Economic development continues to be a major objective of state governments. Some states appear to be much more successful than others are at achieving it. For example, as can be seen in Table1, economic growth among Southern states differed widely during the 1980s. Texas and West Virginia had very slow growth, while Florida, Georgia, and Virginia achieved extremely high growth rates. However, Louisiana and Oklahoma experienced economic declines during the decade.
Governors from across the political spectrum are searching for ways to reduce tax burdens and improve education in order to enhance their state's economic growth. At the same time, due to the need to be globally competitive, firms are seeking places with low-cost labor. What role do taxes, education, and wage rates play in determining the ability of a state to increase the growth of its economy?
This study examines the economic competitiveness of the economies of the Southern United States by using Gross State Product (GSP) data from 1982 through 1989 (as reported in the Survey of Current Business). In it, factors affecting the competitiveness of each of these states are empirically tested for their significance.
In order to determine the competitive position of each state, shift-share analysis is employed. Shift-share analysis enables the researcher to isolate the competitive position of a state from the impact on it of national trends and the industrial mix of GSP that existed in the state at the beginning of the time period being studied. To account for changes in the industrial mix during this period, dynamic shift-share analysis is applied. [Barff and Knight,1988] Once the competitive positions of the states are found, factors which help determine them are considered.
Shift-share analysis is used to analyze the composition of the growth of the Southern United States in the 1980s. This technique makes it possible to separate growth into three components: national growth, industrial structure, and regional competition. [Niemi, 1985]
The national growth component, N, measures the increase in GSP that will occur if all the industries in the state grew at the same rate as GDP. Shown below is the equation that represents this effect:
(1)N = S [Ny * Ri] where
Ny represents the growth rate of GDP during the period;
Ri represents the percentage of GSP originating in
The industrial structure effect, I, accounts for the impact of the state's industrial composition. A state with a high concentration of high growth industries will have a positive industrial structure effect; a state with a high concentration of low growth industries will have a negative industrial effect. The industrial structure effect is represented by the equation below:
(2)I = S [Ri * (Ni - Ny)] where
Ni represents the national growth rate of industry i.
The regional competition effect, COM, measures the difference between state and national industrial growth rates. A positive competitive position implies that, after accounting for national growth trends and the industrial mix of the respective state, the state's economic performance is superior to the average state. It can be represented as follows:
(3)COM = S [Ri * (Si - Ni)] where
Si represents the state growth rate of industry i.
By combining (1), (2) and (3), the joint impact on these states' GSP of national growth, these states' industrial structure, and regional competition can be explained. The following equation illustrates the procedure:
(4) Growth rate in GSP = S [Ny * Ri] + S [Ri * (Ni - Ny)] + S [Ri * (Si - Ni)]
In order to account for continuous changes in the industrial mix of the region, this technique was applied annually to the data during the time period under study and then summed to determine the dynamic effect over the entire period. [Barff and Knight, 1988]
The results shown in Table1 indicate that the industrial structure of the region had a positive effect in seven states, though it was quite small in Florida and Maryland (3.9 percent and 4.3 percent, respectively). It was a detriment to economic growth in nine states with Louisiana, Oklahoma, West Virginia, and Texas exhibiting particularly negative effects. Although these states benefitted from the mining boom of the 1970s, they suffered from the major decline of mining which took place in the 1980s. Recognizing this problem, diversification of industry has been a goal of these states' governments so that they can achieve more stable economic growth. Energy-related employment as a percent of overall employment in these states has declined by approximately fifty percent since the early 1980s .[Brown and Yucel, 1995]
Half of the states had positive regional competition effects, which indicates superior economic performance. Five of these states (Florida, Georgia, North Carolina, South Carolina, and Virginia) achieved in excess of twelve percent. Arkansas, Kentucky, Louisiana, Mississippi, Missouri, Oklahoma, West Virginia, and Texas had negative regional competition effects, with Louisiana and Oklahoma experiencing negative effects in excess of thirty percent.
After determining the competitive position of each state (COM), the question arises: why are some states competitive, while others are not? Many studies have analyzed local economic development, but, thus far, there has been little consensus about the relevance of specific factors in explaining relative economic performance.
Most studies have considered the effects of taxes, wages, and education. Traditionally, state and local taxes were thought to play a minor to insignificant role. [Due 1961, Carlton 1979, Schmenner 1982, and Wheat 1986.] However, more recent studies indicate that state and local taxes do have a significant negative effect. [Bartik, 1991 and Munnell, 1990] Although the literature cited suggests many alternatives, a common measure of taxes used is state and local tax revenue per capita. [Place, 1986.]
Both economic theory and past studies [Munnell 1990, Bauer and Cromwell 1989, and Carlton 1979] suggest that wages have a significant effect on business activity and growth. Higher labor costs are likely to reduce the rate of employment growth. Several measures of labor costs have been used in previous studies, including those cited above. Chosen as the measure for this study was the average annual wage in a state.
Many believe that human capital also enhances a region's ability to grow, but a recent study [Duffy, 1994] indicates that it plays a marginal role at best. Used to measure human capital in this study is the percent of college graduates in a state. Some studies have attempted to incorporate a state's provision of public goods. However, much difficulty has arisen about how public services should be measured, and the results concerning their impact are mixed.
Typically, the amount of state funds spent on education or infrastructure is used as a proxy for public goods, but no common approach has been adopted. According to Bartik , "Studies use a wide variety of arbitrary definitions of public service quantities, so the exact magnitude of effects on state and local growth is difficult to calculate for most studies, and even more difficult to compare across studies." (See End Note.)
A cross-sectional model of the sixteen states under study was estimated with the competitive position of each of the states being the dependent variable and taxes, wages, and education being the independent variables. To measure the tax burden, per capita state and local revenue, excluding that received from severance taxes, was used.
Severance taxes, particularly taxes on the extraction of resources, are prevalent in states with large oil and mining sectors and, thus, may serve as a proxy for those states. In addition, the burden of such taxes tends not to be borne by the states themselves, but are exported.
Taxes were expected to have a negative effect on competitiveness. Wages (average annual wage by state) were expected to have a negative impact, while education (percent of college graduates) was expected to have a positive impact.
In accordance with previous studies, data for the independent variables were from 1982, the beginning of the period studied. [Niemi 1985, Duffy 1994] This is proper because the long-run factors affecting economic competitiveness are considered. As such, values of the factors at the beginning of the period are appropriate. All the necessary data were obtained from the U.S. Statistical Abstract. The model was estimated using OLS on the sixteen states studied with the following results:
COM = 94.54 - 0.009 WAGE - 0.02 TAX + 2.38 COL
(WAGE=2.73) (TAX=0.10) (COL=3.06)
adjusted R-squared = 0.53; F = 6.73
where the t-statistics are in parentheses. The coefficient on COL was positive and significant at the 1 percent level, while the coefficient on WAGE was negative and significant at the one percent level (Note: similar, though slightly weaker, results were obtained using high school graduates; the coefficient was slightly lower and significant at the five percent level). Although the coefficient on TAX was negative, it was not statistically significant.
An F-statistic of 6.73 indicates the equation was significant at the one percent level. The adjusted R-squared of 0.53 is unexpectedly high given that the competitive position is similar to a residual effect in that two major determinants of state employment growth - national growth and industrial structure - were already taken into account.
Finally, education and wages were found to have significant impacts in explaining state competitiveness; the former positive and the latter negative. Wages having a negative effect is in accordance with the literature cited earlier. The significance of education differs from that found by Duffy . However, in his study, he examined employment, while this study considers growth in GSP. Education is likely to have a larger effect on value-added, and hence economic growth, than on employment.
Taxes were found to have a statistically insignificant effect on competitiveness. Literature on the effect of taxes has been inconclusive. Previous studies have yielded different results. The insignificance of taxes in this study may be explained by the minimal differences in tax burden in the states included in the study. In a national study which included higher tax states from outside the South, taxes might play a more significant role.
The conclusions this study produced would be strengthened if like analyses of other time periods, other regions of the country, or of a larger sample size produce the same results.
Bartik, Timothy J. Who Benefits from State and Local Economic Development Policies? Kalamazoo, Michigan: W.E. Upjohn Institute for Employment Research, 1991.
Bauer, Paul W. and Brian A. Cromwell. "The Effect of Bank Structure and Profitability on Firm Openings." Economic Review 25.4 (1989): 29-39.
Brown, Stephen P. A. and Mine K. Yucel. "The Energy Industry: Past, Present and Future." The Southwest Economy 4 (1995): 1-5.
Carlton, Dennis W. "Why Do New Firms Locate Where They Do: An Econometric Model." in Interregional Movements and Regional Growth. ed. William C. Wheaton. Washington, D.C.: The Urban Institute, 1979.
Due, John F. "Studies of State-Local Tax Influence on Location of Industry." National Tax Journal 14.2 (June 1961): 163-173.
Duffy, Neal E. "Determinants of State Manufacturing Growth." Journal of Regional Science 34.2 (May 1994): 137-162.
Munnell, Alicia H. "How Does Public Infrastructure Affect Regional Economic Performance?" New England Economic Review (September/October 1990): 11-33.
Place, Frank. "The Relationship of State and Local Government Spending and Taxing to Economic Performance: An Econometric Analysis of the States from 1972 to 1984." Wisconsin Department of Development, Division of Policy Development. Bureau of Research Report No. RP-86-7, September 1986.
Niemi, Albert W. "Gross State Product and Comparative Economic Growth in the Southeast, 1950-80." Review of Business and Economic Research 20 (Spring 1985).
Schmenner, Roger. Making Business Location Decisions. Englewood Cliffs. New Jersey: Prentice Hall, 1982.
Trott, Edward A., Ann E. Dunbar, and Howard L. Friedenberg. "Gross State Product by Industry, 1977-89." Survey of Current Business 71. Commerce Department, December 1991.
U.S. Department of Commerce, Statistical Abstract of the United States, 1984-1985.
Wheat, Leonard F. "The Determinants of 1963-77 Regional Manufacturing Growth: Why the South and West Grow" Journal of Regional Science 26.4 (November 1986): 635-659.