Elsevier

Economics Letters

Volume 116, Issue 2, August 2012, Pages 161-165
Economics Letters

Tax policy and state economic growth: The long-run and short-run of it

https://doi.org/10.1016/j.econlet.2012.02.023Get rights and content

Abstract

This paper uses a pooled mean group (PMG) estimator to evaluate the effects of tax policy on state-level growth. We find that property and sales tax rates have negative effects on long-run income growth, while income tax rates have no impact.

Highlights

► This paper examines the impact of different taxes on state economic growth. ► We use data from 48 states in the US from 1968–2008. ► We use the pooled mean group to estimate short-run and long-run coefficients. ► The results indicates that sales and property taxes have a long-run effect on growth.

Introduction

In the past year, several state governments have raised state tax rates in order to close budget shortfalls. For instance, Illinois raised its personal income tax rate from 3% to 5% and its corporate income tax rate from 7.3% to 9.5%, while keeping sales tax rates the same. On the other hand, Arizona and Kansas each raised their sales tax rate by 1% to 6.6% and 6.3%, respectively. At the same time, Oregon imposed a temporary upper corporate tax bracket of 7.9% for income over $250,000, while Massachusetts lowered its corporate tax rate from 9.5% to 8.2%. What will be the long-run growth implications of each of these tax hikes?

The regional tax and growth literature has adopted three econometric strategies to answer this question. The first strategy is to apply static panel estimators like fixed effects (FE) and random effects (RE) on annual data. Helms (1985), Carroll and Wasylenko (1994) and Miller and Russek (1997) find that property, income and even sales taxes, especially when funding “non-productive” spending, decrease income and employment growth. Although unobserved heterogeneity can be controlled by FE and RE, the panel estimators cannot make distinctions between short-run dynamics and long-run equilibrium relationships. The second strategy is to estimate longer-run cross-sectional data using least squares. Wasylenko and McGuire (1985) and Yamarik (2000) show that personal income tax rates decrease long-run state employment and per capita income growth. However, the cross-sectional method fails to recognize the short-run dynamic paths that the individual economies may take to their long-run equilibrium. The third strategy is to apply an error-correction (EC) model which allows for separate short-run and long-run coefficient estimates. Harden and Hoyt (2003) find evidence that corporate income tax rates reduce long-run state employment growth, while Reed (2008) finds that the overall tax burden reduces long-run state income growth. However, the EC model assumes that each state follows the same short-run adjustment, which seems unlikely given geographical, political and other institutional differences in state-level markets. In particular, differences in internal market size, access to outside markets, labor mobility, zoning, environmental and other regulation; will generate heterogeneous short-run responses to fiscal shocks.

In this paper, we use the pooled mean group (PMG) to determine the short-run and long-run effects of tax policy on state-level economic growth. Using a panel error-correction framework, PMG estimates a common long-run relationship, but allows the short-run coefficients (including the error-correction term and the constant) to differ across states. A common long-run equilibrium across states is likely given factor mobility and access to common technology. At the same time, state-specific geography and institutional differences are likely to introduce heterogeneity in the short-run dynamic paths to the common long-run equilibrium.

The remainder of the paper proceeds as follows. Section 2 describes our econometric methodology and empirical design. Section 3 provides the estimation results. Concluding remarks are presented in Section 4.

Section snippets

Econometric methodology and data

The error-correction (EC) model is often used to examine the short-run dynamic adjustment of cointegrated series to some common long-run equilibrium (Engle and Granger, 1987). Pesaran and Smith (1995) and Pesaran et al. (1999) have developed a panel EC methodology to produce consistent and efficient estimates of long-run parameters for both stationary and integrated variables.1

Results

Table 2 presents the baseline results using total tax burden (tax revenues/personal income) as the tax variable. We choose a ARDL(2, 1) structure in (3) given our limited 40-year time horizon.3 We present the pooled mean group (PMG) results in column 1, the mean group (MG) results in column

Conclusion

This paper used a pooled mean group estimator to estimate the short-run and long-run impacts of state and local tax policy on state-level economic growth. By allowing the short-run dynamics to vary across states, the PMG methodology produced consistent and fairly robust estimates of the long-run structural relationship. The results found that property taxes lowered both short-run and long-run economic growth, sales taxes lowered long-run growth, while income taxes had no short-run or long-run

Acknowledgments

We would like to thank William Blankenau, Tom Downes, Gib Metcalf, Mark Strazicich and seminar participants at the Midwest Economic Association, Regional Science Association International and the National Tax Association meetings for all their help and suggestions. All remaining errors are, of course, our own.

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