy. Public Expenditure is one of the important growth driver of any economy; GDP growth should be sustained for a developing economy to address issues like unemployment, poverty, inflation etc. Public expenditure plays a very crucial role in economic growth and stability. http://www.iaeme.com/IJM/index.asp 1 editor@iaeme.com
Public Expenditure and National Income of India: Investigating Wagnerian Law Public expenditure has been increasing over time in almost all the countries of the world; it is very important for government to study the relation between GDP and public expenditure. Increase or decrease in public expenditure will yield increase or decrease in economic growth by increasing the national income, especially when it is injected in development programs (Omoke, 2009). If fiscal policy is applied through effective fiscal instruments like taxation and public expenditure, it influences the working of the economic system and maximize economic welfare with the overriding objective of promoting long-term growth of the economy (Tanzi, 1994). Fiscal policy and public finance has received much attention in the literature. There is lot of debate on theoretical and empirical analysis on economic effects of public expenditures. Some support a large public expenditure because it helps to put money into circulation, increased investment and employment and reduces tax averseness etc. Others argues that increase in public expenditure will lead to the fiscal deficit and creation of debt. Government size has impact on economic growth; it has emerged as a major fiscal management issue which is faced by economies in transition (Suleiman, 2009). The previous research focuses on size of government in industrialized countries, but given the openness of most developing countries, trade dependency, the vulnerability to external shocks, and volatility of finances, the role and size of government become germane to adjustment and stabilization programmes (Suleiman, 2009). There are two approaches on public expenditure and economic growth relationship: Wagnerian’s law approach and Keynesians approach. 1.1. Wagnerian’s Law Approach Wagner (1883) has introduced a model, which shows that public expenditures are endogenous to economic growth, and that there exists long-run tendencies for public expenditure to grow relatively to some national income aggregates such as GDP. This observation of Wagner led to the Wagner’s law of increasing state activities. According to this law increased government activity and public expenditure will lead to economic growth. Thus, it is said that causality between public expenditure and national income runs from national income to public expenditure. 1.2. Keynesians Approach According to Keynes (1936) the government intervention by fiscal policies will help to increase economic activities; thus public expenditure is an exogenous factor. The causal relationship between public expenditure and national income runs from expenditure to income. The main objective and focus of this paper is to study the components of public expenditure which cause economic growth or vice versa. The long run tendencies that may exist between of public expenditure and economic growth will be investigated using cointegration and causality tests. 2. INDIA’S PUBLIC EXPENDITURE Indian public expenditure can be classified into Revenue expenditure, which is recurrent in nature. Revenue expenditure includes defence expenditure, interest payment, subsidies and other-revenue expenditure. Capital expenditure is incurred on building durable assets in economy. Capital expenditure is non-recurring in nature and includes loan and advances, and capital outlay. Some of the examples of capital expenditure are expenditure on building river dam projects, highways, steel plants, ports, buying of machinery and equipment, etc. Figure-1 shows the revenue expenditures from year from 1966-67 to 2015-16; India’s revenue expenditure has continuously grown over the period. Among the revenue expenditure, other revenue expenditure (ORE) has highest growth rate followed by higher http://www.iaeme.com/IJM/index.asp 2 editor@iaeme.com
Dhyani Mehta growth rate of interest payment expenditure, due to increasing public and external debt. Expenditure on subsidies also show increasing trend with objective of bringing equality and efficiency in economic classes. India faces problem of terrorism and national security, which lead to increase in defence expenditure. 2,400 2,000 1,600 1,200 800 400 0 1966-67 1968-69 1970-71 1972-73 1974-75 1976-77 1978-79 1980-81 1982-83 1984-85 1986-87 1988-89 1990-91 1992-93 1994-95 1996-97 1998-99 2000-01 2002-03 2004-05 2006-07 2008-09 2010-11 2012-13 2014-15 CLE COE Figure 1 Trend is Revenue Expenditure in India: Source: Hand Book of Statistics Reserve Bank of India, 2015-16 Figure-2 show the real capital expenditures from year from 1966-67 to 2015-16. It is clearly observed that India’s capital expenditure has been continuously growing over the period of time. Among the capital expenditure loan and advances were having higher proportion compared to capital out lay expenditure but it has shown downward trend. 8,000 7,000 6,000 5,000 4,000 3,000 2,000 1,000 0 1966-67 1968-69 1970-71 1972-73 1974-75 1976-77 1978-79 1980-81 1982-83 1984-85 1986-87 1988-89 1990-91 1992-93 1994-95 1996-97 1998-99 2000-01 2002-03 2004-05 2006-07 2008-09 2010-11 2012-13 2014-15 RED IPE RSE ROE Figure 2 Trend is Capital Expenditure in India Source: Hand Book of Statistics Reserve Bank of India, 2015-16 Figure-3 shows comparison of percentage change GDP, with real figures of revenue expenditure, capital expenditure, developmental expenditure and non-development expenditure. There is highest fluctuation in percentage change in capital expenditure compared to other public expenditure. Percentage change in GDP is showing a constant trend with upward moment from year 2003-04. http://www.iaeme.com/IJM/index.asp 3 editor@iaeme.com
Public Expenditure and National Income of India: Investigating Wagnerian Law 80 60 40 20 0 -20 -40 -60 1984-85 1985-86 1986-87 1987-88 1988-89 1989-90 1990-91 1991-92 1992-93 1993-94 1994-95 1995-96 1996-97 1997-98 1998-99 1999-00 2000-01 2001-02 2002-03 2003-04 2004-05 2005-06 2006-07 2007-08 2008-09 2009-10 2010-11 2011-12 2012-13 % Change GDP % Change CAP-EX % Change DEV-EXP % Change REV-EX % Change NDEV-EXP Figure 3 Percentage Change in National Income & Public expenditure Source: Hand Book of Statistics Reserve Bank of India, 2015-16 Graphical representation in Figure-1, Figure-2 and Figure-3 shows a positive relationship between the GDP growth rate and the change in public expenditure in India i.e. an increase in public expenditure and increase in growth rate within the considered period. This creates the need for testing the direction of causality suggested by Wagnerian’s law and Keynesian approach. 3. LITERATURE REVIEW Extensive literature on theoretical and empirical debate between Wagner’s law and Keynesian law tries to validate the causal relation between public expenditure and GDP. Singh and Sahni (1984) examined causal link between public expenditure and national income on Indian data and found bi-directional causality between public expenditure and national income. Ahsan et al.(1992) studied United States data and failed to detect any causality between public expenditure and national income. Afxentiou and Serletis (1996); Ansari et al. (1997) and Abizadeh and Yousefi (1998) examined cross-country data, they were not able to find any evidence supporting Wagner’s law. Bohl (1996) studied G7 countries (Post World War-II) and found evidence for Wagner’s law for only countries like United Kingdom and Canada out of G7 countries. Frimpong and Oteng-Abayie (2009) examined West African Monetary Zone country data and results neither supported Wagner’s nor Keynesian view. Verma and Arora (2010); and Ray (2012) examined causal relation between public expenditure and GDP on Indian data and found short run causality between economic growth and public expenditure supporting Wagner’s law. Muhlis and Hakan (2003) used the natural log of annual data of Turkish economy from 1965-2000; co-integration and granger causality tests support neither Wagner’s Law nor Keynes’ hypothesis. Jamshaid et al. (2010) examined direction of causality between public expenditure with some selected expenditure components and national income of Pakistan; Toda-Yamamoto causality test was used for annual data of 1971-2006, results concluded in favour of Wagner’s law that there exists a unidirectional causality relationship flowing from GDP to public expenditure. Olugbenga and Owoye (2007) used data from 1970-2005 of 30 OECD countries and found unidirectional and long-run relationship from public expenditure to economic growth supporting Keynesian law for 16 countries. These were unidirectional and long-run relationship between economic growth and public expenditure supporting Wagner’s law observed for 10 countries, and four countries showed bi-causal relationship between public expenditure and economic growth. Ergun and Tuck (2006) used Granger causality test to investigate the causal links between the two variables for countries like http://www.iaeme.com/IJM/index.asp 4 editor@iaeme.com
Dhyani Mehta Indonesia, Malaysia, Philippines, Singapore, and Thailand, by using annual data from 1960- 2002 and found that causality runs from public expenditures to national income only for Philippines. The relationship between public expenditure and economic growth yields mix results and the debate is never ending. It is very important for making policy to address issues like recession, inflation, stagflation, unemployment, income inequality etc. It gives central authorities ability to stimulate their economy through fiscal measures unless the share of government spending to GNP increases or reduces. Knowing this long-run relationship helps to make estimates of the public expenditure and national output and identify a benchmark against which one can design the fiscal policy. The relationship between government spending and national output is also important for the sustainability of public finances, especially during the time when government is struggling to restrain spending. Thus the identification of this relationship helps to provides a theoretical framework against which to formulate and judge fiscal policy adjustment plans concerning medium term budgetary objectives. 4. METHODOLOGY & DATA Objective of this study is to test and bring out the evidence of the causal relationship between public expenditure and GDP growth. Determinants of GPD growth is not taken in the study as this paper only investigates primary long run relationship between GDP growth and components of public expenditure. Granger (1969) proposed the concepts of causality using a VAR model. In this study, Granger causality is used to investigate the causality between public expenditures and GDP growth based on the VAR model. The data is taken from the RBI’s Handbook of Statistics, 2015-16. The study uses natural log of annual data of GDP, Revenue Expenditure and Capital Expenditure at disaggregate level for 50 years from year 1966 to 2016. Nominal variables are deflated into real ones by the GDP deflator (2004-05 constant price). Study uses test like ADF, Johansen cointegration test, Granger causality test. Study includes seven variables i.e. GDP growth (Y), Variables for Revenue Expenditures are: Defence Expenditure (RED), Interest payment (IPE), Subsidies (RSE), Others-revenue Expenditure (ORE); Variables for Capital Expenditure are: Loan and Advances (CLE), Capital Outlay = (COE). The Unit root test for stationarity, Johansen cointegration test and Granger (1969) causality methodology were employed to determine the direction of causality between public expenditure and GDP growth. 5. DATA ANALYSIS 5.1. Unit Root Tests Any VAR model’s efficacy in establishing the relationship among variables is conditional on the assumption of stationarity of the variables, which means variable should be made stationary before conducting a Granger causality test based on the VAR. In case of non- stationary time series, it implies the variables may be co-integrated. This means that stationarity and co-integration test musts precede the Granger Causality test. According to Greene (2003), the Augmented Dickey Fuller (ADF) test can be employed to test for unit root. The results in Table-1 of ADF test show the order of integration of the variables and presence of unit root. The variables are stationary at first difference, meaning that GDP (Y) is stationary at I(1) first difference, Defence Expenditure (RDE), Interest payment (IPE), Subsidies (RSE), Others-revenue Expenditure (ORE), Loan and Advances (CLE) and Capital Outlay (COE); all values are natural log value stationary at I(1) first difference. http://www.iaeme.com/IJM/index.asp 5 editor@iaeme.com
Public Expenditure and National Income of India: Investigating Wagnerian Law Table 1 Unit Root Test Order of Order of t-statistic t-statistic Variables Integrati Stationarity Variable Integrati Stationarity & Prob. & Prob. on on 0.551228 Not- -4.724860 Y I(0) Y I(1) Stationary (0.9868) Stationary (0.0003) -0.282828 Not- -6.584447 RED I(0) RED I(1) Stationary (0.9198) Stationary (0.0000) -2.458147 Not- -9.693108 IPE I(0) IPE I(1) Stationary (0.1319) Stationary (0.0000) -2.451847 Not- -5.138595 RSE I(0) RSE I(1) Stationary (0.9174) Stationary (0.0001) -2.926899 Not- -3.118285 ORE I(0) ORE I(1) Stationary (0.3170) Stationary (0.3170) -3.862332 Not- -5.429617 CLE I(0) CLE I(1) Stationary (0.4517) Stationary (0.0000) 0.843647 Not- -9.466472 COE I(0) COE I(1) Stationary (0.9938) Stationary (0.0000) For testing the unit root by ADF test the null hypothesis of non-stationarity for all variables was rejected at first difference at the particular level of significance described by the p-values in parenthesis. This implies that all the variables are integrated of order one I(1). 5.2. Co-Integration Test After testing the stationarity, the next step is to check if there were any long run tendencies between components of public expenditure and GDP. For the same Johansen (1988), and Johansen and Juselius (1990) maximum likelihood testing procedure on the number of cointegrating vectors, which also includes testing procedures for linear restrictions on the cointegrating parameters, for any set of variables was used. Two tests statistics to identify the number of cointegrating vectors, namely the trace test statistic and the Maximum Eigen value test statistic were used. Table-2 below shows that the null hypothesis of no co-integration is rejected indicating cointegration at the 5% level of significance and tests were performed with two lag lengths according to the Schwartz criterion. The results suggest that there is cointegration or long-term relationship between GDP (Y) and Defence Expenditure (RDE), Interest payment (IPE), Subsidies (RSE), Others-revenue Expenditure (ORE), Loan and Advances (CLE) and Capital Outlay (COE). Table 2 Johansen Cointegration Test: Critical Trace Critical H0: No Co-integration Max- Eigen Statistic Prob. Prob. Value (5%) Statistics Value (5%) Y and RED Reject 14.49233 14.26460 0.0421 17.37552 15.49471 0.0258 Y and IPE Reject 29.41134 14.26460 0.0001 35.10757 15.49471 0.0000 Y and RSE Reject 38.86122 14.26460 0.0000 42.85451 15.49471 0.0000 Y and ORE Reject 38.60091 14.26460 0.0000 43.11570 15.49471 0.0000 Y and CLE Reject 13.60766 14.26460 0.0063 43.11570 17.18315 0.0276 Y and COE Reject 16.48350 14.26460 0.0219 43.11570 30.67843 0.0001 http://www.iaeme.com/IJM/index.asp 6 editor@iaeme.com
Dhyani Mehta This result indicates that Indian Economic system is in steady state. Cointegration indicating long run relationship between variables may be expected to exist only when the system is in a steady state according to the finding of Ford (1997). As the concept of steady state growth is the counterpart of long-run equilibrium in static theory. It is consistent with the concept of equilibrium growth. In steady state growth all variables, such as output, public expenditure, population, capital stock, saving, investment, and technical progress, either grow at constant exponential rate, or are constant. 5.3. Granger Causality Test Granger Causality Test done for both arguments below show the results for 1) Wagnerian’s law approach 2) Keynesian approach to test the direction of causality. The optimum lags length of VAR in both models is based on AI and SIC criteria. The causality test was carried for both approaches. According Wagner’s approach the direction of causality between GDP and Public expenditure flows from income to public expenditure and Keynesian approach says the causal relationship between public expenditure and national income runs from expenditure to income. Thus, VAR model was estimated at disaggregate level for different components of the public expenditure separately and then were tested for Granger causality direction. Table 3 Granger Causality Test for Y and Revenue Expenditure Acceptance or Rejection Null Hypothesis Chi-Square Prob. of H0 Y and Revenue Expenditure RED cannot Granger cause Y 4.340219 0.1142 Accept H0 Y cannot Granger cause RED 8.53337 0.0140 Reject H0 (Y cause RED) IPE cannot Granger cause Y 1.980139 0.3716 Accept H0 Y cannot Granger cause IPE 170.1289 0.0000 Reject H0 ( Y cause IPE) RSE cannot Granger Cause Y 3.026468 0.2202 Accept H0 Y cannot Granger cause RSE 5.860064 0.0053 Reject H0 (Y cause RSE) ORE cannot Granger cause Y 58.55142 0.2633 Accept H0 Y cannot Granger cause ORE 41.81203 0.0000 Reject H0 ( Y cause ORE) Y and Capital Expenditure CLE cannot Granger cause Y 8.619629 0.0134 Reject H0 (CLE cause Y) Y cannot Granger cause CLE 2.478179 0.2896 Accept H0 COE cannot Granger cause Y 5.779112 0.0056 Reject H0 (COE cause Y) Y cannot Granger cause COE 8.371915 0.1520 Accept H0 Granger causality results between components of public expenditures and GDP reveals that a unidirectional causality runs from GDP to public expenditure. Revenue Expenditures like Defence Expenditure (RDE), Interest payment (IPE), Subsidies (RSE), Others-revenue Expenditure (ORE) show direction of causality from GDP (Y) to revenue expenditures. Capital expenditure like Loan and Advances (CLE) and Capital Outlay (COE) show causality direction from capital expenditure to GDP (Y). These results of Indian public expenditure for disaggregate level support Wagnerian’s law for revenue expenditure and Keynesian proposition for capital expenditure. 6. CONCLUSIONS This study attempts to investigate empirically the relationship between components of public expenditure and GDP. This investigation was based on econometric model of cointegration and Granger Causality. The results of Johansen cointegration revealed that there is long-run relationship among the variables as well as the non-spuriousness of the relationship between http://www.iaeme.com/IJM/index.asp 7 editor@iaeme.com
Public Expenditure and National Income of India: Investigating Wagnerian Law components of public expenditure and GDP. Results from a causality test showed that, growth in GDP causes revenue expenditure like defence expenditure, interest payment, subsidies, other-revenue expenditure whereas capital expenditure like loan and advances and capital outlay show causality direction from capital expenditure to GDP supporting Keynesian hypothesis. Finally, it supports both Keynesian hypothesis and Wagnerian Law showing the feature of mixed economy system in India. Study of this causal relationship helps in designing the fiscal policy more efficiently. The relationship between GDP and public expenditure shows that India’s income growth will lead to expenditure that is more public; causing more government out lay, which in intern will lead to more growth in future. Capital expenditure led to GDP growth relationship can be inferred as, fiscal policy should allocate more resources for the capital expenditure, which in turn will help to stimulate economic growth. Capital outlay will lead to more capital formation in economy. Whereas revenue expenditure such as defence expenditure, interest payment, subsidies and others-revenue expenditure is important to maintain the economy as it neither increases the assets nor reduces the liability but helps in the smooth function of the economy. Primary investigation suggests that the GDP growth will lead to the increase in the revenue expenditure and capital expenditure will cause increase GDP. REFERENCES [1] Abizadeh, S. and Yousefi, M. (1998). An Empirical Analysis of South KoreasEconomic Development and Public Expenditure Growth, The Journal of Socio-Economics, 27(6), 687-94. [2] Afxentiou, P. C. and Serletis, A. (1996). Public expenditures in the European Union: Do They Converge or Follow Wagners Law, International Economic Journal, 10(3), 33-47 [3] Ahsan, S. M., Andy C. K. and Balbir S. S. (1992). Public Expenditure and National Income Causality: Further Evidence on the Role of Omitted Variables, Southern Economic Journal, 58(3), 623-634. [4] Ansari, M., Gordon, D. V. and Akuamoah, C. (1997). Keynes versus Wagner: Public Expenditure and National Income for Three African Countries, Applied Economics, 29(3), 543-550. [5] Bohl M. T. (1996). Some International Evidence on Wagners Law. Public Finance, 51(2), 185-200. [6] Blanchard, O. (2009). The state of macro. Annu. Rev. Econ., 1(1), 209-228. [7] Ergun, D and Tuck, C. (2006). Public expenditure and National Income: Causality Tests for Five South East Asian Countries, International Business and Research Journal Vol.5, No, 10: 49-58. [8] Ford, L (1997). Economic Development, Financial Development and Liberalization: Taiwan, 1960-1995, Discussion papers of the University of Birmingham, 97-25. [9] Granger, C.W.J. (1969). Investigating causal relations by econometric models and cross- pectral methods, Econometrica, Vol. 37, July: 424-38 [10] Granger, C.W.J., Newbold, P (1974). “Spurious Regression in Econometrics”, Journal of Econometrics. http://www.iaeme.com/IJM/index.asp 8 editor@iaeme.com
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