Public Choice

, Volume 171, Issue 1–2, pp 207–221 | Cite as

The political economy of sales taxes and sales tax exemptions



I analyze the choice politicians face when seeking votes from groups that lobby for sales tax rate decreases or tax exemptions, given the constraint that politicians want to raise a certain amount of revenue. Using data on sales taxes, I develop a model predicting a positive relationship between the number of exemptions and the sales tax rate. The estimation results provide support for this prediction. Each additional exemption is associated with an increase of between 0.10 and 0.25 percentage points in the tax rate.


Sales taxes Tax exemptions State politics Interest groups 

1 Introduction

Politicians face conflicting demands from their constituencies. To maximize their vote shares in elections, they attempt to balance these demands. Consumers might demand that politicians raise corporate taxes, while corporations pressure politicians to lower their own tax bills. Politicians can satisfy both groups by supporting increases in nominal tax rates as well as by introducing exemptions or loopholes into tax codes that lower effective tax rates (Anderson et al. 1987).

I analyze how politicians balance sales tax rates and exemptions, given the constraint that they want to raise a certain amount of revenue. I study the equilibrium relationship between the tax rate and the number of exemptions in a state. Theory suggests that when tax rates on a group rise, that group has an incentive to lobby for tax exemptions and politicians have an incentive to accommodate the demands.

Sales tax revenue as a share of a state’s total revenue ranges from zero in states that do not levy a sales tax to 44% in Washington State. The tax rate, the level of economic activity, and the prices of taxed goods determine the amount of tax revenue collected. While sales tax rates vary little among states, states vary greatly in the goods and services they exempt and how they administer the taxes.

To study this variation, I compiled an inventory of all sales tax exemptions. This inventory allows for a quantitative analysis using a model of the impact of exemptions on tax rates and tax revenues across states. I then estimate the equilibrium relationship between tax rates and exemptions and find that it is positive and statistically significant. The finding supports my theoretical model, and the relationship matters for policy purposes since it implies that raising tax rates may not boost revenues as much as legislators might hope for.

The next section reviews the literature and introduces the conceptual model for analyzing the relationship between sales tax rates and exemptions. The third section provides a brief background on the variety of tax rates and exemptions across states. I then describe the methodology I used to collect and classify the tax-exemptions data. The fifth section presents the data analysis; I conclude in the final section.

2 Literature and model

The literature relating sales tax rates to sales tax exemptions is not large. Some of the literature focuses on the impact of nonprofits’ sales tax exemptions on the allocation of resources between the nonprofit and for-profit sectors (Hansmann 1987). Other work analyzes the effectiveness of certain business-tax incentive programs for increasing business activity in a state (Hall 1999; Ihlanfeldt 1995). Still other studies test predictions of sales tax models (Besley and Rosen 1998), estimate the elasticities of the demands for and the supplies of individual items subject to sales taxes (Bruce et al. 2006; Hawkins 2002), and how effective taxes, including taxes on soda or sugar, can be for improving health (Powell and Chaloupka 2009; Brownell et al. 2009; Chouinard et al. 2006). Last, a study shows that “loopholes” are sometimes created in order to buy off opposition to an increase in U.S. income taxes (Anderson et al. 1987).

The model I use to understand sales taxes and exemptions borrows from Peltzman (1976, pp. 222–224), which analyzes how politicians regulate firms, given that firms demand regulations that increase their output prices and consumers demand regulations that lower prices. Peltzman’s work expands on and generalizes Stigler’s (1971) foundational work on the so-called capture theory regulation.

In my model, a politician competes for the votes of two groups in order to maximize electoral votes: one that prefers reductions in the tax rate, and one that prefers increases in tax exemptions. The model presumes that setting tax rates and exemptions redistributes wealth. Given a revenue constraint, politicians cannot fully please both groups. When politicians lower tax rates, thereby increasing support from one group, they lose support from the other group because the revenue constraint forces them to reduce tax exemptions. Similarly, when exemptions are increased, the politicians have to raise tax rates (or expand the basis of taxation at given tax rates) to keep revenues constant. They therefore must choose a combination of a tax rate and a set of exemptions that maximizes their chances of reelection. The equilibrium condition of the politician’s maximization problem states that the marginal return from increasing exemptions must equal the marginal cost from increasing sales tax rates. Assuming that all states raise similar amounts of revenue per capita, the revenue constraint defines all possible equilibrium combinations of tax rates and exemptions. Figure 1 illustrates this situation.
Fig. 1

Theoretical model

The model predicts a positive correlation between sales tax rates and exemptions. Thus in my empirical model I test for the equilibrium relationship between exemptions and tax rates.1

3 Variations in sales taxes and exemptions across the United States

States vary in the definitions and in the categories of taxable transactions they adopt. I provide a brief discussion of these differences here, but for a fuller discussion I refer interested readers to an online appendix.

As for definitions, states differentiate themselves by how they delineate the sales tax base, which turns largely on what qualifies as tangible personal property. Tangible personal property items include cars and trucks.

One restriction on the tax base concerns federally mandated exemptions. These include, among other categories, transactions consummated on federal Indian reservations and in interstate commerce.

Aside from such federal restrictions, states choose what to exempt. One can classify such exemptions based on types of transactions, implementation, tax rates, and policy. Transaction-based exemptions, in turn, depend on the type of product, use, and transacting entity. Implementation differs according to whether an exemption applies automatically or not. Next, some exemptions apply in full and others only in part. Finally, exemptions differ in terms of the policies that create them, such as whether the state designs them for social impact and whether the state finds it too costly to collect taxes on particular types of transactions. Table 1 categorizes exemptions into several categories.
Table 1

Types of exemptions


Federal preemption principle






Automatic (pert se)

Approval-based (certificate of exemption)

Tax rate






Too costly to tax

Sales tax versus other special taxes

Special exemptions

Back to school tax tax holiday

Energy star tax holiday

4 Collecting and categorizing the data

4.1 Data sources

No unified, systematic source reports the numbers and types of all sales tax exemptions in each state. Instead, I collected data from a variety of sources. These sources include state tax codes, tax rules and regulations, and information briefs or reports published on each state revenue department’s webpage. To compile this comprehensive inventory of exemptions, I consulted over 8800 pages of information.

Sales tax codes provide the general framework for enacting a sales tax. They provide an initial understanding of how each state defines its tax base and exempt transactions, if any. However, the codes are not standardized across states and do not list all exemptions. Sales tax rules and regulations complement sales tax codes; they represent each state’s effort to clarify the circumstances under which sections of the sales tax codes apply or do not apply. Thus, they provide useful information about what transactions are exempt from sales taxes.

Furthermore, I reviewed publications listed on each state revenue department’s website that provide information on the latest changes in exemptions and tax rates, as well as information on the forms required to claim certain exemptions. Of all 50 states, only five (California, Iowa, Louisiana, New York and Washington) maintain an updated, comprehensive list of their exemptions. Tax specialists from the department of revenue of many of the other states assisted me in identifying the relevant rules and regulations.

Another source of information is the Streamlined Sales Tax (SST) Project, a unique attempt to standardize and harmonize definitions of goods and transactions for sales tax purposes. The National Governors Association (NGA) and the National Conference of State Legislatures (NCSL) initiated this project in 1999 in response to two Supreme Court decisions: Bellas Hess v. Illinois (1967) and Quill Corp v. North Dakota (1992). In both cases, the court had ruled that a state could not require a remote seller not having a physical presence in the state to collect taxes on sales of items shipped to that state. The court explained that sales tax collection by a business without a physical presence was too complicated under the current sales tax system. To address this difficulty, the SST Project created the Streamlined Sales and Use Tax Agreement. This agreement aims to simplify sales tax administration and certain sales tax exemptions by adopting uniform standards and definitions. Twenty-four states have adopted this agreement.2

Each of the participating states generates a State Taxability Matrix form that records the state’s sales tax coverage for certain standardized categories of transactions. The forms include three major sections: administrative definitions, state tax holidays, and product definitions for ten categories of products. The product categories are clothing and related products, computer-related products, mandatory computer-software maintenance contracts, optional computer-software maintenance contracts, digital products, food and food products, prepared food options, healthcare products (such as drugs, durable medical equipment, mobility-enhancing equipment, and prosthetic devices), telecommunications, and telecommunications-related products. For each category in the State Taxability Matrix, a state lists whether it taxes or exempts a product or transaction and also lists the section of the sales tax code that applies to the product or transaction. However, while the taxability-matrix forms helped me collect data, they record information only on a fraction of the transactions and products a state exempts, and currently only the 24 member states of the SST Project fill out these forms each year.

My data for sales tax rates come from 2012, while data on sales tax revenue, Gross State Product (GSP) information, and resident-population estimates for each state come from 2009 publications by the US Census Bureau. Table 2 reports the sales tax rate for each state. I obtained data on local option taxes from 2010.3 tates allowing statutory local sales tax options permit some legal entities within their states, such as cities, counties or special districts, to levy a tax on a good in addition to the statewide sales tax. Information about each state’s sales tax exemptions comes from the latest updates of state publications, ranging from 2008 to 2012. The SST taxability-matrix forms come from 2011.
Table 2

Sales tax by state


Sales tax (%)

















































New Jersey


New Mexico


New York


North Carolina


North Dakota








Rhode Island


South Carolina


South Dakota














West Virginia






My inventory of sales tax exemptions focuses on identifying tax-exempt transactions and goods. Accordingly, it does not include details on how to claim the exemptions or any other background legal information.

4.2 Devising exemption categories

As mentioned previously, one can categorize sales tax exemptions according to a variety of criteria, and states do not have common definitions for exempt products, services, or transactions. To conduct a statistical analysis, I needed to develop standardized exemption categories that would make counting sales tax exemptions more accurate.

A limitation of my classification of categories is that it cannot account for many variations in exemptions. For example, in some states, “food products” refers to unprocessed food ingredients only. In other states, it also includes candy, soda, dietary supplements, and baked goods. Therefore, while many states exempt food products, the actual products exempted differ widely.

I developed two criteria for defining exemption categories. First, the categories had to be specific enough that exemptions could not fall into more than one of them. Second, the categories had to be broad enough to accommodate a wide variety of definitions that states may have for specific products or transactions.

I categorized exemptions according to their economic characteristics. This approach resembles how states define transaction-based exemptions and count them as entity-based, product-based, or use-based.

I identified 17 broad economic exemption categories. Each category includes a variety of exemptions that qualify as entity-based, product-based, or use-based, and as either partial or full. The 17 categories comprise food, health, clothing, transportation, housing, capital goods/industry, computer, energy/utilities, farming/agriculture, business incentives, school-related, nonprofits, government-related, entertainment, services, tax holidays, and other. Clearly, developing these categories and assigning exemptions to them involved many judgment calls. Table 3 describes my seventeen categories.
Table 3

Exemption categories and subcategories





Food 1

Food ingredients

Food 2

Candy, soda, or bottled water or vending machine transactions

Food 3

Meals in educational institutions or certain health-care facilities

Food 4

Other food-related transactions

Overall description

Exemptions regarding food ingredients, candy, soda, certain meals, as well as other transactions involving food items


Health 1

Prescription drugs

Health 2

Nonprescription drugs

Health 3

Durable medical equipment

Health 4

Mobility-enhancing equipment

Health 5

Dental equipment

Health 6

Other health-care-related transactions

Overall description

Exemptions regarding prescription and nonprescription drugs, durable medical equipment, mobility-enhancing equipment, dental equipment, as well as other health-care-related transactions



Exemptions involving clothing item, accessories, or any clothing-related items


Transportation 1

New or used vehicles powered by alternative fuel or with low emissions

Transportation 2

New or used vehicles (regular fuel), including watercraft, aircraft and/or railroad stock

Overall description

Exemptions involving new and/or used vehicles (trailers, semitrailers, cars), alternative-fuel vehicles, as well watercraft, aircraft, and related items (parts, etc.).


Housing 1

New or used homes (mobile, modular)

Housing 2

Building materials

Housing 3

Other housing-related transactions

Overall description

Exemptions involving new and/or used homes (mobile, modular), building materials, as well as other housing-related transactions

Capital goods/Industry


Exemptions involving machinery, tools, and equipment and parts used in various industries such as manufacturing, processing, etc.



Exemptions involving computer equipment, software development, digital products, and IT-related services


Utilities 1

Utilities for residential purposes

Utilities 2

Utilities for alternative/renewable energy production; alternative fuels; solar panels, etc.

Utilities 3

Utilities for commercial (industrial) purposes

Utilities 4

Utilities for agricultural purposes

Utilities 5

Other utility-related transactions

Overall description

Exemptions involving utilities (electricity, water, fuel) for residential, commercial, and agricultural purposes, as well as other utility-related transactions


Farming 1

Farm/agricultural machinery

Farming 2

Farm/agricultural products (used to feed livestock, etc.)

Farming 3

Medication for livestock, pest treatments, etc.

Overall description

Exemptions involving farm/agricultural machinery, products, medication, etc.

Business Incentives


Exemptions involving certain business activities that fall within certain state economic-development programs



Exemptions involving school-related transactions (charges, fundraising activities) and other transactions performed by educational organizations



Exemptions involving certain nonprofit organizations. For most states, the nonprofit status according to the US IRS code [26 U.S.C. 501 (©3)-(7)] does not automatically entitle such organizations to sales tax exemptions.



Exemptions involving government agencies and instrumentalities as well as other publicly owned entities (public utilities, regulatory commissions, etc.)



Exemptions involving entertainment-related activities: film production; selling, renting, or leasing motion picture films; etc.



Exemptions involving certain personal and professional services

Tax Holidays


Information about whether or not a state has a sales tax holiday, as well as details regarding the holiday



A diverse category of exemptions, ranging from sales of lottery tickets, bibles, flags, to caskets, zoo animals, packaging materials, etc.

One important guide I consulted in developing these categories was a publication by California’s State Board of Equalization (Publication no. 61 “Sales and Use Taxes: Exemptions and Exclusions California Revenue and Taxation Code Part 1, Division 2,” published in February 2012), which lists sales tax exemptions in California. However, my constructed categories differ from those in the California publication. I modified them to reflect the types of goods, transactions, and entities.

4.3 Caveats and subcategories

I did not count exemptions based simply on how many were listed in a state’s tax code. Some states have detailed and very specific conditions about which types of goods or services are exempt and when and how exemptions apply. Other states adopt a few broad and generic exemptions. For an example of the latter, Massachusetts exempts “materials, tools, machinery and replacement parts that will be used directly and exclusively in the actual manufacture, processing or conversion of tangible personal property to be sold, including the publishing of a newspaper or the operation of commercial radio broadcasting or television transmission” (Massachusetts General Laws, Part I Administration of the Government, Title IX Taxation, Chapter 64H Tax on Retail Sales of Certain Tangible Personal Property, Sect. 6S Exemptions). In contrast, Colorado exempts machinery and tools for manufacturing under very specific conditions. Among other conditions, they must be (a) used in Colorado; (b) used directly and predominantly to manufacture tangible personal property for sale or profit; (c) of a nature that would have qualified for the federal investment-tax credit under the definition of Sect. 38 property found in the IRS Code of 1954, as amended; (d) included on a purchase order or invoice totaling more than $500; and (e) capitalized (C.R.S. 39-206-709.1). Moreover, states can have very narrow definitions for categories of goods. One example concerns how states define food products. Some states exempt only general unprepared grocery items; others also exempt items like candy, soda, bubble gum, bakery items, and dietary supplements.

Consequently, comparisons among such exemptions are challenging. For simplicity and accuracy, I developed exemption subcategories. When a state had any exemption that fell within a specific subcategory, I assigned a value of one to that subcategory. Each of my main categories has up to six subcategories. In total, 30 categories and subcategories resulted from my classification choices, as shown in Table 3.

For my analysis, I include exemptions only when states did not apply the general sales tax rate to a good, service, or transaction. I do not consider partial exemptions.

Some states have one standard form that can be used by either party (buyer or seller) in any tax-exempt transaction as validation for not paying (buyer) or collecting (seller) sales tax. Other states use forms that cover only a specific type of transaction. While the number of exemption forms a state uses does not directly indicate the ease of claiming an exemption, it does differentiate how states implement sales tax exemptions.

5 Descriptive statistics and estimation results

The theoretical model assumes that politicians can choose any combination of sales tax rate and exemptions that satisfies a revenue constraint. However, in some states, politicians cannot set the sales tax rate because either the constitution or referendums constrain them. As mentioned previously, five states do not have impose a sales tax because their constitutions prohibit it; I have therefore omitted these states from my study. In Colorado, which I include in my study, voters passed a referendum that does not permit politicians to increase the sales tax rate.4

I also have omitted Hawaii from my analysis. Hawaii’s sales tax is a three-tiered general ad valorem tax assessed on all business activities: 0.15% on insurance agents’ commissions; 0.5% on wholesaling, manufacturing, producing and wholesale services, and importing goods for resale; and 4% on all others.5 Furthermore, Hawaii allows no exemptions of any kind to its ad valorem tax. Since Hawaii has a multi-tiered sales tax rate, choosing a single tax rate for my dataset would have been arbitrary.

I estimate the regression model:
$${\text{Sales Tax Rate}}_{\text{i}} =\upbeta_{1} +\upbeta_{2} {\text{Exemption}}_{\text{i}} +\upbeta_{3} {\text{SalesTaxRevPC}}_{i} +\upbeta_{4} {\text{TaxBase}}_{\text{i}} +\upvarepsilon_{\text{i}} .$$
In this regression, the unit of observation is state i. I control for sales tax revenue per capita because the theoretical model suggests that the politician picks the sales tax rate-exemption combination subject to a revenue constraint.6 A further constraint is the tax base. A narrow tax base may force a different trade-off in setting the sales tax rate and exemptions than a broader tax base. To compute the tax-base measure, I consulted the state laws and regulations regarding sales taxes and assigned to each state a value between one and five, where five indicates the broadest tax base.

For total exemptions, I have two measures: The first stems from my main 17 exemption categories and their various subcategories (Table 3). The second measure collapses all of the subcategories within each exemption category and merges two categories—government-related and nonprofits—to create a new category: exempt organizations. Both nonprofits and government agencies are exempt from sales taxes. Thus, by grouping them into the broader category of exempt organizations, I capture all sales tax exemptions related to organizational status. This specification simplifies the breakdown of exemptions further and narrows the number of categories to 16.

My first measure of exemptions sums full exemptions from all exemption subcategories within the 17 main exemption categories. When a main category does include a subcategory, and the state allows exemptions in the main category, I add one to the count. The exemption count across the states ranges from 19 to 31, with an average of 24.2 (see Table 4).
Table 4

Descriptive statistics



Standard deviation



Sales tax (%)





Sales tax revenue per capita ($)





Tax bases





Exemptions: broad measure





Exemptions: narrow measure





N = 44. AK, DE, HI, MT, NH, and OR excluded

My second measure consists of an exemption count based on my main 17 categories. If a state allows exemptions in more than half of the subcategories, I assign a value of 1.0 to that main category. Conversely, I code the main category as 0.0 if it allows exemptions in less than 30% of the subcategories, and I assign a value of 0.5 if the state allows exemptions in more than 30% of the subcategories, but less than one-half of them. I then sum the values assigned to each category. For this second measure the mean number of exemptions is 11.4 and the exemptions range between seven and 14.5 (Table 4).

Table 4 also shows summary statistics for my other variables. The mean sales tax rate across the 44 remaining states is 5.6%, ranging from 2.9 to 7.25%. Sales tax revenue per capita from 2009 averages about $778 per state and ranges from $421 to $1756. The tax base values range between one and five.

Table 5 reports the regression results when I use my broad exemption measure. The first column includes exemptions, sales tax revenue per capita, and, to allow for nonlinearity, sales tax revenue per capita squared. The second column adds indicators for breadth of the various sales tax bases. In columns 3 and 4, I show that my results for columns 1 and 2 are robust when also controlling for local options. In all four specifications, the point estimates on the exemption measure are positive and statistically significant, lending support to my hypothesis. The point estimates indicate that one additional exemption is associated with an increase in the sales tax rate of between 0.10 and 0.15 percentage points. The last two columns show that when controlling for the presence of a local option law, the resulting levels of statistical significance improve slightly, lending further support to my hypothesis.
Table 5

Summary of results (broad measure)

Dependent variable

Sales tax rate (1)

Sales tax rate (2)

Controlling for local options

Sales tax rate (3)

Sales tax rate (4)

Exemptions (broad)









Sales tax revenue per capita









Sales tax revenue per capita^2









Local option







Tax base 2









Tax base 3









Tax base 4









Tax base 5



















* Indicates p values <0.1; ** <0.05; *** <0.01

Tax base 5 is the broadest tax base

As for my control variables, the first two specifications include the levels and the squares of sales tax revenue as covariates. The result supports the finding that sales tax rates are positively correlated with sales tax revenues, but also that this correlation is weaker at higher revenue levels. Finally local options are negatively correlated with sales tax rates, and this relationship is statistically significant in both specifications.

The reference group for my tax-base indicators in all columns in Table 5 is states with the narrowest sales tax bases. The point estimates on all but the third tax-base category are positive and statistically significant. And with the exception of this third category, the coefficients are larger in magnitude as the tax base broadens.

The finding that sales taxes tend to be higher when the tax base is broader is somewhat surprising because broader bases allow for lower taxes, holding revenue constant. Figure 2 shows the partial regression plot between the sales tax rate and sales tax exemptions. The graph displays the individual data points and the regression line showing the positive correlation between those two variables. The positive correlation appears not just in a couple of states but throughout the data.
Fig. 2

Partial regression plot of sales tax and all exemptions (broad measure). Note The vertical axis displays the residuals of regressing the sales tax on the independent variables, excluding tax exemptions. The horizontal axis displays the residuals from regression total exemptions on the remaining independent variables

Table 6 shows the results from re-estimating the specifications in Table 5, but now using the narrower measure of exemptions. Because the range of the exemption variable shrinks, I expected that the point estimates on this exemption variable would be less precise. Further, given that these categories are narrower than in Table 5, I expected that the point estimates would be larger in magnitude.
Table 6

Summary of results (narrow measure)

Dependent variable

Sales tax rate (1)

Sales tax rate (2)

Controlling for local options

Sales tax rate (3)

Sales tax rate (4)

Exemptions (narrow)









Sales tax revenue per capita









Sales tax revenue per capita^2









Local option







Tax base 2









Tax base 3









Tax base 4









Tax base 5



















* Indicates p values <0.1; ** <0.05; *** <0.01

Tax base 5 is the broadest tax base

The findings in Table 6 broadly support my hypothesis. As with the previous exemptions measure (see Table 4), all point estimates across the four regression equations are positive. The estimate for the exemption measure that includes the tax-base indicators is statistically significant at the 5% level (Table 6, column 2), and the other estimate (Table 6, column 1) barely misses significance at the 10% level. Controlling for local options still leaves one estimate (Table 6, column 3) short of the 10% level of significance. The reduction in the level of statistical significance was expected, given that the regressions now use the more narrowly defined exemption variables, which display less variance. The point estimates on the control variables have the same signs and similar levels of significance as those in Table 5, thus supporting the previous findings that higher sales tax rates are positively correlated with per capita sales tax revenues and the broadness of the tax base.

Figure 3 shows the partial-regression plot for the narrow specification of Table 6. As in the previous partial-regression plot (Fig. 2), a clear positive pattern between sales tax exemptions and sales tax rates continues to hold.
Fig. 3

Partial regression plot of sales tax and all exemptions (narrow measure). Note The vertical axis displays the residuals of regressing the sales tax on the independent variables, excluding tax exemptions. The horizontal axis displays the residuals from regression total exemptions on the remaining independent variables

I performed several robustness tests to further examine my hypothesis of an equilibrium relationship between sales tax rates and sales tax exemptions. First, I added a regional control variable to account for cross-influence between neighboring states’ sales tax rates or exemptions. Second, I ran specifications that control for the state income tax revenue per capita. Third, I re-tested the equations with California removed from the dataset.7 Finally, I re-tested the equations using the least-absolute-deviations method. All of these alternative specifications supported my reported findings.

6 Conclusions and policy implications

This paper shows a positive relationship across the states between the number of sales tax exemptions and the sales tax rate. I find that each additional exemption is associated with a 0.10 to 0.15 percentage point increase in the sales tax rate for my broad measure of exemptions, and with a 0.14 to 0.24 percentage point increase for my narrow measure of exemptions. Those magnitudes indicate that one additional exemption is associated with an increase of between 9% (100[0.10/1.1]) and 13% (100[0.15/1.1]) of the standard deviation in tax rates. They also mean adding another sales tax exemption is associated with a percentage point increase in the sales tax rate of 0.10 to 0.25. Thus, if a state currently has a sales tax rate of 5%, adding another sales tax exemption (as defined in previous sections) is equivalent to increasing the state’s sales tax rate from 5% to between 5.1 and 5.25%. This equilibrium relationship serves as an example of the unintended consequences of a public policy. Individuals and groups who lobbied for more exemptions did not necessarily intend for the sales tax rate to be raised, but their actions had that effect.

High sales tax rates increase the incentive to lobby for special exemptions. When accompanied by exemptions, higher rates may not increase total tax revenues. This provides one explanation for why taxing agencies’ estimates of such revenue increases often are too optimistic. (Cross-border shopping and other tax avoiding behavior also offset expected revenue increases.) To make their estimates more accurate, policymakers should take the relationship between sales tax rates and sales tax bases into account.


  1. 1.

    To test this hypothesis, I assume that cross-border shopping or any online shopping that might give rise to an erosion of tax and exemption differences across states is quantitative small, relative to all sales within the state.

  2. 2.

    The states are: Arkansas, Georgia, Indiana, Iowa, Kansas, Kentucky, Michigan, Minnesota, Nebraska, Nevada, New Jersey, North Carolina, North Dakota, Ohio, Oklahoma, Rhode Island, South Dakota, Tennessee, Utah, Vermont, Washington, West Virginia, Wisconsin, and Wyoming.

  3. 3.

    I chose 2009 for revenue data because it falls within the 2008-to-2012 period, for which I have data on sales tax exemptions. Owing to recessionary conditions in that time frame, sales tax revenues might have been below average; however, if the revenue reduction was similar across all states, it should not affect my estimates of the equilibrium relationship between sales tax rates and exemptions.

  4. 4.

    I kept Colorado in the sample because if politicians there decide to reduce the number of sales tax exemptions, they are unable to raise sales tax rates to offset the narrower sales tax base. The constitutional constraint on raising the state sales tax rate may lead to less significant results if exemptions are reduced, and the sales tax cannot be raised.

  5. 5.

    Tax Facts 96-1, General Excise vs. Sales Tax

  6. 6.

    Sales tax rates are from 2012, while data on exemptions come primarily from earlier years, starting with 2008. This fact mitigates concerns that the error term in Eq. (1) is correlated with exemptions.

  7. 7.

    This is done because California has the highest sales tax rate in the United States and allows one of the largest number of exemptions.



This paper is based on a my co-authored working paper with (Militaru and Stratmann 2014).

Supplementary material

11127_2017_434_MOESM1_ESM.docx (32 kb)
Supplementary material 1 (DOCX 31 kb)


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Copyright information

© Springer Science+Business Media New York 2017

Authors and Affiliations

  1. 1.George Mason UniversityFairfaxUSA

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