Do Tax and Expenditure Limits Hinder the Condition of Public Infrastructure? The Case of the Nation’s System of Bridges

Abstract

Tax and expenditure limitations (TELs) imposed on state and local governments is a popular policy approach to limit the growth in government. At the same time these limits may hinder the ability of state and local governments to provide services and make investments in public infrastructure. We test the relationship between state-level TEL restrictiveness and the United State’s network of highway bridges. We generally find that more restrictive TELs have a weak negative impact on the percentage of bridges deemed structurally deficient but a positive impact on the percentage of bridges deemed functionally obsolete. The states with the most restrictive TELs, those that restrict both revenues and expenditures, tend to have a smaller share of their bridges that are either structurally deficient of functionally obsolete.

Keywords

economic development infrastructure: economy legislation policy regulatory issues

So all told, our aging transportation infrastructure costs American businesses and families about US$130 billion a year. That’s a tax on our businesses; that’s a tax on our consumers. It is coming out of your pocket. It’s a drag on our overall economy.

President Obama speaking today (Nov 2, 2011) about his proposed initiatives to help rebuild America’s roads and bridges

Introduction

The state of our nation’s infrastructure has been cause of concern for a number of years. The American Society of Civil Engineers (ASCE) issues an annual “Report Card” on the nation’s infrastructure and each year the ASCE offers a bleak assessment. For the most recent, the ASCE concluded that “[f]or the second time, America’s infrastructure rates a cumulative grade of D. While not all categories fare as badly or are plagued by the same problems, delayed maintenance and chronic underfunding are contributors to the low grades in nearly every category” (American Society of Civil Engineers [ASCE], 2009, p. i).

The condition of our nation’s bridges is of particular concern. The issue was brought to the forefront of the national consciousness with the collapse of the I-35W Mississippi River Bridge in Minnesota on August 1, 2007, which killed 17 people. While the percentage of bridges experiencing deterioration has declined over the past decade (see Figure 1), as of 2009, 11% of total highway bridges in the United States were classified as “structurally deficient” according to the Federal Highway Administration (FHWA). Over 20% of the bridges in five states—Pennsylvania, Oklahoma, Iowa, Rhode Island, and South Dakota—are structurally deficient. The FHWA estimates that it will take US$70.9 billion to address the maintenance concerns on the deficient bridges. Since bridges are necessary to facilitate the movement of people and goods to markets, investment in bridges and other infrastructure is important not only for the safety of motorists, but also to expand economic activity and growth.

Figure 1.

Condition of U.S. Bridges Over Study Periods.

The impact of the stock of public infrastructure on the economic growth has been the subject of numerous studies. While the link between public infrastructure and economic growth has been previously examined (e.g., Johnson, Deaton, & Segarra, 1988; Ratner, 1983), it was the work of David Aschauer (1989a, 1989b, 1989c) that sparked a resurgence of interest. Aschauer concluded that a 10% rise in the public capital stock would raise the productivity of other factors of production (i.e., growth) by as much as 4%. Gramlich (1994, p. 1176) claims that the work of Aschauer “hit the magic button” in terms of linking infrastructure investments and economic growth; declining investments in our public infrastructure creates a constraint on economic growth.

The findings of Aschauer have also been widely challenged with criticism ranging from the unique nature of the time period he studied (e.g., Holtz-Eakin, 1994), spurious correlation due to the nonstationary nature of the data (e.g., Aaron, 1990; Hulten & Schwab, 1991; Jorgenson, 1991), simple misspecification of the models (e.g., Tatom, 1991a, 1991b), to concerns about the direction of causation (Fernald, 1999). While many of these studies challenge the magnitude of the infrastructure and economic growth relationship, the literature has consistently found that public infrastructure is an important piece of the economic growth and development process. One way to think about this piece of the puzzle is that investment in infrastructure is a necessary but not a sufficient condition for economic growth (Deller, 1991, 1997; Halstead & Deller, 1997). In other words, the lack of adequate public infrastructure can create a bottleneck for the economy placing a drag on economic growth. But at the same time, blind investment on public infrastructure does not guarantee that economic growth will occur.

The transportation network, composed of the inter- and intrastate highways and bridges, along with all of the supporting lower volume roads, are an integral part of the public infrastructure system. While the network of roads and bridges has no intrinsic value other than the land and materials making up the road network, their value is reflective of the services that they provide. In the United States, there are some 4.03 million miles of public roads and about 597,000 bridges supporting some three trillion miles traveled. In 2008, the U.S. transportation system moved nearly 21.5 billion tons of freight worth US$16.8 trillion. Trucks provided the majority of freight movement with 61.6% in weight and 66.8% in dollar value. The highway transportation system is a complement to the transportation industry, where an efficient and well-maintained network of highways and bridges improves the efficiency of the transportation industry. This improved efficiency ripples throughout the economy increasing levels of economic growth and development.

The efficiency of the network of roads and bridges depends not only on engineering standards but also on financial resources to maintain and reinvest in the system. As outlined by Munnell (1992), the decline in public resources devoted to transportation infrastructure though the 1970s and 1980s, coupled with the work of Aschauer, spurred an ongoing political debate over the nation’s public infrastructure. In 2007, the National Chamber Foundation of the U.S. Chamber of Commerce estimated that US$222 billion in public investment in highways and transit is needed annually to maintain our current surface transportation system, and an annual public investment of US$288 billion is needed to advance the system to a level that enhances the nation’s productivity.

Much of the reinvestment in the network of roads and bridges falls to states. In 2008, local governments owned about 76% of public roads. The federal government owns approximately 3% of public roads, most of which are located in national parks and forests, military garrisons, and Native American reservations. State governments own the remaining 19% of public roads, which includes most of the highways in the Interstate highway system. In 2008, state governments provided 50.7% of all funds for the road system, but accounted for 59.2% of all spending. The federal government provided 21.7% of all funding, but directly spent only 1.5%. Local governments supplied 27.6% of the funds, but accounted for 33.7% of the spending. Clearly, there is significant transfer of transportation funds from the federal to the state and in turn to local governments.

Funding for and expenditures on public infrastructure is further complicated by the imposition of tax and expenditure limitations (TELs). Today, 46 states have some form of constitutional or state statutory limits on the ability of local and/or state governments to raise taxes and/or expenditures (Amiel, Deller, & Stallmann, 2009; Kioko, 2011; Mullins & Wallin, 2004). The most direct argument for imposing TELs is that public officials lack the fiscal discipline to control taxing and spending; constitutional and/or statutory limits are needed to impose discipline (Fraser, 2005). But do these limits hinder the ability of state and local governments to make the necessary reinvestments in our public infrastructure system?

Unfortunately, the literature mapping the connection between TELs public infrastructure reinvestment is limited. Nicholson-Crotty and Theobald (2011) examine the roll of TELs on public infrastructure expenditures. They find that as the restrictiveness of TELs increase, the increase in own-source funding contributed by states for public infrastructure in response to federal grants decreases. States without TELs increase own-source funding by US$0.66 for every additional dollar received from federal grants. States with more lenient TELs contribute US$0.62 for every additional dollar of money received from the Highway Trust Fund and states with a TEL of average restrictiveness contribute US$0.59 per an additional dollar of federal aid. These results suggest that states with more restrictive TELs rely more heavily on the federal government for help with infrastructure improvements and contribute fewer own-source revenues compared to states without a TEL. Nicholson-Crotty and Theobald (2011) focus only on government expenditures on public infrastructure and do not address how TELs impact the quality of public infrastructure. The analysis of how TELs are directly related to infrastructure conditions, specifically high-volume statement maintained bridges presented in this study is an important extension of their work.

Anecdotally, there is some evidence to suggest that restrictive TELs lead to greater deterioration of public infrastructure. Consider the case of Colorado’s Taxpayers Bill of Rights (TABOR) that was added to Colorado’s Constitution in 1992. The restriction limited the growth of government spending to a fixed percentage of the previous year’s budget. The recession of 2001 created a dire situation for the state; the rules of TABOR forced a significant downward ratcheting that affected the ability of the state and local governments to support public education, public health, and protective services such as police and fire. More importantly, it essentially put a halt to any reinvestments in the state’s transportation infrastructure. In 2005, the business community of Colorado began to question the wisdom of TABOR. Commerce and economic development groups in fifteen major communities supported the suspension of the TABOR limits, as did Colorado Concern, a group of 80 top CEOs and business leaders in Colorado. Even the Chamber of Commerce in Colorado Springs, the community that originated the TABOR amendment, endorsed putting the spending limit on hold. The Denver Chamber of Commerce was particularly concerned about the inability of the state to invest in the highway system vital to the Denver economy. In 2005, the voters of Colorado passed a referendum to suspend TABOR for a period of 5 years to allow for critical reinvestment in public services including the highway system.

The business community of Colorado argued that limits, such as TABOR, the most restrictive TEL in the United States, put the state’s economy at risk. They argued that the inability to reinvest in key public services, such as the transportation network of roads and bridges, created a bottleneck in the economy that deterred future economic growth. The lesson from Colorado is that limits in the forms of TELs can lead to an under investment in public infrastructure.

Nationwide, it appears on face value that the presence of tax and expenditure limits impact both the percentage of bridges classified as deficient (either structurally deficient or functionally obsolete) as well as the rate of improvement in bridge condition (Figures 2 and 3). Consider first the difference in bridge conditions between states that have expenditure limitations and those that do not (Figure 2). Two patterns in the trends of bridge conditions are apparent: (a) states without a TEL have a smaller percentage of bridges classified as structurally deficient and (b) the downward trend in percentage of deficient bridges is steeper for states without an expenditure based TEL. This suggests that states without expenditure-based TELs have improved the status of their infrastructure at a faster rate than states with an expenditure-based tax and expenditure limit.

Figure 2.

Percentage of Bridges Deficient by Expenditure Focused TEL.

Figure 3.

Percentage of Bridges Deficient by Revenue Focused TEL.

Likewise, the percentage of deficient bridges between states with tax limitations and those that do not reveals a similar pattern (Figure 3). Specifically, states with a revenue-based TEL have a larger percentage of bridges that are deficient compared to states that have no limit on revenues. While the slope of the two trend lines is nearly identical over the entire time period, if the first few years of the time period are discounted, the rate of improvement in the average percentage of bridges classified as structurally deficient is slower in states with revenue based tax and expenditure limits.

One drawback of a simple analysis, such as presented in Figures 2 and 3, is that significant heterogeneity in tax and expenditure limits across states is ignored. Some states, such as Colorado, have very restrictive TELs while other states have very weak TELs. For many states, the TELs are aimed at the property tax that predominately impacts local governments and public school districts and as such do not limit the ability of states to invest in the transportation system. Hence, we refine our question: Do states that impose more restrictive TELs on state governments lead to a deterioration of the transportation infrastructure?

In the applied research reported here, we use unique measures of state TEL restrictiveness to test if TEL restrictiveness is associated with highway bridge conditions. We hypothesize that states with more restrictive TELs are more likely to under-invest in the transportation system than states with less strict TELs. As suggested in Figures 2 and 3 we contend that this hypothesis will be empirically captured in the condition of bridges within the state. We use a panel of the 50 states from 1992 to 2009, the most current year available, for a total sample size of 900 unique observations. In the next section of this study we provide an overview of TELs in the United States and then we discuss the data and modeling approaches. We then present our results and close the study with a summary of key finds and a discussion of policy options.

An Overview of TELs

Nearly every state in the United States has imposed some type of TEL on itself and/or its local governments. TELs range from simple open meeting laws to strict constitutional amendments limiting the growth in state and local government revenues and expenditures to a chosen metric, such as the rate of inflation or population growth rates (Joyce & Mullins, 1991; Kornhauser, 2002; Kioko, 2011; Mullins, 2004; Mullins & Wallin, 2004; Stallmann, 2007). Examples include California’s Proposition 13, Massachusetts’s Proposition 2½, Colorado’s TABOR, Michigan’s Headley Amendment, and Missouri’s Hancock Amendment.

Lowery and Sigelman (1981) identify eight potential reasons why tax revolts, particularly against the property tax, have been so popular in the United States. For practical purposes these eight can be classified into three broad areas. The first follows the Niskanen–Buchanan–Tullock or Leviathan philosophies. It maintains that government is inherently inefficient; hence taxes or revenues are excessive and expenditures inefficient (Fraser, 2005; New & Slivinski, 2005). According to this view, due to political pressures from special interest groups and bureaucrats, elected officials lack the discipline to impose fiscal restraints. For transportation infrastructure, the road construction industry may lobby for more spending on transportation then is ideal. Thus, an outside constraint such as a tax and expenditure limitation rule must be enacted in order to force said fiscal discipline. TELs “curb the perceived excess associated with a piecemeal budgetary process which yields … larger expenditures than a majority of voters deem desirable” (Abrams & Dougan, 1986, p. 105).

Second, others argue that high tax rates negatively affect economic performance (Chandler, 2005) and therefore TELs should be implemented to promote economic growth and development (Deller & Stallmann, 2007; Deller, Stallmann, & Amiel, 2012; Stallmann & Deller, 2010, 2011). Third, many TELs target a specific type of tax, particularly the property tax. Here, distain for the property tax for a variety of reasons has led to a politically popular drive to place limits on how the property tax can be implemented. As the property tax is traditionally the primary source of revenues for local governments, these state-level initiatives place particular burdens on local governments (Springer, Lusby, Leatherman, & Featherstone, 2009). Regardless of the motivation, an increasing number of state and local government officials are finding themselves forced to operate under budgeting rules that include TELs.

The impact of TELs has been studied by economists (e.g., Bradbury, Mayer, & Case, 2001; Deller & Stallmann, 2007; Skidmore, 1999; Skidmore, Ballard, & Hodge, 2010; Stallmann & Deller, 2010, 2011), political scientists (e.g., McCubbins & Moule, 2010; Primo, 2006; Sokolow, 2000), lawyers (e.g., Fino, 2003; Schwartz, 1997), and public administration scholars (e.g., Hou & Smith, 2010; Joyce & Mullins, 1991; Kioko, 2011; McCaffery & Bowman, 1978; Mullins, 2004; Mullins & Wallin, 2004). As the ultimate goal of TELs is to limit government spending and/or reduce a particular type of tax, it follows that the bulk of this literature has focused on how TELs influence state and/or local government budgets (e.g., Abrams & Dougan, 1986; Bae & Gais, 2007; Bae & Jung, 2011; Galles & Sexton, 1998; Kousser, McCubbins, & Moule, 2008; McCaffery & Bowman, 1978; McCubbins & Moule, 2010; Springer et al., 2009). Similarly, because K-12 public education is both a major source of expenditures and a major user of property taxes, significant attention has been paid to the effect of TELs on schools (e.g., Downes, Dye, & McGuire, 1998; Figlio, 1997; Hickam, Berne, & Stiefel, 1981).

A smaller literature focuses on the institutional processes of budget determination, decision-making (e.g., Endersby & Towle, 1997; Maher, Deller, & Amiel, 2011; Mullins, 2004; Stallmann, 2007) and citizens’ perceptions of local government service levels after TELs were imposed (e.g., Cutler, Elmendorf, & Zeckhauser, 1999; Lowery & Sigelman, 1981). There is also a new thread of literature examining the spatial diffusion of TELs across space (Martin, 2009; Moule & Weller, 2009). As far as we are aware, there have been no studies examining the impact of TELs on the quality of public services, in particular, infrastructure (in this case, roads and bridges).

Data, Measures, and Methods

This research faces three challenges: (a) how to measure the restrictiveness of individual state tax and expenditure limits, (b) how to measure the condition of the nation’s network of bridges, and (c) how to model the relationship between TELs and bridge conditions. We address each in turn.

Given that no two TELs are alike, it is difficult to generalize from the literature (Joyce & Mullins, 1991; Mullins & Wallin, 2004). Due to the heterogeneity of TELs across states, much of the literature has either focused on individual states, almost in a case-study framework, or uses dummy variables to indicate the presence of a TEL (such as the simple analysis presented in Figures 2 and 3). Joyce and Mullins (1991) delineate six broad types of TELs, ranging from simple full disclosure—truth in taxation rules—to strict constitutional limits on revenue and/or expenditure increases such as Colorado’s TABOR. “Truth in taxation” rules generally require some type of public discussion and a specific vote in an open meeting prior to enactment of tax or expenditure increases. More restrictive TELs limit the amount by which revenues and/or expenditures can increase from the previous year; the percentage increase is often tied to inflation rates, population growth rates, or growth in per capita income. Most binding are these latter types of TELs that are also constitutional rather than statutory (Kioko, 201;Poulson, 2005). A second challenge to cross-state analysis is that the TEL of any given state may have one or a combination of these requirements and restrictions.

Another complicating factor is the time frame over which TELs have been enacted. Missouri placed its first limit on property tax rates in 1875, West Virginia placed a local property tax rate limit in 1939, and Arkansas passed a supermajority requirement to raise taxes in 1934 (Mullins & Wallin, 2004; Waisanen, 2010). Florida adopted limits on corporate income taxes in 1971, California’s Proposition 13 was enacted in 1979, Massachusetts’s Proposition 2½ in 1980, and Colorado’s TABOR in 1992.

A final element of the complexity in quantifying TELs is that from time to time states modify TELs: adding a new element, tightening a restriction or occasionally loosening one. As outlined above, Colorado recently suspended TABOR for a period of 5 years to allow for major infrastructure projects. Kansas recently shifted from a TEL that strictly limited county property tax levy increases to a truth in taxation type TEL (Springer et al., 2009). These changes overtime must be included for modeling the dynamics of the interplay between the TEL and policy outcomes.

Several researchers have attempted to move beyond studies limited to one state or the use of dummy variables by building indices to reflect the varying characteristics of TELs (Advisory Commission on Intergovernmental Relations [ACIR], 1987; Carr, 2006; Bae & Gais, 2007; Deller et al., 2012; Nicholson-Crotty & Theobald, 2011; Poulson, 2005). In an early study the Advisory Commission on Intergovernmental Relations (ACIR, 1987) built and applied a strictness index of state balanced budget requirements ranging from 1 (least stringent) to 10 (most stringent). They also used a dummy variable for the presence of a tax and/or expenditure limit. They generally found that these constraints had a dampening effect on state government spending. In a study of the impact of TELs on local government structure, Carr (2006) constructed an index of the limits on local revenue and expenditure autonomy. The index starts at 10, indicating autonomy, and autonomy decreases by two points for each limit in effect: general revenues, general expenditures, property tax revenues, assessment increases, and millage rates. In general, Carr (2006) found that the role of TEL restrictions on local governments—in the formation of special districts to circumvent TELs—is more modest than the previous literature suggests.

Bae and Gais (2007) build an index that ranges from 0 for no TEL to 3 for the strongest TEL to test the impact of TELs on government spending. They find that higher values of the index are associated with modestly lower levels of state government per capita spending. Poulson (2005) uses five dimensions to build an index of state TEL restrictiveness for the year 2005, which ranges from 0 for states that have no effect TEL in place to a maximum possible score of 25. Deller, Stallmann, and Amiel (2012) build on ACIR (1987), Bae and Gais (2007), Resnick (2004), and Poulson (2005) by building a restrictiveness index for state as well as local TELs that ranges from 0 (no TELs) to 30 (most restrictive) for a period from 1969 to 2005. Examining the impact of TELs on state economic growth they conclude that stronger TELs imposed on state governments have a dampening effect on state economic growth and TELs imposed on local governments have a weak negative impact on growth.

To address this shortcoming in the literature, we follow the lead of Deller et al. (2012) and construct an index of TEL restrictiveness. We split all of the state TELs into three distinct broad types: (a) those TELs that emphasis the revenue side; (b) those that emphasize the expenditure side; and (c) those that cover both revenues and expenditures. A separate index of restrictiveness is created for each type. The index scores the TEL for each of the 50 states from 1992 to 2009 includes any changes in TELs and allows comparisons across states and over time. As noted by Kioko (2011) the movement to indices, such as the ones employed in this study, is a marked improvement over simple dummy variables.

Each of the three indices reflects five characteristics of the TEL imposed on state governments: (a) method of adoption; (b) constitutional or statutory; (c) growth restrictions; (d) override procedures; and (e) exemptions. Within each category, there are ranges of specific attributes that assume an increasing value as the attribute makes the TEL more restrictive. For example, for the method of adoption there are six possible ways that the TEL was adopted, with a constitutional convention being the strongest (score of 6) to a simple statutory legislative vote (score of 1). For override procedures there are seven possible attributes ranging from a simple majority vote in the legislature to override the TEL (score of 1) to a supermajority vote in the legislature (score 2) to no override provisions allowed (score of 7). The maximum value for the revenue focused TEL restrictiveness index is 20, 22 for the expenditure focused index, and 21 for TELs that cover both revenues and expenditures.

By construction we have an ordinal measure of TEL restrictiveness: higher values of the index means that the TEL is more restrictive. The value of the indices can change over time as states alter their TEL policies. Washington State, for example, had no TELs prior to 1993 when a TEL on both revenues and expenditures was introduced. But in 2000, the state modified its TEL to focus exclusively on the expenditure side and removed the limits on revenues. Our indices are able to capture this transition. Unfortunately, because of the ordinal nature of the index, it is not possible to assert that a state with a TEL restrictive index of 20 is twice as restrictive as a state with an index value of 10. The most that we can say is that one state has a more restrictive TEL than the other. This means that the most that we can draw from our statistical modeling below is that the relationship between TEL restrictiveness and bridge infrastructure condition is positive, negative, or nonexistent. The actual value of any particular statistical coefficient has no meaningful interpretation. As such, we are limited to answering two questions: (a) Are bridge conditions affected by TEL restrictiveness; and (b) if yes, what is the direction of the relationship?

To measure the condition of bridges we use the federal definitions of “structurally deficient” and “functionally obsolete” which is available annually from the National Bridge Inventory complied by the Federal Highway Administration. The particular categories are important because they are used in conjunction with sufficiency ratings to determine the eligibility and allocation of federal bridge replacement funds. “Structurally deficient” means that the condition of the bridge includes a significant defect, which often means that speed or weight limits must be put on the bridge to ensure safety; a structural evaluation of 4 (i.e., meets minimum tolerable limits to be left in place as is) or lower qualifies a bridge as “structurally deficient.” The designation can also apply if the road approaching the bridge floods regularly. A designation of “functionally obsolete” means that the design of a bridge is not suitable for its current use; for example, the bridge could lack safety shoulders or be unable to handle current traffic volume, speed, size, or weight.

In 1992, the beginning of the study period, there were 118,698 structurally deficient bridges, about 20.7% of all bridges, and 80,393 were functionally obsolete, about 14% of all bridges. In 2009, the end of the study period, the number of structurally deficient bridges decline to 71,177, about 11.8% of all bridges, and the number of functionally obsolete bridges was 78,477, about 13%. As outlined in Figure 1, the share of bridges that are structurally deficient has been declining over the study period, but the number of functionally obsolete bridges that may be considered dangerous has remained fairly constant. For this study we limit our analysis to include only those bridges that fall under the responsibility of state governments, smaller lower-volume bridges that are generally the responsibility of local governments are not considered.

The third issue that must be addressed is the estimation methods to test the central hypothesis: more restrictive TELs will lead to an under investment in transportation infrastructure, specifically bridges, which can be measured by bridge conditions. We proceed by estimating a 2-way fixed effects model that allows us to control for both time as well as for time-invariant individual effects. We first estimate a simple model with no control variables, and then we estimate a set of models that control for measures of demand, or pressure, placed on the transportation system. The model can be expressed as:

B C_{i t} = \sum_{j = 1}^{\partial} β_{j} T E L_{j i, t - 5} + \sum_{k = 1}^{n} β_{k} X_{k i t}

Here BCit is the percentage of bridges that are structurally deficient or functionally obsolete for the i^th state in time t, TEL_ij,t-5 are our three (j = 1,2,3) TEL restrictiveness measures for the i^th state in time t-5, and X_kit are our set of demand or pressure measures.

A time lag of 5 years for the TEL was chosen to more accurately reflect the revenue and expenditure decisions of state governments. The current condition of roads and bridges are influenced by expenditures on infrastructure in previous years. Since TELs restrict public expenditures, the presence and restrictiveness of TELs in previous years might impact the condition of bridges today. The control variables include the poverty rate, percentage of employment in manufacturing, state’s share of U.S. crop production, and population density. We hypothesize that higher levels of each of these measures will be associated with a higher percentage of bridges in poor condition. Manufacturing, crop production, and population density all place more pressure on the system. Population density is a general measure reflecting bridge use. In our analysis, population density is a proxy variable for traffic volume. States with a higher population density could have a larger percentage of bridges as structurally deficient or obsolete due to the increased traffic volume associated with larger populations. Similarly, the high weights of semitrucks and farm equipment causes more stress and could lead to faster bridge degradation. Higher levels of poverty reduce the ability to pay for reinvestments.

Empirical Results

We use a simple pooled estimator as well as a two-way fixed effects estimator for individual effects that are time invariant, like regional climate or geography, which in turn minimizes omitted variable bias. The F-test for all three models of bridge conditions shows that we should reject the pooled estimation if favor of the two-way fixed effects. As such we report only the fixed effects models (Table 1). In addition, we ran a base model, which excludes the control variables (i.e., β_k =0, ∀k≠j), as well as the fully specified model. A second set of F-tests shows that the control variables should be included in the analysis (i.e., reject β_k≠j= 0). The explanatory power of the three models, given the R², are generally high with 83.6% of the variation in the percentage of all bridges that are structurally deficient, 93.9% of functionally obsolete, and 94.8% of structurally deficient and functionally obsolete combined.

Table 1.

TEL and Bridge Condition Models (Two-Way Fixed Effects).

	Percentage of bridges structurally deficient	Percentage of bridges functional obsolete	Percentage of bridges structurally deficient and functional obsolete
	Base model
Revenue TEL index lagged 5 years	0.00283	−0.00126	0.00158
	(0.0001)	(0.0008)	(0.0022)
Expenditure TEL index lagged 5 years	−0.00002	0.00012	0.00009
	(0.9624)	(0.6709)	(0.8050)
Revenue and expenditure TEL index lagged 5 years	0.00029	−0.00004	0.00025
	(0.6083)	(0.9096)	(0.5502)
Intercept	0.13652	0.07694	0.21346
	(0.0001)	(0.0001)	(0.0001)
R²	0.8299	0.9367	0.9451
F test for no fixed effects	59.69	175.56	205.17
	(0.0001)	(0.0001)	(0.0001)

	Expanded model

Revenue TEL index lagged 5 years	0.00258	−0.00123	0.00134
	(0.0004)	(0.0015)	(0.0128)
Expenditure TEL index lagged 5 years	0.00029	−0.00020	0.00009
	(0.5675)	(0.4708)	(0.8075)
Revenue and expenditure TEL index lagged 5 years	−0.00025	0.00015	−0.00010
	(0.6614)	(0.6232)	(0.8174)
State share of U.S. crop production	−0.00021	−0.00098	−0.00119
	(0.9505)	(0.5908)	(0.6385)
Population density	−;0.00013	0.00008	−0.00005
	(0.3739)	(0.3254)	(0.6323)
Percent of direct state expenditures on highways	−0.01248	0.00913	−0.00335
	(0.8632)	(0.8153)	(0.9507)
Coincidence index of economic activity	0.00055	0.00007	0.00062
	(0.0005)	(0.4018)	(0.0001)
Percent of employment in durable manufacturing	0.32497	−0.71719	−0.39222
	(0.1745)	(0.0001)	(0.0289)
Percent of employment in nondurable manufacturing	0.64258	−0.34961	0.29297
	(0.0068)	(0.0063)	(0.0990)
Poverty rate	0.21141	−0.22629	−0.01488
	(0.1090)	(0.0015)	(0.8803)
Number of registered vehicles per capita	0.00703	0.00423	0.01126
	(0.2340)	(0.1847)	(0.0111)
Intercept	0.02637	0.08506	0.11143
	(0.4519)	(0.0001)	(0.0001)
R²	0.8363	0.9411	0.9477
F test for no fixed effects	43.95	93.90	111.75
	(0.0001)	(0.0001)	(0.0001)
F test for control variables	4.32	8.23	5.59
	(0.0001)	(0.0001)	(0.0001)

Note: Marginal significance in parentheses.

Generally, TELs that are focused on either expenditures or both revenues and expenditures are not associated with the percentage of bridges that are structurally deficient or functionally obsolete; on the other hand, there is consistent evidence that more restrictive TELs that limit government revenues are associated with a higher percentage of a state’s bridges that are structurally deficient. More restrictive revenue TELs are also associated with lower percentages of bridges that are functionally obsolete. The positive relationship between revenue TEL restrictiveness and the percentage of bridges structurally deficient is consistent with our expectations, but the negative relationship with functionally obsolete is unexpected. The underlying reasons causing this latter result is unclear. One potential explanation is that states with more restrictive revenue TELs are only able to address a portion of the infrastructure needs of the state. The more restrictive the TEL, the less flexibility and resources a state has available to fix bridges. Functionally obsolete bridges show degradation and require significant maintenance or must be replaced and may, therefore, be targeted by states with more restrictive TELs. More importantly, the federal government provides resources to help states fix functionally obsolete bridges.

Building on the work of Nicholson-Crotty and Theobald (2011) it may be the case that states are shifting responsibility to the federal government. Due to limited resources, states with restrictive TELs may choose not to fix functionally obsolete bridges, and instead allow them to gradually degrade until they are classified as structurally deficient bridges before investing in repairs and/or replacement. Thus, while it appears that more restrictive revenue TELs improve the percentage of functionally obsolete bridges, it might actually be the case that TELs prevent maintenance and upgrades, which ultimately leads to some functionally obsolete bridges being reclassified as structurally deficient bridges.

The condition of transportation infrastructure is not only driven by the ability to invest in the infrastructure, which our TEL restrictive indices capture, but also the demand. We find that neither higher levels of crop production or population density are statistically significant determinants of bridge conditions. Dependency on manufacturing for employment has a mixed effect on bridge conditions. Higher dependence on durable manufacturing has no influence on the percent of bridges that are structurally deficient but a negative impact on the percentage of bridges that are functionally obsolete. A higher dependency on nondurable manufacturing for employment is associated with a higher share of bridges that are structurally deficient, but a lower share of bridges that are functionally obsolete. We find a similar pattern with the poverty rate: no relationship with structurally deficient bridges and a negative relationship with the share of bridges that are functionally obsolete. The number of registered vehicles per capita does not appear to be related to the two categories of bridge condition but has a positive and statistically significant impact on the total share of bridges that are either structurally deficient or structurally obsolete.

Perhaps the most interesting result of the control variables is the lack of statistical significance of the percentage of state government direct expenditures that is devoted to highways. One would expect that a higher share of a state’s spending devoted to roads would be associated with bridges that are in better condition. Given the results for revenue TELs and bridge conditions it is reasonable to argue that shares of direct expenditures do not reflect the absolute level of expenditures. A larger share of a small pool of resources might not be sufficient to capture the demand for maintenance levels. Expenditure on highways may also mask the mix of expenditures on roads as opposed to bridges.

We can draw four general conclusions from the empirical analysis. First, the restrictiveness of tax and expenditure limits does matter in the ability to reinvest in the network of bridges. This relationship is, however, not in a simple direct manner: the focus of the TEL (revenue, expenditure, or both) matters. Second, and somewhat unexpectedly, more restrictive TELs that cover expenditures as well as both revenues and expenditures, TELs that in theory should limit the flexibility of state governments the most, are not associated with of the percentage of bridges that are either structurally deficient or functionally obsolete. Third, the results suggest that more restrictive revenue based TELs lead to a higher percentage of bridges in fair to poor condition. These are bridges that authorities might consider dangerous. Finally, contrary to our central hypothesis, more restrictive revenue TELs are associated with a lower share of functionally obsolete bridges.

Conclusions

The viability of the economy is dependent upon a viable stock of public infrastructure, particularly transportation infrastructure such as roads and bridges. While the research is clear that blind investments in transportation infrastructure will not necessarily lead to economic growth and development, a deterioration of that infrastructure can create bottlenecks in the economic growth process. In the United States, state governments are fundamentally responsible for the maintenance of the nation’s network of higher volume roads and bridges. Many of these states have put in place fiscal constraints, in the form of TELs, which could hinder their ability to reinvest in the transportation network. Our central hypothesis is that these TELs, which are intended to force fiscal restraint, results in an under-investment in our nation’s bridges. A second contribution of the study is the use of three unique indices of the restrictiveness of TELs that many states have imposed on themselves.

While simple descriptive analysis suggests that states with TELs tend to have a higher share of bridges deemed inadequate, the more complete models suggest that TELs play a limited role in understanding the share of bridges that are in fair to poor condition (i.e., functionally obsolete). The data generally supports this hypothesis with relation to the share of bridges that could be deemed unsafe (i.e., structurally deficient). Often times what appears to be a simple solution (i.e., TELs) to complex issues results in unintended consequences. The evidence presented here suggests that one unintended consequence of TELs is the creation of bottlenecks in the economic growth and development process via underinvestment in our nation’s infrastructure.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Support for this work was provided in part by the Wisconsin Agricultural Experiment Station, College of Agricultural and Life Sciences, University of Wisconsin-Madison.

Notes

Author Biographies

Steven C. Deller is professor and community development specialist with the University of Wisconsin-Madison and the University of Wisconsin-Extension, Cooperative Extension. His work focuses on rural economic growth and development and policies that communities can implement to affect growth and development.

Lindsay N. Amiel is a PhD candidate in the Agricultural and Applied Economics Department at the University of Wisconsin-Madison. Her research focuses on community economic development, regional economic growth and public finance.

Judith I. Stallmann is a professor of Agricultural Economics and Rural Sociology in the Truman School of Public Affairs at the University of Missouri. Her research areas include state and local public finance, rural economic development and fiscal and economic impact analysis.

Craig S. Maher is an associate professor of Budgeting and Financial Management at Northern Illinois University. His research focuses on local financial condition analysis and measurement, and fiscal federalism.

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