Some tables and equations in this HTML document are under construction.

This document in its complete form is available in PDF format

Executive Summary

The Texas State Tax Analysis Modeling Program
(Texas-STAMP)
Metodology and Applications

Prepared by the Beacon Hill Institute
David G. Tuerck, PhD,
Project Director
Jonathan Haughton, PhD,
Project Manager
In-Mee Baek, PhD,
Project Consultant
James Connolly, BA,
Research Assistant
Scott Fontaine, BA,
Research Assistant

This study was commissioned by the Texas Public Policy Foundation and conducted by The Beacon Hill Institute for Public Policy Research at Suffolk University. 1999 All rights reserved.

January 1999


Executive Summary

For many years there was a tradition in state government to treat taxes as if they didn't matter. It was presumed that businesses and individuals cared mainly about state and local government services and infrastructure: States could raise taxes without regard to any adverse economic effects.

That tradition is giving way to an economic reality: State taxes do matter. This is especially true in today's competitive economic environment in which firms are able and willing to move from one state to another as tax incentives become available to them.

Assessing the effects of proposed tax-law changes using reliable, credible methods is therefore crucial. In response to this demonstrated need, the Beacon Hill Institute at Suffolk University in Boston developed STAMP, the State Tax Analysis Modeling Program. STAMP permits policymakers, opinion leaders and scholars to determine how a change in state tax law will affect the state economy.

As an “econometric model,” STAMP applies economic and statistical methods to state and federal data to determine how state economic indicators vary with changes in state tax law. The economic indicators usually considered by STAMP are the number of jobs, wage rates, the capital stock and tax revenues. The capital stock is the total value of nonresidential capital, including manufacturing facilities, office and warehouse space, business equipment and other items that business uses in production.

STAMP permits its users to “simulate” the effects on these indicators of alternative tax-law changes and combinations of tax-law changes. Using STAMP, we can, for example, estimate the effects on employment of a simultaneous reduction in property taxes and increase in the state sales tax.

States frequently rely on “static” models that attempt to determine the effects of tax-law changes on tax revenues. These models make the simplifying assumption that changes in tax law have no effect on economic activity. For example, in a static model, a rise in the sales tax rate would be assumed to have no effect on sales. A 20% rise in the sales tax rate would be expected to bring about a 20% rise in sales tax revenue.

STAMP is, in contrast, a “dynamic” model. Dynamic models determine the effects of tax-law changes on tax revenues by taking into account how those changes affect economic activity. In a dynamic model, a rise in the sales tax rate would ordinarily be expected to bring about a decrease in sales. Thus a 20% rise in the sales tax rate would bring about a less-than-20% rise in sales tax revenue.

History of STAMP

BHI developed STAMP in 1994 in recognition of a need for a dynamic modeling capability in Massachusetts. The Massachusetts STAMP was first applied to a state ballot initiative that would have replaced the existing flat tax with a graduated income tax. STAMP showed that the proposed graduated income tax would have destroyed about 80,000 jobs and more than $1 billion in wages. The voters overwhelmingly rejected the initiative.

Subsequently, at the request of the Oklahoma Office of State Finance, BHI developed a STAMP for Oklahoma. In 1997, BHI provided evidence supporting the view held by state officials that a cut in income or sales taxes would increase personal income. Also in 1997, BHI built a New Jersey STAMP that showed how recent income tax cuts had resulted in the creation of about 25,000 new jobs and of more than $2 billion in new capital spending.

In January 1998, BHI released the results of an Ohio STAMP showing how a proposed increase in the state sales tax from 5% to 6% would destroy about 100,000 jobs and $3 billion in wages. The governor had proposed the tax hike as a way of raising $1 billion in new revenue to fund education spending. The state legislature rejected the tax hike, as did the voters overwhelmingly in a subsequent referendum.

Other tax analyses performed by BHI include an evaluation, in 1997, of a proposed reduction in the Iowa income tax and, in 1998, of a proposed oil processing tax in Louisiana. The Iowa study figured in a 10% tax cut adopted by the Iowa legislature. The Louisiana study showed that replacing the existing severance tax with a processing tax would slow the state economy by raising refiners' costs and the price of gasoline.

Texas-STAMP

Texas-STAMP is STAMP applied to the Texas economy. Estimated from Texas and U.S. data for 1970-1996 and for eight sectors of the Texas economy, it is designed to trace the economic effects of Texas tax-law changes. It can be applied to changes in the state sales tax, state unemployment insurance and workers compensation tax rates, property tax rates, and the state franchise tax. It shows how increases in these tax rates exert measurable, negative effects on the state economy.

How does STAMP work?

STAMP works by using certain “coefficients” obtained from the data to show how economic indicators such as jobs vary with changes in tax law. The coefficients are obtained from the data by estimating regression equations that link jobs and the other economic indicators to factors, notably tax rates, that influence those indicators.

Economists sometimes estimate the coefficients that link policy changes to economic changes without specifying the underlying theory on which those coefficients are based. STAMP avoids this error. The regression equations in STAMP are “reduced-form” equations, derived from a set of “structural equations” that lay out explicitly the theoretical underpinnings of the model.

STAMP's theoretical underpinnings are the stuff of standard economics texts: Households demand goods and services. If government raises taxes on the purchase of these goods and services, households will buy less of them. Households also supply labor to firms. If labor services are taxed more heavily, then households will supply less of them.

Firms are assumed to maximize profit, which they do by combining labor and capital in order to produce the goods and services that households demand. In this process, firms supply goods and services. If they have to pay a higher sales tax, then they will charge more for their goods, sell less as a result, and have to reduce production. Firms also pay wages and salaries to their workers. If the cost of hiring their workers rises, for example, because unemployment insurance payments grow, then they will economize on their use of labor by cutting back or finding substitutes.

What are the model's “coefficients?”

Our estimates of the model's reduced form equations are as follows:

Equation 1: Jobs

ln(number of jobs) = -0.1342 ln(government transfers per nonworking adult)
(0.00)
    -0.0250 Nonwage labor costs as a percent of the wage
(0.00)
    +0.0061 Federal tax rate on labor income
(0.00)
    -0.0077 Effective sales tax rate
(0.09)
    -0.0306 Cost of capital
(0.00)
    +0.6492 ln(working age population)
(0.00)
    + constant terms for each of eight sectors of the economy
    + terms with indices of U.S. output, for each of eight sectors of the economy.

 

There are six coefficients, each with an associated p-value given below it in parentheses. The p-values measure the statistical significance of the coefficients. We follow the convention whereby a coefficient is deemed statistically significant if its p-value is less than .10. A p-value below 0.10 indicates that there is less than a 10% chance that the true value of the coefficient is zero.

Here the dependent variable is the logarithm of the number of jobs. The first independent variable is the logarithm of government transfers per nonworking adult. The coefficient for this variable reflects the theoretical idea that transfer payments in the form of unemployment and welfare benefits decrease the number of jobs. The negative coefficient indicates that when these payments are larger, employment will be lower, presumably because the transfers will mean that people have less pressure to search for work. Specifically, the coefficient implies that a 1% increase in government transfers decreases jobs by .1342%.

Nonwage labor costs refer to disability and unemployment insurance payments made by employers. These costs have much the same effect as a tax on labor, and the estimated equation shows that when the costs rise, employers will cut back on hiring.

The estimated equation also shows that higher property taxes or sales taxes will reduce employment. The sales tax, as measured here, includes the ordinary sales and use tax and also the state taxes on gasoline, diesel fuel and motor vehicle sales.

A higher cost of capital has the same effect. The cost of capital measures how much employers have to pay to "hire" the capital they use. It is a complex measure, which reflects the size of depreciation, the cost of borrowing (i.e. interest rate), and the numerous taxes that bear on capital (including the state corporate franchise tax, the federal corporate income tax, and federal taxes on dividend income and capital gains).

Equation 2: Wages

ln (wage rate) = +0.0190 ln(government transfers per nonworking adult)
(0.01)
    +0.0094 Nonwage labor costs as a percent of the wage
(0.03)
    +0.0021 Federal tax rate on labor income
(0.00)
    +0.0175 Effective sales tax rate
(0.00)
    -0.0021 Cost of capital
(0.50)
    +0.3550 ln(working age population)
(0.00)
    + constant terms for each of eight sectors of the economy
    +terms with ln(non-Texas wage rate), for each of eight sectors of the economy.

This equation also gives sensible results, but needs to be interpreted with care. It shows that when government transfers are higher, the wage rate will also be higher. A reasonable explanation is that the safety net gives workers an alternative to working at very low wages. At first sight it might seem odd that a higher sales tax, nonwage labor costs, or federal tax rate would raise the wage rate. Yet the logic is sound; when these taxes are higher, workers will require higher pre-tax wages in order for it to be worth their while to work. In each case, however, the after-tax wage would be lower than before.

Equation 3: Capital Stock

ln (stock of capital) = -0.0389 ln(government transfers per nonworking adult)
(0.00)
    -0.0133 Nonwage labor costs as a percent of the wage
(0.08)
    +0.0018 Federal tax rate on labor income
(0.18)
    +0.0088 Effective sales tax rate
(0.18)
    -0.0286 Cost of capital
(0.00)
    +1.2760 ln(working age population)
(0.00)
    + constant terms for each of eight sectors of the economy
    + term with index of U.S. output.

This equation has no surprises. If capital is more expensive, less will be used. If sales and property taxes are higher, business will refrain from investing in the state.

How does the model simulate the effects of tax changes?

The simulations are done for 1999 and proceed in two steps. First we project what the value of the most import variables - employment, wages, capital stock, and the like - will be in 1999. Then we use the model to measure what happens to these variables when a change is made to the tax system. The 1999 baseline values for the most important variables are summarized below. Further details are provided in the main report.

Baseline Values of Variables Required for Simulations
Variable Units 1996 1997 1998 1999 Assumptions
Labor mill. jobs 8.725 9.092 9.401 9.617 Same as growth in nonfarm employment
Capital $ billion 656 707 758 811 Constant capital/payroll ratio
Wage rate $/job/yr 27704 28688 29714 31109 Same as growth in personal income net of labor growth
Working age population thousands 12274 12519 12745 12974 Same as growth of resident population
Welfare payment per nonworking adult $ 1799 1833 1869 1904 Extrapolate using 1993-96 nominal growth rate
Nonwage labor

costs as % of wage

% 0.52 0.52 0.52 0.52 Extrapolate using 1992-1996 nominal growth rate
Federal tax on

labor income

% 18.4 18.4 18.4 18.4 Constant over time
Tax on industrial & commercial prop. % 1.38 1.38 1.38 1.38 Constant over time
Sales tax rate % 6.89 6.54 6.31 6.19 Tx projections; extrapolation for 1999
Cost of capital % 12.82 12.82 12.82 12.82 Constant over time
Source: From Table 1 in the main report.

Applying the model to current tax issues in Texas

A large number of tax proposals have surfaced in Texas over the past couple of years. Most of these can usefully be analyzed using Texas-STAMP. Five of the most important such proposals are summarized below, followed by a discussion of their economic effects.

Five important tax proposals or changes
Sales tax cut Governor Bush recently proposed changes in the sales tax that would, according to the Governor Bush Committee, amount to a tax cut of $200 million. Specifically, the change would repeal the current 6.25% sales tax on over-the-counter medicines, diapers and first-aid items; and it would provide a two-week "back to school" sales tax holiday for school clothing and footwear.
Business R&D tax credit Texas is one of only five states that does not give businesses a tax credit for research and development (R&D) or for capital investments. Intel Corporation leads a coalition that is lobbying for an investment tax credit. Telecommunications firms, heavily concentrated in the North Dallas area, favor an R&D tax credit. The budget office estimates that a tax credit would cost about $250 million in lost revenue over a two-year period, which means an annual cost of $125 million. The R&D credit has the backing of Governor Bush.
Raise the homestead exemption by $10,000 In early 1997, Governor Bush proposed that the homestead exemption, then at $5,000 per residence, be raised by $20,000 for the purposes of computing school maintenance and operation (M&O) property tax. The intention of the proposal was to reduce the fiscal pressure on homeowners, who had seen their property tax payments rise rapidly over the previous decade. The direct effect of the larger exemption would be to lower tax revenue (to school districts) by $981 million, making this a sizeable tax cut. The legislature ultimately raised the exemption by $10,000, which is the policy change whose effects are simulated in this study.
Reduce the property tax rate by 13 per $100 As part of the 1998 package of property tax relief proposals, Governor Bush has proposed reducing the school M&O property tax by 13 per $100 (i.e. 0.13 percentage points), from its average of about $1.24 per $100 of valuation. The change would apply to property tax levied on residential as well as commercial and industrial property. The direct revenue effect would be to lower takings by $1.11 billion.
Exempt certain businesses from the franchise tax The business franchise tax is levied on corporate income and/or capital, depending on which method yields the most. The tax is particularly onerous on small businesses, which sometimes incur hundreds of dollars in expenses in order to calculate tax bills that may be as low as $100. In order to reduce the burden on small firms, Governor Bush has proposed exempting from the franchise tax all firms with a turnover under $100,000 annually. The direct effect would be to lower revenues by $28.6 million per year.

The economic effects of these tax changes are summarized in the next table. Some additional comments on the findings are in order.

The cut in the sales tax would lead to 10,953 more jobs. While this is a large number, it represents an increase of just 0.11% in the number of jobs in Texas. The "static" effect of this tax change would be to reduce state revenue by $200 million. However this would be offset to some degree by additional revenues that would result from the fact that more people would be working, and there would be more capital to subject to property tax. The net effect would be to reduce tax revenue (at the state and local levels together) by just $182 million.

Summary Effects of Tax Changes

A

Cut sales tax by $200m

  B

Business R&D tax credit of $125m

    Mean response 95% Range
    %   %    
Economic effects            
Number of jobs +10,953 0.23 +136 0.001 92-180
Capital stock ($ million) +900 0.22 +11 0.001 7-14
Wage rate ($/job/year) -31 -0.20 0 0  
Working age population +11,288 0.17 0 0  
Payroll ($ million) +44 0.03 +4 0.001 3-6
Revenue effects ($ million):            
"Static"            
Sales tax -200          
Franchise tax     -125   -125
Property tax (business)            
Property tax (residential)            
"Dynamic”            
Sales tax +3   +.2   0.16-0.30
Franchise tax +2          
Property tax (business) +13   +.2   0.10-0.20
Therefore            
Net effect on tax revenue -182 -1.78 -125 -0.61 -124.5 to -124.7
Memo items:            
Total state tax revenue 20,564          
Revenue from sales tax 12,248          
  C

Cut residential property tax via extra $10,000 exemption

D

Cut property tax via rate reduction of

13/$100

E

Exempt businesses with gross receipts of $100,000 or less from franchise tax

    %   %   %
Economic effects            
Number of jobs +25,449 0.265 +39,710 +0.41 +31 0.0003
Capital stock ($ million) +4,220 0.520 +5,059 +0.62 +2 0.0003
Wage rate ($/job/year) +45 0.145 -5 -0.02 0 0.0000
Working age population +52,990 0.408 +60,868 +0.47 0 0.0000
Payroll ($ million) +1,226 0.410 +1,186 +0.40 +1 0.0003
Revenue effects ($ million):            
"Static"            
Sales tax            
Franchise tax         -28.6  
Property tax (business)     -547      
Property tax (residential) -491   -563      
"Dynamic”            
Sales tax +67   +66   +.05  
Franchise tax +10   +12   +.01  
Property tax (business) +58   +70   +.03  
Therefore            
Net effect on tax revenue -355 -1.726 -962 -4.68 -28.5 -0.14
Memo items:            
Total state tax revenue            
Revenue from sales tax            

Source: From simulations using the Texas-STAMP model.

Rounding may occur in the numbers.

The business tax credit would have a surprisingly small economic effect - creating no more than about 180 jobs overall - but there is a clear and logical explanation for this. First, the tax cut is relatively small; it represents just 0.6% of state revenue, and would cut the cost of capital to Texas firms by a mere 0.05%. Second, the tax credit leaves corporations with more profit after tax, but over a third of this windfall goes immediately to the federal government, as the higher profit triggers higher payments of corporation income tax. Third, as the fast-diminishing windfall is paid to owners as dividends (or accrues as capital gains), it is subject to federal taxes on personal income, which will again reduce the amount left for owners. The net effect is to lower the after-tax rental cost of capital from 14.21% to 14.20%. It is not surprising that such a small change in the cost of capital will have almost negligible economic effects.

It is sometimes argued that if the business tax credit takes the form of an R&D tax credit, this would ultimately have additional "downstream effects." This reasoning is based on the idea that when firms locate their R&D in Texas, then manufacturing and other facilities will tend to follow. It is not at all evident that R&D leads and manufacturing follows; an equally plausible case can be made that manufacturing facilities lead and R&D follows, in which case the argument for providing tax credits for R&D (rather than for other forms of investment) is greatly weakened. The Texas-STAMP model treats all tax credits equally, and is not designed to measure the possible differential effects of different forms of tax credits.

On the other hand, these estimates are based on the assumption that the tax credit for R&D done in Texas is significantly offset by higher tax payments to the federal government. However, firms undertaking new R&D in Texas would benefit not only from the Texas tax credit, but also from the federal R&D incentive. The net effect is to lower the cost of R&D quite substantially, leading to new R&D expenditures for which we do not attempt to account. Thus our estimates of the effects of the Texas R&D should be thought of as lower bounds.

The effect of the $10,000 extra property tax exemption, according to the Texas-STAMP model, is to increase the number of jobs by 25,449 (+0.265%) and the capital stock by $4.2 billion (+0.520%). The increased exemption will add $1.2 billion to state payrolls and induce almost 53,000 working-age adults to enter the state.

The Texas-STAMP model shows that a 13 per $100 cut in the property tax rate would have a substantial economic effect: employment would rise by 39,710 and the capital stock by $5.1 billion. While the direct ("static") loss of tax revenue would be $1,110 million, the additional economic activity triggered by this change would lead to $148 million in extra tax revenue (the "dynamic" effect), for a net revenue loss of $962 million.

Exempting businesses with gross receipts not exceeding $100,000 from the franchise tax would have almost no effect on the economy: The effects on jobs and capital spending, and therefore also tax revenue, would be negligible. However the main purpose of this tax cut is to reduce the burden of paperwork for small firms, an effect that the Texas-STAMP model is not designed to measure.

These simulation exercises illustrate the manner in which the Texas-STAMP model can shed light on the economic effects of changes in the system of state taxes in Texas. As with any modeling, the results should be taken as indicative of the orders of magnitude involved, since it is not possible to predict the effects of tax changes with great precision.