Do States Optimally Set Tax Rates? the Portfolio Approach vs. the Tax Smoothing Hypothesis (2004)

ABSTRACT There are two strands of literature addressing optimal taxation. One, using a portfolio approach, assesses to what degree a tax system balances tradeoffs between revenue growth and stability. The second strand of literature of optimal tax theory, the tax smoothing hypothesis (TSH), claims that changes in tax rates should be unpredictable in order to minimize the excess burden of the tax. This paper considers both theories to determine if there is any overlap of the requirements for optimization. For example, are states with a tax portfolio offering high revenue growth and stability also able to smooth tax rates? Results show there appears to be little connection between the two conditions for optimal taxation. INTRODUCTION There are two strands of literature addressing optimal taxation. One, using a portfolio approach, assesses to what degree a tax system balances tradeoffs between revenue growth and stability. (1) (White, 1983; Harmon & Mallick, 1994; Gentry & Ladd, 1994; Braun & Otsuka, 1998). This approach examines how a state's mix of revenue sources (sales, property, income and other tax types) situates the state along a tax efficiency frontier. In general, a tax portfolio that provides both high revenue growth and low variability is deemed an optimal combination. The second strand of literature of optimal tax theory, the tax smoothing hypothesis (TSH), claims that changes in tax rates should be unpredictable in order to minimize the excess burden of the tax. This approach does not consider revenue sources or a tax efficiency frontier. Instead, a basic level of this research has examined the stationarity of tax rates (Barro, 1979; Sahasakul, 1986; Strazicich, 1996; Strazicich, 1997; Dole, 2000) at the state and federal levels. Extending the basic assumptions of the TSH, optimal taxation has also been tested using the relationship between changes in government spending, tax rates and budget balances. (Ghosh, 1995; Olekalns, 1997; Cashin, et al, 1998). This paper considers both theories to determine if there is any overlap of the requirements for optimization. For example, are states with a tax portfolio offering high revenue growth and stability also able to smooth tax rates? Or does the desire for high revenue growth and stability hamper a state's ability to vary tax rates unpredictably? We use state-level data from 1966 through 1999. After computing revenue growth rates and variability, the states are grouped into quadrants based across spectrums of high to low growth and high to low variability. To examine the relationship between these groups (which account for the portfolio approach's standards) and the TSH requirements, we use an extension of the TSH suggested by Ghosh (1995) and Olekalns (1997). Results show that only two states are smoothing according to the TSH and that only one falls into high revenue-low variability quadrant as proposed by the portfolio approach. That is, there appears too little connection between the two conditions for optimal taxation. The remainder of the paper is organized as follows: a review of the two optimal taxation theories, a description of the data, regression analysis, and a summary. THE PORTFOLIO APPROACH The portfolio approach to taxation follows from finance literature and was adapted initially by White (1983). This approach constructs a tax efficiency frontier that shows the tradeoff between revenue growth and predictability (or stability) for a state's tax structure. States' tax structures are then compared to this frontier to determine how close their portfolio of taxes (income, sales, property, etc.) is to the optimal frontier (Harmon and Mallick, 1994; Gentry and Ladd, 1994, Braun and Otsuka, 1998). A shortcoming of this line of research is that most of it examines a state's portfolio for only one year; there is no time series approach investigating how this portfolio behaves over time. …