Public Expenditure, Income Distribution, and Growth ...

Public Expenditure, Income Distribution, and Growth in OECD Countries OSCAR ALFRANCA∗ AND MIGUEL-ANGEL GALINDO∗∗

Abstract Economic growth and the several topics related to it have been studied by economists since their earliest publications. Two different approaches to this area can be found in Neoclassical and Endogenous growth models. The economic growth analysis has focused its attention on the factors that inßuence the growth of nations, such as Þscal policy or improvement of human capital. Nevertheless, it is also interesting to study the effects of income distribution on economic growth to determine if it has positive effects on growth. The aim of this paper is to study these effects. The authors will develop a theoretical model in which they will introduce public capital in a typical Cobb-Douglas production function. They will estimate OLS, GLS, and SUR Þxed effects models for time series and cross-sectional data. (JEL 040); Int’l Advances in Econ. Res., 9(2): pp. 133-39, c May 03. ° All Rights Reserved.

Introduction Economists have been deeply interested in the relationship between income inequality and growth. The publication of The General Theory by Keynes can be understood as the starting point of this relationship. This is because if one accepts the Keynesian hypothesis about savings, then it is necessary to get a redistribution of income to determine whether the richest economic agents get more income, thereby improving savings and eventually the growth of the economy [Kaldor, 1956]. By considering this assumption during the 1950s and 1960s, economists focused their attention on the effects of income distribution on growth, taking into account consumption and saving behavior. Up until the 1980s, theorists were less interested in the growth theory and their analysis accepted the representative agent behavior in overlapped generations models. In both cases, the income distribution is not included. From the 1980s, and especially with the introduction of endogenous growth models [Romer, 1986, 1987; Rebelo, 1991], models took into account the effects of income distribution on growth.Two conclusions emerged [Aghion, García-Peñalosa, and Caroli, 1998a]. (1) Income inequality motivates economic incentives, improving economic growth. The reason is if we need savings to improve growth, it is necessary to shift income from poor to rich individuals. (2) The Kuznets [1955] curve which states that inequality will increase in the Þrst development stages and will be lower later. The main goal of this paper is to analyze the Þrst statement. The next section will consider the effects of income distribution on growth. In section three, the authors will develop an economic growth model, including public sector behavior and income distribution using the GIN I index. Section four provides econometric evidence. The last section concludes. ∗

Polytechnic University of Catalonia and

∗∗

University of Castilla-La Mancha–Spain.

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Income Distribution Effects on Growth When the relationship between income distribution and economic growth is analyzed, several mechanisms are considered [Benabou, 1996; Aghion et al., 1998b; Alfranca, Galindo, and Sánchez-Robles, 2001]: 1) Investment indivisibilities. New investment implies the appearance of sunk costs. Therefore, wealth must be concentrated. 2) Incentives [Mirrlees, 1971]. When the beneÞts derived from the product are uncertain, the economic agents are discouraged and investment is reduced, damaging the economic growth process. Hence, wealth concentration is necessary to reduce such uncertainty. 3) Credit market imperfections [Loury, 1981; Galor and Zeira, 1993; Piketty, 1997; Barro, 1999]. When limitations to loans appear, some behavior must be considered. First, poorer economic agents try to increase their investments in human capital that offer them a higher earnings rate. Second, if the previous mechanism is accepted, higher education would positively affect economic growth if carried out beyond some minimal level in the same way that the entrepreneurial activity is also positively affected if it goes beyond some threshold level. These effects are more important in less developed economies than in the more developed ones. 4) Macroeconomic volatility that is generated by inequality negatively affects growth [Alesina and Perotti, 1996]. Inequality encourages political and institutional instabilities, and as savers and investors are different. When macroeconomic volatility appears, the former group can become discouraged about saving, resulting in negative effects to investment and growth processes. 5) Political economy aspects [Perotti, 1993; Bertola, 1993; Alesina and Rodrik, 1994; Persson and Tabellini, 1994; Benabou, 1996]. Inequality effects on taxation exist in a country through the political process when individuals modify or choose the taxation rate by voting. The reason is that in an economy with a high inequality rate, voters prefer better income distribution through higher taxation. In this case, investment could decrease, reducing the economic growth process, at least in the transition to the steady-state. 6) Social effects [Venieris and Gupta, 1986; Gupta, 1990; Benhabib and Rustichini, 1996]. Higher inequality implies the appearance of social problems, such as crime and riots. These, together with other disruptive activities, can negatively affect economic growth because economic agents will not be interested in improving or maintaining their productive activity. On the other hand, institutional instability is threatened producing a loss of resources as well as private property. All these situations discourage investment, resulting in a reduction in productivity and growth. Economic Growth Model The authors will now develop an economic growth model by introducing public capital as another productivity factor in each period1 and the income distribution including the GIN I index. They start with the traditional Cobb-Douglas production function: Y = K α Gβ (AL)1−α−β

,

(1)

where: Y = income; K = private capital; G = public expenditure; L = labor factor; A = technology indicator; and α < 1 and β < 1 are elasticities. There are constant returns to scale in the function and the authors consider neutral technological progress a la Harrod. ˙ ˙ L = n and A Also, suppose that L A = x, where n is the constant population growth rate and x

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the exogenous and constant technological growth. By dividing (1) by L and considering the dynamics of the economy, the Þnal equation is obtained: y y y˙ = (1 − α − β)a + αs(1 − τ ) − α(n + δ) + βτ y k g

,

(2)

where: k = the capital per worker; g = public expenditure per worker; s = the propensity to save; τ = the tax rate; and δ = the private capital depreciation rate. a includes the GIN I index. The Econometric Model, Data, and Results An econometric model of aggregate annual GDP growth is speciÞed and Þtted to panel data consisting of 19 OECD countries (Austria, Belgium, Canada, Denmark, Finland, France, Germany, Greece, Ireland, Italy, Japan, Netherlands, New Zealand, Norway, Portugal, Spain, Sweden, U.K., and the U.S.). The main aim of the econometric estimation is to test the relationship between income distribution and growth when public expenditure is a relevant variable. The econometric model of economic growth incorporates variables representing the effects of production factors, public expenditure, and income distribution. A Þxed effects panel data model will be estimate using the following equation: yit = αi + Xit β + uit

.

(3)

In this model, it is assumed that β coefficients are identical for all countries in the sample, but some differences could exist in the constant term. The constant term reßects the effects of the omitted variables that are peculiar to any of the countries in the sample. Models are presented under a log-linear speciÞcation in order to avoid heteroskedatiscity problems. The variables considered are: y ∗ /y = growth rate of real GDP per worker; y/k = ratio of real GDP per capital stock; y/g = ratio of real GDP per government consumption; and GIN I = Income GINI index.2 The econometric economic growth equation is: µ ¶ y˙ ln = y Eµlt

µ ¶ µ ¶ y y + β 3 ln + β 4 GIN Iit + µlt Constanti + β 2 ln k g

= 0, Eµ2lt = σ2lt , Eµlt µqt = σ2lt , 5 l, q, t

,

(4)

where µlt is a random disturbance term representing the effects of omitted variables. It has zero mean, constant variance over time for any given country, but differs across countries and presents non-zero contemporaneous correlation across countries. Results Equation (4) is Þtted by the OLS estimation method to the 437 observations obtained by pooling the 23 observations for 19 OECD countries. The estimated coefficients and t-value are reported in Table 1.

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TABLE 1 Growth and Income Distribution, 1970-92. Dependent variable = µ ¶ y log k t-value µ ¶ y log g t-value GIN I t-value CONST AN T t-value CONST AN T t-value CONST AN T t-value CONST AN T t-value CONST AN T t-value CONST AN T t-value CONST AN T t-value CONST AN T t-value CONST AN T t-value CONST AN T t-value CONST AN T t-value CONST AN T t-value CONST AN T t-value CONST AN T t-value CONST AN T t-value CONST AN T t-value CONST AN T t-value CONST AN T t-value

(1)

Austria Belgium Canada Denmark Finland France Germany Greece Ireland Italy Japan Netherlands New Zealand Norway Portugal Spain Sweden United Kingdom

∗

y y

(2)

0.210

0.186

2.898

2.561

0.008

-0.004

0.157 0.002 2.673 0.475 1.188 0.512 1.283 0.496 1.206 0.506 1.231 0.597 1.565 0.445 1.082 0.574 1.471 0.519 1.405 0.442 1.106 0.500 1.244 0.576 1.648 0.459 1.126 0.454 1.111 0.580 1.491 0.431 1.081 0.463 1.176 0.454 1.071 0.451 1.046

-0.075 0.648 1.624 0.688 1.729 0.660 1.607 0.652 1.585 0.737 1.926 0.647 1.581 0.736 1.887 0.679 1.842 0.640 1.612 0.671 1.672 0.731 2.099 0.618 1.516 0.630 1.546 0.733 1.882 0.609 1.529 0.621 1.578 0.619 1.460 0.613 1.418

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TABLE 1 (CONT.) (1) CON ST AN T United States of America 0.431 t-value 1.006 Durban Watson 1.563 F-statistic 20.179

(2) 0.611 1.828 1.540 32.490

The Þtted model performs well and most of the coefficients are different from 0 at the 5 percent signiÞcance level. The hypothesis that income redistribution has no explanatory power on economic growth is rejected at the 1 percent signiÞcance level. In order to maintain this conclusion, the following inequality should be satisÞed (from equation (1) and Table 1, one Þnds the marginal effects on economic growth from changes in income distribution ): µ ¶¶ µ ³ ´ y y + 0.0028∗ log . 0.0244 > 0.0035∗ log k g

Otherwise, the effects would be different and reducing µ ¶a positive µ ¶ inequality would cause y y (-0.086173) and log (8.066), effect on economic growth. Using the means for log k g the value of the right side of the inequality is equal to 0.022283, which is slightly smaller to the GIN I elasticity (.0244). Hence, increasing inequality will have small positive effects on economic growth. Regarding particular effects, capital productivity is the common variable with the highest incidence on economic growth. Income distribution presents high signiÞcance levels, despite a reduced impact (very similar to a public expenditure incidence). Public expenditure productivity presents the expected sign, although its signiÞcance is fairly low. It is important to point out that, in spite of the income distribution variable being quite strong, regression equation (4) is estimated with the restriction of no effects related to income distribution (reported in Table 1, regression (2)). It is noteworthy that the sign for the marginal impact of public expenditure is reversed. This is consistent with income distribution being correlated with the other variables and being an important factor in determining economic growth. The estimates of the country-speciÞc Þxed effects are always positive. Coefficients are largest for Norway and Finland and smallest for the U.S., Japan, Norway, and Finland which reject the hypothesis of non-signiÞcance for omitted variables at the 10 percent signiÞcance level. For the rest of the countries, the t-values are smaller. Conclusions Using annual data for 19 OECD countries, the authors rejected the hypothesis that income distribution does not matter. They have shown that increases in public expenditures and improvements in capital productivity lead to larger economic growth, other things being equal. Income redistribution toward increased inequality has been shown to be a positive force behind economic growth, although this effect is not very intense. SigniÞcance of the GIN I index used in the speciÞcation of the econometric model is high, in spite of the coefficient being small. The effects of changes in income distribution on economic growth appear to be weaker than the impact derived from public expenditures or increases in capital productivity. Capital productivity appears to be the main variable behind economic growth. Positive Þxed effects reßecting the incidence of omitted variables appears for all countries. Nevertheless, signiÞcance of this constant term is weak, and the non-signiÞcance hypothesis is rejected only for Japan, Norway, and Finland.

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In the econometric estimations presented in this paper, the authors accept changes in the constant term but not in the coefficients. The existence of different Þscal policies for the countries included in the sample could distort the presented econometric results if the null hypothesis about similarity of public policies is not the right one. Footnotes 1 For a similar model using Ramsey optimization analysis in an endogenous growth model, see Futagami, Morita, and Shibata [1993]. Other relevant studies can be found in Diamond [1989]; Engen and Skinner [1992]; Evans and Karras [1995]; Cashin [1995]. For a development of this model, see Escot and Galindo [1999]. 2 The source of the three Þrst variables is Summers and Heston Penn World Tables and in the case of the Income GIN I index, it is Deininger and Squire [1996].

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