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BHI FaxSheet: Information and Updates on Current Issues

Ohio sales tax hike from 5% to 6% would destroy 99,000, cut capital by $8.8 billion

On March 24, 1997, the Ohio State Supreme Court ruled that funding for poorer school districts must be brought closer to the statewide average. This ruling will entail additional state spending of about $1 billion. Two proposals for raising the new funds have emerged. One proposal would increase the state sales tax from 5% to 6%. A second proposal would freeze or cut spending on other government programs and use money from the state budget surplus.

According to an econometric analysis performed by the Beacon Hill Institute, the sales tax increase would, at a minimum, result in the loss of 99,000 jobs and leave Ohio's capital stock $8.8 billion smaller. The analysis shows that there is a 90% probability that this outcome will occur.

Minimum Economic Effects of Increasing the Ohio State Sales Tax from 5% to 6%

Change in Payroll Cumulative
Change
in Jobs
Cumulative
Change
in Capital Stock
Cumulative
“Static”
Tax Revenue Effect
Cumulative
“Dynamic”
Tax Revenue Effect
Cumulative
Net Tax
Revenue Effect
-$2.917 billion -98,538 -$8.77 billion $1,143 million -$119 million $1,024 million

The tax increase would lower employment by at least 1.7%. As a result, the annual payroll in Ohio would fall by $2.9 billion. This would raise the state unemployment rate, which stood at 4.4% in November, to as much as 6%. It is noteworthy that when Ohio raised the sales tax from 4% to 5% in 1981, the unemployment rate increased from 8.9% in December 1980 (1.6% above the national average of 7.3%) to 13.7% in December 1982 (4.0% above the national average).

The tax increase would produce a net revenue gain of up to $1,024 million in 1998. This is the net result of two effects: (1) the “static” revenue gain of $1,143 million (computed on the assumption that the tax hike had no effect on the Ohio economy) and (2) the “dynamic” revenue loss of at least $119 million (the revenue lost as a result of the decreased production and personal income brought about by the tax hike).

________________________________________

Methodology

Two steps are needed in order to measure the effect of the tax increase on the variables of interest – these variables being the number of jobs (L), the wage rate (w), the capital stock (K) and state tax revenue (TR). First we must establish baseline values for the variables, projecting them out through the end of 1998. Then we use the Beacon Hill Institute's State Tax Analysis Modeling Program (STAMP) to estimate and project employment, wages and the capital stock in the presence of a tax increase.

A. Baseline Projections of Wages, Jobs and Capital

The baseline projections are shown in the table below and were constructed as follows. Information on the number of jobs is available through 1996 and information on the number of workers is available for 1997. We assume that the number of jobs in 1997 grows at the same rate as the number of workers did for the first eight months of 1997 relative to the first eight months of 1996 (1.13%), and assume that the number of jobs in 1998 grows at the same speed as it did from 1995-1997 (1.74%).

The value of the total payroll is known through 1996, and we assume that it will continue to grow (in nominal dollars) for the rest of 1997 at the same speed as it did between the first half of 1996 and the first half of 1997, which is by 5.70% per year. We assume that it grows at the same speed in 1998 that it did from 1995-1997 (5.27%). We also assume that the capital stock grows at the same speed as the total payroll, so that the capital to labor ratio does not change. Since information on the capital stock in Ohio is available for 1995, we use the historical growth rates of payroll to generate the capital stock value for 1996, and the projected growth of payroll to arrive at the capital stock for 1997 and 1998. The average wage is simply the total value of payroll divided by the number of jobs.

The state sales tax base for the calendar year 1994 ($92,076 million) was estimated by taking an average of sales tax collections for fiscal year 1994 and fiscal year 1995 and dividing them by the sales tax rate of 5%. The 1996 sales tax base ($97,181 million) was derived in a similar manner. For 1996 ($102,569 million), 1997 ($108,256 million) and 1998 ($114,258 million), we assume that the sales tax base grows by the 1995 growth rate (5.54%).

B. Applying the Tax Analysis Model

A fuller description of the tax analysis model is given in The Economic Effects of Changing the Ohio Sales Tax: Estimates Using the BHI State Tax Analysis Modeling Program (Beacon Hill Institute, January 1998); the basic model has been modified and re-estimated so that it is applicable to Ohio. [1] The model is designed to allow the analyst to trace the effects of changes in state tax rates on employment, wages and the capital stock. It begins with a series of structural equations that aim to capture the behavior of firms and households, and then rearranges these equations to arrive at a set of reduced form equations which are both theoretically consistent and may be estimated econometrically. The equations are estimated using data from 1970-1994. In simplified form, the two that are relevant here are the labor equation and the capital equation.

The labor equation shows how changes in state sales tax rates (and other variables) affect the number of jobs in Ohio. The estimated equation is of the form

(1) ln(L) = -0.0375t + other terms

SE=0.01215

where ln(L) is the natural log of the number of jobs, and t is the state sales tax rate. The coefficient -0.0375 is statistically significant, and measures the effect of a change in the tax rate (deltat) on ln(L); in other words deltaln(L)/deltat = -0.0375. With 90% certainty, the coefficient is equal to -0.0375 + 1.645 x 0.01215, or somewhere in the interval between -0.0575 and -0.0175. Since our concern is with the minimum reasonable effects of the tax change on labor demand, it is the latter number (i.e. -0.0175) that we need to use.

The capital equation is similar, except that the dependent variable is capital rather than labor. Specifically the estimated equation is of the form

(2) ln(K) = -0.0493t + other terms

SE=0.01472

where ln(K) is the change in the natural log of the value of the capital stock from one year to the next. The coefficient -0.0493 is statistically significant, and with 90% probability lies between -0.0735 and -0.0251.

C1. Projecting the Effects of the Tax Increase: Employment

We project the minimum number of jobs that will be destroyed as a result of the tax hike. Since t increases from 5% to 6%, we have deltat = 1.0. Thus

(3)delta4 ln(L) = (-0.0175)delta4t = (-0.0175)(1.0) = -0.0175.

The baseline value of ln(L) [=15.5543 = ln(5,690,274)] now falls by 0.0175 to 15.5368; taking the antilog gives the number of jobs with the tax hike, which (when done precisely) is 5,591,736, or a decrease of 98,538 below the baseline case.

C2. Projecting the Effects of the Tax Increase: Capital

The minimum effects of the tax increase on the capital stock are estimated in the same manner as for employment. Thus

(4) delta4ln(K) = (-0.0251)delta4t = (-0.0251)(1.0) = -0.0251.

The baseline value of ln(K) [=12.7751 = ln($353,297 million)] now falls by 0.0251 to 12.7500; taking the antilog gives a new capital stock, after the tax increase, of $344,530 million, or a decrease of $8,767 million over the baseline case.

C3. Projecting the Effects of the Tax Increase: Wages

The estimated reduced form equations of the tax analysis model show that the state sales tax rate does not have a statistically significant effect on the wage rate in Ohio. Wages are thus assumed to follow the baseline projections both with, and without, the tax increase. The total value of the payroll, in the presence of the tax hike, is calculated by multiplying these average wage rates by the number of people employed.

C4. Projecting the Effects of the Tax Increase: Tax Revenue

What effect would a hike in the tax rate have on state tax revenue? First there is a “static” revenue gain, which is measured as the increase in the sales tax rate times the sales tax base.

The static revenue gain would be $1,143 million (=1.0%*$114,258 million). But this overstates the true revenue gain, because there is also a “dynamic” revenue effect: The tax increase leads to an decrease in the number of jobs and hence the total payroll, and therefore to some offsetting decrease in revenue. Since the number of jobs falls by (at least) 1.73%, the dynamic revenue loss is 1.73% x 6% x 114,258 = $119 million.

Appendix Table:

Minimum Effect of Ohio Tax Increase on Employment, Capital Stock and Tax Revenue*

    Amount  Growth Rate
  Baselines
 
A Employment 5,690,274  
B Payroll ($ mill) 168,475  
C Average wage ($ p.a.) (=B/A) 29,608  
D Capital stock ($ mill) 353,297  
E State sales tax base ($ mill) 114,258  
F Old sales tax rate 5%  
  Minimum Effects with Tax Increase
G New sales tax rate 6%  
H Employment in presence of tax increase 5,591,736 -1.73%
I Job decline with tax increase (=A-H) 98,538  
J Capital stock in presence of a tax increase ($ mill) 344,530 -2.48%
K Decrease in capital due to tax increase ($ mill) (=D-J) 8,767  
L Payroll in presence of tax increase ($ mill) 165,558 -1.73%
M Decrease in payroll due to tax increase ($ mill) (=B-L) 2,917  
N "Static" tax revenue effect: cumulative ($ mill) (=E*(G-F)) 1,143  
O "Dynamic" tax revenue effect: cumulative ($ mill) (=G*E*((H/A)-1)) -119  
P Net tax revenue effect: cumulative ($ mill) (=N+O) 1,024  

Note: Figures are rounded.

*There is a 90% probability that the effect of the tax increase will be larger than the amounts shown

in the table.


Footnotes

[1] Regression results for Ohio are available upon request.


 

Last update: 1/15/98
HTML format revised on 07/11/2007 2:28 PM
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