All posts by Rick Mattoon

Where are the Jobs? Midwest Jobs Recovery by State and Sector

The Great Recession, which lasted from December 2007 through June 2009, had a profound effect on U.S. employment. At its height, U.S. unemployment reached 9.5% and job losses totaled approximately 7.3 million. The current recovery is now entering its eighth year, so it may be a good time to take a look at how many jobs lost during the recession have been recovered as one measure of the nature of the labor recovery. In this blog, we examine the pattern of recovery for all five Seventh District states (Iowa, Illinois, Indiana, Michigan, and Wisconsin) in four industry sectors that were heavily impacted by the recession—construction, finance (finance, insurance and real estate or FIRE), manufacturing, and professional and business services.

Figure 1 provides evidence of the job recovery through September 2016 across industries for the U.S. and the five Seventh District states. The first column for each state shows the number of jobs lost in that sector during the Great Recession (in thousands). The second column shows the number of jobs added during the current recovery (in thousands). And the third column shows the recovery rate (jobs added divided by jobs lost in percent). To provide some perspective on the concentration of each industry’s employment within the state relative to the U.S. total, the fourth column shows an employment location quotient. For example, if you look at Illinois, employment in professional and business services is 1.10 (or 10%) above the U.S. total.


The first thing to notice is that there is considerable variation in job loss and recovery both within sectors and across states. Two industries, health and education and government, actually added jobs during the recession (except in Michigan, where government employment decreased). However, while job gains have been sustained for the health and education sector, government has actually contracted during the recovery. At the other end of the spectrum, job losses were largest in manufacturing, construction (mining, logging, and construction), and transportation (trade, transportation, and utilities). While transportation has seen a strong recovery (143.6% nationally), the job recovery in manufacturing is only 29.7%, and in construction the figure is 48.1%. On a state level, total non-farm employment recovery ranges from a low of 114.2% to 240.9%. Based solely on this measure, the best job recovery rate among Seventh District states would appear to be in Iowa and the worst in Illinois.

Iowa has consistently outperformed the region and the U.S. in job recovery, both in aggregate and by sector, since the end of the Great Recession (figure 1). A clear contributor was the role of agricultural production and rising farm incomes that the state experienced up until 2015. Currently, low crop prices are weighing on farm incomes, so it may be that this pattern of growth is starting to flatten out. As figure 2 shows, over the longer time horizon, Iowa tracked the rate of U.S. job growth coming out of recession but shows a noticeable divergence starting in 2014.


Michigan entered the Great Recession significantly weaker than other states in the region and the U.S. as a whole, having continued to lose jobs and suffer economic decline through the recovery from the 2000–01 recession. However, since the end of the Great Recession, the state’s job recovery has accelerated. Particularly noticeable is that Michigan has almost fully recovered its lost manufacturing jobs (98.2%), far exceeding the U.S. (29.7%) and significantly better than Indiana, the most manufacturing-intensive state in the region (73%). Clearly, the auto recovery has been a boon to the state.

Illinois has clearly underperformed both the region and the nation in post Great Recession job recovery, both in aggregate and across industry sectors. While Illinois has more than recovered the total number of jobs it lost during the recession (114.2%), only two sectors of the state’s economy have significantly gained jobs. The leisure and hospitality sector is up 482.3% and the professional and business services sector is up 191.5%. While wages in professional and business service jobs are relatively good, the gains in leisure and hospitality are likely to be lower paying jobs. Now, we look at job performance since January 2000 in four key industries—construction, finance, manufacturing, and professional and business services.


As we see in figure 3, construction employment in the Seventh District states has underperformed the U.S. with the clear exception of Iowa, which has seen a gain of 40% over the 2000 level. U.S. construction employment has returned to its 2000 level, while the remaining four Seventh District states have yet to reach their January 2000 level, with Michigan particularly hard hit—off roughly 25% over the period. The loss in jobs was particularly sharp in 2009 through 2012. Since then, jobs have gradually but steadily come back.


Finance, Insurance and Real Estate

Like construction, finance experienced a boom running up to the Great Recession, followed by a sharp contraction during the recession. Figure 4 indicates that the employment declines in this sector were most pronounced in Illinois, Indiana, and Michigan.  Recovery rates are now above the 2000 level for the U.S., Wisconsin, Iowa, and Michigan. Where recovery has clearly lagged is in Illinois and Indiana.



Manufacturing has been seen as a relatively good news story during the recent recovery. Particularly in the automobile industry, production levels have been consistently high. In addition, export-led capital goods had strong sales growth until the past couple of years. The question is has the rebound in output been reflected in employment? Figure 5 shows that manufacturing continues to follow a stair-step path when it comes to employment. Since 2000, after a shock, employment steps down; during recovery it tends to level off and not fully recover. Manufacturing continues to see a trend toward higher production with fewer labor inputs. For example, even in Michigan, with record-level auto production, manufacturing employment is still 30% below its 2000 level. Similarly in Indiana, the most manufacturing-intensive state in the Seventh District, employment is still roughly 25% below the 2000 level.


Professional and Business Services

The sturdiest employment performance emerging from the recession has been in professional and business services. Figure 6 shows that all five Seventh District states (and the U.S.) now have professional and business service employment levels above the 2000 level. Admittedly, the sector was not hit as hard by the recession as many others. Indeed, in many cases employment levels remained above the 2000 level during the worst months of the recession. The clear laggard is Michigan. As the figure shows, Michigan was shedding professional service jobs during the expansionary period emerging from the 2000 recession and then faced an even sharper downturn during the Great Recession. As such, it had had more ground to make up, and by early 2016 it had moved back up to its January 2000 level.



There is little doubt that aggregate employment growth has rebounded from the depths of the Great Recession. However, as we see in the data, the distribution of those gains has been uneven across states and industry sectors.

Measuring Tax Capacity for Municipalities in Cook County

Illinois’s fiscal situation will likely require tax and revenue increases. How might we assess a municipality’s tax capacity, or ability to “absorb” a larger tax bill? In our previous blog, we reviewed various methods of assessing tax capacity. Now, we use the municipal-gap method to estimate tax capacities for Cook County municipalities.

The municipal gap is the difference between revenue capacity and expected expenditures. We estimate revenue capacity by multiplying the total equalized assessed property values (EAVs) in each municipality by a standard tax rate-the rate required to bring the total property tax revenues of Cook County municipalities in line with their total expenditures on non-school municipal services. Our measure of (own-source) revenue capacity excludes intergovernmental transfers. We predict expected expenditures based on estimates of each municipality’s socioeconomic and physical characteristics. Finally, we subtract expected expenditures from revenue capacity to get the municipal gap. A positive gap implies that a municipality has a larger tax capacity, and a negative gap implies a smaller tax capacity.

In practice, this analysis need not be restricted to municipalities located within one county. However, differences across counties in property assessment practices, as well as the quality and composition of services provided, may distort differences in the municipal gap. Restricting the sample to Cook County municipalities should limit differences due to these extraneous characteristics. To this end, we also exclude municipalities with smaller populations (those with populations below the 25th percentile for Cook County). Consequently, results from our analysis can be generalized to a subset of Cook County municipalities and expenditures, namely general government, which largely consists of public safety expenditures.

Data Sources and Calculations

Non-school municipal expenditures and EAVs were obtained from the Illinois Comptroller’s Fiscal Year 2014 Annual Financial Report.1 In the report, expenditures are categorized according to their reported functions (e.g., public safety) and governmental fund (e.g., general fund). We calculated non-school expenditures by combining all reported expenses across functions and funds. Revenue capacity was calculated by multiplying each municipality’s EAVs by a standard tax rate, which is the aggregate Cook County expenditures divided by aggregate EAVs; the resulting rate is 12.8%. Both expenditures and revenue capacity are normalized across municipalities by expressing them in dollars per capita.

Estimates of socioeconomic and physical characteristics were obtained from the Census Bureau 2014 American Community Survey 5-year estimates.2 We separated characteristics into two groups: environmental and control variables. Environmental variables are assumed to be more exogenous to the choices of local officials and are used to predict expected expenditures. They include the unemployment rate, poverty rate, population density, and population (logged). In contrast, control variables are assumed to be less exogenous, and either failing to control for these factors or using them to predict expenditures may bias our predictions of expected expenditures. Control variables include the percentage of the population ages 25 and older with a bachelor’s degree or higher, income per capita, the percentage of housing units that are owner-occupied, the median age of the population, and whether the municipality owns or operates a public utility company (this last measure comes from the Comptroller’s report).

Brief Data Summary

Table 1 provides descriptive statistics on expenditures, revenue capacity, and the environmental and control variables. On average, a municipality spends $2,545 per capita on non-school services. Cook County municipalities allocate, on average, 33% of non-school expenditures to public safety, and only 2% to social services. The large gap between average revenue capacity ($4,199 per capita) and average expenditures underscores the fact that we exclude a large portion of all expenditures municipalities face, such as those appropriated to overlapping governments. The sizes of standard deviations reflect substantial heterogeneity in the compositions of expenditures across municipalities, in particular for debt and capital outlay. The minimum value for the other expenditures/expenses category in part reflects reimbursements.


Calculating Municipal Gaps

We use regression analysis to derive expected expenditures. First, we estimate the effects of environmental variables on the dependent variable, actual municipal expenditures, while holding constant the control variables. Second, we predict expected expenditures using a municipality’s actual values of the environmental variables and the estimated effects.

Table 2 provides results from estimating the effects of environmental and control variables on non-school municipal expenditures. Altogether, we could find no evidence that the environmental variables affect municipal expenditures, controlling for additional factors. In addition, the adjusted R-squared value suggests that we explain roughly 40% of the variation in expenditures (around its mean). Table 3 provides an example of calculating expected expenditures for the City of Chicago (values were rounded to 2 decimal places). Multiplying a municipality’s actual values for the environmental variables by each variable’s corresponding effect results in that variable’s contribution to expected expenditures; summing all the contributions leads to expected expenditures. The final step in the analysis is subtracting expected expenditures from revenue capacity, resulting in the municipal gap.



Results and Conclusion

Table 4 displays the results for municipalities with the largest and smallest gaps. Glencoe Village is assigned the largest positive gap, with an additional $15,846 in revenue per capita available after appropriating funds for expected expenditures. In contrast, Park Forest Village would require an additional $1,802 in revenue per capita to fund its remaining expected expenditures. How do the results of the municipal gap analysis using expected expenditures compare to those using actual expenditures? Table 5 provides findings for the latter scenario. Results for all municipalities included in our study may be obtained here.



Mapping the municipal gaps illustrates the geographic discrepancies in tax capacity. Figure 1 displays the municipal gaps calculated using expected expenditures. For comparison, figure 2 displays the municipal gaps calculated using actual expenditures. Results are largely consistent between the two; one primary difference is that tax capacity is larger for several southern Cook County municipalities in the analysis with actual expenditures. Perhaps one unsurprising result is that, in general, northern Cook County municipalities have greater tax capacity than more central and southern Cook County municipalities. However, there are “pockets” of municipalities with smaller tax capacity located within regions that have greater tax capacity, and vice versa.

Figure 1: Gap with Expected Expenditures


Figure 2: Gap with Actual Expenditures


In sum, identifying the ability for municipalities to absorb larger tax bills is becoming increasingly crucial to estimating local governments’ capacity to generate additional own-source revenues. Several methods exist that rely on comparisons between each government’s revenue and expenditures under hypothetical conditions. Here, we utilized the municipal-gap method to identify tax capacities for a subset of Cook County municipalities. Among the limitations of our analysis is the fact that we exclude important information on both the revenue and expenditure sides. Our analysis relies on non-school expenditures and property values to derive expected expenditures and revenue capacity. Local officials with more complete information on expenditures (e.g., for overlapping governments and schools) and revenues from additional sources (e.g., intergovernmental transfers) may benefit from estimating tax capacity using the municipal-gap approach, or one of the other methods we talked about in our previous blog.

  1. FY2014 Annual Financial Report data procured from the financial database website.
  2. U.S. Census Bureau; 2014 American Community Survey 5-Year Estimates,

What is Illinois’s Tax Capacity?

A recent study ranked Illinois 47th among U.S. states and Puerto Rico for its fiscal health.1 Particularly concerning was the report’s finding that the combination of total debt, unfunded pension liabilities, and underfunded other post-employment benefits amounts to 61% of total state personal income. In contrast, the same figure for other Seventh District states ranges from a high of 38% in Michigan to a low of 16% in Indiana. Given the magnitude of Illinois’s debt, any plan aimed at improving the state’s fiscal solvency will likely require both expenditure cuts and tax and revenue increases.

So what is the taxable capacity of Illinois? Two broad issues arise. First is the issue of fairness: Would further taxation violate society’s notions of imposing undue burdens on those who can least afford it? Second is the issue of impairing economic activity: Would further taxation discourage economic activity or otherwise drive out taxable wealth to an unacceptable degree?

In this blog post, we describe several methods for identifying a community’s tax capacity. In general, researchers have attempted to measure and compare capacities for specific places by calculating hypotheticals that rely on norms or averages across all places. For example, how much revenue might we expect to raise in a community if we imposed average tax rates there? And how much should a community be spending on public services, given its population characteristics and its need for services? And importantly, how do the two estimates differ? Are there obvious gaps between resources and needs?

Gordon, Auxier, and Iselin (2016)2 used such a representative revenue and expenditure approach to estimate this hypothetical gap in funds a state has available for government operations. The study documents that there is enormous variation in the amount of revenue states collect and what they spend on public goods and services. To drill down to tax capacity, the study measures what each state would collect in revenues and spend on government services if it followed national averages, adjusted for state-specific economic and demographic factors. Table 1, section (1) shows the actual gap, or the difference between actual revenues and expenditures, in FY2012, assuming that states rely only on revenues that they raise themselves through taxes and fees. The gaps are sizable, but adding in federal transfers largely erases the gaps. Turning to the hypotheticals as they relate to tax capacity, Table 1, section (2) compares representative revenues, or revenues that a state would raise if it had an average tax structure, to representative expenditures, or expenditures if the state had an average spending per capita. In contrast to the actual gap, the representative gap remains even after the addition of federal transfers in all of the Seventh District states other than Iowa. In this hypothetical case, if Seventh District states (other than Iowa) adopted a nationally representative tax structure, they would not have sufficient resources even after federal transfers to provide a representative level of public expenditures.


Haughwout et al. (2003)3 developed a more refined analysis, termed the “revenue-hill” method, that estimates the deterioration in tax capacity that takes place as higher tax rates discourage taxable activity. The revenue hill builds a hypothetical schedule of tax rates and revenues that demonstrates how fully a city is utilizing its tax base. The goal is to build a “Laffer Curve” that allows policymakers to estimate the economic effects of the next tax dollar (e.g., effect on employment). The closer the measure is to the top of the hill, the closer the city is to exhausting its tax capacity. Once a city is over the top of the hill, increases in tax rates will become so unproductive that revenues actually decline. These measures can be constructed for each tax base a city might use. Therefore, while a city may have reached capacity for one tax base (e.g., sales tax), it may still have capacity in another (e.g., property tax). Haughwout et al. (2003) examined four cities—New York, Philadelphia, Houston, and Minneapolis—and found that only Minneapolis was “comfortably” below its revenue hill, and thus had additional tax capacity. In the case of Minneapolis, additional taxes could provide net benefits to property owners. New York and Houston were at the top of their revenue hills, implying that additional taxes would have a negative impact on employment.

Finally, Bo Zhao and Jennifer Weiner of the Boston Fed suggested the “municipal-gap” method for measuring tax capacities across municipalities in Connecticut, by recognizing that taxable capacity can only be measured in the context of a government’s particular needs and resource costs in providing adequate services.4  For example, limited tax capacity can exist when a community faces higher costs or fewer resources for providing public services (or both). In both cases, it can be driven by economic, topographic, and demographic factors specific to the community (e.g., a relatively high rate of poverty or significant risk of extreme weather).

First, one identifies revenue capacity. Revenue capacity is defined as the ability of municipalities to raise revenue from all of the sources they are authorized to tax, even if they choose not to tax a particular base. Capacity is calculated using the “representative tax system” approach, where all communities use a standard uniform tax rate against the tax base. The rate is determined by ensuring that the statewide rate raises enough revenue to cover existing expenditures. Second, one identifies expected expenditures–the average level of spending based on the municipality’s underlying socioeconomic and physical characteristics. This number is is calculated using regression analysis to predict a municipality’s expenditures based on actual values of the underlying characteristics. One purpose of deriving expected expenditures is to remove the variation in expenditures due to the choices of local officials who may favor particular government programs.

The study focused on the costs of providing largely non-educational local services, primarily public safety. It found that large fiscal disparities in Connecticut were primarily driven by their differences in revenue raising capacity. The uneven distribution of the property tax base coupled with the relative dependence on property tax revenues in the state meant that resource-rich municipalities had, on average, per capita revenue capacity eight times that of resource-poor towns. The cost of providing municipal services was less dispersed, with the highest-cost municipalities spending 1.3 times that of the lowest-cost towns. Importantly, the study also found that non-school revenue grants from the state had limited effect in reducing fiscal disparities.

What can tax capacity studies tell us about Illinois’s fiscal problems?

Illinois has a particularly difficult choice when it comes to future tax adjustments. First, the debt overhang at the state level is so large that any future tax increases will necessarily be directed to paying down debt rather than purchasing new services. Incremental tax increases will pay for services already consumed and, as such, it is difficult to see how future taxes will provide governments with resources to support programs that enhance growth. Second, capacity studies, such as Gordon et al. (2016), suggest that Illinois has already reached its capacity limits. While it would be a stretch to adapt this to the revenue-hill concept of actual declines in revenues in response to tax hikes, it does imply that Illinois has little room to increase taxes without reducing economic activity in ways that would be damaging. The depth of the problem increases when recognizing that many Illinois municipalities also face revenue gaps that would make the compound effects of a state tax increase coupled with a local increase that much worse. As these studies show, there tends to be considerable variation in both the level of expenditures and available revenues across any state when it comes to financing government services. The question then becomes what is the geography of tax capacity in Illinois?

In a second blog, we will apply local revenue capacity and service cost to Illinois municipalities. Stay tuned to see what fiscal disparities might exist for municipalities in Cook County.

  1. Norcross, E., & Gonzalez, O. (2016). Ranking the States By Fiscal Condition.
  2. Gordon, T., Auxier, R., & Iselin, J. (2016). Assessing Fiscal Capacities of States.
  3. Haughwout, A., Inman, R., Craig, S., & Luce, T. (2003). Local Revenue Hills: Evidence from Four U.S. Cities.
  4. Zhao, B., & Weiner, J. (2015). Measuring Municipal Fiscal Disparities in Connecticut.

Making Value for America: A study by the National Academy of Engineering

Production technology and the nature of work are changing rapidly, giving rise to job declines in the manufacturing sector. In this context, can the U.S. design policies that support manufacturing while providing greater opportunity for U.S. workers? This was the question asked of a study panel at the National Academy of Engineering, which produced “Making Value for America: Embracing the Future of Manufacturing, Technology and Work.”

On May 4, Nick Donofrio, who chaired the study committee, joined a panel of experts at the Federal Reserve Bank of Chicago to present the findings and implications from the report. Donofrio was the Executive Vice President for Technology at IBM and a member of the National Academy. Joining him were panelists Dan Swinney (Manufacturing Renaissance and study committee member), Chad Syverson (University of Chicago Booth School of Business and study commission member), Haven Allen (World Business Chicago) and Craig Freedman (Freedman Seating).

Setting the stage for the program was Bill Testa, Vice President and Director of Regional Programs at the Chicago Fed. Testa focused on the key role of manufacturing in the Midwest economy. Within the Midwest region, the manufacturing job base remains 53% more concentrated than in the U.S. as a whole. However, dramatic declines in manufacturing jobs have led many policymakers to pursue other economic development targets. Since 1969, when manufacturing accounted for roughly 40% of the regional job base, manufacturing employment has fallen to 13.5%. Testa noted that from 2000 through the recession of 2009, manufacturing jobs in the Seventh District states of Illinois, Indiana, Michigan, Wisconsin, and Iowa dropped by 35% or 1.16 million; and only 224,000 or 21% of those jobs have returned during the recovery to date.

Testa commented that some of this trend can be traced to technology and productivity. What took 1,000 workers to make in 1950 can be done by 200 today. Moreover, increasingly workers in manufacturing jobs are upskilling and are required to have the ability to work with advanced technology—and to do so at pay scales set by global competition. Despite the many challenges, Testa argued that the Midwest still holds some advantages for manufacturers, such as a strong supply chain and the infrastructure to move goods efficiently. Recreating the region’s network of rail, road, air hubs, and ports would be difficult elsewhere. Second, manufacturing directly comprises 20% of the region’s overall output, but more importantly is responsible for almost two-thirds of the research and development in the region. Additionally, the region’s universities are well positioned to create innovation in engineering and technical fields that can lead to new products and processes.

Donofrio presented the findings from Making Value for America. Donofrio emphasized that this was not a typical manufacturing study. He suggested that in some ways manufacturing is a 20th century word and that what matters today is not simply making things but adding value through production. Understanding where value is added is critical; and in many cases, value comes from services related to the final product. Specifically, he defined adding value as the process of using ingenuity to convert resources into a service or process that contributes additional value to a person or a society. In particular, the study was interested in how the nature of work is changing. Donofrio quoted former MIT president Charles Vest who said, “Far too much of our nation is waiting for new ways of work to arrive. We hear lots of rhetoric about how the nature of work will change, as it relates to some unknown distant future. The fact is that it is happening now, and we need a broader recognition of this fact and policies and education that reflects it.”

Donofrio noted that U.S. employment in manufacturing will never regain its historical levels, but growth will be facilitated by policy that focuses on adding value and innovation. Recommendations from the study focused on three areas—education, collaboration, and being inclusive. A goal is to develop a robust innovation ecosystem that includes business; federal, state, and local governments; economic development organizations; educational institutions; and research organizations. A partial list of recommendations appears in Table 1; the complete list is available at


Chad Syverson kicked off the panel discussion by talking about the university’s role in supporting education at the pre K to 12th grade level. He noted that the University of Chicago has been active in urban education, ranging from the creation of charter schools to the creation of the Urban Education Lab. All of these efforts use rigorous social science evaluation to develop best practices for education.

Additionally, the university works directly to support entrepreneurship through the Polsky Center, which serves as a resource for supporting business formation. Syverson noted that the U.S. has had a 30-year downward trend in new business formation and that the dynamics behind this are not well understood. However, it is though business formation that significant innovation occurs, so the trend is disturbing, he said. Complementary services are provided by the Booth School of Business working with the Chicago Innovation Exchange, the 1871 tech incubator, and directly with businesses to disseminate best practices. Syverson noted that large amounts of value are left on the table when firms fail to keep up with best practices and that significant gains for the U.S. economy can be provided by better educating firms.

Haven Allen described the multitude of programs that can be found in Chicago that create manufacturing networks. These include national efforts such as the Digital Manufacturing and Design Innovation Institute (DMDII) and its related Illinois Manufacturing Labs. A clear goal is to connect local firms to this national network of innovative firms. This requires broad partnerships that include businesses, local community groups, and education. Allen stressed that training is key and that recent apprenticeship programs offered by organizations such as the Jane Addams Resource Center, the University of Illinois-Chicago, and Daley College provide models for supporting work force development. Finally, Allen emphasized that successful partnerships will focus on improvements in people, process, and product.

Craig Freedman offered the perspective of a manufacturer. Freedman suggested that the pace of change means that businesses and their workers need to get smarter at all levels. Business needs to link with education in order to make sure that relevant skills are learned at all grade levels. For example, Freedman cited the Manufacturing Connect program at Austin Polytech as a model that deserves replication. The school is located in the Austin community on the west side of Chicago. The program teaches high school students metal-working skills and provides them with certified credentials upon graduation. Local businesses partner with the school and provide apprenticeships and job shadowing opportunities.

Freedman also praised local training organizations such as the Jane Addams Resource Center, Daley College, and the 1000 Jobs Campaign as helping support critical work force development. Finally, Freedman suggested that more work needs to be done to promote the image of manufacturing as a good career path. Current perceptions of manufacturing are based on outdated notions of the industry that need correcting if young people will be attracted to these jobs.

Concluding the discussion was Dan Swinney. He noted that social inclusion should be a goal of the new emphasis of manufacturing rebirth in cities. He also cited the efforts of the Manufacturing Renaissance and the Manufacturing Connect program in the Austin Community in Chicago. Swinney stressed the importance of bringing these types of programs to areas that have suffered disinvestment. The challenges communities like Austin face are clear in the data. While unemployment in Chicago has fallen to 6.4%, in Austin it hovers near 30%. Similarly, manufacturing job loss in Austin is near 90%. However, to address the challenges faced by communities like Austin, Swinney argued, programs like Manufacturing Connect must be scaled up, since they currently only reach a small subset of students.

Infrastructure and Economic Growth — A Conference Preview for November 3

A common trait among economists is that they rarely agree on anything. However, the latest survey of economic experts by the Initiative on Global Markets of the University of Chicago’s Booth School of Business found unanimity on the value of infrastructure to the economy. When the 44 participants were presented with the proposition, “Because the U.S. has underspent on new projects, maintenance, or both, the federal government has an opportunity to increase average incomes by spending more on roads, railways, bridges and airports,” exactly zero disagreed. When further asked whether the U.S. has underspent on infrastructure, 36 agreed, 3 were uncertain and 5 did not respond. While such overwhelming agreement among economists might scare some people, it does suggest that the best economic researchers clearly have identified a relationship between infrastructure investments and economic growth. However, this same group of economists was skeptical about the efficiency of infrastructure programs. Nearly half agreed that past experience suggests that many infrastructure projects would have low or negative returns. As Austin Goolsbee put it, “hard to argue with the reality that some money will end up in powerful [Congressional] districts without much need for it.”

Given the perceived value, why has the U.S. apparently fallen behind in the infrastructure race? One theory is that fiscal pressure at all levels of government during and after the Great Recession caused governments to put off infrastructure investments in order to balance operating spending. Evidence for this shows up in data on the average age of government fixed assets, which have risen from 21.6 years to 22.4 years since 2007 (see figure).


Further complicating this has been a cloudy picture for funding sources directly related to infrastructure spending. The most prominent federal source, The Highway Trust Fund, has seen growth in gas excise tax revenue steadily erode as the 18.4 cents per gallon rate has been unchanged since 1993 while vehicle travel has declined. This year, Congress acted to prevent a deficit in the trust fund through a short-term fund transfer and by allowing companies to smooth pension returns, which would boost tax revenues in the short run. This clearly will not be a long-term fix. At the same time, state and local governments have faced very difficult fiscal conditions emerging from the Great Recession. For most states, revenues are only now returning to pre-recession levels. States that rely on excise taxes on fuel to fund infrastructure have seen the same erosion in revenues as the federal government, while states with sales taxes have suffered from declining gas purchases. In Illinois, gas tax receipts fell from $1.59 billion in 2007 to $1.21 billion in 2013 adjusted for inflation. Similarly, vehicle miles traveled per capita in the state have fallen by 6.5% since 2004. This inability of fuel tax revenues to keep pace with inflation has left dedicated infrastructure spending squeezed.

On November 3, the Chicago Fed will host a half-day program looking at key issues related to infrastructure. The first panel will start with a presentation from Therese McGuire of Northwestern University’s Kellogg School, who chaired a Transportation Research Board study that examined the role of the infrastructure component of the American Recovery and Reinvestment Act of 2009 on economic outcomes. Joining McGuire will be Dan Wilson from the San Francisco Fed, who has written extensively on infrastructure and will present his work on measuring the economic impacts of highway infrastructure. (For an example, see Rounding out the panel will be Tracy Gordon, who recently joined the Urban Institute after a stint at the Council of Economic Advisors and will discuss how to incentivize state and local governments to do more to fund infrastructure.

The second panel will examine methods for paying for infrastructure. Ben Husch from the National Conference of State Legislatures will discuss the current status of federal infrastructure funding, including prospects for the Highway Trust Fund. Michigan state budget director, John Roberts, will discuss a comprehensive infrastructure funding proposal that was introduced by Governor Rick Snyder this year. This proposal would have boosted infrastructure funding for the state and allowed for future fuel taxes to be indexed to inflation. Joining us from Oregon will be James Whitty, who has been responsible for administering the state’s pilot effort for a vehicle mile tax. States are considering this type of tax as a possible replacement for traditional fuel taxes. Finally, public–private partnerships are frequently seen as key to expanding infrastructure funding. Stephen Beitler, CEO of the Chicago Infrastructure Trust, will discuss how this new approach is working.

The program will be held at the Chicago Fed on November 3, 2014, starting at 8:30 a.m. There is no charge to attend. To register, follow this link.