CHAPTER IV TAX REVENUE AND EXPENDITURE - THE CAI@& NEXUS The size of the government is influenced by both demand and supply factors of government spending. Among the demand factors, growth of population, per capita income and price elasticity of demand are the most important ones. 1 Fiscal illusion, special interest, group favouritism and bureaucratic incentivesd are some of the important supply factors. Further, the annual budget decisions of the government may also have an impact on the size of the public sector. With regard to this, there are three hypotheses propounded by economists. Firstly, the government may change expenditure and taxes concurrently.3 Under this condition, the spending level and taxes are decided by the citizens of a locality by comparing the benefits of government to its marginal cost. Secondly, taxes may lead to government spending which is consistent with the local and state finances. This view is supported by the supply side economists who argue that increases in taxes only 4 result in increased spending and not deficit. Thirdly, spending may lead to taxes, which was explored by Peacock and wiseman.' Their main argument is that temporary changes
in government spending may lead to permanent changes in taxes. There has been a debate in literature concerning evidence on the above three hypotheses Causal relationship may he either one-way or two-way. One-way causality implies that one variable determines the other unilaterally, while in two-way causality both variables are simultaneously determined. While assessing the causal relationship between government tax revenue and expenditure, L31ackley6 concludes that tax increases may not lead to smaller deficits. Similarly, Manage and ~ arlow~ report some evidence of a unidirectional causation running from revenues to expenditures. In contrast, "on perstenbergs has found support for the spend tax hypothesis and concludes that increases in spending lead to an increase in taxes and not vice versa. A similar conclusion has also been reported by ~nderson.' In the light of this background, this chapter attempts to identify the causality between the tax revenue of Indian States and expenditures, and to verify empirically whether a causal relationship exists between expenditure and tax revenue when the total expenditure is disaggregated into capital and revenue expenditure.
4.2 CAUSALITY TESTS For examining the causal relationship between expenditures and tax revenues, the tests of %ranger and Sims are used in the present study. These tests are defined based on the criterion of minimizing the forecast error variance of a given time series conditional upon a given information set. The tests are described below: 4.2.1 GRANGER TEST For a simple bivariate model, these patterns of Causality can be identified by estimating regressions of H and E on all the relevant variables including current and past values of p and E respectively, and by testing the appropriate hypotheses, which may be done by applying the Granger test. With the help of the following two equations, the Granger test may be explained. Where et and Et are mutually uncorrelated. We may estimate (1) and (2) and test the null hypothesis that ci = Ji = 0 for all i(i=0,1,2,... n.) against the alternative hypotheses that ci f- 0 and $i f 0 for at least some its.
4.2.2 SIYS TEST The Sims test (1972)1 follows the logic that future cannot cause past. The causation betgeen Xt and Yt may be identified by estimating the following equation: Under the maintained hypothesis that Xt causes Yt, we have, for bi-directional causality (feedback) between the two variables, it is to be satisfied that $a. (i L 0) = 0 and 4bj (j L 0) = 0. And the condition of independence is that Generally, the F test is quite sensitive to the presence of autocorrelation among the residuals. Hence, the causality test is also examined with the help of filtering. These tests are subject to the limitations of bivariate analysis.
For examining the causality between expenditure and tax revenue, the sum total of expenditure of all Indian States from 1969-70 to 1988-89 is used. 5 Further, the revenue and capital expenditure are also considered as the components of total expenditure in order to test the causality between tax revenue and disaggregated expenditure. The necessary data are collected from the various issues of the Reserve Bank of India Bulletin of various years. Then the nominal data are deflated with wholesale price index. 4.3 EMPIRICAL RESULTS The Granger and Sims tests of causality is used on the deflated data of total expenditure and tax revenue, and revenue expenditure and capital expendlture. These tests are also examined on the actual data and in log series. Further, the data are also filtered in each case in order to avoid the sensitiveness of F - test to the presence of autocorrelation among residuals. The relationships tested are (i) total expenditure vs tax revenue, (ii) capital expenditure vs tax revenue, and (iii) revenue expenditure vs. tnx revenue. Tables 4.1 to 4.3 summarise the results of Granger test between expenditure (total, capital and revenue) and tax revenue at constant prices of Indian States. In the
TABLE 4.1: GRANGER TEST OP CAUSALITY BETWEEN TOTAL EXPENDITURE MD TAX REVENUE OF INDIAN STATES TE on TR TR on TE LAG FORM Signifi- 1- Signif i- F-RATIO cance Level F-RATIO cance Level LAG FORM Log(TE) on Lo~(TR) F-RATIO Signif i- cance Level (1.1) 4.3514 0.0215 (2,2) 4.2395 0.0382 WITH FILTER (1-KL)', ~=0.75 0.2876 0.7555 0.1875 1.0644 0.4166 2.4376 0.1395 Note: TE - Total Expenditure TR - Total Revenue
TABLE 4.2: GRANGER TEST OF CAUSALITY BETWEEN CAPITAL EXPENDITURE AND TAX REVENUE OF INDIAN STATES LAG FORM CE on TR Signif i- TR on CE (181) (3.,2) (3,3) 0.1274 0.9417 0.0734 0.9729 LAG FORM Log(CE) on Log(TR) Signif i- Log(TR) on Log(CE) Signif i-- (1,l) WITH FILTER (1-KL)', K=0.75 4.1251 0.0382 0.2131 0.8011 3.995 0.0496 0.1923 0.8278 (393) 4.9158 0.0319 0.3386 0.7982 Note: CE - Capital Expenditure TR - Total Revenue
TAEILE 4.3: GRANGER TEST OF CAUSALITY BETWEEN REVENUE EXPENDITURE AND TAX REVENUE OF INDIAN STATES LAG FORM RE on TR Signifi- TR on RE (191) (2,2) 2.7222 0.1029 2.1774 0.1529 (3~3) 4.4027 0.0321 2.8055 LAG FORM Log(RE) on Log(TR) Signif i- Log(TR) on Log(RE) Signifi- (191) (2,2) (3t3) 2.4144 0.1283 0.5123 0.6107 1.9056 0.1927 2.6505 0.1060 WITH FILTER (1-KL)~, K=0.75 Note: RE - Revenue Expenditure TR - Total Revenue
Granger test, for the equation with expenditure as a dependant variable, the null hypothesis that the lagged values of tax receipts do not improve tqe forecasts of expenditure is tested. For equations with tax revenue as the dependent variable, the null hypothesis is that the lagged values of expenditure do not improve the forecasts of tax revenue over the one obtained on the basis of lagged values of tax receipts alone. The empirical results of Granger test (Table 4.1) show that tax revenue causes the total expenditure in Indian States. In addition, capital expenditure is also caused by tax revenue (Table 4.2). The causality result of capital expenditure versus tax revenue is obtained only on filtered series, which shows that this test on actual, data and log series is sensitive to an existence of autocorrelation among the residuals. Further, the revenue expenditure is also determined by tax revenue (Table 4.3). Thus, the Granger test of causallty between expenditure and tax revenue of the Indian states supports the view of supply side economists, who argue that increases in taxes only result in increased spending and not deficit. Tables 4.4 to 4.6 highlight the Sims test of causality between expenditure (total, capital and revenue) and tax revenue of Indian States. In the Sims test, if the inclusion of information on future expenditure improves the predictability of current tax revenue then, tax revenue
TABLE 4.4: SIMS TEST OF CAUSALITY BETWEEN TOTAL EXPENDITURE AND TAX REVENUE OF INDIAN STATES LAG/LEAD TE on TR TR on TE Signif i- F-RATIO cance Level F-RATIO cance Level ORM (-1,l) (-2,2) 3.0889 0.0902 2.4157 0.1393 (-393) 1.8528 0.2332 2.2471 0.1833 LAG/LEAD Log(TE) on Log(TR) Log(TR) on Log(PE) (-1,l) 0.0027 0.9594 0.0116 (-232) 2.451 0.1361 0.0448 (-3~3) 1.2535 0.3709 0.9459 0.4755 WITH FILTER (1-KL)~, K=0.75 0.4557 0.5124 0.0776 0.7853 2.2876 0.1638 2.942 0.1102 (-383) 1.2847 0.3937 2.1101 0.2417 Note: TE - Total Expenditure TR - Total Revenue
TdSLE 4.5: SIMS TEST OF CAUSALITY BETWEEN CAPITAL EXPENDITURE AND TAX RFVENUE OF INDIAN STATES LAGILEAD FORM CE on TR TR on CE (-1,l) (-292) (-3,3) 0.4966 0.9324 0.4809 -'I Log(CE) on Log(TR) Log(TR) on Log(CE) LAGILEAD FORM F-RATIO cance Level F-RATIO cance Level 1: (-191) 0.4073 0.6759 0.6240 (-2~2) (-3,3) 0.5834 0.6474 WITH FILTER (I-KL)~, K=0.75 Note: CE - Capital Expenditure TR - Total Revenue
TABLE 4.6: SIMS TEST OF CAUSALITY BGTWEEN mpal EXPENDITURE AND TAX REVENUE OF INDIAN STATES - I I Log(RE) on Log(TR) Log(TR) on Log(RE) LAGJLEAD FORM Signifi- Signif i- WITH FILTER (1-KL)', K=0.75 (-191) 0.5915 0.4567 0.0261 0.8742 2.4623 0.1468 1.5488 0.2761 1.9842 0.2586 1.2363 0.4065 Note: TE - Total Expenditure TR - Total Revenue
causes expenditure. On the other hand, tax revenue is determined by expenditure if the future tax revenues improves the prediction of current expinditure. The empirical results of the Sims test of tax revenue versus total expenditure shows a unidirectional causality, i.e., from tax revenue to total expenditure (Table 4.4). But there is a feedback between capital expenditure and tax revenue (Table 4.5). Further, revenue expenditure is also determined by tax revenue in Indian States (Table 4.6). By and large, the inference drawn from the results of Sims test also supports the supply side economists view which is more or less similar to the result of the Granger test.
Borcherding T. E., The Sources of Growth of Public Expenditure in the United ~tat=:in~udgets and Bureaucrates. Ed: Durham, N.C: Duke University Press, 1977, pp.45-70. Blackley, R., "Causality Between Revenues and Expenditures and the Size of the Federal Budget", -- Public ---- Finance Quarterly. Vo1.-a4, April, 1986. pp.139-56. Musgrave, K., "Principles of Budget Determination". In --- Public Finances Selected Readings. H. Cameraon and W. Henderson, Eds. New York Bandom House, 1966, pp.15-27. Roberts, P.C., The Su 1 Side Revolution. Cambridge M. A. Harvard Uni~sity~~Pr%e6=984. Peacock A.T. and Wiseman, "Approaches to the Analysis of Government Expenditure Growth", Public Finance Quarterly, Vo1.7. Jan. 1979, pp.3-13. Blackley, R., op.cit., p.139 Manage, N. and Michael L. Marlow, "The Causal Relation Between Federal Expenditure and Receipts", Southern Economic Journal, Vo1.52, Jan. 1986, pp. 617-29. Von Ferstenburg, George, R. Jeffrey Green, and Jin-ho Jeong, "Have Taxes Led Government Expenditures? The United States as a Test Case", Journal of Public Policy, ~01.3, 1985, pp.321-348. 9. Anderson, William, Myles S. Wallace, and John T. Warner, "Government Spending and Taxation What Causes to What?", Southern Economic Journals, Vo1.52, Jan. 1985, pp.630-39. 10. Sims, Christopher, "Money, Income and Causality", American Economic Review, Vo1.62, 1972, Vo1.62, pp.540-552.