The effect of state corporate income tax rate cuts on job creation.
Business Economics (2013) 48, 183-193.
Keywords: state tax rates; corporate taxes; job creation; employment; state budgets
One of the most far-reaching consequences of the "great recession" of 2008 and 2009 was the massive job loss and the subsequent slow recovery. Since the recession started in December 2007, the U.S. economy shed over 8.7 million jobs by February 2010. Job losses continued after the recession officially ended in June 2009. Almost four years after the recession, national employment has increased by only 6.2 million through April 2013, still 2.5 million short of its pre-recession peak [Bureau of Labor Statistics 2013].
The sluggish job growth has led to stubbornly high unemployment. In October 2009, the national unemployment rate reached 10.0 percent [Bureau of Labor Statistics 2013]. Although the labor market has been growing sporadically since the recession ended, the unemployment rate remained at an elevated level of 7.5 percent in April 2013 [Bureau of Labor Statistics 2013]. This is significantly higher than the 5-6 percent unemployment rates in 2006 and 2007 before the recession began. Many economists predict job creation will remain weak for the next two years with unemployment staying over 7 percent until 2014 [Federal Reserve Bank of Philadelphia 20131.
Given this environment, it is not surprising that many state and local governments around the country, such as California, Virginia, and Wisconsin [Brian 2010; Bauer 2010], have made job creation and economic development their first priorities. Of the various state policy tools directly affecting business, one option is to cut state corporate taxes to stimulate job creation. Although such a change in policy may seem ill-advised when most state governments are saddled with budget shortfalls, it is possible that a cut in corporate income tax may stimulate economic growth enough to offset the lost tax revenues. This, plus other arguments for job creation, argues for taking action despite the slow economic recovery.
Although the debate over the interaction between tax cuts and economic growth is not new, many of the past discussions focused on federal taxes [Romer and Romer 2010]. This paper examines whether a cut in state corporate tax rate can affect employment growth at the state level. We choose the state corporate tax rate because it is a policy tool states can directly influence; and a large majority of states have corporate taxes, thus ensuring a wide application of the study results. The results of this study should be useful for policymakers, policy analysts, and government economists, as they are often tasked to evaluate the effects of potential policy changes, with tax policy being one of the most fundamental fiscal policies for the federal as well as state government.
In this paper, we evaluate the effect of tax cuts through two approaches. The first approach is a direct comparison. Data are collected on state corporate income tax rates and employment for the past 23 years. For states that lowered their corporate income tax rates during that period, we compare their job creation performance with states whose tax rates were not changed. The second is an econometric approach where we establish a fixed-effect panel model to quantify the impacts, if any, of a tax cut on job growth as well as the timing of the effect of a tax-cut action.
The next section provides a brief review of the studies related to the research question, followed by a description of the current status of state corporate income taxes in the nation. Section 3 compares the job growth of tax cutting states and those without changes, whereas Section 4 quantifies the results between a tax cut and employment growth through a fixed-effect panel model. Section 5 summarizes our conclusions.
1. Brief Literature Review
General economic theory on profit maximization indicates that firms seek to maximize profits and minimize costs. In those models, high taxes act as additional costs to reduce a firm's profitability and its ability to invest and hire more workers [Wu 2010].
At the federal level, Romer and Romer  used national time-series data to perform an exhaustive analysis on federal corporate taxes. They provided evidence that federal tax increases had "a large, rapid, and highly statistically significant negative effect on output." In their study, output was measured as gross domestic product (GDP). The study also found that higher federal taxes increased the unemployment rate in the nation.
There is a plethora of empirical studies on the effects of state and local taxes on regional economic activities, such as income growth, a firm's location choice and establishment growth, capital investment, foreign investment, and employment. However, the empirical results of state corporate tax rates on economic activities are not conclusive [Deller and Stallmann 2007].
Early studies on state taxes and economic growth were summarized in a comprehensive review of literature conducted by Battik . Using a modified Delphi method summarizing dozens of studies conducted since 1979, Bartik concluded "that taxes have quite large and significant effects on [economic] activity," such as employment, output, business capital stocks, and number of business establishments. Of the 57 interregional studies reviewed. 70 percent reported at least one statistically significant negative effect of taxes on one or more measures of economic activity. More specifically, Barak  summarized that state and local business taxes (including business property tax and corporate income tax) had a negative impact on local business activities, with the average elasticity of business activities with respect to state and local taxes being-0.3, ranging between 0.1 and-0.6.
A few years later, Wasylenko , in a second review of the literature on the link between taxation and economic growth, pointed out that even though Bartik's review identified negative effects of state and local taxes on economic activities, the magnitudes of the effects varied widely. The tax effect depends on the source of data and economic variables used--employment, income, investment, or firm locations. In terms of the effect of business taxes on employment, two of the three studies included in the review indicated a negative and significant effect of business taxes. Wasylenko found that over time, tax differences between states have become less important in employment growth, perhaps because states have adopted similar tax systems.
Debates over the effect of state and local taxes continued. Since then, a study by Pjesky  raised questions on the robustness of the effect of state and local taxes. Pjesky  attempted to replicate and expand on what he identified as five "influential" studies on the roles of state and local taxes in regional economic performance. Through the replication effort, Pjesky  concluded that the estimated tax effects in those studies were sensitive to model specification and the time periods examined. As a result, it is not prudent to make any definitive statements about the relationship between state and local taxes and regional economic activity, as taxes can have both positive and negative effects on economic activities.
More recently, Reed  attempted to resolve the conflicting results from the existing literature and provided a robustness test on the relationship between state and local taxes and personal income growth as the indicator of regional economic growth. This study tested the robust relationship between state tax and personal income by varying different control variables, different estimation methods, as well as data structures (annual data vs. five-year data interval), and time period. This study used per capita personal income as the dependent variable, and tax burden (total state and local taxes as a percentage of personal income) as the key independent variable. He found that state and local taxes used to fund general expenditures are associated with significant, negative effects on per capita income growth. This finding is generally robust across alternative control variable specifications, alternative estimation procedures, and different time periods. Although this study is illuminating on the effect of state and local income taxes on per capita income and the approach to achieve a robust estimate, it did not address the issue of the effect of state corporate taxes on job creation.
The above review of the literature suggests that the effects of state and local taxation on economic activities vary and it depends on the types of state taxes and economic activities. Studies should choose carefully the economic indicators and tax types. As Wasylenko  pointed out, "job growth is still the variable politicians identify most often with prosperity." Under the current economic environment of inept job creation, we chose employment as the dependent variable in our study. We also choose the corporate income tax because that is the most important business-related tax for states when they try to attract business and improve their business climate. The remainder of this literature review summarizes studies that are narrowly focused on state corporate income taxes and/or state employment growth.
Even with a narrowed focus, the literature remains inconclusive on state corporate taxes and job creation. Goss and Phillips  found that state personal income taxes had a negative and significant impact on state-level employment growth from 1982 to 1992 but corporate taxes had little effect. Carroll and Wasylenko  implemented a switching regression model to analyze a set of state and local tax variables on state-level employment from 1967 to 1988. They found that corporate income tax had little effect on nonfarm employment for both the 1970s and 1980s. But the same tax had a negative effect on manufacturing employment in the 1970s but not the 1980s.
The conflicting literature justifies another look at how state corporate income tax can affect job creation. Our study contributes to the literature in the following three aspects. Firstly, it evaluates the effect of state corporate income tax rates on employment growth directly, rather than other variables that have been explored such as per capita income, business establishment, and capital investment. In addition, our study focuses not only on the level of the tax rate, but also on whether the action of a cut in the state corporate income tax rate can benefit job creation. Thirdly, using the most up-to-date employment and tax data, our study covers the period of the most recent recession and subsequent slow recovery.
2. State Corporate Income Taxes, 1990-2012
State corporate income taxes are based on business profits. They emerged in the first half of the twentieth century. By 1930, 23 states adopted corporate income taxes, and the number reached 40 states 10 years later [Felix 2009]. As of 2012, Nevada, Wyoming, Texas, Ohio, South Dakota, and Washington are the only states that do not tax corporate income. Thirty-one states have flat tax rates, whereas the remaining 14 have a progressive tax structure where multiple tax rates are applied depending on the size of the corporate income [The Tax Foundation 2013]. Calculated with U.S. Census Bureau data, Felix  found that the importance of corporate income taxes on overall state revenues has been declining since the 1980s, from a national average peak of 10 percent in the 1980s to about 7 percent in 2007. The declining importance of the state corporate income tax is because of multiple reasons, including states cutting tax rates, offering tax breaks to corporations in competing for businesses, and corporations' aggressive tax avoidance strategies [Fox and Luna 2002].
The levels and structures of state corporate taxes are evolving continuously. In the past 23 years, dozens of states made changes to their corporate income taxes in response to changing political or fiscal environments. Tax increases are often proposed when governments are facing a budget shortfall. The political climate also affects the evolution of state corporate taxes. For instance, Republicans often favor lower taxes. Consequently, when they are in power, they tend to cut tax rates.
Table 1 identifies the changes in state corporate income taxes from 1990 to 2012 based on data compiled by The Tax Foundation . All states (including the District of Columbia) are classified into four groups. From 1990 to 2012, 21 states did not make any changes to their corporate taxes. They are classified as "no change" or control states. It is with this group of states that the employment growth of the tax-cutting states is compared in the first stage of the analysis. As Figure 1 shows, the average corporate tax rate of the no-change states was constant at 5.3 percent from 1990 to 2012.
Table 1. State Corporate Income Tax Changes (1990-2012) Tax-Cutting No Tax-Increasing Other States Stales Change/Control States States Arizona Alaska Alabama Arkansas California Delaware Illinois Connecticut Colorado Georgia Indiana District of Columbia Idaho Hawaii Maryland Florida New York. Iowa Missouri Kansas North Louisiana Nebraska Kentucky Dakota West Maine Tennessee Massachusetts Virginia Minnesota Michigan Mississippi New Hampshire Montana New Jersey Nevada North Carolina New Mexico Ohio Oklahoma Oregon Rhode Island Pennsylvania South Carolina Texas South Dakota Vermont Utah Virginia Washington Wisconsin Wyoming Source: The Tax Foundation.
The seven states from 1990 to 2012 that consistently reduced their corporate tax rates are classified as tax-cutting states. Some of the tax cuts are small. For example, Colorado lowered its corporate income tax rate from 4.75 to 4.63 percent in 2000. Other states significantly reduced their corporate income taxes. New York, West Virginia, and Arizona each lowered their tax rates at least three times in 23 years. Arizona's rate was reduced from 9.3 percent in 1990 to 7.0 percent in 2012, whereas that of New York was reduced from 9.0 percent in 1990 to 7.1 percent in 2012. The average corporate income tax rate of the tax-cutting states fell from 8.6 percent in 1990 to 6.9 percent in 2012.
On the other hand, seven states have consistently increased their corporate income taxes from 1990 to 2012 and are classified as tax-increasing states. States with sizable tax increases include Alabama, Indiana, Illinois, and Maryland. The average tax rate of those states rose from 5.3 percent in 1990 to 7.5 percent in 2012. The tax rate in the tax-increasing states started from a position lower than the tax cutting states in 1990, but moved higher than the group since 2008.
The "other" group includes the states that both increased and decreased their corporate income taxes since 1990, such as New Hampshire, Vermont, and the District of Columbia. This group also includes states that have shifted away from taxing corporate profits. For example, Ohio has gradually phased out the corporate income tax during this period and replaced it with commercial activity taxes (CAT) based on gross receipts. As Figure 1 shows, the average tax rates of those states fluctuated from 1990 to 2012. (1)
3. Correlation between Tax Cut and Employment Growth
Table 2 presents the annual employment growth rates from 1990 to 2012 based on whether a state made changes to its corporate income taxes. (2) In this table, employment growth rates of three groups of states are presented--control, tax-cutting, and tax-increasing states. The employment growth rates are five-year averages to remove annual fluctuations.
Table 2. Average Annual Employment Growth Rate No Change Tax-Cutting Tax-Increasing States (%) States (%) States (%) 1991-1995 2.12 -0.10 1.50 1996-2000 2.48 2.77 1.74 2001-2005 0.53 0.34 -012 2006-2010 -0.36 -0.60 -0.77 2011-2012 1.23 1.47 1.16
The comparisons of employment growth for states in the three groups suggest that a reduction in corporate income tax is associated with relatively faster employment growth. The states that cut corporate income taxes started with slower employment growth than the control group. From 1991 to 1995, the average annual employment growth rate in tax-cutting states was -0.10 percent, whereas that of the control states was 2.12 percent--a difference of more than 2 percentage points. As more states cut taxes, the gap in employment growth between tax-cutting states and the control states narrowed. In the second half of the 1990s, the average annual employment growth of the tax-cutting states was slightly higher than that for the control states. After 2000, the employment growth of tax-cutting states kept pace with those of the control states. Although tax-cutting states experienced slightly larger percentages in employment decline during the last recession (-0.60 percent as opposed to -0.36 percent from 2006 to 2010), they also rebounded faster than the control states. The overall impression is that, starting from the disadvantaged status in the early 1990s, job growth in tax-cutting states has grown relatively faster and have caught up with control states. This effect is more easily demonstrated in Figure 2.
The experience of the tax-increasing states is different. In all time periods in the last 23 years, their job growth was consistently lower than the control states, as shown in Table 2. The difference is more dramatic between tax-cutting and tax-increasing states. In the first half of the 1990s, annual job growth in tax-cutting states was 1.6 percentage points lower than tax-increasing states. But job growth in tax-cutting states overtook tax-increasing states in the second half of the 1990s, and has been consistently higher, regardless of whether the national economy is in recession or in expansion.
These observations imply that tax cuts are associated with faster job growth in the past 23 years, but they do not conclusively establish a statistical link. Moreover, as tax-cutting states were grouped together and they enacted tax cuts at different times, the exact effect of tax cuts can be muddied. To establish a clear and quantitative connection between tax cuts and job creation, we performed an econometric analysis.
4. Econometric Analysis
Mode/specification and data
The econometric analysis is based on a panel data set of 50 states and the District of Columbia, spanning from 1990 to 2012. This timeframe was chosen because of the availability of the state-level corporate tax and employment data. During this timeframe, there are over 30 states that changed their corporate tax rate. This variation makes it possible to estimate the effect of the tax change on employment. In addition, the long time period allows us to control for other independent factors on employment [Goolsbee and Maydew 2000]. As the data set is in time-series and cross-sectional format, panel data econometric models perform better than pooled ordinary least square (OLS) models. We also performed a Haussman test on the model specification, which suggests that fixed effect panel models are appropriate.
In a fixed-effect panel model, both state-specific and time-specific fixed factors can exist. Time-specific factors capture macroeconomic conditions that affect all states--such as recessions, global influences, interest rates, and federal government spending. With a time-specific fixed-effect model, we don't specify those factors separately. Similarly, state-specific impacts are captured by state fixed factors. (3) F-tests indicate no strong presence of state fixed factors, but there are strong time-specific fixed factors. As a result, the econometric model is estimated with time-specific fixed factors only. More specifically, the model is expressed as follows:
E[G.sub.i, t] = [[beta].sub.1]P[G.sub.i,t - 1] + [[beta].sub.2]Tax_[Rate.sub.i,t] + [[beat].sub.3]Tax_Cut_[Ind.sub.i,t - L] + [[gamma].sub.1] + [[epsilon].sub.i,t]
where the dependent variable [EG.sub.i,t] refers to the annual employment growth rates in state i and year t. It is calculated based on the statewide employment data from the Quarterly Census of Employment and Wages (QCES), released by the Bureau of Labor Statistics [Bureau of Labor Statistics 20131. This data source has been used in a number of empirical studies examining employment growth and tax policies [Gabe 2003; Wu 20101.
The two key explanatory variables in this study are state corporate income tax rates (Tax_[Rate.sub.i,t]) and the variable representing the action of a tax cut (Tax_Cut_[Ind.sub.it] Tax_[Rate.sub.i,t] represents the level of corporate tax rate in state i at year t, whereas Tax_Cut_[Ind.sub.i,t] is constructed as a dummy variable that takes the value of one if a state reduces its corporate income tax rate in year t, and zero otherwise. In theory, the tax rate variable is expected to have a negative impact on employment growth because higher taxes imply less profit for businesses and less capacity of hiring [Huber and Runkel 2009] .
In this model, we choose to use the statutory tax rate (or absolute tax rate) as the key independent variable, rather than the relative tax rate (or tax burden) as other studies have done [for example, Reed 2008]. The relative tax rate, as a percentage of actual tax revenue paid in total profits, may have a more direct impact on corporate profit and employment decisions. But the tax burden is less transparent and not directly linked to the tax rate that policymakers can control. The relative tax rate deviates from the absolute tax rate in that it is the composite of the tax rate and other practices, such as tax incentives and exemptions, as well as corporations' tax avoidance strategies. The purpose of this study is to provide evidence to support or oppose whether a tax cut can promote job creation. This study aims to delineate the effect of the statutory tax rate and a tax-cut action, rather than the effect of the less transparent business tax burden, even though it may have a stronger association with employment growth.
A tax-cut indicator variable is used, in addition to the tax rate variable, to capture the effect of a sudden change in tax policy. To illustrate the difference between the effect of the Tax_Rate and Tax_Cut_Ind variables, consider the following scenario. Assume two similar states--state A and B--have the same corporate tax rates at 5 percent. State A has kept this rate steady for many years whereas state B recently reduced the tax rate from 6 to 5 percent. As state B just changed its tax policy, businesses are in the process of adjusting to the lower tax rate. Their actions during this period might be different from businesses in state A, where no such adjustment process occurs. The variable of Tax_Cut_Ind can capture differences in business responses during this adjustment period. If the estimated coefficient of Tax_Cut_Ind is positive and significant, that will imply additional benefits exist and state B will grow faster than state A during the adjustment period. Thus, if the action of a tax cut has a beneficial effect on job growth in addition to that of Tax_Rate, the Tax_Cut_India variable should have a positive sign
We also test the timing of the effectiveness of a tax cut. If a tax cut has additional benefits on employment growth, does this benefit take place immediately or is there a time lag? We estimated several models with different time lags. Let L be the variable representing the time lag in years 0 to 5 in this study. Tax_Cut_[Ind.sub.i,t-1] explores the effect of a tax cut enacted L years ago on the employment growth in year t. Additional tests show that when L is greater than 5, the coefficient estimates of the Tax_Cutind variable are generally minimal.
As noted earlier, data on corporate income tax rates were obtained from The Tax Foundation . As of 2012, for example, 31 states have fixed tax rates; five had no corporate income tax, whereas 14 states have progressive tax systems, with businesses subject to different tax rates based on the amount of income. For those states, an average tax rate for all income brackets is used in the econometric analysis.
Outside those two key variables of interest, one control variable included in this model is the lagged population growth rate (P[G.sub.i,t-l]). Overall population growth can drive a large part of the employment growth of a state, both in labor demand and labor supply [Friedburg 2000; Hamermesh and Trejo 2000]. This variable is expected to have a positive impact on employment growth. Statewide population data are obtained from the U.S. Census Bureau , from which year-over-year population growth rates were computed for each state. Lastly, the time-specific fixed factors are represented by 7, in the econometric models. The summary statistics of the data are listed in Table 3.
Table 3. Descriptive Statistics Employment Population Average Tax Tax Growth (%) Growth (%) Rate (%) Cut Ind 1991 -1.67 1.07 6.62 0.00 1992 0.46 1.13 6.60 0.01 1993 1.90 1.07 6.29 0.06 1994 2.76 0.98 6.26 0.07 1995 2.52 0.94 6.38 0.12 1996 2,04 0.91 6.19 0.04 1997 2.64 0.95 6.17 0.03 1998 2.46 0.91 6.33 0.13 1999 2.27 0.90 6.27 0.12 2000 2.25 3.36 6.21 0.18 2001 -0.18 1.02 6.21 0.06 2002 -1.09 0.95 6.15 0.13 2003 -0.35 0.87 6.24 0.01 2004 1.15 0.93 6.23 0.00 2005 1.75 0.92 6.54 0.01 2006 1.70 0.95 6.47 0.04 2007 1.12 0.99 6.47 0.00 2008 -0.41 0.92 6.38 0.13 2009 -4.82 0.86 6.02 0.13 2010 -0.61 0.75 6.04 0.03 2011 1.22 0.73 6.11 0.05 2012 1.52 0.74 6.11 0.03
Regression results--Key conclusions
Six fixed-effect models were estimated, with different time lags on the tax cut variable. The regression results are listed in Table 4.
Table 4. Regression Results Variable Model 1 Model 2 Model 3 Model 4 Model 5 L=0 L=1 L = 2 L=3 L=4 State 0.5037 * 0.5002 * 0.5086 * 0.4973 * 0.4549 * Population Growth (PG) Corporate Tax -0.04952 -0.0493 -0.0434 -0.0391 -0.0313 Rate * * * * * (Tax_Rate) Tax Cut 0.0038 * 0.0009 -0.0001 -O.0018 0.0012 Indicator (Tax_Cut_Ind) Year Fixed Effect Estimate [gamma]) 1992 0.0106 * 0.0107 * -- -- -- 1993 0.0219 * 0.0220 * 0.0216 * -- -- 1994 0.0293 * 0,0295 * 0.0291 * 0.0289 * 1995 0.0238 * 0.0242 * 0.0238 * 0.0237 * 0.0237 * 1996 0.0180 * 0.0181 * 0.0178 * 0.0177 * 0.0175 * 1997 0.0234 * 0.0234 * 0.0230 * 0.0230 * 0.0227 * 1998 0.0218 * 0.0219 * 0.0215 * 0.0215 * 0.0211 * 1999 0.0208 * 0.0212 * 0.0208 * 0.0207 * 0.0204 * 2000 0.0234 * 0.0207 * 0.0204 * 0.0202 * 0.0200 * 2001 -0.0146 * -0.0143 -0.0149 -0.0147 -0.0137 * * * * 2002 -0.0088 * -0.0087 -0.0090 -0.0090 -0.0094 * * * * 2003 -0.0021 -0.0021 -0.0024 -0.0024 -0.0029 2004 0.0133 * 0.0134 * 0.0130 * 0.0129 * 0.0125 * 2005 0.0165 * 0.0167 * 0.0162 * 0.0161 * 0.0159 * 2006 0.0170 * 0.0171 * 0.0167 * 0.0165 * 0.0164 * 2007 0.0110 * 0.0110 * 0.0106 * 0.0105 * 0.0103 * 2008 -0.0041 * -0.0037 * -0.0041 -0.0042 -0.0043 * * * * 2009 -0.0441 * -0.0439 -0.0442 -0.0443 -0.0445 * * * * 2010 -0.0067 * -0.0066 -0.0070 -0.0071 -0.0073 * * * * 2011 0.0091 * 0.0093 * 0.0089 * 0.0089 * 0.0087 * 2012 0,0135 * 0.0137 * 0.0133 * 0.0132 * 0.0128 * Observations 1047 1047 997 947 897 R-squared 0.6910 0.6893 0.7037 0.7072 0.7041 Variable Model 6 L=5 State 0.4121 * Population Growth (PG) Corporate Tax -O.0329 Rate * (Tax_Rate) Tax Cut 0.0022 Indicator (Tax_Cut_Ind) Year Fixed Effect Estimate [gamma]) 1992 -- 1993 -- 1994 -- 1995 -- 1996 0.0181 * 1997 0.0232 * 1998 0.0216 * 1999 0.0208 * 2000 0.0202 * 2001 -0.0122 * 2002 -0.0089 * 2003 -0.0 *23 2004 0.0128 * 2005 0.0162 * 2006 0.0168 * 2007 0.0108 * 2008 -0.0038 * 2009 -0.0440 * 2010 -0.0068 * 2011 0.0092 * 2012 0.0133 * Observations 847 R-squared 0.6999 Note: * significant at 95 percent level, ** Significant at 90 percent level.
Overall, the fixed-effect panel models explain around 70 percent of the annual state employment growth in the past 23 years, with an adjusted [R.sup.2] ranging from 0.69 for Model 2 (one-year lag in tax cut) and 0.71 for Model 4 (three-year lag in tax cut). Considering that state employment growth is affected by a complex set of global, national, and regional factors, the performance of this simple model with only three independent variables is satisfactory.
Three key results are concluded from the regression. First, population growth has a positive and significant effect on employment growth in all six models. One percent of population growth in the previous year contributes an average of 0.49 percent growth in state employment, making it one of the fundamental driving forces for job creation. Other studies on state employment growth found similar positive and significant influences from population growth [Deming 1999; Edmiston 2006]. For example, Edmiston  discovered that the elasticity between state population and employment growth is 0.587, which is consistent with the result estimated from our study. Population growth affects both labor supply and labor demand [Friedberg 2000, Hamermesh and Trejo 2000]. Large population changes imply an increased demand for workers, as more residents purchase from retail, restaurants, health care, and other consumer services establishments in the state. In addition, high population growth also implies more people are in the local labor market, driving up the labor supply. Consequently, it is not surprising that population has a strong effect on employment growth.
The second key result is that the level of the tax rate has a negative and significant effect on the pace of state employment growth for all six models. This result implies that higher state corporate income tax rates reduce employment growth because a higher tax rate represents a direct reduction in business profits, impeding the ability of businesses to expand and hire more workers. The average coefficients of all six models show that employment in a state with a corporate income tax rate that is 1 percentage point lower than other states grows about 0.03 to 0.05 percentage points faster, other things equal. This implies that the elasticity of state corporate income tax on employment is about -0.2, which is consistent with the findings of earlier studies. For example, Bartik's  literature review of the effect of state and local tax summarized that the average elasticity of those taxes on economic activities was -0.3, ranging from 0.1 to -0.6.
The third key result is that a tax-cut action also has additional benefits to state employment growth. Unlike the Tax_Rate variable, this effect is not uniformly significant across the six models. The coefficient of the Tax_Cut_[Ind.sub.t,i-l]_L variable is positive and significant when L = O, meaning that the tax-cut action has some immediate benefits in boosting employment growth in the year when a tax cut was implemented. When L=1, the coefficient becomes insignificant, but positive, implying that there might be some residual benefits associated with a tax cut, but the model cannot conclusively detect them. The effect becomes close to zero in all years afterwards, implying the action of a tax cut has no additional benefits in the following years.
The fact that a tax cut has additional, but temporary benefits indicates that those benefits occur as a result of businesses adjusting to the new tax policy. When a tax cut is enacted, businesses need to evaluate and respond to the new policy. Some of the expansion or staffing plans may be accelerated following a tax cut. Moreover, a tax cut always comes with great publicity and public debates. Some businesses may be actively involved in the lobbying efforts to reduce the corporate income tax. As a result, when it is enacted, those involved businesses may be motivated to demonstrate that a tax cut helps the economy by increasing investments or hiring. The public debate of the policy changes can also reinforce the image of the state as a business-friendly place, potentially boosting business expansion or relocation. For businesses in the process of an expansion and relocation decision, the action of a tax cut may steer the site selection process to tax-cutting states. This change in businesses' behavior may explain the incremental and temporary benefits of a tax cut action. However, once the adjustment process is complete--in about one year--and publicity associated with the tax cut dies down, the temporary benefit disappears. Businesses, however, still enjoy a lower tax rate afterwards, as lower taxes can continue to benefit job creation in the long run.
The panel structure of the econometric model specifications reveals the effect of individual states cutting rates, rather than all states cutting tax rates simultaneously. The boost in employment from a tax cut, estimated in this model, includes not only new jobs resulting from organic expansion of the employment base, but also jobs created because of relocation as businesses chase after lower taxes. As a result, the coefficients estimated here are presumably larger than the effects of all states cutting taxes simultaneously. When all states are cutting taxes simultaneously, the job creation due to relocation will be negated, akin to a cut of federal corporate income tax.
This study indicates that cutting corporate income tax rates is associated with faster employment growth. Although a tax cut can benefit employment growth in the state-wide economy, state government officials often want to understand if a tax cut will be revenue positive, negative, or neutral. Cutting corporate income tax in exchange for faster job growth is fundamentally a trade-off between corporate income and individual income taxes. Reducing corporate tax rates will lead to lower corporate income tax revenues, whereas faster job growth results in more wages and salaries, leading to additional individual income tax revenues. (4)
Naturally, this trade-off will vary by states. For those states that have no individual income taxes, cutting corporate taxes would tend to be revenue negative. (5) Similarly, the revenue impact will also vary when states with different personal income tax rates cut corporate taxes by the same amount. This section illustrates the fiscal trade-off of an average state, with average corporate and individual income tax rates. This illustration assumes that individuals in jobs created due to tax cuts will earn the average wage of the state.
Utilizing estimated state corporate tax revenues estimated by Ernst & Young and the Council on State Taxation , Table 5 illustrates the net fiscal impact of various levels of cuts in corporate income tax rates. For example, if the tax rate was cut by 100 basis points (1 percentage point), an average state will lose $157.5 million in corporate tax for the year; meanwhile, the additional job creation can generate $27.0 million in individual income taxes, resulting in a net revenue loss of $130.5 million. However, if the corporate tax rate is reduced by 50 basis points, the state will lose $78.8 million of corporate income tax revenue whereas individual income tax can increase by $25.4 million, for a net loss of $53.4 million. The analysis shows that if the degree of a tax cut is 15 basis points, an average state can generally break even.
Table 5. Estimated State Fiscal Impact-First Year of Tax Cut (2011 Base) Tax Cut Action Decrease in Increase in Corporate Tax Individual Tax Revenue ($million) Revenue ($million) 100 Basis Point Reduction $157.5 $27.0 50 Basis Point Reduction $78.8 $25.4 30 Basis Point Reduction $47.3 $24.8 20 Basis Point Reduction $31.5 $24.5 15 Basis Point Reduction $23.6 $24.3 10 Basis Point Reduction $15.8 $24.2
The reason that a smaller tax cut is more beneficial to a state's fiscal health lies in the fact that the tax cut action (represented by the dummy variable) has the additional affect in promoting employment growth. The model coefficient estimate indicates that each tax cut action, regardless of the degree of the cut, has a positive effect on job growth. To enjoy such temporary benefits more, it is better to have a series of moderate tax cuts, rather than a deep tax cut in one setting, because businesses react not only to the tax rate itself, but also the publicity surrounding the tax-cut action.
Although the main regression results indicate that tax cuts can stimulate changes in state employment, further exploration is needed whether those effects are caused as a result of endogenous tax policy. If policymakers change the tax rate based on the state's output or employment growth performance, this endogeneity will bias the coefficient estimates presented in Table 4. On the other hand, it is also possible that the tax cut actions are independent of the economic performance, thus exogenous. For example, if the tax cut is mainly driven by political forces and depends on which party is in control of the state legislature, a change in tax rate may be exogenous to the economic performance.
To further understand whether tax cuts in state corporate income tax in the past 23 years is endogenous with respect to employment, we used a technique employed by Goolsbee and Maydew [20001. We estimated a logit model of tax policy action. The dependent variable is a binary variable, taking the value of one if a state reduces its corporate tax rate for the year, and zero otherwise. The explanatory variables are one-year lagged state corporate tax rates, one-year lagged state employment growth rates, and one-year lagged population growth rates (Table 6). Those variables represent the general tax and economic conditions.
Table 6. Logit Regression for Tax Cut Variable Intercept -4.2589 * 65.66 Lagged Employment Growth 14.8482 2.3531 Lagged Population Growth -13.1567 0.85 Lagged Tax Rate 20.1341 * 9.98 Observations 1173 Note: * Significant at 95 percent level. Numbers below coefficient estimate are Wald chi-square value.
The policy regression results suggest that among the economic variables, such as state employment and population growth rates, none is significant at the 5 percent level. The explanatory power of the policy regression is very small, indicating that decisions to enact a tax cut may not be endogenous to the economic variables used in our study. The only variable that is significant is the one-year lagged state corporate tax rate. The positive and significant coefficient suggests that high tax states are more likely to reduce the corporate tax rate. That seems to suggest that the decision to cut tax is decided not by economic conditions, but by factors outside the economy, the same conclusion reached by Goolsbee and Maydew . The endogeneity of the tax-cut action is not a serious issue in this study. (6)
The regression results show that generally lower corporate tax rates can result in faster employment growth. More importantly, the action of a tax cut has the added bonus of boosting employment growth in the short term. This has important implications for state policymakers. As the economy climbs out of recession, citizens remain worried about a slow job recovery. The persistently slow job growth four years after the recession officially ended highlights the urgent need for effective policies that can stimulate job creation. States that enact a tax cut now can help alleviate the lingering impact of the recession. In addition, if a future tax cut is implemented when the early signs of a weak economy emerge, it may successfully forestall or alleviate the impact of the pending recession on that state.
The fact that the action of a tax cut has significant additional benefit in the first year of the policy implementation also has important policy implications. Owing to the additional benefits of the tax-cut action, it is beneficial for the state to enact the tax cuts in a series of small steps, rather than a dramatic reduction in the tax rate as one event. By reducing the tax rate with a series of small steps, the tax-cut discussion will remain constant in public discourse and will reinforce the state's image as business friendly. The publicity can also help attract businesses in the process of relocation and expansion decisions.
From the perspective of state fiscal health, enacting tax cuts in a series of small and gradual steps over the years is likely to be revenue neutral and even positive for the state budget. By doing so, the state will not experience the drastic tax revenue reduction due to a deep tax cut, thus avoiding painful cuts in other areas such as education, health care, and transportation, which can adversely affect employment in those sectors.
This paper contributes to the literature by taking two approaches to establish the link between a cut in state corporate income taxes and employment growth. Overall employment comparisons show that states that cut corporate income taxes started with slower year-over-year employment growth than states making no changes in corporate income tax rates. In later years, the tax-cutting states have caught up or even grown faster in terms of job creation. The fixed-effect panel regression model finds that state corporate tax rates have a significant negative effect on employment growth. In addition, the tax-cut action has the added benefit of employment growth in the short term, as businesses react to the new policy and adjust to the policy change. This additional benefit is temporary, lasting only for one year.
There are a couple areas for extensions and future research. First, this study only focuses on the easily measureable statutory corporate tax rate, not other state corporate income-related practices that could affect business profits and employment, such as methods of allocating national profits, depreciation rules, and other tax incentives and exemptions. Future research should quantify such variables and include them in regression analysis or other quantitative analyses. Second, this paper focuses on corporate income tax as a direct policy measure that states can influence at a time of slow job growth. There are other taxes that could be related to corporate income taxes, but not exogenous to economic conditions. The indirect endogeneity may introduce bias in the effect in the corporate income tax. Future research is needed to test the correlation of state corporate income taxes with other state taxes such as sales, personal income, or property taxes, and include those variables in the study. (7)
Caption: Figure 1. Average State Corporate Income Tax Rate (1990-2012)
Caption: Figure 2. State Average Employment Growth Rates (1991-2012)
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(1.) Those states are excluded from comparisons in Section 3, as the changes in different directions make the effect of tax changes less clear-cut.
(2.) The employment data are from the U.S. Department of Labor's Quarterly Census of Employment and Wages.
(3.) The F-test on the state-fixed effect yields a P-value of 0.58, suggesting that we cannot reject null hypothesis of the no state fixed factor at 95 percent confidence level. The F-test on the time-specific fixed effect yields a P-value of 0.0, indicating rejecting null hypothesis of the no time-specific fixed factor.
(4.) Although the expansion of output that accompanies faster job growth after a tax cut can potentially boost corporate profits, this secondary fiscal effect is believed to be minor and is not included in this exercise.
(5.) The states without individual taxes typically have higher sales tax, which can increase after a cut in corporate tax rate. That would offset corporate tax revenue reduction to some degree. The revenue trade-off between the corporate income and sales taxes are more complicated, as it depends on the marginal propensity of consumption for consumers, as well as allocation of consumption among goods subject to sales tax, and those that are exempt. As only a small number of states do not have individual income tax, we did not explore this further in this paper.
(6.) Although the corporate tax changes in the past 23 years are exogenous, there might be indirect endogeneity, as corporate income taxes may be correlated with other taxes, which could be endogenous to economic conditions. Future research is needed to test the correlation of state corporate income taxes with other state taxes. The authors thank an anonymous referee for this insight.
(7.) The authors thank an anonymous referee for this suggestion.
XIAOBING SHUAI and CHRISTINE CHMURA *
* Xiaobing Shuai is a senior economist at Chmura Economics & Analytics, having joined the firm in 2004. His duties include model building and forecasting regional and macroeconomic trends. His interest rate forecasts are published in the Blue Chip Financial Forecasts. His research with Chmura also includes regional economic development, workforce development, and other education-related issues. Previously he worked as a senior analyst with Capital One Financial Corporation in Richmond. He graduated from Fudan University in Shanghai. He obtained an M.A. in agricultural economics and a Ph.D. in economics from the University of Wisconsin-Madison.
Christine Chmura is the President and Chief Economist for Chmura Economics & Analytics, a quantitative research and economic development and workforce consulting firm located in Richmond, Virginia, that she founded in December 1999. For eight years prior to that, she was the Chief Economist at Crestar Financial Corporation, after serving as an Associate Economist at the Federal Reserve Bank of Richmond for seven years. She currently serves on the Governor's Economic Advisory Board of the Commonwealth of Virginia and the Governor's Commission on Economic Development & Job Creation. She is a former member of Governor Kaine's Commission on Climate Change, the Virginia Commonwealth University Foundation Board of Trustees, and the Board of the National Association for Business Economics. She received her bachelors' and masters' degrees from Clemson University and a Ph.D. in business with a major in finance and a minor in economics from Virginia Commonwealth University.
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|Comment:||The effect of state corporate income tax rate cuts on job creation.|
|Author:||Shuai, Xiaobing; Chmura, Christine|
|Date:||Jul 1, 2013|
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