0 To. Brennan and Buchanan (1980) propose a &dquo;new&dquo; theory of. relationship between the degree of decentralization and the share

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1 This article is an empirical examination of the "Leviathan hypothesis" developed by economists Brennan and Buchanan (1980). The hypothesis states that as individuals turn over control of public spending to higher levels of government, the preferences of the politicians, bureaucrats, and special-interest lobbyists who determine fiscal policy at these higher levels of government replace the tastes and preferences of the individual for the amount of spending and taxing. This transfer of control from decentralized to centralized decisionmaking and this replacement of taxing for individual preferences by political-bureaucratic preferences toward spending lead to an expansion of the public sector. Regression analysis shows support for the hypothesis in specific public-service areas. LEVIATHAN AND FEDERALISM IN THE UNITED STATES HENRY J. RAIMONDO University of Massachusetts, Boston 0 To rein in the public sector turned Leviathan, theorists Brennan and Buchanan (1980) propose a &dquo;new&dquo; theory of federalism based on their interpretation of public sector behavior. The new theory states that the greater the degree of decentralization of fiscal decisionmaking, the lesser will be the share of income claimed by the public sector; that is, there is an inverse relationship between the degree of decentralization and the share of income used to support the public sector. This article is organized into three parts. The first part reviews past empirical work concerning the manifestation of Brennan s and Buchanan s Leviathan hypothesis in the United States. The second part sets out the current model to test this hypothesis, and the third presents the empirical results. AUTHOR S NOTE: My thanks to H. Peter Gray, Oscar Harmon, the participants in the department seminar series, and the referees for their constructive comments. I am responsible for the final version of this article. PUBLIC FINANCE QUARTERLY, Vol. 17 No. 2, April Sage Publications, Inc. 204

2 205 PAST EMPIRICAL EVIDENCE There has been one major empirical test of the decentralizationshare relationship for the state-local public sector in the United States. Oates (1985) examined the relationship for the 48 contiguous states using 1977 fiscal data. His dependent variable is total state-local tax receipts as a fraction of state personal income. Oates looks at three possible state-local decentralization indices: state share of state-local general revenues, state share of statelocal total expenditure, and the absolute number of local government units in the state. Other independent variables are found in his regression equations: per capita income, population, percentage of population that resides in a standard metropolitan service area (SMSA), and intergovernmental grants as a percentage of state-local general revenues. Oates s empirical test produces the signs on the state-local decentralization indices that Brennan and Buchanan predicted. In all of the various formulations of the regression model, however, the signs are not statistically significant. These findings lead Oates to conclude that &dquo;the results of this study suggest that there does not exist a strong, systematic relationship between the size of government and the degree of centralization of the public sector&dquo; (Oates, 1985, p. 756). AN ALTERNATIVE FORMULATION OF THE MODEL The empirical test in this paper owes an obvious debt to Oates s research. As does his, this empirical test is concerned with the Leviathan hypothesis that theorizes an inverse relationship between the degree of public-sector decentralization and the share of income claimed by the public sector. This test uses the state-local public sector in the United States. Also, for the same reasons given by Oates, this test makes use of a series of &dquo;ad hoc reduced form equations to test the hypothesis&dquo; (Oates, 1985, pp ). There are, however, four elements that distinguish this empirical test from Oates s work. First, the data set has more than 48

3 206 observations. These data consist of a pooled cross-section of the 50 states from 1960, 1970, and This set, therefore, has 150 observations. (The inclusion of Alaska and Hawaii did not significantly alter the results in the present study.) All fiscal data have been converted to 1980 real amounts using the appropriate GNP deflator and consumer price index. Second, the dependent and independent variables have changed. These changes will be explained as the model is presented in detail below. Third, statelocal data have been disaggregated. Instead of examining only the fiscal total, this empirical investigation provides a test of the decentralization-share relationship for six categories of statelocal fiscal policy: total, education, public welfare, hospital, highways, and an &dquo;all other&dquo; group. The Leviathan hypothesis may be more appropriate for specific functions than for the total of all functions and more appropriate for some public service functions than for others. The disaggregation allows a test of that proposition. Fourth, as the reader might have anticipated, the outcome gives some empirical support for the Brennan and Buchanan model as well as for the Oates position. MODEL The general form of the model used to test the Leviathan hypothesis for each of the six categories listed above is: share measure = ao + a POP + a2inc + a3hard + a4smsa + [1] as FEDERAL + a6local + e where the dependent variable, share measure, may take on six definitions: TGE, the ratio of total state-local general expenditures to personal income; EDUC, the ratio of state-local educational expenditures to personal income; PWEL, the ratio of state-local public welfare expenditures to personal income; HOSP, the ratio of state-local health and hospital expenditures to personal income; HWY, the ratio of state-local highway expenditures to personal income; and OTHER, the ratio of &dquo;all other&dquo; state-local expenditures (e.g., police and fire protection, parks and recreation, housing and urban renewal, and sewer and sanitation) to

4 207 personal income. Here the independent variables are POP, the resident population in thousands by state, which measures economies of scale in public-service provision; INC, the per capita personal income (in constant 1980 dollars) by state, which measures ability-to-pay for public services; HARD, the relative state hardship index, which measures the overall development or sociodemographic well-being of the state resident population; SMSA, the percentage of the population that resides within standard metropolitan statistical areas, a measure of the additional congestion costs in public service provision. Two additional variables are especially associated with the Leviathan hypothesis: FEDERAL, the percentage of the state-local expenditure item (i.e., TGE, EDUC, PWEL, HOSP, HWY, or OTHER) that is funded by the federal government; and LOCAL, the percentage of the state-local expenditure item (i.e., TGE, EDUC, PWEL, HOSP, HWY, or OTHER) that is funded by the local government. Each variable is calculated for the years 1960, 1970, and The constant term is ao and the error term is e. DATA The Census of Government Finances for the appropriate years is the source of the state and local fiscal data: TGE, EDUC, PWEL, HOSP, HWY, and OTHER, and FEDERAL and LOCAL for each of the six categories. The Census of Population for the appropriate years is the source for POP, INC, HARD, and SMSA. ISSUES CONCERNING THE MODEL The model in equation (1) raises three issues: definition of the dependent variable, the predicted sign of the independent variables, and the relationship between the dependent variable and FEDERAL and LOCAL. The first issue is the definition of the dependent variable. In all six forms, the dependent variable is a ratio of public-service expenditure to personal income. Public-service expenditure

5 208 includes a government s own source revenue and intergovernmental grants. Studies of government expansion often use revenues as a measure of government size rather than expenditures. The expenditure definition of the dependent variable, however, allows the model to capture the degree to which local governments and the federal government fund total and specific public services. A revenue measure would complicate the process of disaggregating public service functions and their funding sources. For example, if the local contribution is relatively small, then the public service function has become centralized, and the Leviathan hypothesis predicts that the share of income claimed by the public sector for this category of spending will be relatively large. Although this article uses the expenditure measure in the empirical estimation of the model, another version of the model has been estimated using the revenue measure. The results of the revenue model are generally consistent with the results of the expenditure model, which are presented later. The second issue is the independent variables predicted sign. The independent variables capture the characteristics of the state and local jurisdictions. POP measures the sheer numbers of people; INC represents ability-to-pay, or the resources available to the public sector; HARD and SMSA account for the sociodemographic features; and FEDERAL and LOCAL describe the institutional financial arrangements found in each state. The hypothesized relationship between the dependent variable and the independent variables is clear in some cases. For example, if the Leviathan hypothesis holds, then the sign on the FEDERAL variable must be positive. In addition, if the Leviathan hypothesis holds, then the sign on the LOCAL variable must be negative. The state government share of each expenditure category is omitted from the regression equation to avoid econometric problems. It should be noted that FEDERAL and LOCAL are not systematically inversely related. The state government share of each expenditure category varies by state. In any one state, FEDERAL and LOCAL may both be &dquo;high,&dquo;&dquo;low,&dquo; or inversely

6 209 related. There is no formula that ties FEDERAL and LOCAL together across all states and across all expenditure categories. But the hypothesized relationship between the share measure and POP, INC, HARD, and SMSA is not obvious because the dependent variable is expressed as a ratio. For example, while INC is positively associated with state and local public-service spending, INC may not be positively associated with the share measure, for as INC increases, public-service spending may be increasing, although at a slower rate. The share measure would decline. The relationship between the share measure and INC would be negative. The relative changes in the variables will determine the sign of the independent variable. The problem in accurately predicting the signs of the independent variables also is evident: If federal grants increase expenditures in low-income states, more than in high-income states, then the dependent variable in the low-income states will be large, while the income variable is low. Again, the result is a negative sign. The third issue is the relationship between the dependent variable and FEDERAL and LOCAL. Because the numerator of the dependent variable (in all forms) is in expenditure terms and the denominator of the independent variables LOCAL and FEDERAL is in expenditure terms, the association between the dependent variable and these independent variables may seem definitional rather than a test of the Leviathan hypothesis. But a look at the correlation matrix for these variables dispels any concern. There is little association between FEDERAL and LOCAL and the forms of the dependent variables. ESTIMATION PROCEDURE The empirical results present one form of the regression model. Other elements of the estimation procedure received attention but are not presented: for example, values for the dependent variable regardless of its form range between zero and one. Some economists would recommend the use of a logistic transformation of the dependent variable in this case (Theil, 1971). The

7 210 model has been estimated both with and without the transformation. Because the results were remarkably similar, those presented here do not make use of the logistic transformation. In addition, alternative forms of the dependent variable were explored. Although the share variable is consistent with Oates s research and earlier work done on the size of the public sector, four variables-per capita expenditure, per capita revenues levels, growth rates in expenditures, and growth rates in revenueswere examined as dependent variables. In many cases the outcomes were consistent with the results of the Leviathan hypothesis shown here. Because the data set consists of pooled, cross-section observations, a cross-sectionally heteroskedastic and time-wise autoregression model was used (Kmenta, 1971). The adjustment for heteroskedasticity in the cross-section observations corrects for any association between the size of the disturbance term and the size of independent variables. The adjustment for autoregression among the time-series observations corrects for an association between a given variable across time periods. Although sociodemographic, economic, and institutional arguments guide the selection of independent variables, and even with empirical procedures determining the inclusion of operational variables, the functional form of the model in equation (1) is not known a priori. The choice of a functional form will be based upon several well-known goodness-of-fit criteria: R2, adjusted R2, F, and minimum mean-squared error. That approach has led to the double-log model for the estimation of equation (1). EMPIRICAL RESULTS Table 1 presents the results of the regression analysis for the pooled, cross-section data set for state and local government expenditures using the model in equation (1). The dependent variable is the share measure for the six expenditure categories. Table 1 also displays the adjusted R2 and the t-statistics for each model.

8 211 TABLE 1 Estimated Regression Equations, Pooled Cross-Section Data for 1960, 1970, and 1980 (Cross-Sectionally Heteroskedastic and Timewise Autoregressive Models) NOTE: The models are double-log. The numbers in the parentheses below the estimated coefficients are the absolute values of the t-statistic. An asterisk indicates that the estimated coefficient is statistically significant at the.01 level. The results of the regression analysis begin with the independent variable POP. POP is statistically significant in all six models. It is positively associated with PWEL and HOSP, two redistributive state and local public services. POP is negatively associated with TGE, EDUC, HWY, and OTHER. The second relationship could very well capture economies of scale in the provision of these four categories of public services. INC is also statistically significant in all six models, negatively associated with the dependent variable in each. This paradoxical

9 212 relationship may result from the income elasticity for all categories of public service being less than 1. The relationship may also result from any of the explanations that were offered earlier. HARD is statistically significant in all the models except PWEL. The variable has a positive relationship with EDUC and HWY that may be the result of the federal and state intergovernment-grant system directing funds to achieve equality of educational opportunity, provide compensatory education, and build roadways. HARD is negatively associated with TGE, PWEL, HOSP, and OTHER. This outcome may indicate that public service spending is not tied to this particular measure of sociodemographic well-being and that public &dquo;needs,&dquo; consequently, are not being satisfied. SMSA is statistically significant in the models for EDUC, HOSP, and HWY. It is not statistically significant in the models for TGE, PWEL, and OTHER. This independent variable has a positive relationship with TGE, EDUC, PWEL, and HOSP, which is consistent with an additional (congestion) cost argument. The relatively few miles of roadways in an SMSA may well explain the negative association between SMSA and HWY. The FEDERAL and LOCAL variables directly test the Leviathan hypothesis. Recall the argument that Brennan and Buchanan make. To the degree that a public service is centralized, the share of personal income spent on that public service will increase. FEDERAL captures that relationship, and its predicted sign is positive. To the degree that a public service is decentralized, then the share of personal income spent on that public service will decrease. LOCAL captures that relationship, and its predicted sign is negative. The relationship between FEDERAL and LOCAL was discussed in the section &dquo;issues Concerning the Model.&dquo; The conclusion is that these two independent variables are not systematically related, and so any combination of signs is possible for FEDERAL and LOCAL. The disaggregation of the state and local public-service expenditures allows for a test of the Leviathan hypothesis for total and specific public-service spending. The regression analysis begins

10 213 with FEDERAL, which is statistically significant in all six models. Its sign is positive for TGE, PWEL, HOSP, and HWY. The positive relationship can be interpreted as a form of the Leviathan hypothesis. To the degree that public service spending is centralized, the share of personal income claimed by that public service will increase. In the case of EDUC and OTHER, the Leviathan hypothesis is not confirmed. LOCAL also tests for the Leviathan hypothesis, and is statistically significant in all models except EDUC. Its sign is negative for TGE, PWEL, and OTHER. This outcome supports the Leviathan hypothesis; namely, that to the degree spending on a public service is decentralized, the share of personal income claimed by that public service will decrease. In the case of EDUC, HOSP, and HWY, the Leviathan hypothesis is not confirmed. To the extent that local residents believe that spending for the local public school, municipal hospital, and road system (which supports the local economy) benefits them, they are willing to tax and spend more to receive more. Another way to interpret the regression results would divide the public-service categories into three classes: Leviathan supported, Leviathan rejected, and Leviathan undecided. In the first class, Leviathan supported, FEDERAL has a positive sign and LOCAL has a negative sign. TGE and PWEL fall into this class. In the second class, Leviathan rejected, FEDERAL has a negative sign and LOCAL has a positive sign. EDUC fits this description. In Leviathan undecided, the last class, the signs on FEDERAL and LOCAL are not consistent with the first or second class. HOSP, HWY, and OTHER are in this last class. The Leviathan over time is the last consideration. Because the data set possesses a time-series component, the regressions were estimated for each period-1960, 1970, and 1980-to determine whether the effect of the Leviathan hypothesis had changed over time in a statistically significant manner. A Chou test on the equivalence of the coefficients on FEDERAL and LOCAL across data sets shows that the null hypothesis (i.e., that the coefficients are equivalent) cannot be rejected.

11 214 The regression analysis provides evidence that supports the Brennan and Buchanan notion of the Leviathan hypothesis-to some degree! The pragmatic fiscal federalism practiced in the United States is not as neat as the Leviathan hypothesis presumes. Although there is evidence for the Leviathan hypothesis in specific public-service areas, that evidence must be treated carefully because there is also evidence to reject the notion of the Leviathan in other specific public-service areas. NOTE 1. To determine state hardship we use a modified version of an index developed by Nathan and Adams (1976). The measure uses five variables: unemployment, dependency (percentage of the population less than 18 years of age or greater than 65 years of age), education (percentage of the population more than 25 years of age that has not completed four years of high school), crowded housing (percentage of owner-occupied housing that has more than one person per room), and poverty (percentage of families living below 125% of the poverty level). Higher than average values of any of these five variables would be considered undesirable and lower values more desirable. The variables are standardized numbers to give equal weight to each, and summed to arrive at a set of composite index numbers. Equation (2) explains this procedure. where Y, equals the standardized number to be calculated for each of the five variables, X, equals the value for one of the five variables, k equals the difference between the maximum and minimum values for X,, and Xmin equals the minimum value of X,. The average index number was found by dividing the sum of all Y, by five. The higher the composite number, the greater the state s hardship. REFERENCES BRENNAN, G. and J. M. BUCHANAN (1980) The Power to Tax. New York: Cambridge Univ. Press. KMENTA, J. (1971) Elements of Econometrics. New York: MacMillan. NATHAN, R. and C. ADAMS (1976) "Understanding central city hardship." Pol. Sci. Q. 91: OATES, W. ( 1985) "Searching for Leviathan: an empirical study." Am. Econ. Rev. 75: THEIL, H. (1971) Principles of Econometrics. New York: Wiley & Sons.

12 215 Henry J. Raimondo is associate professor of economics at the University of Massachusetts at Boston. His interests include public finance, state and local finance, and the economics of sports, and his articles have appeared in Growth and Change, the Journal of Labor Research, the Journal of Public Budgeting and Finance, and Land Economics.