Category Archives: Midwest

The Midwest Feels the Sting of an Extended Agricultural Downturn

On November 29, 2016, the Federal Reserve Bank of Chicago will hold a conference to examine the agricultural downturn in the Midwest and discuss future directions for farming, concluding with a panel discussion on the evolution of agricultural lending. (Check for more details on the conference, including the agenda, and to register.) Experts from academia, industry, and policy institutions will explore the implications of the downturn for both the farm sector and the broader regional economy. The goals of the conference include understanding key trends in farm income, product prices, and input costs; assessing the primary factors behind the sector’s downturn; examining policies that provide support to farm operations and promote risk management; and discussing the role of agricultural lending under these challenging circumstances, as well as in the next phase for agriculture.

Bountiful harvests since 2012’s drought have replenished crop stockpiles to such an extent that supply has outstripped demand, leading to significant reductions in crop prices for midwestern farmers (see charts 1 and 2). Moreover, livestock product prices have tumbled in recent years (see chart 3). Depressed revenues for crop and livestock operations have translated into lower profits as costs of production have been slower to adjust, particularly for crop farms. This downturn in farm profitability followed on the heels of historically high levels of real net farm income[1] (see chart 4). In addition, diminishing income for farm households and operations negatively affected businesses on the Main Streets of towns across the Seventh Federal Reserve District (all of Iowa and most of Illinois, Indiana, Michigan, and Wisconsin).

This latter point was reinforced through a special question included in the Chicago Fed’s latest Agricultural Land Value and Credit Conditions Survey, to which banks responded during October (results were recently released in AgLetter). Bankers were asked: “Is a weakening agricultural economy leading to weaker Main Street business activity in your area?” In all five states of the District the consensus answer was “Yes,” with varying degrees of certainty—30% said definitely and 43% probably, while only 12% did not agree with this take on current business activity in their areas (15% were not certain of any impacts). Based on these observations, the downturn in farm country appears to have slowed the economy of the rural Midwest on Main Street as well.

As for farm households and farm operations themselves, the U.S. Department of Agriculture (USDA) forecasted real net farm income for 2016 to be $64.3 billion, a decrease of 12% from 2015 and the lowest result since 2009 (the most recent reading that was below the median of $66.9 billion from 1950 to 2016).[2] In 2009 dollars, net farm income for the U.S. averaged $95.2 billion over the previous five years, dipping down from the prior five-year period ($95.7 billion, a level that was the highest since the period from 1949 to 1953). With farm incomes even higher than during the 1970s farm boom, the just-concluded era of high farm incomes looks likely to have set the bar quite high for the current generation of farmers.

Furthermore, looking at the District, farm incomes were even bleaker. Real net farm income for each state is available through 2015. Using these USDA data, we estimate that the net farm income for the five states of the Seventh Federal Reserve District was $9.1 billion in 2015, a decrease of 31% from 2014 and the lowest outcome since 2003. The District’s value was also below that of the median year from 1950 to 2015 of $12.8 billion. District states accounted for only 12.4% of U.S. net farm income in 2015, after hitting 22% as recently as 2013.

The spillover impacts of farm income declines on Main Street activity in the region can be attributed to the relatively large role played by farmland rentals in the District—39% of net rent received by non-operator landlords nationwide. Such rental transactions provided $5.5 billion for non-operator landlords in 2015, down 27% from a peak of $7.5 billion in 2013 (adjusted for inflation). These payments lift the direct economic impact of agriculture on the District, although some landlords reside elsewhere. Also, $3.1 billion in 2015 was paid out to hired labor by farms in the District (down 8.8% from $3.4 billion in 2014). Additionally, District agricultural operations spent $23.5 billion in real terms on purchased inputs that did not originate on farms in 2015 (declining 10% from 2013’s peak of $26.1 billion), implying that farms reduced their purchases from cooperatives, equipment dealers, and other businesses. These negative effects on income and business activity reinforce a pullback in spending by farm households. Hence, the economic fortunes of agriculture radiate out into communities and the businesses of the District, which are sharing the pain of the current downturn.

At our conference on November 29, the first session will dig deeper into the impacts of the agricultural downturn, especially on farm operations and rural economies. The second session will explore trends in agricultural financing, with a particular focus on bankruptcy research. Following the keynote address by Bill Northey, the Secretary of Agriculture and Land Stewardship for Iowa, there will be a session devoted to the role of farm policy during the downturn and potential directions for future legislation. Finally, a panel discussion will look into the evolution of agricultural financing as distress in the sector builds, as well as innovations in response to the changing farm environment. These sessions should enhance our understanding of the agricultural downturn and provide clues about potential changes that will affect the sector’s future. Visit for more information and to register.

Chart 1.


 Chart 2.


 Chart 3.


Chart 4.


[1] 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. See for details.

[2] See for data.

Updated Forecasts of Seventh District GSP Growth

Several years ago, the Chicago Fed began providing estimates of annual gross state product (GSP) growth for each of the five states in the Seventh Federal Reserve District.1 The U.S. Bureau of Economic Analysis (BEA) releases annual GSP data for the prior year each June. This post discusses GSP projections for 2015 and presents an alternative forecasting model using quarterly GSP data from the BEA.2

The 2015 Growth Picture

To provide context for our projections, we first take a brief look at the main indicators of our model. Figure 1 shows annual U.S. gross domestic product (GDP) growth and GSP growth aggregated across the five states in the Seventh District from 2005 through 2014. Actual GSP data for 2015 will not be released for another month. However, we can get a sense of what this data is likely to show by comparing the recent histories in the figure. While growth in the Seventh District has lagged behind the nation in recent years, it has tended to follow a similar trend over longer periods. The U.S. maintained an annual growth rate of around 2.4% from 2014 to 2015, providing a reasonable starting point for our estimate of District growth in 2015.


The Chicago Fed’s Midwest Economy Index (MEI) then provides a useful link between national and regional growth that can give us a sense of the likely persistence of the recent shortfall between District and national growth. As figure 2 shows, the MEI indicated that the Midwest economy experienced growth that was somewhat above trend in the first half of 2015 and slightly below trend in the second half. Additionally, the relative MEI dipped below zero in the third quarter, suggesting that Midwest economic growth was further below its trend than national growth was in the second half of the year. Though the MEI does not explicitly pertain to GSP growth, historically a zero value for the index has been roughly consistent with 1.5% annual GSP growth for the District. In light of this, both the MEI and relative MEI suggest that District GSP growth in 2015 likely rebounded from its 2014 rate of 1.1% to somewhat above its trend rate of 1.5%, but still below the national growth rate of 2.4%.


Finally, we turn to annualized quarterly growth of state real personal income over 2015which provides an indication of how state-specific factors may have affected District GSP growth in 2015. Figure 3 shows that both Illinois and Michigan experienced strong income growth in the first quarter of 2015. Though the District states generally experienced weak income growth in the second quarter in comparison with the national average, growth rates in the remaining quarters of 2015 were of similar magnitudes to the national rate. Taken together, these data suggest some likely variation in GSP growth rates across the District states, but for the most part, they are consistent with the MEI and U.S. GDP growth data in figures 1 and 2.


Forecasts for 2015

Our forecasts for 2015 combine the information in the indicators discussed in the previous section to arrive at an estimate of annual GSP growth for the District states and the District as a whole. Since 2011, the Chicago Fed has used the following statistical model to estimate annual GSP growth:


This model explains the annual GSP growth rate of each Seventh District state as a function of national GDP growth, regional economic conditions as captured by the monthly MEI and relative MEI, and state-specific conditions (specifically, quarterly real personal income growth and annual GSP growth in the previous year).3 We aggregate state projections into a District-wide forecast using each state’s respective share of nominal District GSP.

Figure 4 shows for each District state and the entire District their respective historical GSP growth (blue bars), in-sample fits (orange lines) of GSP growth obtained from our statistical model, and 2015 out-of-sample projections (green lines). With the exception of Iowa, the model predicts an increase in the GSP growth rate for the Seventh District states, as well as the District as a whole. Interestingly, this seems out of line with the national GDP data and the MEI and relative MEI data discussed earlier. It is of note, however, that for 2014 the model also estimated higher GSP growth than what was realized for each state.


Motivated by our model’s recent shortcomings, we developed a similar model estimated using the experimental quarterly GSP data recently published by the BEA. Figure 4 also contains projections of annual GSP growth (red bars) obtained from this new model. At the time of writing, these data were available through the third quarter of 2015. To obtain a GSP growth projection for all of 2015 with these data, we need only estimate the fourth quarter’s value. Using the new statistical model to obtain this estimate and combining it with the data from the first three quarters, we arrive at an alternative forecast for 2015.

Figure 4 clearly shows a large difference between our two forecasting models. As table 1 further demonstrates, the projections from our new quarterly model (Q4 forecasted column) are below those of our original annual model in every instance, and often by quite large magnitudes. For the District as a whole, our quarterly model predicts more modest GSP growth of 1.6%, compared with 2.5% as forecasted by the annual model. This estimate from our quarterly model is also in line with the previous evidence suggesting growth was slightly above the historical trend of 1.5% but below the national growth rate of 2.4% for 2015.

Table 1. Annual GSP Growth Forecasts for 20154


To illustrate the sources of the discrepancy between our model forecasts, we plot in figure 5 the annualized quarterly GSP growth data from the BEA (blue bars) for 2015, including our fourth quarter estimates (red bars) and fitted values from the model (orange lines). It is important to note that both our annual and quarterly models use the same 2015 data for the variables that they share in common, with the exception of the three quarters of GSP data that we have for 2015. These data show sharp contractions in GSP for every District state (with the exception of Illinois) in the first quarter. More than anything else, this feature of the quarterly data is the dominant source of the discrepancies between our annual and quarterly model projections. The model fits in figure 5 make this clear, as they demonstrate very large negative residuals in the first quarter and only small misses in the other quarters, reflecting the fact that the declines in GSP in the first quarter are not consistent with the indicators in our statistical model.


It is possible that the quarterly GSP data for 2015 will be revised upon the release of the annual figure next month. As noted previously, our model predicts weak first quarters for the District states, but not nearly as dramatically as what has been released by the BEA thus far. Considering the apparent inconsistency between the quarterly data and the model, we also generate a forecast for 2015 that uses the fitted values for the first three quarters of 2015 GSP growth instead of the quarterly data. These projections, presented in the Q1–Q4 forecasted column of table 1, are larger than the quarterly model’s estimates using the quarterly values for 2015, but are still below those of the annual model. Moreover, these projections suggest that at 2.0%, District GSP growth improved in 2015 and was closer to the national average, but still below it.


We will continue to monitor the performance of both our annual and quarterly forecasting models. However, based on the results presented here, we intend to report annual GSP growth rates for each District state from our new quarterly model combined with the available quarterly data for the 2015 forecast (as presented in the Q4 forecasted column in table 1). From now on, we will continue to report estimates from this model as long as the quarterly data from the BEA make it possible to do so.

  1. The Seventh District comprises parts of Illinois, Indiana, Michigan and Wisconsin, as well as all of Iowa.
  2. The quarterly GSP data provided by the BEA is still in an experimental phase. For more information, visit
  3. The model is explained in more detail in Brave and Wang (2012).
  4. To allow for “like-for-like” comparisons among District forecasts, we aggregate state-specific annual forecasts to the District level using annual nominal GSP shares. The 2015 projections were aggregated using the 2014 shares.

“Early Benchmarking” the State Payroll Employment Survey

One of the most important sources of information we have on current economic conditions is the Bureau of Labor Statistics’ (BLS) Current Employment Statistics (CES) program (also known as the payroll survey). The payroll survey reports monthly estimates of nonfarm payroll employment, hours, and earnings at the national, state, and metro area levels. Because the CES covers only a representative sample of employers, the BLS is able to release the results of the survey in a timely manner (typically three weeks after the reference month at the U.S. level, eight weeks after at the state level, and ten weeks after at the metro area level). At the same time, relying on a survey—instead of a census—means the results are subject to sampling error. The BLS does revise the CES estimates to address sampling error. With each new monthly release, it adjusts the two previous months’ estimates; and once a year in March, it revises the two previous calendar years at the U.S. level and the five previous calendar years at the state and metro area levels.1 In this blog post, I discuss a method pioneered by researchers at the Dallas Fed to predict the once-a-year revisions at the state level as many as nine months in advance. These predictions can provide valuable information, because state-level revisions can be substantial.

For their state CES estimates, the BLS relies primarily (but not entirely) on a sample of about one-third of the universe of employers that participate in states’ unemployment insurance (UI) programs. The information on employment and earnings from all employers participating in UI is eventually reported under the BLS’s Quarterly Survey of Employment and Wages (QCEW) program, with a delay of six months from the reference period. As noted above, in March of each year, the BLS revises state-level CES data for the prior five calendar years, using the previously unavailable QCEW data as a benchmark.2 It is important to note here that QCEW is only a benchmark (not the final answer), because the CES and the QCEW do not cover the same universe of workers. The CES does not count farm workers, but it does count the 3 percent of nonfarm workers who do not receive unemployment insurance. The QCEW only counts workers with unemployment insurance, which includes some farm workers. Because their universes are not exactly the same, the CES and QCEW have different levels. However, they overlap enough that their trends are about the same.

While the BLS rebenchmarks the payroll survey data once a year, the QCEW data are released four times a year (three months at a time). And because the payroll survey uses the QCEW as its benchmark, it is possible to use newly released QCEW data to predict how the BLS will eventually revise the CES data. For example, table 1 shows when the new QCEW data used for the March 2015 rebenchmark became available. Data for the fourth quarter of 2013 were available nine months before they were used to benchmark the CES. And by December 2014, it was possible to have a good idea of how the CES would be revised through the second quarter of 2014, even though the BLS had only revised the CES through the third quarter of 2013.

In what follows, I explain a method for “early benchmarking” the state payroll survey data pioneered by researchers at the Dallas Fed (explained by them here). I then look at how the method performed at predicting the March 2015 revisions for the five states in our Seventh Federal Reserve District.


The method begins with the last month of CES data that are benchmarked to the QCEW. From then on, monthly changes are calculated using growth rates from the (seasonally adjusted) QCEW, not the CES. Once the QCEW data run out, monthly changes are again calculated using the CES. In essence, the method amounts to substituting in growth rates from the QCEW data that are newly available but have not yet been used to benchmark the CES.

Figure 1 shows the early benchmarking method visually for the Seventh District states using the data available in December 2014.3 The blue line is the CES, where the dashed portion of the line represents months that have not been benchmarked by the QCEW. The green line is the QCEW; and it is clear that while the CES and the QCEW have different levels, their trends are quite similar. The red line is the early benchmarked version of the CES. The solid portion of the red line is the path generated by monthly growth rates from the QCEW, and the dashed portion of the red line is the path generated by monthly growth rates in the remaining CES data.



How did the early benchmarking procedure do at predicting the March 2015 CES rebenchmark? Figure 2 shows the revised payroll survey data from March 2015 in black. The QCEW-benchmarked data now go through the third quarter of 2014. Overall, the early benchmarked CES series appears to predict the most recent rebenchmarking of the CES better than the March 2014 rebenchmarked CES series does. This is especially true before the QCEW data run out in June 2014.


One way to measure the accuracy of a forecast is to calculate its root mean squared error. Table 2 shows the root mean squared error for predictions of the March 2015 rebenchmarked CES using the March 2014 rebenchmarked CES and the early benchmarked CES. The early benchmarked CES performs as well or better at both the District and state levels. At the District level, the early benchmarked CES is typically about 31,000 jobs off, while the March 2014 rebenchmarked CES prediction is typically about 51,000 jobs off. In the case of Michigan, the early benchmarked CES performed substantially better. Figures 3 through 7 show the state-level comparison. Taken as a whole, these results demonstrate that early benchmarking the CES provided a tangible improvement in measuring growth in the Seventh District over the last year or so.







  1. For example, in March 2015, the BLS revised data for 2013–14 at the U.S. level and 2009–14 at the state and metro-area levels.
  2. While the new QCEW data only cover the previous year, the revisions go back five years because the BLS also recalculates its seasonal adjustment factors.
  3. I calculate the early benchmark series for the Seventh District by summing the early benchmark series for the District states.

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.

Seventh District Update

by Norman Wang and Scott Brave


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: Economic activity in the Seventh District continued to expand at a slow pace in January and February.

Consumer spending: Consumer spending increased at a slower rate. Retailers pointed to the negative impacts on household budgets from rising gas prices and the end of the payroll tax holiday as explanations for the slower pace of retail sales. Auto sales were steady for much of the reporting period before increasing slightly over the last few weeks.

Business Spending: Growth in business spending slowed. Inventory investment declined, and spending on equipment and structures was again limited. Labor market conditions were little changed.

Construction and Real Estate: Construction and real estate activity was mixed. Demand for residential construction continued to increase slowly, buoyed by ongoing strength in multifamily construction. Although there was some modest growth in nonresidential construction, the level of activity remains weak.

Manufacturing: Growth in manufacturing production picked up over the reporting period. The auto industry remained a source of strength, with light vehicle sales expected to increase throughout the year. Demand for heavy equipment weakened, with lower coal prices contributing to less mining activity.

Banking and finance: Credit conditions continued to ease. Credit spreads and financial market volatility remained low and asset quality continued to improve. Banking contacts reported moderate growth in business and consumer loan demand, with pricing relatively unchanged but some loosening of loan standards.

Prices and Costs: Cost pressures were moderately higher. Contacts noted some upward pressure on raw materials prices, particularly for lumber, drywall, steel, aluminum, and copper. Wage pressures remained moderate.

Agriculture: Snow and rain continued to boost topsoil moisture levels, although depleted subsurface moisture remained a concern for farmers. Corn, wheat, milk, hog, and cattle prices dipped during the reporting period, while soybean prices moved a little higher.

The Midwest Economy Index (MEI) increased to –0.18 in December from –0.30 in November, but remained negative for the sixth consecutive month. The relative MEI decreased to –0.01 in December from +0.55 in November, primarily because of significantly lower contributions from the Midwest’s manufacturing and service sectors.

The Chicago Fed Midwest Manufacturing Index (CFMMI) increased 0.7% in December, to a seasonally adjusted level of 94.7 (2007 = 100). Revised data show the index was up 2.0% in November. The Federal Reserve Board’s industrial production index for manufacturing (IPMFG) moved up 0.8% in December. Regional output rose 6.2% in December from a year earlier, and national output increased 2.7%.

Manufacturing: Been down so long, it looks like up?

Those having keen interests in the U.S. manufacturing sector are somewhat encouraged by its performance over the past three years. The sector has bounced back sharply since the end of the severe 2008–09 recession. Job growth in manufacturing is running up 2 percent on a year-over-year basis, and the sector has recovered three-quarters of the output lost during the 2008-09 recession. Encouragement about manufacturing prospects derives not only from the recent bounce, but also from the possibility that the change in direction may represent a turnaround in manufacturing’s fortunes that will be sustained over the longer term. The previous peak in manufacturing jobs took place as far back as the 1990s, so this new direction, particularly if it holds up over a long horizon, would be a welcome change.

To put recent events into proper perspective, it is useful to examine the manufacturing sector’s long-term experience in the United States. Since the mid-twentieth century until the 2000s, the level of jobs in the manufacturing sector has stayed fairly constant, even while real output and productivity have risen briskly. The chart below shows the sector’s climbing real output, with the nation experiencing a five-fold growth in real manufacturing output since the early 1950s through today. Output growth here reflects both the increase in the quantity of goods produced and the improvements in the goods’ quality, such as durability and performance. Over most of this period in the United States, real output growth in manufacturing matched or exceeded the real growth in overall goods and services production[1]. In contrast with this hearty performance of real output growth in manufacturing, the sector’s levels of employment have remained steady over the latter half of the twentieth century—in the range of 17–19 million workers—and then moved much lower until very recently.

Source: Bureau of Labor Statistics/Haver Analytics

Effectively, these gains in output with generally steady employment levels mean that productivity growth in the manufacturing sector has been quite robust. The application of more “know-how” and capital equipment has boosted manufacturing output, but with little need for more accompanying labor. Such productivity improvements, along with cheaper imports, have contributed to falling real prices for many manufactured goods sold in the United States. On the flip side of the same coin, falling prices of manufactured goods have boosted standards of living for U.S. households during the post-World War II era. The ability of American workers to produce more with greater efficiency—as well as to buy more—has translated into real wage gains.

But while such gains have benefited broad swaths of the U.S. population, it is also true that many manufacturing-oriented towns and cities have experienced decline and that manufacturing workers and firms have suffered dislocation. Such changes have led analysts to probe more deeply into the sources of both manufacturing progress and upheaval. Why haven’t rising standards of living done more to sustain manufacturing jobs?

For the most part, there are fundamental aspects to the ways we live that have prevented a large enough rise in our purchases of manufactured goods to outweigh falling labor content (and jobs) in the domestic manufacturing sector. For one, the rising incomes of U.S. households have not lifted the demand for manufactured goods sufficiently. Even with the introduction of new manufactured goods, such as televisions, medical equipment, home computers, and microwave ovens, households have tended to shift consumption toward services, such as medical care, education, and personal services. So too falling real prices for manufactured goods have not sufficiently induced consumer demand for standard manufactured goods, such as home furnishings and automobiles.

To be sure, exports of goods abroad have helped to lift employment in the manufacturing sector. The United States remains a global leader in innovation, as well as research and development (R&D), in many capital goods sectors, especially machinery and equipment. Rapid growth and development of nations throughout the world have raised the demand for U.S.-made capital equipment and certain high-tech products, such as farm equipment, pharmaceutical products, medical equipment, aerospace equipment, and earth-moving machinery. Manufactured goods continue to represent the largest share of U.S. exports abroad, and exports as a share of U.S. gross domestic product (GDP) have risen from 5.8 percent in 2001 to 9.3 percent in 2011.

However, at the same time, imports of manufactured products have also been rising. In fact imports of manufactured products have risen more rapidly than our exports of manufactured products abroad. Some imports become components of U.S.-produced goods that are exported abroad. But for the most part, rising imports displace manufactured goods that might otherwise be produced domestically.

Source: WISER/Census Bureau/Haver Analytics

Source: WISER/Census Bureau/Haver Analytics

Given these mixed trends, some analysts have argued that the long-standing trend of nearly flat manufacturing job levels and rising production levels was interrupted by a decline in the number of manufacturing jobs beginning in the late 1990s, possibly accompanied by a slower pace of real output growth. From that time until recently, the United States experienced a rising trade deficit in manufactured goods. This was not the first time that the U.S. economy had experienced rising competition with other countries for sales both abroad and within its home markets. In particular, the rise of industrialization in Japan and other “Asian Rim” countries had a significant impact in the 1970s and 1980s on U.S. markets for major product segments in home electronics, steel, and automotive. Such developments were facilitated by globalization factors, including tariff reduction agreements and falling costs for transportation and communications.

The era from the late 1990s through the recent recession and recovery may represent a different order of magnitude in this regard. According to economist Robert Fry of Dupont, the large size of China and its low costs of production—coupled with the production capabilities of other “Asian tiger” nations—brought forward sharp competition for U.S. producers both in markets abroad and within the U.S. marketplace. One recent study conducted by David Autor, David Dorn, and Gordon Hanson lends weight to rising import competition as a significant cause for domestic manufacturing job loss over the past two decades. It does so by examining the varied experiences of many U.S. subregions and their relative exposure to rising imports from low-wage countries. In their most conservative estimates, the authors attribute one-quarter of the decline in U.S. manufacturing employment over the period 1990–2007 to changes in Chinese imports.

Since 1998, U.S. manufacturing employment fell precipitously from the levels that had prevailed through the 1960s, 1970s, 1980s, and the early part of the 1990s. Manufacturing employment fell from its peak in 1998 by over 3 million jobs by 2007 (by one fifth) and then by another 2 million jobs by 2010.

Regional trends in manufacturing also shifted during this time. Whereas job losses had been previously concentrated in the traditional industrial belt extending from western Pennsylvania and New York through the Great Lakes states, manufacturing job losses showed no favorites this time around. As seen below, states of the Southeast had been gaining manufacturing jobs versus the Great Lakes states from the late 1960s through the late 1990s. In contrast, jobs in both regions have fallen in tandem since that time.

Source: Bureau of Economic Analysis/Haver Analytics

As mentioned before, a recent rebound in manufacturing activity and jobs has followed on the heels of the severe 2008–09 recession. To some observers, the recent bounce is a harbinger of a change in direction for the manufacturing sector in terms of employment. Since last year’s tsunami and aftermath in Japan, some multinational corporations are rethinking their supply chains overseas in favor of North American production sites. Similarly, falling energy prices for domestic natural gas are enticing some chemical/plastics production operations back to U.S. shores. And as fundamental operational costs are rising in China and the rest of Asia, it may be the case that, at the very least, the strong wave of production relocation toward developing countries is beginning to slow. However, given the sustained decline that the U.S. manufacturing sector has experienced since the 1990s and during the recent recession, along with many cross currents underway general business activity and structure, analysts will not know for at least several years into the future whether manufacturing activity has truly bottomed out.

Meanwhile, in the near term, overall economic growth has entered a soft patch around the world over the past several months. And as usual, when overall growth slows, the trend tends to be magnified for manufacturing activity. And so, the informational signals on whether U.S. manufacturing has turned around in a major way have become more difficult to read.


[1]Some analysts have challenged the veracity of recent output gains from the manufacturing sector. Output gains may be overstated as final goods are produced here with an increasing amount of foreign content, especially purchased inputs and intermediate parts and components. Susan Houseman notes that such inputs are undercounted (so that final U.S. output as recorded is then overcounted). In a 2009 paper, Houseman and co-authors found that “from 1997 to 2007 average annual multifactor productivity growth in manufacturing was overstated by 0.1 to 0.2 percentage points, and real value added growth by 0.2 to 0.5 percentage points.”(Return to text)

Midwest Outlook Workshop

By Thom Walstrum and Norman Wang

On December 1, 2011, a group of experts convened to discuss developments in the Midwest economy in 2011 and to look forward to 2012 and beyond. The forum drew upon a variety of perspectives, hosting researchers from across the Midwest and from government, academic, and private institutions. As the conversation progressed, themes began to emerge.

Data from 2011 give a picture of an economy that is recovering, but lacking the vigor needed to return quickly to full employment. The outlook for the Midwest economy for 2012 is more of the same: slow improvement.

Looking beyond the current business cycle, the Midwest will be challenged by the economic fundamentals of a manufacturing-based economy. So far, economic development policy remains disappointing in addressing the challenges of diversification and competitiveness.

Sophia Koropeckyj from Moody’s Analytics noted that growth in the first half of 2011 was accelerating, but that it had slowed in the second half. The tepid pace of recovery means that the rate of job growth remains below the rate of population growth. It may take until 2017 to return to full employment. Koropeckyj highlighted manufacturing employment because it is concentrated in the Midwest relative to the rest of the U.S. She saw growth in manufacturing jobs in 2011, but noted that total manufacturing employment is still far below its pre-recession peak. Exports from the Midwest overseas continue to grow, but with possible challenges from a weak European economy in 2012. However, growth in Asia and South America could provide a backstop.

Ernie Goss from Creighton University provided a perspective on the rural economy that focused on the Plains states. They are doing better than many other parts of the country, driven by a good year for farms and farm-related businesses. Revenues were high in 2011, creating a push for consolidation that is driving up farmland prices (possibly to “bubble” levels). Federal Reserve economist David Oppedahl noted that farmland prices in other Midwestern states to the east are a bit stronger than in the Plains states. Price growth for the most productive land has outpaced prices for less productive land because of reduced recreational demand. While the farming industry did well in 2011, sectors that do not participate directly in the international marketplace (for example, construction) are subject to the same malaise afflicting other parts of the country.

Beth Weigensberg from the University of Chicago’s Chapin Hall discussed the CWICstats Dashboard Report, a quarterly assessment of the economies of Chicago and Illinois. She saw unemployment rise for Chicago and Illinois in the first half of 2011 even as labor force participation fell. Total employment is still 5% below its December 2007 level. Like other Midwest employment sectors, manufacturing employment is slowly rising from a trough in late 2009; it is still 15% below its December 2007 level.

George Erickcek from the Upjohn Institute provided an outlook on Michigan’s economy. Michigan lost 410,000 jobs from December 2007 to the trough in June 2009. It has recovered 85,200 jobs since then. Erickcek estimates that 37,100 (39%) of the new jobs were created by the auto industry. He noted that there has been no structural change for Michigan’s economy over the course of the recent recession and recovery. The auto industry is as important as ever. Even as many call for diversification, the Great Recession does not seem to have pushed Michigan’s economy in that direction.

In the near term, Michigan’s continued reliance on the auto sector will continue to lift the state and other auto-intensive communities in the Midwest. However, the longer term prospects are not so sanguine. As manufacturing growth begins to level off, longer term trends suggest little new employment will be generated by the sector. Some observers are a little more optimistic about the longer term. Federal Reserve economist Bill Strauss argued that rising overseas costs may result in the return of some manufacturing jobs to the U.S.

However, Geoff Hewings from the University of Illinois presented a less optimistic outlook on the region’s longer term future, predicting that the Midwest would continue to underperform the rest of the U.S. in several areas. According to Hewings, the Midwest’s GDP is forecasted to grow by 1.7% annually, compared with the 2.4% annual growth rate forecasted for the U.S. from 2007 to 2040. Over the same period, employment is forecasted to grow annually by 0.5% for the Midwest and 0.7% for the U.S., and personal income is forecasted to grow annually by 1.7% for the Midwest and 2.8% for the U.S.

Additionally, Hewings highlighted several trends that have shaped the Midwest in recent years. States are becoming increasingly interconnected as they fragment and hollow out; typical establishments have lengthened their supply chains by sourcing from more plants for increasingly specialized components (fragmenting) and are now less dependent on sources of inputs and markets within the state (hollowing out). Hewings noted the outsized volume of intra-Midwest trade as evidence; Midwest export trade to other Midwest states in 2007 amounted to $450 billion. Such strong intra-region trade linkages generate benefits for the Midwest economy during good times, but they amplify job losses during downturns. During the latest recession, 1.78 million jobs were lost in just five Midwest states, representing 20% of the total jobs lost in the U.S.

The close intra-region trade linkages in the Midwest sparked discussion about the need for more thoughtful and concerted policy actions within the region. Midwest states continue to play “beggar-thy-neighbor,” by offering selective tax abatements to lure businesses. Given the cohesion of the regional economy, such policies may be counter-productive. In particular, investment in overland transportation infrastructure to compliment the region’s goods-oriented economy would be worthwhile. Such investments should be carefully planned and coordinated both within and across Midwest states.

Selected presentations from the forum can be found on the following website link.

Digging Out of a Hole – A View from Detroit

Paul Traub

Digging out of a hole sounds like an oxymoron, but that seems to be what is happening with this particular economic recovery compared with recoveries from past recessions. Rather than the more rapid growth we would expect from the type of recession the U.S. just experienced, the economy is experiencing very tepid growth. The latest gross state product (GSP) data show just how slowly the recovery is proceeding for the Seventh District. [1]

Even though the District is leading the nation during the recovery in its manufacturing and agricultural sectors, as of the end of 2010 its total output is still lower than it was in 2005. The District is making some progress, but the direction of the recovery does look more like tunneling out of a hole than a vertical assent.

To get a sense of how different this recovery is, we can look at past rebounds from recession. For example, on average, three years after the start of the previous two recessions, the region had already experienced expansion of over 10.0%. By 2010, three years after the start of the 2007 recession, total GSP for the District is still 2.6% below its 2007 level. This hole is pretty deep.

It is important to note that the recession was not evenly distributed across all District states. The following chart shows the GSP for each state in the District indexed to calendar year 2000. It can be seen here that Michigan never really recovered from the 2001 recession. In fact, Michigan’s previous GSP peak was eight years earlier back in 2003.

While Wisconsin, Indiana, and Illinois seem to have tracked each other very closely over the past decade, Iowa has shown the strongest growth of all the states in the District. In fact, Iowa has experienced 21.3% growth since 2000. Its growth has been supported by a rise in agricultural commodity prices and the fact that it didn’t experience a housing price bubble, which has allowed the real estate sector to continue to show growth over the last decade. On the other hand, Michigan’s economy, which has been hurt significantly by declines in auto sales, has shown the weakest growth, its 2010 total GSP is still below where it was in 2000.

The next chart compares real state product growth in the District states from 2009 to 2010 with the nation as a whole.

The District grew at 2.8% in 2010, compared with 3.0% for the nation. Two of the five states grew at rates greater than the nation and four out of five states grew faster than more than half the states in the country. Michigan, which has been struggling for the past decade, actually did quite well growing at 2.9% and coming in at 16th place among all the states. Indiana, Iowa, Wisconsin and Illinois placed 3rd, 13th, 23rd, and 32nd, respectively.

In terms of job growth, the region’s economy may be performing slightly better than the nation overall in 2011. Through June 2011, the District had created jobs at a faster pace (0.9%) than the nation as a whole (0.7%), albeit from a much lower trough.

Michigan, which lost population in the last census, actually led the District in the first half of this year with job growth of 1.9%, it ranked 4th in the nation in growth of nonfarm payroll jobs. On the other hand, Indiana ranked last with employment down 0.4% in July 2011 on a year-to-date basis.[2] Even though Indiana has seen a decline in total nonfarm July 2011 year-to-date, the state has experienced job gains in two sectors, mining and logging (1.5%) and manufacturing (1.2%).

Still, total nonfarm payroll employment in the District remains well below its previous peak. In fact, as can be seen in the following chart, nonfarm payroll employment for the District is still below where it was in 1996. In addition, the nation as a whole has also seen a sharp decline in nonfarm payroll jobs since the start of the latest recession — nonfarm payroll employment for the country is currently about where it was in 2004.

If we take a closer look at manufacturing employment data for the nation and the District, we see an even more distressing picture. Since 1990, the nation and the District have lost about 35% of their manufacturing jobs. This is equivalent to over 6.0 million jobs nationally, of which the District accounts for about 1.1 million. At its peak in 2000, the District accounted for 19.1% of the nation’s manufacturing employment. By July 2011 its share had fallen to about 18.6%. Also at the peak in 2000, the region had 474,000 auto related jobs, which accounted for about 14.4% of the region’s manufacturing employment. As of July 2011, manufacturing employment in the region was 2.2 million jobs, of which 203,600 or 9.3% were in the auto industry.

Some of the employment declines have come about from labor-saving productivity improvements, but many are the result of declining U.S. auto sales together with declining market shares of the Michigan-based Detroit 3 auto makers and their suppliers.

In the past couple of months total light vehicle sales have been disappointing but, on the bright side, the traditional domestic manufacturers have been doing relatively well. In fact, on a year-over-year basis through June of this year, the Detroit 3 collectively saw sales increase by 15.5% versus an increase of just 7.6% for the industry as a whole. The Japanese manufacturers experienced a decline in sales on a year-over-year basis of 11.6%, largely due to supply disruptions as a result of devastating earthquake in Japan. In addition, some customers may be postponing purchases until the Japanese manufacturers can get their inventories replenished. Thus, absent the impact of the earthquake and related supply disruptions, auto sales overall would have been stronger in recent months.

It remains to be seen when auto sales will regain the positive momentum they had shown earlier in the year but despite recent setbacks, the August 2011 Blue Chip consensus for light vehicle sales for 2012 is 13.6 million units. This is a 30.1% increase from the 10.6 million units sold in 2009 and an increase of 1.4 million units from the July SAAR of 12.2 million units. In addition, Ward’s Automotive is projecting that by 2012, vehicle production in the District will be up by 2.3 million units from its low point in 2009. If these projections are correct we would expect to see some more positive gains in manufacturing employment for our region — especially Michigan. Meanwhile, we just have to keep digging.


[1]GSP is the equivalent of GDP at the national level – the sum total value of all goods and services.(Return to text)

[2]State rankings include the District of Columbia. (Return to text)

What’s Behind the Seventh District Resurgence?

Fame and fortune can be fleeting, but over the past year the Seventh District has been leading other U.S. regions in the pace of economic recovery. It is not so much that economic conditions are better here. Rather, it is that the pace of improvement has been quicker. As the map below illustrates, unemployment rates have fallen most rapidly in Michigan, followed by Illinois, and in quick succession by Indiana and Wisconsin.

[click to enlarge]

The rebounding District economy is being pulled along by its two hallmark goods industries—agriculture and, especially, manufacturing. The manufacturing output recovery has far exceeded overall output growth in both the nation and the District. Since the District’s manufacturing concentration exceeds that of the nation, this unbalanced recovery has exerted an outsized effect on the District economy. Moreover, output gains in the Seventh District have outpaced those in the U.S. manufacturing sector overall. The chart below compares U.S. industrial production to its regional counterpart, the Chicago Fed Midwest Manufacturing Index. From their respective troughs in mid 2009, the IPMFG has gained 14.2 percent and the CFMMI has gained 24.2 percent. Jobs in the manufacturing sector have also been rebounding from deep lows. From the first quarter of 2010 to the first quarter of 2011, the District states of Michigan, Wisconsin, and Indiana, in that order, have led all other states in net job growth in the sector.

The fact that the District’s manufacturing has outpaced that of the nation during the expansionary period is not surprising, since the District’s industry composition is highly concentrated in the most cyclically sensitive sectors, such as automotive, primary metals, and basic machinery. Prominent automotive companies GM and Chrysler underwent bankruptcy-like events during the recent recession, in which their production activity dropped severely. Afterward, during their rebirth, these companies have ramped up rapidly to rebuild depleted inventories.

More generally, the process of rebuilding inventories has spurred manufacturing production activity. Inventory-rebuilding is somewhat typical during economic recoveries. At the low point of this past recession, as businesses began to raise their forecasts of national economic growth, they began to rebuild their inventories in earnest in order to meet anticipated product demand for both consumer products and business equipment. Since the trough of the recession in mid 2009, inventory rebuilding has contributed an average .93 percentage points to the growth rate of U.S. GDP. This contribution from inventory rebuilding amounts to one-third of total realized GDP growth from mid 2009 through the first quarter of 2011.

Realized sales of manufactured goods have also benefited District manufacturers of both business equipment and consumer durable goods. The annual pace of U.S. sales of business fixed investment in “equipment and software” have averaged over 14.1 percent so far during the economic recovery. Prominent District producers in this category include makers of farm, mining, and construction machinery, medical equipment, and electrical machinery such as engines and turbines.

Among consumer goods manufacturers that are highly concentrated in the District, the automotive assembly and parts makers are experiencing rapid growth in sales. From annual sales of 10.4 million light vehicles in 2009, the annualized pace of vehicle sales have averaged over 13 million over the first four months of this year. In response, light vehicle production in the U.S. climbed almost 73 percent from the first quarter of 2009 to the first quarter of 2011.

Analysts see more room for growth in domestic light vehicle production and sales. The scrappage rate of the “automotive fleet”– vehicles now on the road– has been running very low so that, according to Detroit Branch Business Economist Paul Traub, the average age of the automotive fleet has been rising since 2000. As the existing fleet wears out, demand for new vehicles will grow. In addition, the age and quality-adjusted price of used cars is running high in comparison to prices of new vehicles due to both the slow pace of new vehicle sales since 2008 and the 2009 “Cash for Clunkers” program, which took used cars off the road.

A revival in U.S. exports abroad is a third leg that underpins the manufacturing resurgence in the District. U.S. exports abroad grew strongly from 2004 to 2007 as world GDP growth averaged 5.0 percent per year. [1] However, during 2008 and 2009, world trade fell dramatically due to the global financial crisis and evaporating availability of credit to finance imports and exports. According to a recent article by Senior Economist Meredith Crowley, “ ….in April 2009, the world economy appeared to be in a free fall. Global trade in goods and services had fallen 15.8 percent over the final two quarters of 2008 and first quarter of 2009. This world trade collapse had been the largest three-quarter decline of the past 40 years.”

Led by economic recovery—principally in Asia and Latin America—world growth and trade recovered sharply in 2010 and into this year, supporting a recovery in U.S. exports. Over the seven quarters of the U.S. economic recovery since mid 2009, export growth has contributed an average 1.25 percentage points to annual output growth. .

Exports of manufactured goods have also rebounded in the District. The District exports capital goods, heavy machinery, and medical and transportation equipment needed by developing countries as they build their own economies. The District’s overall export orientation in manufacturing is very similar to the nation’s, and it has recovered similarly as well. The five District states experienced 48 percent growth in manufactured exports from the first quarter of 2009 through the first quarter of 2011 versus 38 percent for the U.S. Barring any unforeseen stumbles to the expected and continued pace of world economic growth, exports should continue to support economic expansion in both the District and the nation.

The District’s primary agricultural sectors have also contributed mightily to economic recovery. So far in 2011, both corn and soybean prices are trading well above 2010 and well above their previous 5-year ranges. Milk and hog prices are also trading at prices above their previous averages (below).

Production of both corn and soybeans has climbed over the decade, especially corn. Corn usage in meeting production mandates of ethanol fuels has especially spurred both the volume of corn planting and its price. Exports of soybeans and related products have responded to rising global demand, especially in Asia. These developments have acted to lift farm-related incomes and jobs, as well as purchases of farm equipment and traded prices of farmland. As reported by Dave Oppedahl in the AgLetter “At 16 percent, the year-over-year increase in farmland values in the first quarter of 2011 for the Seventh Federal Reserve District was the largest since 2007 and was last surpsassed in 1979.” As also reported, domestic sales of harvesting equipment and large tractors have shown strong gains over the past two years.

One dark cloud has been the cold and wet spring of 2011, which has delayed planting, thereby threatening this year’s crop yields and production.

While it is clear that goods-producing sectors are driving the District’s economic gains, it is also significant that labor market improvement are concurrently taking place in service-oriented metropolitan areas. Much like other large MSAs, Chicago’s employment composition is not highly concentrated in goods-producing sectors—at least not directly. However, among the 20 most populous MSAs, Chicago’s unemployment rate declines have been among the most precipitous, declining 2.2 percentage points year over year versus .9 percent for the nation (below). Here, the surrounding region’s goods-producing activity has apparently lifted Chicago area business and professional services employment, as well as its leisure and hospitality sectors. Similarly, service-oriented Indianapolis experienced declining unemployment rates of 1.6 percentage points. Meanwhile, those Seventh District metropolitan areas that serve as both financial-service hubs for their surrounding regions and as manufacturing centers in their own right also saw significant unemployment rate declines. The Detroit MSA recorded a 3.5 percentage point decline; Indianapolis MSA a 1.6 percent decline, and the Milwaukee MSA, a 1.9 percentage point decline.

What’s ahead for the Seventh District economy? Much, but not all, of the recent resurgence derives from transitory causes. In particular, the marked U.S. growth rebound from the deep recession to a modest expansion has lifted inventory building of durable goods. But as inventory accumulation returns to normal, this element of growth in demand will ease off. In a similar vein, the return to robust world economic growth is expected to continue, but not accelerate. Accordingly, manufacturing exports will continue to grow, though perhaps at a more subdued pace. Similarly, domestic U.S. demand for manufactured goods and capital equipment is expected to continue but not to greatly accelerate. However, domestic demand for light vehicles to replace the aging U.S. fleet is thought to hold promise for expansion.

The current period of strong prices for farm commodities is being watched with caution by market participants. As developing countries supplement their diets with U.S. farm products, export demand will continue to support farm prices. However, farm commodity prices are also notoriously volatile as they are buffeted by climate events related to surprise crop failures or successes round the world.


[1] IMF, April 2011. (Return to text)

Interpreting the Midwest Economy Index

by Scott Brave, senior business economist

On March 31, 2011, the Chicago Fed will begin releasing on a monthly basis an index designed to measure growth in nonfarm business activity in the Seventh Federal Reserve District states of Illinois, Indiana, Iowa, Michigan, and Wisconsin. This monthly index, called the Midwest Economy Index (MEI), will serve as a regional counterpart to the Chicago Fed’s National Activity Index (CFNAI), available here, and allow for a comparison of national and regional growth trends.

This blog serves as a source of background information on the MEI, detailing its construction and interpretation. In the future, this information will be available at To receive email updates on the MEI as well as future releases, you can sign up at beginning March 31.

Background on the MEI

The MEI is a weighted average of 128 state and regional indicators encompassing the entirety of the five states in the Seventh Federal Reserve District. It measures growth in nonfarm business activity from four broad sectors of the Midwest economy: 1) manufacturing, 2) construction and mining, 3) services, and 4) consumer spending.

As with similar indexes of regional economic activity, the majority of the indicators in the MEI are based on data from the Payroll and Household Employment surveys and State Initial Unemployment Insurance claims.[1] However, for the manufacturing and construction and mining sectors, the MEI also captures production indicators, while for consumer spending it additionally includes data on personal income and home and retail sales.

The MEI incorporates indicators that are observed at both a monthly and quarterly frequency. To express the monthly index at a quarterly frequency, we translate all 128 indicators into a common frequency by taking a three-month moving average of the monthly indicators. In this sense, the MEI’s closest national counterpart is the three-month moving average of the CFNAI (the CFNAI-MA3). Every indicator is then given a stationary transformation and standardized to have a zero mean and unit variance.

The weight each indicator receives in the MEI depends upon the relative degree to which it explains the overall variation among all the indicators. In this fashion, greater influence in the index is given to those indicators that are able to best explain broader fluctuations in the Midwest economy. The degree to which this is true for any individual indicator is captured in the absolute value of its weight. A full list of indicators and their weights can be found here.

To be able to incorporate indicators that differ in originating date and reporting frequency, we follow the estimation strategy outlined by Stock and Watson.[2] This strategy is based on a statistical method called “principal component analysis” and is used to create a system of relative rankings, or weights, for the indicators. These weights are re-estimated each month, but in practice change very little given the substantial history of the index.

To illustrate the role played by each of the four sectors and five states, the pie charts below show what percentage of the variation in the 128 indicators explained by the MEI can be attributed to each sector (figure 1) or state (figure 2). Broad fluctuations in Midwest nonfarm business activity have historically been explained by the manufacturing sector and, to a lesser extent, the service sector, as well as by the three largest District states (Illinois, Michigan, and Wisconsin).

Interpreting the MEI

Our motivation in creating the MEI is to better understand the relationship between growth in national economic activity and growth in Midwest economic activity. The MEI is a measure of regional economic activity in much the same way as the CFNAI is a measure of national economic activity. CFNAI values above zero indicate growth in national economic activity above its historical trend, and values below zero indicate growth below trend. Similarly, MEI values correspond to deviations of growth in Midwest economic activity around its historical trend.

Over long periods, Midwest economic activity has tended to track national economic activity—as shown in figure 3, which compares the MEI and CFNAI-MA3. Both indexes in this figure have been expressed in standard deviation units, so that a value of –1 corresponds with growth that is 1 standard deviation below trend.

However, over shorter periods this has not always been the case, particularly around the beginnings and ends of recessions (the shaded regions in the figure as defined by the National Bureau of Economic Research, or NBER). To highlight such differences, we construct two separate index values: an absolute value and a relative value. The MEI (absolute value) captures both national and regional factors driving Midwest growth, while the relative MEI (relative value) provides a picture of Midwest growth conditions relative to those of the nation.

A positive value of the relative MEI indicates that regional 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. To obtain this interpretation for the relative MEI, we use the standardized residuals from linear regressions of each of the 128 indicators on the CFNAI-MA3 to construct the index.[3] This construction accounts for differences in national and regional growth trends and volatility that prohibit comparisons of magnitudes in the figure above.

Figure 4 shows the relative MEI in comparison to the CFNAI-MA3. The unit of measurement is again standard deviation units, so that a value of 1 for the relative MEI indicates that Midwest growth is 1 standard deviation greater than would typically be suggested given the level of the CFNAI-MA3. This figure shows that the Midwest business cycle was particularly pronounced during and after the recessions of the late 1970s, early 1980s, and 2007–09.

Other significant periods in which Midwest growth deviated substantially from national growth include the 2001 recession, which more adversely affected the Midwest region, and the 1990–91 recession, which was milder regionally but was preceded by a period of relative weakness.

Contributions to growth by sector and state

Additional information on the sources of growth in Midwest economic activity can be found by decomposing the MEI and relative MEI into contributions from the four broad sectors of the Midwest economy. The figure below plots the time series of these contributions over the history of the index.

Much of what we see in this figure can be summed up by the following: When manufacturing has thrived, so has the region. However, the contributions of the service sector to Midwest growth over time have become increasingly important. Consumer spending indicators show a similar pattern, making sizable contributions at business cycle peaks and troughs. Finally, the region has historically been less prone to large fluctuations in growth coming from the construction and mining sector than other parts of the nation.

Looking at regional versus national growth, the manufacturing and service sectors explain the vast majority of movements in the relative MEI. However, the contribution of services to the relative MEI is larger than it is to the MEI and nearly equal to that of manufacturing. This feature of the relative MEI reflects the importance of the service sector during periods where the Midwest economy has expanded or contracted faster than the nation. A good example of the former is the early to mid-1990s, while the early to mid-2000s exemplify the latter.

Using only the indicators for the respective states in the Seventh District, we construct state-level contributions to the MEI and relative MEI.[4] Figure 7 plots the time series of these contributions over the history of the index. No single state dominates growth in Midwest economic activity, although Illinois tends to make the largest contribution to both; and growth trends in nonfarm business activity across states are similar, with the exception of the weakness of the Michigan economy over the past decade.

During the recent recovery, all five Seventh District states have made positive contributions at one time or another to the MEI and relative MEI, suggesting that the manufacturing-driven recovery has benefited the region disproportionately. In the future, we invite you to track these developments through the charting utility for the Seventh Federal Reserve District found here.


[1] See, for instance, Theodore M. Crone and Alan Clayton-Matthews, 2005, “Consistent economic indexes for the 50 states,” Review of Economics and Statistics, Vol. 87, No. 4, pp. 593–603. (Return to text)

[2]J. H. Stock and M. W. Watson, 2002, “Forecasting using principal components from a large number of predictors,” Journal of the American Statistical Association, Vol. 97, No. 460, pp. 1167–1179.(Return to text)

[3]Every indicator is regressed on the contemporaneous value of the CFNAI-MA3. Some indicators are also regressed on the lagged value of the CFNAI-MA3. These indicators are chosen based on the Bayesian Information Criterion, which balances the explanatory power gained by including an additional lag of the CFNAI-MA3 in the regression against the uncertainty introduced from the estimation of an additional parameter.(Return to text)

[4]A handful of indicators exist only at a regional level. To construct state contributions, we omit these variables. Therefore, the state contributions do not sum to the overall index in each period.(Return to text)