Detroit Association of Business Economists 2015 Annual Automotive Outlook

On January 22, 2015, the Detroit Association of Business Economists (DABE) held its annual Automotive Outlook Symposium at the Detroit Branch of the Federal Reserve Bank of Chicago. The event was attended by approximately 50 guests, including DABE members together with other local business leaders, academics, and media representatives. I was among the speakers, as was Peter Sweatman, director of the University of Michigan Transportation Research Institute (UMTRI).

Sweatman was appointed UMTRI director in September 2004. UMTRI was created in 1965 with the main goal of improving vehicle safety and sustainable transportation in the U.S. and around the world. It currently has a staff of 102 full-time researchers, faculty, graduate students, and administrative staff affiliated with the University of Michigan, who have conducted over 1,000 research projects over the years. In its latest endeavor, UMTRI has created a public/private research and development partnership called the Michigan Mobility Transformation Center (MTC). The goal of the MTC is to be in the forefront of research and development of vehicle connectivity. This includes vehicle to vehicle (V2V) and vehicle to infrastructure (V2I) technology. As Sweatman pointed out, it’s not just about transportation but about safe and sustainable personal mobility that transcends just getting from one place to another. The vehicles of the future will free the occupants from many of the hands-on tasks and decision processes that are part of operating a vehicle today. By doing this, it is believed that the driving experience can be transformed into a much safer and more productive and enjoyable experience for the vehicle occupants. The major goal of the initiative is to make vehicles of the future much safer by adding technology that will aid in accidence avoidance. Vehicles will not only be able to communicate with one another, they will also be linked with their surrounding environment. For example, Sweatman explained that the connected vehicle (CV) technology could warn drivers before they reach areas of dangerous weather, poor visibility, or other hazardous road conditions. The vehicle could be programed to respond to these conditions on its own either by adjusting its speed or offering alternative routes or a truly autonomous vehicle could choose to take an alternative route on its own. If the driver were to decide to continue to travel on the perilous road, the CV would inform the driver of any accidents in path ahead immediately giving the driver or the vehicle time to adjust accordingly.

CV technology is in its infancy today, and there is still a lot of research and development to do before it can be implemented. To aid in this work, MTC has adopted a plan in collaboration with the Michigan Department of Transportation (MDOT). The plan has three pillars:

  1. Ann Arbor Connected Vehicle Test Environment (2014+)
  2. Southeast Michigan Connected Vehicle Deployment (2015+)
  3. Ann Arbor Automated Vehicle Field Operational Test (2016+).

Pillar 1 of the connected vehicles (CV) pilot deployment program commenced on August 21, 2012, and included a pilot deployment of 2,836 vehicles— cars, trucks, buses and motorcycles—equipped with wireless communication devices in the Ann Arbor area. This phase ran for six months and was extended for an additional three years by the U.S. Department of Transportation.

Pillar 2 will test the rationality of connected vehicles by implementing a jump from research to regional deployment. It will include 20,000 vehicles together with 500 infrastructure nodes located based on safety and congestion needs and the installation of 5,000 vehicle and pedestrian safety devices. The U.S. has invested approximately $1.0 billion dollars over a ten-year span for this research.

Pillar 3 will include an automated Ann Arbor, where a select group of industry and government partners will work together. This phase will include testing in a simulated city (M City) a $6.5 million 32-acre site located in Ann Arbor near the University of Michigan campus and is scheduled to open in July 2015.

The investment that has taken place so far is likely just the tip of the iceberg in terms of what will be needed to complete a national intelligent transportation system. Sweatman argued that if the needed investment is made to complete a national system, it will not only provide an opportunity for the U.S. to lead the world in developing a CV technical knowledge base, it will also lead to the creation of numerous high-tech jobs in Michigan and throughout the country.  For more information on this topic, follow some of the links provided in this article or on the University of Michigan Transportation Research Institute website.

Following Dr. Sweatman’s presentation there was a short presentation summarizing the 2014 light vehicle industry. Here are some of the highlights from that presentation. There were 16.434 million light vehicles sold in the U.S. in 2014 making it the best year the industry had seen since 2006, when 16.504 million light vehicles were sold. Although job growth has been good in the auto industry, the pace of growth has slowed in conjunction with the slowing pace of growth in sales. As a result, the automotive and parts sector added 41,600 jobs in 2014, down slightly from the peak job growth year of 2012 when the industry added 59,600 jobs. Average hourly earnings of automotive manufacturing workers, which were flat for most of the period following the 2008 recession, grew only slightly in 2014, up just 0.5% when adjusting for inflation. According to data from J.D. Power and Associates, vehicle incentives as a percentage of total vehicle prices rose to 9.1% in 2014, while the average transaction price for a new vehicle grew to an estimated 56.7% of median household income. One of the more controversial developments of 2014 was the number of vehicles recalled. According to data from the National Highway Traffic Safety Administration, vehicle manufacturers recalled almost 64.0 million vehicles in 2014, the most ever reported. And, of course, the biggest story was the reduction in gasoline prices through the year, with the national average for a gallon of regular gasoline falling more than $1.10 from December 2013 to December 2014. This resulted in about $600 per year in fuel cost savings for the average driver. Looking ahead, there will be 16.9 million and 17.0 million light vehicles sold in the U.S. in 2015 and 2016, respectively, according to the Blue Chip Indicators consensus forecast. If you’d like to see more information or to view the entire presentation you may click here.

Seventh District Update, January 2015


A summary of economic conditions in the Seventh District from the latest release of the Beige Book and from other indicators of regional business activity:

  • Overall conditions: Growth in economic activity in the Seventh District remained moderate in December, and contacts expected growth to continue at a similar pace in 2015.
  • Consumer spending: Growth in consumer spending remained moderate. Holiday sales slightly exceeded expectations and light vehicle sales increased steadily.
  • Business Spending: Inventories were generally at comfortable levels and capital expenditures and spending plans continued to rise. Hiring increased and contacts expected job growth to continue in the coming year.
  • Construction and Real Estate: Demand for residential construction was little changed. Home prices and residential rents both increased, while the pace of home sales slowed. Nonresidential construction and commercial real estate activity increased moderately.
  • Manufacturing: The auto, aerospace, and energy industries remained a source of strength, though demand for energy production inputs was expected to slow. Steel production grew steadily, while demand for heavy machinery grew slowly.
  • Banking and finance: Credit conditions were little changed on balance. Market volatility stabilized and equity markets moved higher. Business loan demand was steady and consumer loan demand increased in line with expectations.
  • Prices and Costs: With the exception of falling energy prices, cost pressures were little changed. Wage pressures continued for skilled workers, but were less pronounced for unskilled workers. Non-wage labor costs changed little on balance.
  • Agriculture: Corn and wheat prices rose during the reporting period, while soybean prices were flat. Low crop prices led farmers to focus on minimizing costs instead of maximizing output in 2015, and ethanol margins compressed with the drop in oil prices.

The Midwest Economy Index (MEI) increased to +0.52 in November from +0.36 in October, remaining above average for the eighth straight month. The relative MEI rose to +0.72 in November from +0.35 in October, reaching its highest value in three years. November’s value for the relative MEI indicates that Midwest economic growth was moderately higher than would typically be suggested by the growth rate of the national economy.

Seventh District Update, December 2014


A summary of economic conditions in the Seventh District from the latest release of the Beige Book and from other indicators of regional business activity:

  • Overall conditions: Growth in economic activity in the Seventh District remained moderate in October and November. Contacts expressed optimism for the coming year, but were concerned about weakening foreign growth and the possibility of another severe winter.
  • Consumer spending: Growth in consumer spending was moderate. Non-auto retailers had a positive outlook for the holiday season and auto sales and leasing activity remained strong.
  • Business Spending: Inventories were at comfortable levels, capital expenditures and spending plans continued to rise, and actual hiring and hiring plans continued to increase at a moderate pace.
  • Construction and Real Estate: Residential construction rose, and home sales picked up more than expected. Nonresidential construction and commercial real estate activity increased moderately.
  • Manufacturing: The auto, aerospace, and energy industries remained a source of strength. Steel production grew steadily, while demand for heavy machinery grew slowly. Manufacturers of construction building materials reported an increase in shipments.
  • Banking and finance: Credit conditions were little changed on balance. Equity market volatility increased in mid-October and then declined. Business loan demand was mixed, and consumer loan demand increased.
  • Prices and Costs: Energy and steel prices declined, but transportation costs increased for many contacts. Retail prices were little changed. Wage pressures continued for skilled workers, but were less pronounced for unskilled workers. Non-wage labor costs changed little.
  • Agriculture: The District harvest was behind, but yields should still set records. Corn, soybean, wheat, and cattle prices moved up, while milk and hog prices declined.

The Midwest Economy Index (MEI) decreased to +0.36 in October from +0.46 in September, but remained above average for the seventh straight month. The relative MEI moved down to +0.33 in October from +0.43 in September. October’s value for the relative MEI indicates that Midwest economic growth was somewhat higher than would typically be suggested by the growth rate of the national economy.

Chicago City Trends

By Bill Sander and Bill Testa

The fortunes of the city of Chicago have become clouded in recent years as concerns over its weakening finances and heavy debt obligations have grown. The tally for the unfunded public employee debt obligations of Chicago’s overlapping units of local governments (including those for public schools, parks, and county services) is now approaching $30 billion. Moreover, the city government has been criticized for its practices of funding current public services with proceeds from the issuance of long-term debt and the long-term leases of public assets (such as its parking meter system). However, faith in Chicago’s ability to address its debts has not fallen so far as that in Detroit’s, chiefly because the Windy City’s economic trends display more vibrancy.

Population change is a prominent indicator of the health of an urban economy because it reflects a city’s ability to hold on to its residents (as opposed to losing them to the suburbs or other locales). Over the past few decades, similar to other central cities, Chicago has experienced an erosion in its population share of the broader metropolitan statistical area (MSA);[1] in contrast, the surrounding suburbs have seen their share climb. According to the U.S. Census, Chicago held 38% of the MSA’s population in 1980, with this share falling to 35% by 1990; in the subsequent 20 years, Chicago’s population share of the MSA decreased another 3 percentage points per decade, reaching 29% by 2010 (see table below). During the 1980–2010 period, Chicago lost a total of over 300,000 residents. At the same time, suburban Chicago gained close to 2 million in population. Since 2010, the city of Chicago’s population and population share of the MSA have strengthened somewhat, though the (off-Census year) estimates are probably not as reliable.

While population trends can be telling for a city’s prospects, they can also belie changes in its residents’ wealth and income. Despite the city of Chicago’s population loss over the past few decades, its economic trends have been generally more encouraging.[2] Household income is an important indicator of Chicago’s fortunes relative to those of its suburbs. In 1990, median household income in the city was just 67% of the median household income in suburban Chicago. By 2010, this income ratio had climbed to 73% (see table below). Decomposing household income statistics by (self-reported) racial/ethnic group reveals that this trend was pervasive for the three largest groups: non-Hispanic white, black, and Hispanic. The ratio of city median income to suburban median income among white households experienced the greatest change; it rose from 77% in 1990 to 98% (near parity) in 2010.

These robust trends are echoed by Chicago’s rising share of adults aged 25 and older who have attained at least a bachelor’s degree. In 1990, among adults aged 25 and older, 19% of those residing in the city had attained a four-year college degree versus 28% of those residing in the suburbs (see table below). By 2010, Chicagoans in this age demographic had almost reached the same share in this regard as their suburban counterparts (33% for city residents versus 35% for suburban residents). The non-Hispanic whites again experienced the greatest change among the three largest racial/ethnic groups. In 1990, 29% of the white city population aged 25 and older had a four-year college degree—the same percentage as the white suburban population in this age demographic; however, by 2010, 55% of such white city dwellers had a bachelor’s degree, while 39% of their white suburbanite counterparts did. Between 1990 and 2010, the city’s black population also made substantial gains in education, as evidenced by the share of black adults aged 25 and older with a bachelor’s degree having risen from 11% to 17%.

By “drilling down” through the data to examine specific neighborhoods, we can see how geographically concentrated the city’s gains in college-educated adults aged 25 and older have been. These gains have been highly concentrated in Chicago’s central business district (“the Loop”) and the surrounding areas, as well as the neighborhoods west of Chicago’s northern lakeshore. As shown in the table below, dramatic gains in the college-educated population were seen in the Loop and the neighborhoods just south, west, and north of it. For example, the Near South Side saw an increase in the share of adults with a four-year college degree climb from 9% in 1980 to 68% in 2010. No less dramatic were such gains in Chicago’s neighborhoods west of its northern lakeshore: The shares of the college-educated population there typically doubled or tripled between 1980 and 2010 (in the case of the North Center neighborhood, this share increased sixfold—from 11% in 1980 to 66% in 2010).

As one might expect, many college-educated Chicago residents work in proximity to their residence. Of those living in the Central Area and Mid-North Lakefront, an estimated 57% work in the Central Area of Chicago and 79% work somewhere in the city.[3] Of those who do work in the Central Area, an estimated 19% travel to work by driving alone (as opposed to walking, public transit, bike, and carpooling); this percentage is much smaller than the nearly 70% of metropolitan Chicago workers who travel to work by driving alone.[4] The trends highlighted thus far point to the fact that the city of Chicago draws and retains many jobs. By one count, the city of Chicago’s Central Area is the domicile of over half a million jobs. As seen below, job counts in the Central Area have remained fairly constant over the past 13 years, even while job levels in the remainder of the city and in the remainder of Cook County have been falling.

Meanwhile, compensation levels per job have continued to climb in Chicago’s Central Area, reflecting a work force with greater skills and education. Annual compensation per worker on the payroll in Chicago’s Central Area exceeds that of the overall MSA by 50%.

Many of the trends shown here bode well for the city of Chicago, despite the fiscal challenges it currently faces. To be sure, many large central cities in the Midwest, including Detroit, are experiencing strong growth of both jobs and households centered around their central areas and downtowns. In this, the central Chicago area enjoys a strong start. ________________________________________

[1] Current and historical delineations of MSAs are available at (Return to text)

[2] This is not to say that all parts of the city have been on the economic upswing. Several Chicago neighborhoods have seen severe deterioration in wealth and income, as well as in living conditions, as evidenced by increasing incidences of homelessness and crime in certain areas in the past few decades; see, e.g., (Return to text)

[3] This statement covers 113,000 workers living in these areas as of the year 2000. Estimates were pulled from and are based on the Census Transportation Planning Package (CTPP), “which is a special tabulation of the decennial U.S. Census for transportation planners” and “contains detailed tabulations on the characteristics of workers at their place of residence (‘part 1’), at their place of work (‘part 2’), and on work trip flows between home and work (‘part 3’)” (see Workers who work at home are excluded. See also; this report ranks Chicago second among major U.S. cities in terms of the percentage of residents living within one mile of downtown who work downtown (figure 3 in the report), and ranks Chicago first in terms of population growth in the downtown area over the period 2000–10 (figure 4 in the report). (Return to text)

[4]Estimates are from and are based on the Census Transportation Planning Package (CTPP). (Return to text)

A Seventh District Labor Market Dashboard

In March 2013, Federal Reserve Board Chair Janet Yellen (then Vice Chair) gave a speech where she discussed the centrality of labor market conditions in the Fed’s decision-making process. The most often discussed indicator of labor market conditions is the unemployment rate, but in this speech and others since,1 Chair Yellen has said that she tracks a number of other labor market indicators as well. This broader set of indicators is now widely referred to as Chair Yellen’s Labor Market Dashboard. The dashboard serves to show that while the unemployment rate has been improving steadily since the depths of the Great Recession, many other labor market indicators have made less progress, and few have returned to where they were prior to the Great Recession.

In this blog post, I look at indicators on Chair Yellen’s dashboard, with a focus on how they measure the Midwest economy. The set of indicators I’ve compiled tell a story quite similar for the Midwest to that for the United States as a whole. While conditions in the Midwest have steadily improved since the depths of the Great Recession, things are not back to normal yet.

Household Survey Measures. Figure 1, panel A shows the unemployment rates for the United States and the Seventh Federal Reserve District2 since 2000. The two rates track each other closely, though there are some notable differences. First, the unemployment rate was somewhat higher in the District before the recession that hit in 2008. Figure 1, panel B shows that the unemployment rate in Michigan was particularly high during this period, largely because of struggles in the auto industry. Second, in terms of unemployment, the District did worse than the nation during the depths of the recession, though it caught up by 2011 as manufacturing recovered. Finally, the District’s unemployment rate again diverged from the nation’s in 2012, but by now it has nearly closed the gap.

1 - Unemployment

A key feature of the unemployment rate is that to be counted as unemployed, an individual without a job must be actively looking for work. Those who report that they are not working and not actively looking for work in the U.S. Bureau of Labor Statistics’ (BLS) Current Population Survey, or the household survey as it’s commonly called, are not considered unemployed. Thus, the unemployment rate can decrease because people give up looking for work, not because they find a job. For this reason (and to provide greater detail), the BLS publishes what it calls alternative measures of labor market underutilization. I take these alternative measures and break them down into five comparable rates.3 Each rate is a percentage of the labor force plus marginally attached workers. The rates are as follows:

  1. Short-term unemployed: people unemployed for fewer than 15 weeks.
  2. Long-term unemployed: people unemployed for 15 weeks or more.
  3. Marginally attached: people who want to work and have looked for work in the last 12 months, but not in the last four weeks.
  4. Discouraged: marginally attached workers who are not looking for work because they believe there are no jobs available or none for which they would qualify.
  5. Part time for economic reasons: workers who are employed part time but would like to be employed full time.

2 - Under_usdi

Figure 2 presents the five measures for the United States and the Seventh District. The measures are 12-month moving averages, so trend movements show up later than in figure 1. The bottom, darkest blue area represents the short-term unemployed. Many people in this group are between jobs or will find work without ever being long-term unemployed. Aside from a blip in 2009, this measure has been steady at around 3.5 percent for the United States and 3.7 percent for the District. The story is much different for the long-term unemployed. There was a substantial increase when the Great Recession hit, and the rate remains elevated today, for both the United States and the District. The same is true for marginal workers (discouraged and not discouraged) and part-time workers who would like to have full-time work.

Figure 3 breaks the District’s unemployment and underutilization rates down by state. Each state has a different baseline. Before the recession, Iowa and Wisconsin had the lowest rates in the District, while Michigan had the highest. Despite the differences in labor market structure highlighted by the different baselines, no state has returned to its pre-recession unemployment and underutilization levels.

3 - Under_dist

The BLS’s household survey provides two additional measures that account for the possibility that the unemployment rate can go down even if labor market conditions don’t improve. The two measures are benchmarked by the overall (working-age) population (specifically, noninstitutional civilians age 16 and over) so that people who leave the labor force are still counted. The disadvantage of benchmarking by the population is that people may not be in the labor force for reasons unrelated to difficulty finding work, such as to attend school, to have a family, or to retire.

The first measure of these two additional BLS measures is the labor force participation rate, which is the number of people in the labor force as a percentage of the population. The second measure is the employment-to-population ratio, which (as you may guess) is the number of employed people as a percentage of the population. Figures 4 and 5 show the measures since 2000 for the United States, the District, and the District states. There is a downward trend in both measures, which largely reflects an aging population. Given the trends, it is possible to spot cyclical movements as well. There is clear upward movement over the housing bubble years and clear downward movement over the recession. It is difficult to discern visually where the measures are relative to trend, but recent research by Chicago Fed economists suggests that they are currently below the trend.4

4&5 - LFP&EtoP

Business Survey Measures. The BLS surveys households to obtain the unemployment rate (and related indicators) and it surveys businesses to obtain their employment levels, openings, turnover, and costs. The most widely discussed indicator from BLS surveys of businesses is payroll employment growth. Figure 6, panel A shows quarterly payroll growth for the United States and the District since the onset of the Great Recession. I’ve scaled the District growth numbers to be as if the District and the nation had the same baseline employment levels.5 Like the unemployment rate, employment growth numbers for the United States and the District are generally in sync, with some notable exceptions. The growth numbers show that the District did worse than the nation during the recession, over 2012, and in the first quarter of 2014, when the District experienced especially harsh winter weather. Figure 6, panel B breaks down employment growth by state. As usual, Michigan is noteworthy. While Michigan was hit hard during the recession, the subsequent strong recovery of the auto industry made important contributions to District employment growth, especially during 2012, when the other states were struggling.

6 - Employment

The BLS also asks businesses about their employment turnover, and figure 7 shows three such measures.6 Panel A is the ratio of the number of unemployed workers to the number of job openings that businesses report; panel B is the number of new hires as a percentage of overall employment; and panel C is the number of quits as a percentage of overall employment. Once again, movements in the United States and Midwest are closely related, though the Midwest was doing somewhat worse before the recent recession. Each measure has a clear cyclical component. Taking the pre-recession period as a baseline, the rate of unemployed per job opening is now close to normal (the Midwest’s rate is slightly closer to normal than the nation’s). The hires and quits rates have not yet fully recovered, but have been growing at a strong pace since the middle of 2013. The quits rate, in particular, tends to be a leading indicator of improvement in labor market conditions, as people are more likely to leave their current positions when their job prospects elsewhere are improving.7

7 - Jolts

The BLS also asks businesses about their employment costs, which are driven in large part by wages. Figure 8 shows two indexes of wage growth for the Midwest states (see note 5) and the United States. Panel A is nominal wage growth, panel B is wage growth adjusted for inflation. Taken together, the panels show that while wage growth has consistently been positive, it has not consistently been above inflation (periods of real wage growth are often followed by periods of real wage decline). This reflects a long trend of slow real wage growth for all but the highest wage earners.

8 - Wages

Figure 9 shows that the quits rate and nominal wage growth move together quite closely in both the United States and the Midwest. Figure 9 also shows that nominal wage growth during the recovery has underperformed a bit relative to the quits rate. This may be a sign that wage growth will pick up in the future.

9 - QtsWge

Taken as a whole, this labor market dashboard indicates that while the U.S. and District labor markets continue to recover from the Great Recession, they are still not back to normal. The employment turnover numbers are the most promising, and they may well lead the other indicators I’ve highlighted. The labor market is clearly headed toward full recovery, but the amount of time it will take to get there remains unclear.

  1. See for example, Chair Yellen’s first press conference and her August 2014 speech at Jackson Hole.
  2. The Seventh District comprises all of Iowa and most of Illinois, Indiana, Michigan, and Wisconsin.
  3. For details on how I calculated the rates, please contact me at
  4. See the Explaining the Decline in the U.S. Labor Force Participation Rate by Aaronson, Davis, and Hu and Estimating the Trend in Employment Growth by Aaronson and Brave.
  5. Specifically, for each quarter, I calculated the ratio of U.S. employment to District employment and multiplied District employment growth by that factor. U.S. employment is roughly eight times District employment.
  6. Note that these measures are not available at the state level; the smallest geographic area for which these measures are available is the Census Region. According to the U.S. Census Bureau, the Midwest region comprises the following states: Illinois, Indiana, Iowa, Kansas, Michigan, Minnesota, Missouri, Nebraska, North Dakota, Ohio, South Dakota, and Wisconsin.
  7. See Labor Market Flows in the Cross Section and Over Time by Davis, Faberman, and Haltiwanger.

Farm Income’s Impact on the Midwest — A Conference Preview

Agriculture is a vital building block for the economy of the Midwest, producing raw materials for food and biofuels manufacturing, as well as stimulating demand for farm equipment, trucks, and more. Income produced by agricultural operations is a key component of personal income in rural areas. This income from farm households supports businesses on the Main Streets of rural towns. However, there has been a decline in the number of farms over the decades,1 which raises concerns about the role of farm income in the future of the rural Midwest.

On November 17, 2014, the Federal Reserve Bank of Chicago will hold a conference to examine the role of farm income in the Midwest economy. (Check for more details on the conference, including the agenda, and to register.) The conference will explore both the decline in agriculture’s role over the longer term and the marked increase in the level of agricultural income over the past decade. This phenomenon contrasts sharply with the troubled fortunes of the broader economy of the Midwest during and after the Great Recession.

Net farm income is a standard way to measure the size of returns from agricultural operations. Basically, net farm income equals the value of agricultural production and net government transactions minus purchased inputs, capital consumption, and payments to stakeholders.2 The latest U.S. Department of Agriculture forecast of net farm income for 2013 was $131.3 billion for the U.S., an increase of 15% from 2012 and the highest result since 1973 (adjusted for inflation).3 In 2009 dollars, net farm income has averaged $115 billion over the past three years, a level that was previously exceeded only during the period from 1943 to 1948 (going back to 1929). Moreover, the latest decade has seen the highest levels of net farm income since the 1950s, even higher than during the 1970s farm boom. However, net farm income is projected to fall to $113.2 billion for 2014, as crop price decreases will more than offset increased yields from this fall’s harvest.

In addition, net farm income for each state is available through 2012. Using this data, one can estimate the net farm income for the five states of the Seventh Federal Reserve District.4 The District states accounted for 19.5% of U.S. net farm income in 2012 ($22.16 billion). Due to the relatively large role played by farmland rentals in the District, 43% of net rent received by non-operator landlords nationwide was in the District’s states ($6.7 billion). These payments boost the economic impact of agriculture on the District, although some landlords reside outside the region. Another $3.4 billion in 2012 was paid out to hired labor by farms in the District. Furthermore, District agricultural operations spent $26.9 billion on purchased inputs that did not originate on farms. So, the economic benefits of agriculture reach out into communities and the businesses of the District.

Net cash farm income is a somewhat different measure of agriculture’s cash flow.5 It provides helpful information to understand the financial positions of farm operations. Moreover, the 2012 Census of Agriculture provided data on net cash farm income by county.6 Combining this data with personal income by county7 allows computation of the share of personal income generated by net cash farm income. Using these sources to compute a total for just counties in the District, I find the District generated $23.9 billion of net cash farm income in 2012. This represented 1.5% of the District’s total personal income.

Also, one can categorize counties by how rural they are.8 For the nonmetropolitan counties of the District, $15.96 billion in net cash farm income represented 5.8% of total personal income. For the metropolitan counties of the District, $7.95 billion in net cash farm income represented 0.6% of total personal income. These numbers reinforce the greater dependence of nonmetropolitan counties on agriculture, as one would expect, yet they also demonstrate that even metropolitan counties have significant farm operations. The map below provides the spatial distribution of District counties in terms of the shares of net cash farm income relative to total personal income. Notice that counties in northwest Iowa tend to have the greatest dependence on farming operations, with four having over 30% of personal income from agriculture in 2012.

While such trends and patterns are illuminating, there are many channels between agriculture and the Midwest economy. Please join us on November 17 as experts from academia, government, and business take a deeper dive into Midwest agriculture and its impacts.





  1. See for a chart and details.
  2. See for details.
  3. See for data.
  4. The Seventh Federal Reserve District comprises all of Iowa and most of Illinois, Indiana, Michigan, and Wisconsin.
  5. Net cash farm income “represents the amount of cash available to service debt, pay family living expenses, and make investments. It is not a comprehensive measure of profitability, however, since it does not account for changes in inventory, accounts payable, accounts receivable, and depreciation.” See for details.
  6. Census of Agriculture data are available via for 2012 and earlier.
  7. See for data under “Local Area Personal Income & Employment.”
  8. See for details.

Seventh District Update, October 2014


A summary of economic conditions in the Seventh District from the latest release of the Beige Book and from other indicators of regional business activity:

  • Overall conditions: Growth in economic activity in the Seventh District remained moderate in September, and contacts maintained their optimistic outlook for the rest of the year.
  • Consumer spending: Consumer spending was led by continued strength in auto sales. Non-auto spending increased slightly, as growth picked up for discretionary spending categories. Retail contacts generally expected that holiday sales would be up slightly relative to a year ago.
  • Business Spending: Capital expenditures and spending plans increased, as a number of manufacturing contacts reported plans for expansion in the near future. Both actual hiring and hiring plans increased at a moderate pace, and many contacts reported slightly higher turnover.
  • Construction and Real Estate: Residential and nonresidential construction increased. Growth in home sales and prices slowed somewhat, while vacancies ticked down and leasing of industrial buildings, office space, and retail space all increased.
  • Manufacturing: The auto, aerospace, and energy industries remained a source of strength. Demand for steel increased and demand for heavy machinery picked up some on net, as higher demand for construction machinery overshadowed weakness for ag and mining machinery.
  • Banking and finance: Credit conditions were mixed. Equity market volatility increased and corporate bond spreads widened, even as business and consumer lending increased.
  • Prices and Costs: Energy costs declined, while steel and aluminum prices increased. Retail prices were down slightly as contacts reported more generous sales promotions. Overall, wage pressures were modest, and non-wage labor costs changed little.
  • Agriculture: Overall crop conditions were very good and the District should see record corn and soybean harvests. The huge anticipated harvests pushed down corn and soybean prices.

The Midwest Economy Index (MEI) decreased to +0.55 in August from +0.63 in July, but remained above average for the fifth straight month. The relative MEI edged down to +0.26 in August from +0.31 in the previous month. August’s value for the relative MEI indicates that Midwest economic growth was somewhat higher than would typically be suggested by the growth rate of the national economy.

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.

Gross State Product Growth and the Midwest Economy Index

In August 2014, the U.S. Bureau of Economic Analysis (BEA) published prototype quarterly estimates of gross state product (GSP). In releasing this quarterly supplement to its existing semiannual releases of annual GSP, the BEA noted that the availability of higher-frequency information on state output should help researchers to better understand national and regional business cycles.

In this blog entry, we take another look at the GSP data for the five states of the Seventh Federal Reserve District to see how they compare with the Midwest Economy Index (MEI) produced by the Chicago Fed.1 We find that the MEI is highly correlated with the new quarterly GSP data; moreover, the MEI remains timelier as an indicator of the Midwest business cycle because it is released on a monthly basis.

In 2011, the Chicago Fed began providing four times a year estimates of annual gross state product growth for each of the five states in the Seventh Federal Reserve District2 as an accompaniment to its MEI release.3 Using the forecasting model underlying these estimates and the BEA’s new quarterly GSP data, we extend our annual projections to include quarterly GSP growth. Below, we present what we’ve forecasted for each District state through the first half of 2014.

The MEI and GSP growth

The MEI is a weighted average of 129 state and regional indicators that measure growth in nonfarm business activity. Two separate index values are constructed, the MEI (providing an absolute value), which captures both national and regional factors driving Midwest economic growth, and the relative MEI (providing a relative value), which presents a picture of the Midwest’s economic conditions relative to the nation’s.

Both indexes are business cycle indicators capturing deviations in growth around a historical trend. MEI values above zero indicate growth above a Midwest historical trend, and values below zero indicate growth below trend. For the relative MEI, a positive value indicates that Midwest growth is further above its trend than would typically be suggested based on the current deviation of national growth from its trend, while a negative value indicates the opposite.

Together, the MEI and relative MEI provide a picture of the Seventh District’s state economies that is closer to being in real time than does the BEA’s GSP data. To see this, consider figure 1, which plots the MEI and the year-over-year gross domestic product (GDP) growth for all five District states combined using the BEA’s annual and quarterly data. The correlation here is quite striking, with the major difference being that the MEI is often released six months to a year (or more) in advance of the quarterly or annual GSP data.4


Forecasting annual and quarterly GSP growth

By exploiting the historical correlation between annual GSP growth in each of the five District states and the MEI, we have been producing quarterly estimates of annual GSP growth since 2011. The statistical model we use to explain the annual growth in GSP for each Seventh District state is shown below.

The model succinctly summarizes the historical relationships between national (real GDP growth), regional (MEI and relative MEI), and state-specific (lagged GSP and state real personal income growth) factors driving each Seventh District state’s annual GSP growth since 1979.

We use a similar model applied to quarterly data to assess how well we can predict growth in the BEA’s new quarterly estimates of GSP. Before we do so, we review the annual GSP growth model. The regression coefficients estimated for our annual model using data through 2013 are listed in table 1. Each coefficient represents the “effect” of an input on GSP growth. For example, a 1% increase in real U.S. GDP growth leads to about a 0.5% increase in GSP growth on average across the     Seventh District states (first row of the table).


The historical fit of our annual model varies across the five District states, as seen in their root mean-squared errors (RSME) (next to last row of the table). To put these deviations in perspective, we generated figure 2, which plots the actual annual GSP growth for each state, as well as GDP growth for the United States (blue bars), against the fitted values from the regression (red lines). The model does quite well at predicting Illinois’s and Wisconsin’s GSP growth rates, which tend to be less volatile and more closely resemble U.S. GDP growth. Its worst fit is for Iowa’s GSP growth rate, largely because it does a poor job of capturing fluctuations in agricultural conditions.


We now extend our analysis using the BEA’s quarterly GSP data. To predict GSP growth for the first and second quarters of 2014, we estimate a “bridge equation” for each District state linking current and previous values of the monthly MEI and relative MEI to its quarterly annualized GSP growth, where the number of monthly lags spans both the current and previous quarters.5 We also include the current and previous quarters’ state real personal income growth and the previous quarter’s annualized GSP growth. We estimate the model on data from 2005 through 2013 and then project forward two quarters.

Figure 3 displays the quarterly regressions’ fitted values (red lines) against actual quarterly annualized GSP growth (blue bars). As our model did with the annual GSP data, it fits quite well for the majority of District states’ GSP growth rates. The green lines in the figure denote the forecasts for the first and second quarters of 2014. We project declines in GSP growth for District states in the first quarter that are largely offset by second quarter growth—consistent with U.S. data. The green lines in figure 2 depict similar annual forecasts for the entirety of 2014.


Our 2014 forecasts

Table 2 shows our complete projections for District states’ 2014 GSP growth rates. Our annual growth projections suggest that Illinois’s growth rate will be closer to the District average in 2014, at around 2%. We project Michigan and Wisconsin to grow at above-average annual rates, while we project below-average growth for Indiana and Iowa. However, our quarterly model projections through the first half of 2014 suggest some downside risk to our annual Michigan and Wisconsin forecasts and upside risk for our annual Indiana and Iowa forecasts.


As we’ve seen from tables 1 and 2, each state’s forecast is affected differently by the five inputs to our model. To further illustrate this point, we break down each state’s projected GSP growth rates into the expected contributions from national, regional, and state factors in table 3. National factors represent the effect of national GDP growth on our state GSP growth forecasts. Regional factors capture the roles played by the MEI and relative MEI, while state factors incorporate the effects of state real personal income growth, as well as the idiosyncratic dynamics of each state’s GSP growth.


State and national factors have played a dominant role so far in 2014, but not every District state is projected to share equally in the national second quarter rebound from the slow start to the year. Regional factors have increased in importance over the course of the year; and with both the MEI and relative MEI showing above-trend growth so far in the third quarter, they are likely to continue to do so in the second half of 2014.

As we work to merge our annual and quarterly forecasting models, we will be reporting both annual and quarterly annualized estimates of District states’ GSP growth in conjunction with the MEI. These projections following the third release of national GDP data are available at



  1. This blog entry serves as an update to a previous Chicago Fed Letter examining GSP growth and the MEI, available at
  2. The Seventh District comprises all of Iowa and most of Illinois, Indiana, Michigan, and Wisconsin. The MEI and our GSP forecasts are for the entirety of each state that lies within the District.
  3. Our estimates of annual GSP growth are made available following the third release of national gross domestic product (GDP) data for each quarter at
  4. The 2014 release schedule for the MEI and the quarterly GSP growth forecasts can be found at
  5. A similar model linking quarterly annualized U.S. GDP growth and the Chicago Fed National Activity Index is described in an article available at

Mid-year Export Trends

By Bill Testa

Recently released data on U.S. foreign trade for July from the U.S. Census Bureau and U.S. Bureau of Economic Analysis (BEA) show an improvement in exports of U.S. goods. On a month-over-month basis, exports increased $1.8 billion, to $138.6 billion. This rise in exports—which helps to narrow the trade deficit—points to a stronger pace of U.S. gross domestic product (GDP) growth for the third quarter of 2014 relative to earlier this year.

July’s improvement in trade performance also bodes well for the economy of the Seventh Federal Reserve District. As seen below, exported manufactured goods make up a greater percentage of District production than of national production. Moreover, each District state’s ratio of manufactured export value to annual state output meets or surpasses the nation’s ratio of manufactured export value to GDP (7.1%). Notably, by this measure, Indiana and Michigan significantly exceed the nation as a whole, owing to their strong industry concentrations in transportation equipment (cars and trucks).

Looking more closely at July’s performance, one can see that the composition of July’s U.S. export growth favored District industries. As the Census/BEA trade report states: “The June to July increase in exports of goods reflected increases in automotive vehicles, parts, and engines ($1.7 billion); industrial supplies and materials ($1.3 billion); and capital goods ($0.4 billion).” In addition to the District economy’s high concentration in the export of transportation equipment, several District states also export significant amounts of capital goods: machinery and equipment such as agriculture, construction, and mining equipment, as well as computers and electronic equipment (see below). Moreover, several District states export chemicals, including both industrial chemicals and pharmaceuticals.

According to measures of export growth in first half of the year as compared to a year ago, not all industry categories have been holding up in 2014 (see below). Of particular note, machinery exports from Illinois, Michigan, and Wisconsin have been lagging compared to last year’s first half. And while automotive sales and production have been generally growing, transportation equipment exports from Michigan, Wisconsin, and Illinois recorded declines in first six months of 2014 over last year.

And so, if continued export growth can be sustained for the rest of this year and beyond, it will be welcome news for the District economy. Following a surge in growth during 2010–11 (see below), District (and U.S.) manufactured exports slumped in tandem with slowing growth in eurozone countries, which are important buyers of District manufactured goods. District manufactured export growth has also faltered on account of slower economic growth in China and in other lesser developed countries. Since global economic growth slowed down, global demands for commodities such as minerals and energy have eased, depressing Midwest exports of mining and construction equipment.

Rising District manufactured exports in 2014 would be consistent with modestly stronger global economic growth as compared with 2013.[1] As of its July forecast, the International Monetary Fund (IMF) expects global growth to be 3.4% this year, up from 3.2% in 2013 (see below). World economic growth is expected to further accelerate to 4.0% in 2015, according to the IMF. As our trading partners continue to experience faster economic growth, we can expect that their purchases of the District’s manufactured goods, such as machinery, transportation equipment, and industrial supplies, will begin to bolster the region’s manufacturing production.

Note: Thanks to Rebecca Friedman and Paul Traub for assistance.
[1] Year to date through June, the five District state total of manufactured exports has risen 1.4% from $91.2 billion to $92.6 billion, according to Chicago Fed Staff calculations using data from the US Census Bureau, the Bureau of Economic Analysis, and Haver Anlalytics. (Return to text)

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