Division of Economics
AJ Palumbo School of Business Administration
Duquesne University
Pittsburgh, Pennsylvania
IS THE INFLUENCE OF GOVERNMENT SIZE ON SOCIAL WELFARE DIFFERENT AMONG LESSER DEVELOPED, DEVELOPING AND MORE DEVELOPED NATIONS? AN ECONOMIC PANEL ANALYSIS
James Vogelgesang
Submitted to the Economics Faculty
in partial fulfillment of the requirements for the degree of
Bachelor of Science in Business Administration
December 2008
Faculty Advisor Signature Page
Matthew Marlin, Ph.D. Date
Professor of Economics
IS THE INFLUENCE OF GOVERNMENT SIZE ON SOCIAL WELFARE DIFFERENT AMONG LESSER DEVELOPED, DEVELOPING AND MORE DEVELOPED NATIONS? AN ECONOMIC PANEL ANALYSIS
James Vogelgesang, BSBA
Duquesne University, 2008
Abstract
Previous research has examined the relationship between the size of a country’s government and its GDP growth. In this paper, I conduct an analysis modeling the impact of a government’s size against several social welfare indices. The regression will be empirically analyzed using generalized method of moments with two staged least squares in a panel data framework. I hypothesize that higher levels of social welfare occur with a larger government in lesser developed nations compared to developing or developed nations.
The results of this analysis find that the impact of government size varies significantly for lesser developed, developing, and developed nations. Evidence shows that as a country becomes more developed, the presence of a larger government decreases the level of social welfare.
Table of Contents
I. / Introduction……………………………………………………………………...... / 5II. / Literature Review……………………………………………………………………. / 5
III. / Methodology……………………………………………………………………...... / 13
IV. / Results …………….………………………………………………………………… / 19
V. / Analysis of Impact on Human Development Index…………………………………. / 21
VI. / Analysis of Impact on Social Welfare Function…………………………………….. / 25
VII. / Economic Implications………………………………………………………...... / 29
VIII. / Suggestion for further research………………………………………………...... / 30
IX. / Conclusion………………..…...…………………………………………………….. / 31
X. / References……………………………………………………………………...... / 32
XI. / Appendix…………………….………………………………………………...... / 35
I. Introduction
Beyond economic status, social welfare research has become increasingly popular as a method of determining the well-being of individuals in a given country. The need for an appropriate measure of social welfare has brought much debate and different perspectives. The most commonly cited measurement for government size is government expenditure as a percentage of GDP. This has been used to determine its impact on economic growth while neglecting to take into account how it affects a country’s social welfare. This paper will analyze it’s affect on the country’s social welfare.
This paper is an empirical analysis of the effect of the size of government on social welfare for lesser developed, developing and developed nations. Using two separate measurements of social welfare, the Human Development Index (HDI) and a Social Welfare Function (SWF) developed by Amartya Sen, I will compare the effects of government size on countries with different levels of development. I expect that increases in government size will influence a country’s social welfare differently depending on their level of development. I hypothesize that a lesser developed nation will require a greater amount of government to maximize their social welfare while a larger government in developed nations will have a negative impact on social welfare based on findings of Yavas (1998) and Hetger (2001).
II. Literature Review
a. Size of Government
Previous research into the optimal size of government falls somewhere on the spectrum from Keynesian models, which states that increases in government spending will increase aggregate demand and lead to economic growth, to Neoclassical models, that claim that increases in government spending lead to decreases in economic growth.
Ram (1986) uses a cross sectional analysis of 115 countries over the period of 1960-1980. To measure government size on economic growth Ram uses OLS regressions to test the effect of government size on economic growth[1]. From his results, Ram argues that, for most countries, larger governments are associated with increased economic growth in both the 1960s and the 1970s. Along with a positive effect on growth, Ram finds that governments become more productive. Although countries of every level of development show economic growth, evidence for increased growth with greater government size is strongest for lesser-developed countries. Yuk (2005) finds similar results for the United Kingdom in the years 1830-1993. He finds structural breaks in the data, which he then divides into four separate subgroups[2]. These groups allow Yuk to examine government size on growth to observe separate periods and test for cointegration across time. Yuk finds that government size Granger-causes growth for all three of the four subgroups. The subgroup of 1830-1867 only shows causality for increased government spending resulting in increased GDP.
Loizides and Vamvoukas (2005) take the relationship between government size and growth a step further by testing for correlation as well as Granger-causality. The study uses data on economies for the UK, Greece, and Ireland. They define the UK as a developed nation and consider Greece and Ireland to be developing nations. Their study examines the three countries from the years 1950-1990 using bivariate and trivariate models. The analysis, uses government expenditure as a percent of GNP as a proxy for size, and find that an increase in government size results in an increase of real GNP per capita for all three countries. They also conclude, for all three countries, that an increase in real GNP per capita results in an increase in the size of government. The results of these studies are consistent with the Keynesian theory.
In contrast Barro (1991) examines economic growth in a cross sectional study of 98 countries for the years 1960-1985. He finds a negative relationship between government consumption expenditure and per capita growth in GDP. This study shows that countries with higher human capital, measured in GDP per capita, experience higher investment in GDP. Maddison (1987) finds similar results in an analysis that looks at six developed countries from 1913-1984. He uses separate OLS regressions for each country and theorizes that increased government spending is used to improve the quality of life within these countries and is a significant contributor to the decrease in GDP growth.
Landau (1985) performs an OLS cross sectional analysis of 65 countries to test the effects of government consumption, education, investment, financial capital, military, and transfer payments on countries’ growths in per-capita RGDP. Landau’s results show that all five government expenditures cause negative growth. He also finds that private investment has a significant positive impact on growth in per capita GDP while all measures of public expenditure result in decreased per capita GDP growth. Landau states that for less developed countries, government support used to help the private sector was only beneficial if it promotes economic growth and does not protect it from competition.
Saxton (1998) expands on the Neoclassic model through his use of the Armey Curve in the United States[3]. Saxton’s use of the Armey Curve predicts that a country with low per capita output will increase its per capita output with government input. As the country continues to develop, the need for government input decreases and at a certain point begins to decrease output per capita. Saxton estimates the maximum size for the US government from the years 1801-1996 to be 13.42%. From his findings he points out that when government output increased to 16.28% in 1956, the United States experienced a decade of slower growth. Although the United States is a developed nation, one can make the argument within the period of the data set that the United States was at one point considered a developing nation and experienced diminishing returns from the government output.
Recent research has discovered that government size affects countries economic growth differently based on their level of development. Yavas (1998) models the effects countries in a steady-state output level to changes in government size. His findings show that countries with a low-steady state that increasing government size increases the steady-state level[4]. Conversely, those countries with a high steady-state will have a lower steady-state with increased government[5]. Yavas points out several shortcomings in the modeling done by Ram and Landau and believes that his adjustments allow for a better interpretation of the effects of government size.
In another study of the effects of government size on economic growth Heitger (2001) hypothesizes that increased government spending will allow for the building of the private sector in lesser developed nations while increased government spending in a developed nation will crowd out private sector investment. He confirms his hypothesis by using a 21-country panel study of European nations from 1960-2000. Heitger concludes that countries, which are under-producing, will have increased growth with greater government-provision of public goods provided; while more developed nations will have decreased growth with high government expenditure. Heitger also subdivides expenditure to examine investment expenditure alone. This reveals different effects on growth, but overall still negative. According to Heitger, the decrease in growth occurred due to increased taxes that took money away from private investment and resulted in an overproduction of public goods.
The reasoning given by Heitger follows the logic that Joseph Stiglitz notes for lesser developed nations. Stiglitz (2002) argues that lesser developed countries forced to sell off their public sector caused their failing economies. He states that these countries’ private sectors do not have capable financial systems and that without the protection and guidance of the government, their private sector will fail. Decreasing the public sector works for developed nations with a mature and stable private sector, but it has been proven fatal for lesser developed economies.
While debates on what size of government enable economic growth in a country to continue, it must be noted that policy makers alone do not make this decision. Voters in a democratic society elect officials who determine the tax rates and spending by the government. Voters choose officials based on policies that they believe will benefit themselves. Meltzer and Richards (1981) argue that the upper or lower classes do not decide the income redistribution by the government, but the middle class does, and over time, the size of government has increased because of their decisive votes. In a democratic society, a person’s vote is his or her idea on what size government will maximize his or her own social welfare.
While most studies on government size measure its effects on government growth, very few studies have looked at government size’s influence on social welfare. Davies (2008) discusses the differences in the effects of increased GDP compared to increased HDI. He argues that countries with higher levels of GDP do not necessarily have higher levels of HDI, and that the criterion for a good government is to maximize the social welfare of the individuals in that country. Davies concludes that there is a relationship between government size and social welfare.
b. Social Welfare
The study of social welfare indicators began in the mid-1960s when Raymond Bauer originally investigated this topic. He defined social welfare indicators as “statistics, statistical series, and all other forms of evidence that enable us to assess where we stand and are going with respect to our values and goals.” The United Nations later stated that:
Social indicators can be defined as statistics that usefully reflect important social conditions and facilitate the process of assessing those conditions and their evolution. Social indicators are used to identify social problems that require action, to develop priorities and goals for action and spending to assess the effectiveness of programmers and policies.
It is difficult to determine what actually determines a good “quality of life.” Many studies find that measures for subjective quality of life, where measurements experienced at the individual level, are the best indicators (Noll 2004).
Bjornskov (2003) does a cross sectional analysis to determine the factors influencing life satisfaction across various countries. Data for life satisfaction is gathered from World Value’s Survey and tested on 32 countries across Europe. The purpose of his analysis is to determine the effectiveness of social capital on life satisfaction. [6] Bjornskov concludes that high levels of life satisfaction result from decreased levels of income, and those countries with the highest level of social capital have higher levels of life satisfaction. He also states that the countries with the highest level of social capital are not the countries with the greatest level of GDP.
Using the same indicator of social welfare, The World Value’s Survey, Bjornskov, Dreher and Fischer (2006) create a cross sectional analysis of 70 countries using over 90,000 observations to find the best indicators of social welfare by conducting robustness tests. Their robustness tests indicate how well an independent variable predicts the dependent variable. They find that variables showing a person’s ability to move up in status are important, while indicators such as GDP per capita, by itself, do not pass their robustness test for being a good indicator.
Stroup (2006) tests the relationship between economic freedom and social welfare is examined. For the measurement of social welfare, Stroup individually uses life expectancy, mortality rates, literacy rates, grades, water availability, and shot availability. As a result, Stroup argues that it is beneficial for a country to increase its level of economic freedom or decrease government intervention to increase a country’s social welfare. He also concludes that market forces and the private sector allow for the best allocation of goods that help improve social welfare.
Wickrama and Mulford (1996) take into account the level of political democracy in a country and test its impact on a country’s well being. They test this using a cross-sectional analysis in 82 countries, excluding oil-exporting economies. To measure social welfare, Wickrama and Mulford use the Human Development Index because of its inclusion of life expectancy, adult literacy, and purchasing power. They find that social welfare is determined not only by economic growth, but also by the level of democracy. These findings expand on Richards (1998) study, stating that by increasing the voters ability to choose there will be an increase in social welfare.
Previous literature looks at the use of GDP per capita or income as a measurement of social welfare. Welsch (2006) argues that by only observing income you cannot determine the level of happiness in a country. Although income may be a good supporting variable to determining the quality of life, it cannot be the only indicator. He argues that variables such as air pollution, which can be controlled by government regulations, are better determinants of one’s social welfare. Welsch gives the example that when air pollution increases, it subjects people to higher health risks and lower life expectancy. His findings show that indicators that affect people are better at explaining social welfare than measurements such as income.