In this report, Ball State University economist Michael Hicks examines the impact of prevailing wage laws across the country on the cost per quality-adjusted mile of road construction from 2004 to 2019. He also reviews the impact of these laws on the labor share of road construction costs. Hicks relies on data from the Federal Highway Administration, the Bureau of Economic Analysis and the Bureau of Transportation Statistics.
His research demonstrates that prevailing wage laws increase the cost of road construction by 8.5% to 14.3%, in line with previous Mackinac Center estimates and other scholarship. These results are both economically and statistically significant.
Michigan lawmakers passed the state’s Prevailing Wage Act in 1965. The law mandated that workers hired on taxpayer-funded construction projects be paid the wages and fringe benefits which were prevailing in the locality where the project was to be built. This prevailing wage was tantamount to union-scale compensation because the law required wage rates to be based on the union contracts covering construction workers operating in the city, township or school district where the work was to be done.
The law covered a wide range of projects, including “new construction, alteration, repair, installation, painting, decorating, completion, demolition, conditioning, reconditioning, or improvement of public buildings, schools, works, bridges, highways, or roads.”[*] The purpose of the law is to artificially raise the cost of labor on government construction projects. This benefits unionized construction firms that can more easily compete for these bids. But prevailing wage also increases the costs to taxpayers of public construction.
The federal government similarly mandates prevailing wages on construction projects it funds through the Davis-Bacon Act of 1931. Many state construction projects involve both federal and state dollars, which complicates attempts to analyze the cost-benefit of these laws. According to a 2016 Congressional Budget Office report, however, repeal of the Davis-Bacon Act could have saved taxpayers some $13 billion between 2018 and 2026.[†]
The economic and fiscal impacts of Michigan’s prevailing wage law have long been of interest to Michigan policymakers and to scholars at the Mackinac Center for Public Policy. Indeed, the Mackinac Center has weighed in on the debate over prevailing wage mandates since 1990.[‡] This study represents our third major analysis of the impact of prevailing wage laws, with a specific focus on Michigan and the law’s impact on road construction and repair.
The Mackinac Center’s first study on prevailing wage involved a unique dataset created incidentally by a federal court decision. That ruling effectively suspended Michigan’s prevailing wage law from December 1994 to June 1997. The temporary change provided a natural experiment that Ohio University economist Richard Vedder used to measure the law’s economic impact for the 30 months before and the 30 months after its suspension.[§]
Vedder found that suspending Michigan’s prevailing wage law made possible at least 11,000 construction jobs that would not otherwise have been created. He also calculated a likely savings of 10% on public construction costs, equal to about $275 million, or 5% of the money generated by Michigan’s personal income tax in 1995. Vedder noted at the time that this 10-percent estimate “accords with several studies of the impact of prevailing wages on construction costs” and may “actually be conservative.”[**]
In 2007, then-Director of Labor Policy Paul Kersey authored the Mackinac Center’s second major prevailing wage study. He compared prevailing wage rates to nonunion wages in different regions in Michigan and estimated that the law increased the cost of construction projects by 10% to 15%. These additional costs are passed along to taxpayers. Measured in 2007 dollars, Kersey calculated that state taxpayers could have saved up to $250 million by repealing the state’s prevailing wage.[††]
In 2018, voter-initiated legislation that was passed by the Michigan Legislature repealed the state’s prevailing wage law.[‡‡] The change was short-lived, however, as the current Legislature voted to reinstate a prevailing wage law, which was signed by Gov. Whitmer on March 24.[§§] This study — the Mackinac Center’s third full study on the matter — suggests that doing so will significantly raise the cost of road construction for Michigan taxpayers.
In this report, Ball State University economist Michael Hicks examines the impact of prevailing wage laws across the country on the cost per quality-adjusted mile of road construction from 2004 to 2019. He also reviews the impact of these laws on the labor share of road construction costs. Hicks relies on data from the Federal Highway Administration, the Bureau of Economic Analysis and the Bureau of Transportation Statistics.
His research demonstrates that prevailing wage laws increase the cost of road construction by 8.5% to 14.3%, in line with previous Mackinac Center estimates and other scholarship. These results are both economically and statistically significant.
As the table below shows, Hicks finds that Michigan’s additional cost per quality-adjusted road mile ranged from a low of $5,932 to $9,205 due to the presence of a prevailing wage law. Other states that recently repealed their own prevailing wage laws were also demonstrably overpaying for road work.
That is not all. Hicks also examined labor’s share of road construction spending that flows to workers. When examining the proportion of highway spending that accrues to workers as income and benefits, he “found no compelling evidence that a prevailing wage law reduces the labor share of road construction.”
Hicks creates a two-way, fixed-effects model to control for many of the variables that impact the cost of road construction in states. He uses several specifications of the model to add confidence to the findings and tests the validity of the results. A full description of the model is provided in the full text of the study below.
The results of the modeling efforts confirm that prevailing wage laws raise the cost of road construction and maintenance. This suggests that Michigan lawmakers have made it more expensive to fix the state’s roads, impairing the goal of improving Michigan’s public infrastructure.
Prevailing wage laws are expensive and unfair. They force taxpayers to pay more than they otherwise would for construction projects like road construction. They harm taxpayers at the expense of a select group of unionized construction workers fortunate enough to land government-supported projects. In other words, these laws benefit a few at the expense of the many.
[*] “Prevailing Wages on State Projects: Act 166 of 1965” (State of Michigan, 2018), https://perma.cc/M7RT-7V85.
[†] “Options for Reducing the Deficit: 2017 to 2026” (Congressional Budget Office, Dec. 8, 2016), https://perma.cc/ 2393-XTTV.
[‡] George Leef, “Michigan’s Prevailing Wage Act: A Disaster for the Taxpayers” (Mackinac Center for Public Policy, March 5, 1990), https://perma.cc/2JWS-UFYE.
[§] Richard Vedder, “Michigan’s Prevailing Wage Law and Its Effects on Government Spending and Construction Employment” (Mackinac Center for Public Policy, 1999), 8, https://perma.cc/H8MT-FBDC.
[**] Richard Vedder, “Michigan’s Prevailing Wage Law and Its Effects on Government Spending and Construction Employment” (Mackinac Center for Public Policy, 1999), 11-15, https://perma.cc/H8MT-FBDC.
[††] Paul Kersey, “The Effects of Michigan’s Prevailing Wage Law” (Mackinac Center for Public Policy, 2007), https://perma.cc/ SY2L-94XX.
[‡‡] “Initiation of Legislation" (State of Michigan, 2018), https://perma.cc/Y34R-YJ65.
[§§] “2023 Michigan Public Acts Table” (Michigan Legislative Service Bureau, March 27, 2023), https://perma.cc/JL85-KX6R.
Policymakers are keenly interested in the effect of state-level prevailing wage legislation on the costs and labor markets of road construction and maintenance. Federal, state and local spending on highways and streets averaged $87.2 billion per month during the last expansion (July 2009 to January 2020). And as of January 2020, heavy and civil engineering construction employment peaked at over 1.1 million.[1] This is a large industry that provides significant employment and attracts substantial federal, state and local spending each year.
State prevailing wage laws mandate that a minimum wage be paid to workers on public construction projects. This prevailing wage is set by a survey of wages paid by contractors on similar projects in the local geographical area. The legislation establishes a detailed mechanism by which state and local governments must set wages for some classes of construction workers employed on publicly funded projects. Today, 29 states have prevailing wage laws, eight of which have no lower-bound thresholds for project size and apply the mandate to all publicly financed construction projects. There are substantial policy debates over the effect and efficacy of state legislation.
This research seeks to evaluate how the presence of a state prevailing wage law affects the cost of constructing and maintaining roads and the labor share of production on road construction projects. The labor share is that proportion of road spending that flows to workers in the form of wages and benefits. To accomplish this analysis, we review the relevant research literature on these questions, highlighting the sparse nature of that work. We then present the data we use to define maintenance construction costs and labor share.
Following that, we present two basic models to test, with two specifications each, along with robustness tests for the two-way, fixed-effect model with heterogeneous timing. We also test potential bias introduced by high project cost thresholds in states with a prevailing wage law in place. Because some states exempt some projects, using the prevailing wage legislation as a dummy variable may not appropriately treat the legislation. We also separately test the six states that changed their prevailing wage laws during the sampled period.
We follow this with a description of our results, and how they may be used, along with cautions on their use. We end with a summary of our findings. We begin with a discussion of modelling issues surrounding the analysis of state prevailing wage legislation.
The prevailing wage elements of the Davis-Bacon Act and the state versions of prevailing wage legislation are designed to increase wages for construction workers involved in publicly financed construction projects. Federally financed projects are controlled by Davis-Bacon, while state-funded ones are governed by state prevailing wage laws. Most jointly funded projects are also subject to Davis-Bacon requirements for prevailing wage.
An inescapable aspect of prevailing wage laws is that to affect wages they must be set above the market equilibrium. In other words, they always artificially raise the cost of labor on public construction projects. That there is concentrated opposition by labor interests to repealing these laws offers compelling evidence that they set prices above market equilibrium.
However, this does not mean that these wage rates depart significantly from market equilibrium. Nor does it mean that in the absence of prevailing wage laws these labor markets would be in competitive equilibrium. There are surely some local construction markets in which monopsony power sustains wages beneath the competitive equilibrium. These factors affect the empirics of tests of PWL on wages, costs and labor share of production. Indeed, the Davis-Bacon Act has faced a longstanding debate over its intent. Goldfarb and Morrall provide a good discussion of that debate regarding the presence of federal monopsony.[2]
The actual effect of PWL, including Davis-Bacon, is an empirical matter.
Higher wages, due the presence of a prevailing wage law, motivate firms to alter the capital-labor ratio in construction. Supra-normal wages would result in more capital-intensive production and reduce the labor share of production. Importantly, this clouds the interpretation of wage studies on this issue, since relaxing the provisions of prevailing wage would potentially change the skill mix of employees. O’Connell outlines this issue well.[3]
Nonwage compensation may also be affected by the provisions in prevailing wage legislation. This could include benefits, which are often invisible to empirical analyses, as well as investment by firms in such matters as worker training or safety. Phillips et al. provides a review of this issue.[4]
Prevailing wage requirements affect the procurement process, motivating researchers to analyze several issues as disparate as the effects on bidding practices and the advantages of incumbent firms. This latter effect has also been studied with some rigor since the protection of incumbent construction firms was a likely intent of the Davis-Bacon Act.[5]
The diversity of state prevailing wage laws motivates researchers to look at a wide variety of empirical tests on wages, construction costs, labor share of production, bidding practices, workplace training and safety. This paper addresses two of these, but before moving to our tests, we provide a review of the literature.
Economic analyses of state prevailing wage laws and road construction costs are sparse.[*] Only four studies make direct comparisons in this area. So, we must rely on a broader suite of research to evaluate the role state-level prevailing wage laws play in construction costs. The following review focuses on three types of studies. First, there are case studies or small sample studies with either specific data on bids or costs. These weakly mimic a natural policy experiment. That is not a critique, since there are often important policy questions at issue, and few research options that permit clear identification of PWL effects.[†]
Second, we examine studies that have microdata on construction costs for non-highway projects and use it to construct a causal estimate of the effects of prevailing wage laws on costs. These studies use several different methods, which we describe briefly. Finally, we review the effects on road construction costs that are directly assessed in four studies.
Two studies of bids for large samples of public construction projects report no wage differences between prevailing and non-prevailing wage bids.[6] These are within a single state (Ohio) and illustrate the challenges of interpreting single-state estimates. Ohio has a larger than typical threshold for contract costs to trigger prevailing wage rates, but the presence of prevailing wage laws may affect all construction markets in the same regions. This is a common problem in evaluating projects within the same labor markets.
Studies which make comparisons of contract costs for projects uniformly report higher costs for prevailing wage projects. The first of these studies reported large geographic and prevailing wage costs disparities in New York state. The prevailing wage comparison most applicable to this research is a 28% cost differential.[7] Kersey performs a similar study comparing median wage rates and legally established prevailing wage rates in Michigan, finding 10% to 15% added cost to public construction projects.[8] Rosaen and Taylor updated their 2013 study reporting cost increases of roughly 10% for school construction.[9] They were strongly criticized by Philips for, among other things, overestimating the labor share of workers affected by prevailing wage.[10] The Vermont Legislature commissioned a study that estimated the internal costs of prevailing wage to be in the 5% to 12.5% range.[11]
Estimates of prevailing wage include Vedder, who estimated a 10% cost increase in those occupations affected by state prevailing wage legislation.[12] Glassman et al. examined wage level differences in prevailing and nonprevailing wage markets of 9.9%, with the prevailing wage markets facing the higher wages.[13] Kessler and Katz use Employment Security 202 administrative data to test the effect of prevailing wage on union wage premiums in affected regions.[14] This is the most important of the studies we review, both for its method and its depth of analysis. I impute their construction cost estimates from their union wage premium to be from 2% to 5% of public projects, using labor share of 20% to 30%.[‡]
Studies with micro data on nonroad construction projects focus primarily on schools, where data are more readily available. These studies include Azari-Rad, Phillips and Prus, who report no effect of prevailing wage laws on school construction costs in a large sample of contracts during the 1990s.[15] Bilginsoy and Philips perform a similar test in Canada, which has comparable prevailing wage legislation in its provinces, and also found no effect.[16] Duncan, Philips and Prus report no differences in construction costs when comparing private and public school construction costs.[17] This natural experiment in cost differences would appear useful in identifying the effects of prevailing wage. However, prevailing wage may influence construction wages market-wide, which would bias these results.[18]
Keller and Hartman provided a review of multiple types of projects and estimates for their own analysis of school projects.[19] They report that prevailing wage laws increase school construction costs by 2.2%. The most extensive study of the issue was performed by Vincent and Monkkonen, which examined 3,000 school projects between 1995 and 2004.[20] This study used state variation in thresholds for projects, types of wage-setting agreements and state and local building requirements in their analysis. They report school costs in projects affected by prevailing wage laws are 13% higher than in those not affected.
In a unique study of state projects that used confidential state administrative data, Clark found a 28% wage difference in prevailing wage versus non-prevailing wage projects.[21] I impute that this results in a roughly 5% to 10% increase in project costs.[§] Kelsay, Wray and Pinkham studied project costs across a 12-state region in the Midwest and found no difference in construction costs across prevailing wage and non-prevailing wage states.[22]
Four studies of construction costs offer a modest level of analysis on a large cost issue. Fraundorf, Farrell and Mason study nonresidential building construction projects in 1977-78, finding a 26.1% difference between prevailing wage and nonprevailing wage projects.[23] Duncan offers two studies of highway contracts in Colorado, comparing costs on state and federal roads. Colorado repealed its prevailing wage legislation in 1985, offering an identification opportunity in that state.[24] He reports no impact on costs, and no differences in effects on disadvantaged businesses. Vitaliano estimates state highway and maintenance productivity, finding that using prevailing wages adds roughly 10% to the cost of construction.[25]
This literature does not provide a clear picture of consensus or method of analysis. Of the 22 studies cited here, 10 report no effects on construction costs due to PWL. There is considerable overlap in the study teams here, with only three wholly separate groups of authors. They employ case comparisons and econometric studies of large samples to draw these conclusions.
Those who report higher construction costs due to prevailing wage use the same methods as those who do not. There are notably large sample sizes on both sides, and unique data sets employed across all methods. In terms of journal reputation, the better studies all find some prevailing wage effect on costs.[**] However, much high-quality work by well-known scholars with highly varied findings was prepared for policy debate, not for the academic literature. Moreover, the specificity of the research question biases the journal placement of prevailing wage work toward field journals in labor economics.
These studies do not provide clear evolution over time. There is no evidence that later or earlier studies report different effects, as is the case with other labor market regulations, such as right-to -work laws.[26] Also, there are a wide variety of prevailing wage studies that examine issues not relevant to this study, such as those related to worker demographics, productivity and compensation. Duncan and Ormiston provide a very well-organized review of the multiple research questions posed about the effects of prevailing wage.[27]
We provide a table review of the literature cited above in two tables. Graphic 1 summarizes those studies that report a cost effect of prevailing wage, and Graphic 2 summarizes those studies that find no cost effect. A graphic of effect sizes is reported in Graphic 3.
Graphic 1: Selected Literature Reporting Cost Effects of Prevailing Wage
Graphic 2: Selected Literature Reporting No Cost Effects of Prevailing Wage
Graphic 3: Cost Effects (Percent) of Prevailing Wage Studies, 1984-2020
[*] This is not the first time Mackinac Center scholars have performed reviews of reports relating to prevailing wage. Of recent note are a series of papers produced by the Midwest Economic Policy Institute. These reports analyze prevailing wage laws in a variety of states and produce similar results in each case: states with prevailing wage laws benefit from them and those without are harming workers, tax revenues and whole communities. For more information, see: Michael D. LaFaive and Ronald Klingler, “Prevailing Wage Repeal Critiques: Cookie Cutter Criticism” (Mackinac Center for Public Policy, March 3, 2020), https://perma.cc/4PMM-7DL9.
[†] For additional commentary on recent prevailing wage studies, see: Michael Thom, “Do Construction Wages Fall after Ending a Prevailing Wage Mandate?” (Mackinac Center for Public Policy, May 6, 2021, https://perma.cc/EG5M-ZSED; Michael Thom, “The Weak Case Against Repealing Prevailing Wage” (Mackinac Center for Public Policy, May 13, 2021), https://perma.cc/T3TC-WGHL; Michael Thom, “What Do We Know About the Impact of Prevailing Wage Laws?” (Mackinac Center for Public Policy, June 4, 2021), https://perma.cc/9BHS-CYKC.
[‡] This is calculated simply by multiplying their estimated wage rate differential by these labor share estimates.
[§] As with the Katz and Kessler imputation, I multiply the wage premium by the labor share to estimate total cost differences.
[**] These include Martha Norby Fraundorf, John P. Farrell and Robert Mason, “The Effect of the Davis-Bacon Act on Construction Costs in Rural Areas” (The Review of Economics and Statistics 66, no. 1, February 1984): 141-146, https://doi.org/10.2307/1924706; Daniel P. Kessler and Lawrence F. Katz, “Prevailing Wage Laws and Construction Labor Markets” (ILR Review 54, no. 2, January 2001: 259-274, https://perma.cc/QD7Z-9SVB; D.F. Vitaliano, “An Econometric Assessment of the Economic Efficiency of State Departments of Transportation” (International Journal of Transport Economics 29, no. 2, June 2002): 167-180, https://www.jstor.org/ stable/42747624.
We are interested in the role state-level variation in prevailing wage legislation plays on key cost and labor market outcomes. This empirical test focuses on deriving causal inference on road construction costs per quality-adjusted mile, the labor share of spending, and the presence of a state prevailing wage law.
We pursue two parallel paths with identification of the prevailing wage effect on road cost and labor share. The first comes from Kessler and Katz, who argue the timing of changes to prevailing wage laws are exogenous due to unexpected court and legislative action.[28] Of the six states that saw changes to prevailing wage during our sample period, two passed legislation that immediately affected pay (e.g., emergency legislation in Kentucky). Given the high share of construction contracts awarded for lengthy periods, the legislative actions appear to be exogenous. If the timing of changes to prevailing wage legislation is wholly exogenous, then simple panel techniques are sufficient to provide unbiased estimates.
Still, among the challenges of this modeling effort are the potential endogeneity of prevailing wage legislation across states. In this setting, efforts to provide causal estimates are appropriate. The most common of these is the two-way, fixed-effect model, which is a generalized version of a difference-in-difference estimator when confronted with variation in timing. These models have been subject of considerable recent improvements.[29]
There are also concerns about the variation in construction costs between states that might be due to other factors such as climactic variation. The recent changes to prevailing wage laws in six states, which were enacted at different times, also influences the results across our observation period. We handle these through fixed effects in the initial panel, or through controls where possible.
Finally, we have the challenge of heterogeneity of the effects of prevailing wage, with different states using different thresholds of project eligibility. These variations compel a multiple estimation strategy to test robustness of our modeling. We accomplish this by estimating both a full sample and those states that change prevailing wage laws during this sample period. The heterogeneity in the prevailing wage threshold also argues for separate estimates that code a state with a prevailing wage when its minimum threshold for a project is either $100,000 or $1,000,000. The justification for these two thresholds is simply that $100,000 is the mode threshold, while there are no thresholds above $1,000,000. Thus, these threshold values were selected to provide reasonable basis for considering what impact thresholds may have on the effect of prevailing wage laws.
Our model estimates two observable outcomes of changes to state-level prevailing wage laws. The first of these is the quality-adjusted cost of road construction. Thus, our variable of interest is state-level spending, per dollar of road mile rated acceptable by the Federal Highway Administration. This measure includes both new construction and maintenance spending.
Formally it is:
Quality-adjusted road spending R, in state i, in year t, is a sum of spending across all highway/roadway types, s, in state i, in year t. We divide this spending by the sum of road miles, m, in state i, in year t, times the share rated acceptable, δ, for all roads. This is a quality-adjusted, cost-per-mile measure of construction and maintenance.
This measure is designed as a relatively straightforward approximation of cost per mile of maintenance and construction. Annual variation in spending on roads from traditional dedicated funds varies by state. Also, state general funds are often tapped for road construction and maintenance. Another source of annual variation is bonding of larger road projects. A bonding cycle and construction exhibit significant variability. Road spending is not a deterministic fiscal outcome as, say, the result of an excise tax only on gasoline is.
The lengths of available roads also vary significantly. States regularly build new roads and retire others. Municipalities regularly take control of private roads. Over our sample period the largest annual change of road miles in a state was a decline of over 3,500. There was also substantial variation in quality, with the largest annual change of the national mean being two nearly 6% declines in quality.
A potential issue in this specification is the value of including the road quality measure. Federal road quality measures are likely endogenous to previous and current levels of spending. Lagged “poor” ratings may incent higher levels of state spending, thus displaying a negative sign. Contemporaneous rankings may be positively correlated with current spending. Our primary concern is that low rankings may suggest states are spending too little to maintain roadways, and if omitted, may bias the effect of prevailing wage legislation and other coefficients.
Treating the quality ratings as endogenous means they must either appear in the dependent variable, as proposed here, or be instrumented in a first stage estimation. We focus on the first approach through the remainder of this paper. However, we also estimated a first-stage dependent variable where the state and local spending per road mile was regressed on the federal quality measure. Such that:
so,
This measure yielded results that were statistically identical. The point estimates of the Ȓi,t estimates were marginally higher (1.5 log points) than the Ȓ i,t estimates. We report the more conservative point estimates and prefer the dependent variable Ri,t viewing it as a more direct adjustment of the variable of interest (cost per mile of well-maintained roads) than is Ȓi,t; though the empirical interpretations of both are effectively identical.
Our second model tests the labor share of heavy civil engineering and construction, or formally, total wages and salaries in this sector, divided by total state spending on road construction. This ratio is simply described as Li,t, the labor share of road construction in state i, in year t.
The cost variable R relies solely on data from the same source, without the potential for meaningful miscounting of values due to spending flows to non-construction activities. The labor share variable, L, introduces more risk of dependent variable error since some share of heavy civil engineering and construction employment is spent on non-road construction projects. While our reported labor share estimates in Table 2 fall within reported levels, this is a weakness in the structure of the data we cannot resolve. We will discuss it in more detail in the results and summary sections.[*]
This offers two general specifications:
and
The dependent variables are state and year fixed effects (a), with a prevailing wage dummy PW, in state i and year t, and a matrix X, of explanatory variables and a white noise error term. The values a, ρ and matrix B are to be estimated. This is a standard two-way, fixed-effect model.
The data we employ are from the Bureau of Economic Analysis, the Bureau of Transportation Statistics and the Federal Highway Administration. Construction worker incomes, as defined by the BEA, are placed into real terms using the Consumer Price Index, All Urban Consumers. Overall road spending is deflated using the Producer Price Index, Streets & Highways. Summary statistics appear in Graphic 4.
There are a few considerations that affect the econometrics of this. In September 2005, President Bush suspended the Davis-Bacon Act, the federal prevailing wage law, for four Gulf Coast states (Alabama, Florida, Louisiana and Mississippi) due to Hurricane Katrina (see Olam and Stamper, 2006). This occurred for less than 60 days. This period is both too brief and too clouded by other factors to provide an identification strategy. However, we did construct a Hurricane Katrina dummy (labeled PW Suspension) for those states in 2005 and included it in full models for each of our dependent variables.
A second concern is the treatment of prevailing wage legislation as a discrete dummy variable. There are states with no state-level prevailing wage laws, and most states with such a law have some minimum applicable cost threshold. For example, California Labor Code Article 2, Sect. 1771 states:
Except for public works projects of one thousand dollars ($1,000) or less, not less than the general prevailing rate of per diem wages for work of a similar character in the locality in which the public work is performed[30] [. . .]
Maryland, which also possesses an active prevailing wage law, has a much higher applicability threshold.
The Prevailing Wage law applies to a public work project including school construction where the contract value is $250,000 or greater and (1) the State or an instrumentality of the State is the contracting body and there is any State funding for the project; (2) a political subdivision is the contracting body and 25% or more of the money used for the construction is State money; or (3) a political subdivision is the contracting body for the construction of an elementary or secondary school and 25% or more of the money used is State money.[31]
The $1,000 threshold in California is sufficiently low that its prevailing wage law functions no differently from laws without thresholds, such as exists in Illinois, Nebraska, New York and Texas, where all government-funded projects apply prevailing wage. We are concerned with the heterogeneity of the dummy and find no effective way to ascertain the size distribution of projects. These contracts are led by state and local governments, and they are made available sporadically across municipal, county, special and state government websites. There is no centralized repository of these data.
Including a small sample dummy variable introduces significant collinearity in our two-way, fixed-effects model. So, in order to test for a role in heterogeneous prevailing wage treatment, we reduce the sample of states. In this case, we provide two ranges to test. We simply omit from our test any state with a minimum prevailing wage contract threshold of $100,000 or less. We do this again based on a threshold of $1,000,000 or less in a state’s legislation. This effectively removes all states with thresholds from our sample. This resulted in the sample size declining from the 48 conterminous states to 35 and then 29 states, respectively.
We omitted Washington, D.C., from the model of roadway costs because its roads have a quality rating that seems unrealistically low. We surmise this is due to factors related to sampling or characteristics, not necessarily related to maintenance issues. This omission significantly reduces the estimated effect of prevailing wage, since Washington, D.C., a prevailing wage jurisdiction, has such high costs per quality-adjusted mile. Not knowing if this is an irrelevant artifact of the data collection or actual data generation process leads us to omit this cross section.
An optimal modeling approach would be a spare treatment model, with both state and year fixed effects; the traditional two-way, fixed effect. Because we have no data preceding the passage of the Davis-Bacon Act, we are unable to evaluate pre-trends that would help us identify this estimation on all our data. However, as noted above, the prevailing wage literature argues against a strong identification problem in a traditional panel, versus difference-in-difference setting.[32] We believe this remains substantially correct.
However, there are reasonable cost elements that should be addressed with controls. The most obvious of these are traffic differentials, which could be included as a value per vehicle miles traveled. Likewise, cost differences include the effect of a federal share of road miles in a state. This fact bolsters the argument against including the District of Columbia in this estimate, since the entirety of that system is federal.
We also aim to have a fuller modeling of annual cost variation. In one version of our estimate, we add to the model a linear time trend, a recession dummy variable and a single series of total U.S. real road construction spending by year. We explain these results more fully in the results section.
Spatial autocorrelation is a concern. We address that problem a priori through the method recommended by Pesaran.[33] However, road work also has network characteristics that warrant direct modeling. The rationale for this is that some roadway funding may include interstate construction, modification or maintenance between two states that is federally funded for both states. The data generating process here is cross-border construction through agreements, such as the Lewis and Clark Bridge between Indiana and Kentucky. Thus, the spatially weighted dependent variable is appropriate, and we use a direct, local spillovers, specification model of the type recommended by LeSage.[34] For this estimation we construct a first-order, contiguity matrix,