From December 22, 2018, to January 25, 2019, the federal government was partially shut down. In the latest round of the Chicago Fed Survey of Business Conditions (which was conducted from February 11 through 27), we asked our contacts about the extent to which the shutdown affected their businesses in terms of product demand, business operations, business decisions, and outlook for the U.S. economy. Overall, the effects were limited.
On December 22nd of last year, President Trump signed the Tax Cuts and Jobs Act, a law that makes substantial changes to the federal tax code for individuals and businesses. An important provision of the act is tax cuts for both groups worth an estimated $1.46 trillion over the next ten years. Congress’s Joint Committee on Taxation estimates that businesses will pay $330.4 billion less in taxes over that period, with more than two-thirds of the reduction coming in the first three years.
In the run-up to the tax bill’s passage, there was a substantial debate about what businesses would do with the extra money from the tax cuts. Commentators in favor of the bill generally argued that strong competition would force businesses to invest their tax savings in capital, which would result in higher worker productivity, output, and wages. Commentators opposing the bill generally argued that weak competition would allow businesses to forgo spending on capital and labor and instead allow them to pay out increased profits to shareholders.
While it is still too soon to know what business leaders will actually do, it is possible ask them what they expect to happen. We did just that: We asked the respondents to our Chicago Fed Survey of Business Conditions (CFSBC) how they expect the new tax act to affect their businesses and how they expect to spend their tax windfalls (if they get one). While the sample size is fairly small and not representative of the universe of Seventh Federal Reserve District firms, the results do offer some perspective on these very interesting questions.
Figure 1 shows the results from our first question. It reports that 63 percent of respondents expect the tax act to have a positive impact on their firms. Most respondents who expect a positive impact anticipate a direct effect on their firms’ net incomes, though some said that while they do not anticipate a direct effect on their firms, they do expect the act to stimulate the economy, which would result in greater demand for their firms’ products. The few respondents (17%) who said they expect the tax act to have a negative impact were from multiple sectors. However, one sector that we survey—nonprofits—was particularly negative about the tax act because they believe that the large increase in the standard deduction will encourage more households to not itemize, thereby reducing the incentive to make charitable donations.
We next asked our contacts how they expect to spend their tax windfalls, if any. Sixty percent of the respondents answered this question. Businesses have options in addition to capital spending, labor expenditures, and profit payouts, such as mergers and acquisitions, price decreases, and balance-sheet repair (i.e., holding more cash, paying down debt, or buying other financial assets). Figure 2 shows the average share our contacts expect to put toward each major spending category. The largest was capital spending (27%), followed by balance-sheet repair (25%), profit payouts (18%), and labor spending (14%). Our manufacturing contacts expect to spend a greater share of their savings on capital and balance-sheet repair than our nonmanufacturing contacts.
The results shown in figure 2 suggest that there is some truth to the arguments made in favor of the act and those made in opposition to it. Our contacts expect to spend about 40% of their tax savings on capital and labor and just under 20% on profit payouts. They also expect to spend a large share on balance-sheet repair, which could be interpreted as a wait-and-see approach: Rather than spend the money now, they plan to put their firms in a better financial position for the future.
Look for a follow-up blog post about a year from now, when we will be able to learn how things went for our business contacts after a year under the new federal tax regime.
Appendix: Below is the full distribution of responses for how our contacts expect to allocate their tax savings across each of the five spending categories.
A summary of economic conditions in the Seventh District from the latest release of the Beige Book and other indicators of regional business activity:
- Overall conditions: Growth in economic activity in the Seventh District slowed to a modest pace in April and early May. Respondents’ outlooks for growth over the next 6 to 12 months also pulled back some, but remained positive on balance.
- Employment and Wages: Employment growth remained at a moderate rate. While contacts indicated that the labor market was tight, wage growth was only modest.
- Prices: Prices again rose modestly. That said, retail and materials prices changed little.
- Consumer spending: Consumer spending decreased slightly overall. Non-auto retail sales levels were flat and sales of light vehicles slowed some.
- Business Spending: Growth in capital expenditures picked up to a moderate pace. Retail and manufacturing inventories were generally at desired levels, though auto dealers thought inventories were too high.
- Construction and Real Estate: Residential construction rose moderately, though the pace of home sales was little changed. Nonresidential construction and commercial real estate activity were up slightly.
- Manufacturing: Manufacturing production again grew at a moderate pace. Growth was widespread across industries, helped by greater demand from the energy sector.
- Banking and finance: Market participants reported stable market conditions and low volatility. Business loan demand increased slightly and consumer loan demand was unchanged.
- Agriculture: The outlook for crop income was unchanged, incomes for hog and cattle operations improved, and incomes for dairy farmers deteriorated a bit.
The Chicago Fed Survey of Business Conditions (CFSBC) Activity Index decreased to –9 from +14, suggesting that growth in economic activity slowed to a modest pace in April and early May. The CFSBC Manufacturing Activity Index declined to +19 from +45, while the CFSBC Nonmanufacturing Activity Index moved down to –25 from –5.
The Midwest Economy Index (MEI) increased to +0.70 in April from +0.61 in March, reaching its highest value since June 2014. All four broad sectors of nonfarm business activity and all five Seventh Federal Reserve District states made positive contributions to the MEI in April. The relative MEI rose to +0.64 in April from +0.44 in March. All four sectors and four of the five states made positive contributions to the relative MEI in April.
In partnership with World Business Chicago, the Federal Reserve Bank of Chicago hosted the Civic Research Forum on March 17, 2015. The forum was attended by researchers from a wide range of organizations and agencies throughout Chicago. It offered attendees an opportunity to discuss their current research and their positive and negative experiences with collecting and using data. Rob Paral of Rob Paral and Associates addressed the gathering, discussing his research on demographic trends in Chicago. Moreover, he described his research challenges given the lack of some key historical data series, as well as the structure of available data sets and surveys. He also encouraged the audience to brainstorm innovative ways of using the accessible data.
Paral explained that his firm helps strengthen relationships between organizations and the broader communities they serve by providing data on the city’s social and economic conditions. He also shared that his firm gathers information on residents’ activities and attitudes. In his presentation, Paral focused on the income data he uses to study demographic trends in Chicago. While socioeconomic and demographic U.S. Census data are available for the 77 Chicago community areas (see map below) dating back to 1930, the data necessary to calculate median household income only go back to 1970. The limitations of these historical data hinder the potential to analyze income developments in Chicago over time (both at the neighborhood level and across demographics).
According to Paral, constructing income data for Chicago became even more difficult when the U.S. Census Bureau’s geographic grid, which includes the boundaries of blocks, tracts, and Public Use Microdata Areas (PUMAs) changed for the 2010 U.S. Census. The boundaries for these geographic units were redesigned in such a way that researchers could no longer aggregate PUMAs to match Chicago’s geography. Furthermore, beginning with the 2009–13 American Community Survey, it was no longer possible to select the Chicago-portions of census tracts for the few tracts that cover areas both inside and outside of the city limits, like it had been in previous versions. This change made it impossible to construct precise data for some individual community areas by combining data on the component census tracts.
Paral went on to discuss some of the questions related to income trends in Chicago that he is currently probing. He said his research focuses largely on the period between 1990 and 2010. Over this span, Illinois’s household income increased and then fell rapidly—a trend that was seen nationwide, though not to the degree it was within the state. According to Paral, the average household in Chicago earned 10% less income in 2010 than in 2000. Moreover, while nine out of every ten community areas had less income in 2010 than they did in 2000, some lost much more income than others. For instance, average household income declined by as much as 45% in some community areas, while other areas have seen an increase in income.
Looking at income trends of individual neighborhoods over time reveals interesting patterns about how wealth and poverty shift and consolidate geographically, Paral explained. In 1990, the wealthiest community areas were located in the far Northwest Side, the far Southwest Side, and the downtown and near-north areas. So, Chicago’s wealthiest neighborhoods were fairly dispersed back then. However, wealth became more geographically concentrated over time. In 2000, Chicago’s wealthiest areas were near the North Side and along the lakefront. And in 2008–12, this remained the case. In 1990, the poorest areas were largely consolidated in an area just west and south of the Loop (Chicago’s central business district). But over time, the poor moved farther away from the city center. In 2000, Chicago’s areas of greatest poverty were on the West and South Sides. And in 2008–12, this was still the case. The greatest income losses between 2000 and 2008–12 occurred on the far South Side, while the greatest income gains over that period happened in the “inner ring” areas near downtown (primarily just west and south of the Loop).
Paral said that while median income is the principal indicator he uses to analyze many trends, he also takes advantage of other measures of wealth provided by the U.S. Census Bureau—such as average and total household income—to get more robust views of wealth patterns and distribution across Chicago. Paral explained that by taking the ratio of average income to median income, he is able to assess the extent to which income distribution is skewed in an area—that is, how great the disparities are between the wealthiest and poorest residents in a given neighborhood. For example, a very high ratio of average income to median income suggests that there are some very wealthy residents pulling up the average (even if a majority of that neighborhood’s residents are poor).
As Paral shared, using innovative ways of combining available data, such as this method of studying the ratio of average to median income, has allowed him to examine potential weaknesses in current policies that are based on more-conventional income data and analysis. For example, he questioned the use of census tracts to determine how children are placed into public Selective Enrollment High Schools within Chicago. The current policy assigns each census tract to a socioeconomic tier, where 1 is the poorest and 4 is the wealthiest. The policy is designed to give children of poorer tiers a better opportunity of enrolling in a strong public school. However, some very poor children live in the same tract as very wealthy children. This means the average income is skewed up by these wealthy families, decreasing the chances the poor children have of being accepted into a strong public high school. Paral mentioned several census tracts where this pattern is especially problematic, such as those where there are large public housing buildings nearby very wealthy homes. In such tracts, the gap in median income between one (poor) subsection and another (rich) one can be over $100,000. Yet, because both poor and wealthy households are located in the same census tract, their children have an equal likelihood of entering the city’s best public schools.
The forum ended with the attendees sharing the research they are working on, the data they use, and any challenges they are facing. This portion of the program gave researchers the opportunity to learn of new data sources and approaches to analysis and to meet others in the Chicago research community. The forum sponsors hoped that innovation and collaboration among the attendees would eventually yield more-productive research in the coming years.
By Bill Testa
As the US economic recovery approaches the five-year mark, a look back shows that it has been far from a smooth and upward ride. Since the end of the Great Recession, the economy has grown at a generally disappointing pace with fits and starts due to repeated setbacks. Many parts of the U.S. economy are still working their way through the effects of the financial crisis that accompanied the recession. For instance, the labor market has been healing quite slowly. And many households and businesses are still repairing their balance sheets after having suffered steep losses in asset values. Also, the overhang in housing inventory has been slow to clear. Meanwhile, global economic recovery has faltered several times—first, in Europe and, most recently, in East Asia.
As the U.S. economy began to recover in mid-2009, Illinois and other states in the Great Lakes region bounced back at a quick pace, albeit from a very low point. The Great Lakes region’s strong industrial orientation—that is, its heavy involvement in durable goods production—translated into a steep economic recovery as the nation’s businesses sought to rebuild their depleted inventories of capital goods and equipment while households similarly began to replace automobiles and other consumer durable goods. Moreover, since the global recovery was quite strong back then, exports of machinery and foodstuffs from the Great Lakes region also contributed to the economic climb. However, the Great Lakes region’s pace of growth began to decelerate two years into the recovery. The aforementioned growth impetus of inventory rebuilding and exports abroad eased. Among the major sectors, only the automotive industry continued to grow quickly.
Following the Great Recession, Illinois began to recover and even gain ground on the nation, but its economic performance began to alarm many observers in 2011. As seen below, Illinois’s unemployment rate fell quickly in 2010 and into early 2011. However, the state’s unemployment rate then failed to show much improvement, even as the nation’s unemployment rate continued to fall more.
It could be that Illinois’s deviation from the national trend in unemployment is related to the economic performance of the broader Great Lakes region. The Illinois economy is highly integrated with the other industrial states of the Great Lakes region—Wisconsin, Indiana, Michigan, and Ohio. Accordingly, the Illinois economy regularly rises and falls along with the economies of these states. If Illinois’s performance differs from its neighbors, it would be a cause for concern—and the degree of concern would be higher as Illinois fell further behind its neighbors. As the chart below suggests, the aggregate unemployment rate of the Great Lakes states (less Illinois), has continued to decline since 2011; Illinois progress has been much less. In what follows, I discuss possible sources of the deviation, including Illinois tax structure and Illinois industrial structure. In addition, I examine an alternative measure of labor market performance, namely the growth in payroll jobs.
Illinois’s seemingly poor economic performance compared with that of its neighboring states has sparked a policy debate as to whether the state’s recent hikes in statewide income taxes may be deterring investment and hiring in the state. Beginning in January 2011, the state’s personal income tax rates were hiked from 3.0 percent to 5.0 percent for the period 2011–14; they are scheduled to go down to 3.75% for the period 2015–23 and then to 3.25% from 2024 onward. (Similar hikes were enacted to the state’s corporate income tax—also with a schedule of phasing out the higher rates). These tax hikes were enacted to help the state pay down a rising stack of short-term debt for operating expenditures and to make progress on a much larger amount of unfunded public employee obligations (such as pensions). To date, the state’s finances have improved only modestly with respect to both short-term debt obligations and its longer-term pension-related debt. For this reason, some observers believe that Illinois tax rates will not be allowed to (fully) phase out as planned.
Are tax rate hikes discouraging hiring and investment in Illinois? It may come as no surprise that the effects of state and local tax differences on state economic growth are far from a settled science. Among the difficulties for settling the debate are that states seldom allow their business climates to get very far out of line with those of their neighbors, thereby making it difficult to find the growth effects of tax differences. However, in the case of Illinois, there is ample cause for concern. The state and its local governments face the possibility of having to pay down very large debt obligations—on the order of $100 billion or more—for employees covered by statewide pension systems. Moreover, the City of Chicago and other overlapping units of local government within the city’s limits face similar amounts of liabilities when measured on a per capita basis, while other Illinois local governments also carry very large unfunded liabilities. As discussed previously, depending on how fast these liabilities are amortized, they could give rise to tax rate differences between Illinois and neighboring states that are very sizable.
In a recent analysis of Illinois’s economic performance since the beginning of the hike in its income tax rates, Andrew Crosby and David Merriman examine several labor market measures of performance of the state versus the rest of the Midwest region. Similar to the charts above, the authors note that the unemployment rates diverge in a striking fashion right around the time that Illinois hiked its income tax rates. However, given the high variability of unemployment rate measurement at the state level, the authors think it best to consider other measurements. In examining payroll job growth, they show that growth in payroll employment displays a far less prominent deviation between Illinois and the rest of the Midwest region. In addition, the timing of the growth difference between Illinois and its neighbors does not develop until 2013—two years beyond the income tax hike.
While there is some evidence, then, that Illinois’s fiscal problems are weighing down its recovery, such problems are more of a long term concern. Illinois’s slow recovery may have more to do with its industrial structure. To further the analysis, I draw on data from the U.S. Bureau of Labor Statistics that are called the Quarterly Census of Employment and Wages (QCEW). These data are reported for states and the nation from the comprehensive reporting of those firms and establishments that are covered by the Federal-State Unemployment Insurance Program. One clear advantage of using such data is that specific industry employment data are reported by firms and establishments, which allows us to investigate the possible effects of differences in industry mix. On the downside, the data are compiled and released with a time lag of one half year or more.
The chart of the QCEW data for Illinois versus the four remaining Great Lakes states (Indiana, Michigan, Ohio, and Wisconsin) are shown below. Illinois’s employment outperformed the remaining states of the Great Lakes region in the years prior to the recession and during the recession. As a matter of interpretation, I would argue that Illinois’s relative superior performance prior to the recession likely reflected Michigan’s collapsing auto industry employment from 2003 onward, along with the unsustainable residential property construction boom that took place in the Chicago area prior to the onset of the recession in December, 2007. Illinois also outperformed the region during the recession, and this is somewhat typical. Illinois is the domicile of highly compensated professional and business service workers who are not as readily laid off during economic downturns.
However, the period following the recession—from mid-2009 onward—contrasts mildly but unfavorably from the previous periods. After the recession, the Great Lakes region’s employment recovers faster than Illinois’s in each year. This trend is again somewhat consistent with the possible pernicious effects of the 2011 tax hike. While Illinois’s employment performance lagged in the year prior to the tax hike, which seems counterintuitive, it is possible that firms began curtailing investment and hiring prior to the tax hike itself in anticipation of an inferior climate in which to do business.
That said, it is notable that, as opposed to the unemployment rate gap that was observed, the payroll job growth difference seen here is small. More importantly, there are alternative possible causes for Illinois’s lagging payroll job growth. In particular, Illinois’s mix of industries, while similar in some respects to those of other Great Lakes states, differs as well. It is possible that the small differences in job growth between Illinois and its neighbors are due to its somewhat different industry mix rather from disinvestment and a reluctance to hire in the state.
To investigate further, I compiled the QCEW data covering the five Great Lakes states from third quarter of 2007 to the third quarter of 2013, with detailed counts of jobs for each of 88 private sector industries. In the table below, the first row displays the actual job growth in Illinois for three two-year periods, as well as the entire period 2007:Q3–2013:Q3. During 2007:Q3–2009:Q3, Illinois experienced a net loss of 377,000 private sector payroll jobs, and gained back all but 158,000 by the third quarter of 2013.
As an analytic exercise, I further ask how the Illinois economy would have fared 1) if it had the same industry composition as the four other Great Lakes states combined and 2) if its industries had the same job growth rates as those in the other states. The second row of the table reports the results of this exercise (based on the two hypothetical scenarios, as well as an interaction of the two); the final row is the difference in hypothetical growth from actual growth. As shown above, Illinois hypothetically outpaced the region by 89,300 jobs in the 2007:Q3–2009:Q3 period by having a different industry mix and employment growth performance, but it gave back those jobs (and more) in the four years afterward.
To examine the results of this exercise in a different way, I decompose the differences in actual and hypothetical job growth in the table below. The first component shows the effects of maintaining Illinois’s actual industry-by-industry rates of employment growth but then hypothetically imposing the Great Lakes mix of industries. In the first row of the table below, one can see that during 2007:Q3–2009:Q3, Illinois’s industry mix was favorable to that of the remaining Great Lakes region, because it accounted for a 40,300 hypothetical gain in jobs. Seemingly, there are noteworthy differences in Illinois’s mix of industries from its neighbors’ that account for some of the year-to-year performance differences that we observe. For the subsequent two periods of the recovery, the mix of industries in Illinois (below) shows a hypothetical employment loss of 11,000 (from 2009 – 2011), and a further loss of 16,000 (2011 – 2013).
What are some of the industry mix differences that are notable between Illinois and other Great Lakes states? The large professional and financial services employment base in the Chicago area has already been noted. Further, in relation to other states, Illinois is now much more services oriented overall rather than goods producing. Manufacturing’s share of employment for 2013 clocks in at 11.4 percent of private sector payroll jobs in Illinois, versus 16.4 percent for the other four states. (See the appendix below for a more detailed illustration of Illinois employment base versus the GL region).
The schism in manufacturing employment share between Illinois and the Great Lakes region is wholly attributable to the Chicago area. As of 2013, the Chicago MSA employment base recorded only a 9.5 percent share in manufacturing, while the remainder of Illinois recorded 15.9 in manufacturing. From a geographic perspective, these differences may also explain part of the overall performance difference between Illinois and the remaining Great Lakes states. As the graphic below suggests, annual payroll employment growth in the Chicago MSA has kept pace with the remainder of the Great Lakes region while Illinois (non-Chicago) has fallen behind since 2011.
And within manufacturing, Illinois tends to lean more toward food processing and farm, construction, mining machinery relative to the other Great Lakes states. In contrast, while there are important auto assembly operations in the Bloomington–Normal and Rockford areas of Illinois, as well as important links to the automotive supply chain throughout the state, Illinois’s ties to the automotive industry are much less prominent than those of Michigan, Indiana, and Ohio.
Despite such industry differences between Illinois and the other Great Lakes states, an extension of the analysis suggests that the state’s competitive job performance did not kept pace during the recovery. For the same time periods, a second hypothetical component shows the effect of holding Illinois’s actual industry mix constant, but imposing the average job growth rates of the same industries from the neighboring Great Lakes states (second row below). Here, because the industries that make up Illinois’s mix tended to grow more rapidly (decline more slowly) than they did in the Great Lakes region, the state hypothetically gained another 44,100 during the 2007–09 period, but subtracted 63,000 and 50,000 jobs in the subsequent periods. (The final component is the interaction of two hypothetical effects).
As measured by labor market indicators, then, the Illinois economy has not fared as well as neighboring states during the economic recovery that began in mid-2009. Measurements of the state’s unemployment rate show Illinois in the least favorable light. In contrast, other labor market indicators, such as payroll employment growth, suggest that the state’s underperformance is much more mild. Nonetheless, even payroll employment trends suggest that Illinois is underperforming when examined on an industry-by-industry basis. Accordingly, recent changes in public policies that influence the investment climate, such as tax rate hikes, cannot be ruled out entirely,though such policy effects are unlikely to be exerting such a large and immediate effect.
In looking for alternative or contributing explanations, the state’s particular mix of industries is likely contributing to underperformance. For example, the state’s high concentration in construction and mining machinery stands out, as does its lower concentration in automotive as compared to Great Lakes states located to the east. The downstate Illinois economy is highly concentrated in manufacturing, and downstate areas have seen slower payroll employment growth than the Chicago area. And so, Illinois’s performance may yet converge with its neighbors as the automotive boom settles down, and as global economic recovery revives exports of machinery and equipment.
In considering other structural causes, the Chicago area experienced super-normal growth prior to the recession due to excessive home-building and related activities. Accordingly, part of Chicago’s recent performance may derive from a slow healing of residential real estate and related activity following the boom period.
Appendix 1: More on Illinois employment base as compared to the remaining Great Lakes region
The table below constructs an “industry dissimilarity index” between Illinois and other Great Lakes states (using the QCEW database as above) for the year 2013. Illinois is dissimilar to Indiana, Michigan, and Wisconsin, more or less, to the same degree when all industries are accounted for. However, Illinois is more dissimilar to Indiana and Michigan—the two most auto-intensive states in the region—and less dissimilar to Wisconsin in the case when the index is constructed to account for manufacturing industries alone.
Appendix 2: Selected Illinois industries comparison (index based on wages)
Here, the indexes of concentration shown in columns two and three relate Illinois and the four remaining Great Lakes states to the nation. An index value of one indicates parity with the nation, for example, while an index value of two indicates that industry wages in Illinois (or the Great Lakes region) are twice the national average. For example, the first row indicates that Illinois payroll wages in the Agriculture, Construction, and Mining Machinery sector lies at 2.88 times the national average while, in the four remaining Great Lakes states, the sector’s payroll lies at less than the national average—80 percent.
Thank you to Wenfei Du and Thom Walstrum for assistance.
The authors use the U.S. Census definition of Midwest, which comprises Illinois, Indiana, Iowa, Kansas, Michigan, Minnesota, Missouri, Nebraska, North Dakota, Ohio, South Dakota, and Wisconsin. (Return to text)
Some observers have questioned the veracity of Illinois’ high unemployment rates for the post-2011 period to date, citing concerns about measurement error and possible changes in survey methodology. However, some corroboration of the reported unemployment rates is offered by reported first-time claims for unemployment insurance. Over the period from 2011 to date, the annual average of Illinois claims as a share of the national total increased from 3.6 percent to 4.1 percent. At the same time, the Wisconsin share fell from 3.4 to under 3.2, while Ohio, Indiana, and Michigan also fell. Similarly, these same data on UI claims within Illinois corroborate local area unemployment patterns within the state. That is, over the two initial years the recovery, the Chicago area unemployment rate gave ground to the remainder of the state; while gaining ground during the latter half of the recovery.(Return to text)
As measured by permits filed to construct residential units, the Chicago MSA recovery has been weaker than other large MSAs in the region including Detroit, Des Moines, and Indianapolis.(Return to text)
Demographer William H. Frey calls to our attention a striking turnaround in population growth in the central cities of metropolitan areas. Since the 2005-06 peak of the housing construction boom in the United States, the growth rates of central cities have begun to gain ground on surrounding suburban areas. Beginning with 2005 and ending with population estimates reported by the Census Bureau for mid-year 2008, Frey illustrates a convergent city-suburb trend for U.S. metropolitan areas having a population over one million. These trends hold for all four major U.S. regions—North, Midwest, South, and West. (The 12-state Midwest population performance is shown below).
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Similarly, Frey reports that these gains “are not confined to the very largest American cities. Among the 75 cities with populations exceeding 200,000, 41 grew faster in 2007-08 than in the preceding year, and 54 grew faster than in 2004-05.” We show the population trends for such cities by region below. Once, again, we can see that the turnaround has taken place, on average, in all Census regions of the U.S.
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Within the Seventh District states of Illinois, Indiana, Iowa, Michigan and Wisconsin, growth has also tended to rebound in cities over 200,000 in population (below). For the year ending in the middle of 2008, six of seven cities exhibited positive population growth. However, the City of Detroit is an outstanding exception with an accelerated decline in the mid-year ending 2008.
On average, Seventh District cities shifted from zero or negative growth in 2005 to an annual growth rate of 0.5 percent for 2008. The largest swings in performance were registered by Des Moines, with a swing from minus 1.3 percent in 2004 to plus 1.2 percent in 2008, and Chicago, with a swing from minus 0.7 in 2005 to plus 0.7 for 2008.
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At this point in time, the reasons for this shift toward central cities remain open to speculation. But given the timing, there are strong reasons to believe that the housing bust lies behind much, if not most, of the reversal. A general rise in demand for housing, such as that which occurred earlier in this decade, exerted a magnified impact on the fringe of urban areas. Given the lower price of land on the fringe and the ease with which larger single family homes can be constructed there (rather than tear-downs closer in), both population and housing generally shifted towards the periphery. Construction jobs related to fringe development likely bolstered the trend, as some households followed job opportunities to the suburbs. And now we may be seeing a reversal of such trends as home demand and employment have fallen off.
William Frey also attributes the urban population resurgence to the nature of the urban economies, citing “broad economic diversity at a time when smaller cities … are vulnerable to economic shocks” and the “resiliency of large urban centers that are economically and demographically diverse.” There may be some wisdom in thinking that this is so. In pursuing economic development, central cities have been trying to attract and grow “Eds and Meds,” (education and health care). As measured by George Erickcek and Tim Bartik of the Upjohn Institute, health care and hospitals, along with colleges and universities have been a bulwark of the economic base of many cities. These sectors of the U.S. economy have tended to grow and expand consistently, and cities have benefited. From the 2000 Census, Bartik and Erickcek report that earnings derived from the education sector are, on average, 36 percent more concentrated in the principal cities of the nation’s 283 metropolitan areas. Health care earnings are 12 percent more concentrated.
Nonetheless, with the release of the next mid-year Census estimates (for 2009), it will be interesting to see if central cities are able to sustain their momentum of population growth in relation to suburban areas. Beginning with 2009, the influences of the sharp U.S. recession and related job declines may become important.  Favoring central city economies, the education and health care sectors are steady performers even in recessions. So too, many central cities no longer host manufacturing production, which tends to be hit particularly hard during recessions. However, in many cities other elements of the economic base are both concentrated and highly sensitive to economic downturns. Such sectors include professional and business services, law, tourism/business travel, and especially the financial sector, which has been buffeted by the recent financial crisis.
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Little evidence is available so far concerning the differing impact of the two national recessions, 2001 and the current one, on city versus suburb. However, in a recent report by the Metropolitan Policy Program at Brookings, Elizabeth Kneebone and Emily Garr report on year-over-year unemployment rates for city versus suburbs in the nation’s 100 largest metropolitan areas. They find that “in contrast to the last recession,” when city unemployment rates rose more sharply versus their suburbs, “unemployment has increased at nearly equal rates in cities and suburbs.”  The table below excerpts the year-over-year rise in unemployment rates for cities and their suburbs for several Seventh District cities and their suburbs and for the four major regions of the United States.
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Note: Thank you to Emily Engel and Matt Olson for assistance.
The difference in the gap between the two recessions is not large. Year over year changes in unemployment rates in cities rose by 1.9 percent in primary cities versus 1.4 percent in suburbs from May 2001 to May 2002. For May 2008 to May 2009, year-over-year rates rose by 3.9 and 3.7 percentage points, respectively, for cities and suburbs. However, city/suburb unemployment rate differences in level are wider currently than in the 2001-02 period.(Return to text)
For nations, gross domestic product (GDP) is the most widely used yardstick to measure economic activity and growth. Conceptually, GDP measures the value of output produced by the market economy within a year or other period. In addition, GDP is defined as output produced within a designated geographic area such as a nation’s boundaries.
There is one more major wrinkle in this measure; GDP is typically reported as “real” GDP, meaning that the dollar values of goods and services are adjusted to reflect price changes. Such adjustments are made so that, for example, output growth reflects real gains in both the quantity and quality of what a nation produces, and not merely dollars transacted.
GDP matters to people, workers, and households because what is produced gives rise to what is earned in wages, salaries, and earnings on capital and savings. Accordingly, in many economics textbooks, the GDP concept is presented alongside its equivalent yardstick, gross national income.
In the U.S., the Bureau of Economic Analysis (BEA) produces data on GDP so that the pace of overall economic activity and its many components can be tracked on a timely basis. More recently, BEA has begun to provide timely GDP estimates for states and regions. On June 5, for example, the BEA released preliminary estimates for states and regions covering the calendar year 2007.
BEA data on GDP growth by individual states for 2007 shows a general economic slowdown that mirrors the national slowdown from 3.1 percent in 2006 to 2.0 percent in 2007. In all, 36 states experienced slowing GDP growth in 2007 versus 2006, with weakness centered in finance and in construction—especially housing.
The BEA’s map, reproduced below, shows several features of GDP growth in the Seventh District states—Illinois, Indiana, Iowa, Michigan, and Wisconsin.
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GDP growth in all five states of the Seventh District fell short of the national level in 2007. Michigan recorded a decline of 1.2 percent, marking the state’s second year in a row of economic output decline and its third such year over the past four.
In contrast to Michigan’s ongoing slow growth, many previously high-growth states in other regions experienced sharp declines in growth for 2007 versus their 2006 pace of growth. In particular, Arizona’s growth pace slowed from a 6.7 percent pace in 2006 to 1.8 percent in 2007; California went from 3.8 percent to 1.5 percent, Florida from 3.6 percent to flat, and Nevada from 5.4 percent to 0.6 percent.
The overall pace of growth in the Seventh District states slowed much less dramatically—from a pace of 0.9 percent in 2006 to 0.6 percent in 2007. This can be attributed to two major developments. First, the size of the highly impacted residential construction industry is much larger in high-growth states such as Arizona, Nevada, and Florida. While Midwestern states have experienced similarly sharp declines in housing activity, the impact has been proportionately larger outside of the region.
Another factor is that the U.S. manufacturing sector did not decline to the same extent in 2007 as it has in previous economic slowdowns. The falloff in new home sales and construction has exerted a drag on certain manufacturing industries, such as building materials and home appliances. However, other industries, such as machinery and computing equipment, continue to be buoyed by rapid growth in exports abroad, while others, such as mining and farm machinery, are being lifted by the global surge in commodity demand. For the manufacturing-intensive Midwest, then, the pace of overall economic growth has not slowed as much as it has in most previous episodes.
Another notable trend can be seen from the differing pace of growth within the Seventh District (see map above). Starting from the eastern states of the Seventh District, GDP growth in Indiana and Michigan significantly underperformed the western states of Illinois, Wisconsin, and Iowa. By way of explanation, the sagging domestically domiciled U.S. automotive industry exerts a heavier influence on Indiana and Michigan (and Ohio, too).
The nationwide falloff in residential investment activity is unfolding along various channels and to varying degrees across U.S. regions. Falling residential activity is being felt in consumer spending, manufacturing production (e.g. construction equipment, appliances, and materials), the financial sector (e.g. mortgage and development financing), real estate (sales) and, of course, in home building itself. In home building activity, slow-growing regions such as those in the Midwest may be somewhat advantaged. That is because construction activity does not comprise as large a share of total regional employment in comparison to fast-growing regions. And so, a proportionate decline in home building activity does not tend to slow the region’s overall economy as greatly.
The table below reports payroll employment for the overall construction sector in major U.S. regions and in the Seventh District. States in the West and in the South such as Nevada, Arizona, California, and Florida report construction employment as comprising 6–11 percent of the state’s total employment for the year 2006 (see column 3). In contrast, the District’s construction industry makes up 4-5 percent of total payroll jobs—a share which lies below the national average of 5.6 percent.
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The upshot of these differences is that a falloff in construction activity can be expected to be felt more keenly in those regions whose work forces are more concentrated in home building. At least this is true if construction activity declines are proportionate across regions. And if the rate of decline in construction activity were more rapid in regions outside of the Midwest, this would additionally contribute to some favorable convergence toward the Midwest pace of economic activity. By some reports, speculative home buying activity had been running very hot in many coastal states in recent years.
Data trends also indicate that the pace of recent declines in Seventh District home building activity have been on par with the U.S. Constructed square feet of residences from the McGraw-Hill Construction Dodge reports currently indicate that home-building has in fact been declining about the same as the remainder of the U.S. Since January 2006, the pace of home building has averaged declines of 25 percent year-over-year on a monthly basis in the Seventh District versus 26 percent in the overall U.S. over the same time period. Similarly, the pace of housing starts in the graphs below indicates that Seventh District declines have largely paralleled the U.S. since 2006, though the U.S. level of activity had climbed to a higher peak over the decade. Accordingly, though the construction sector covers more than residential activity alone, steeper-than-average job declines reported in the table above (column 6) are consistent with greater drops in home-building activity in the top construction-job states.
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On the flip side, however, in many parts of the Midwest lagging general economic growth has tended to limit home buying and associated construction activity. In particular, Michigan’s construction employment peaked long ago during the fourth quarter of 2004 (see table above, column 4) and has fallen by 16 percent since then. So, too, housing starts (above) have fallen more steeply in Michigan versus both the U.S. and other District states.
But aside from Michigan’s woes, the pace of national construction employment growth (decline) has been converging (on average) with that of the Seventh District over the 2006-2007 period. The chart below illustrates the year-over-year pace of construction employment growth in the Seventh District versus the nation.
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This convergence cannot be attributed to home building activity alone because construction employment includes the nonresidential sector as well. As measured by jobs, residential building and construction make up 43 percent of the total. However, available data on commercial construction activity also indicates a pace of growth in the Seventh District that is roughly coincident with that of the nation. Consequently, the fact that the Midwest economy has a lesser share of total jobs devoted to new housing construction is likely contributing in some small measure to convergence of District employment growth with the nation’s.
To be sure, this convergence of construction employment will not spare Midwest households from financial loss and dislocation associated with a slowing national economy. As economist Leslie McGranahan demonstrates in a recent analysis, local economic conditions are one of the primary determinants of home foreclosure in addition to a state’s foreclosure procedures and the degree of subprime and FHA borrowing. Accordingly, because automotive industry structuring has been weighing heavily on the Midwest economy, home foreclosure rates in Seventh District states are now running ahead of national averages (see figure below). An expected slowing of national economic growth during the first half of 2008 will continue to pressure many Midwestern homeowners who are stretching to meet their mortgage obligations.
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Note: Emily Engel and Vanessa Haleco-Meyer assisted this blog.
As I described in my August 2006 entry, government statistics tend to significantly undercount manufacturing activity. The undercounting occurs because manufacturing companies increasingly outsource service activities that they formerly performed “inhouse,” such as accounting, payroll, design, R&D, and others. These activities are increasingly attributed to service industry sectors in the national statistics rather than to manufacturing. For the Midwest, where manufacturing plays an important part in its economy, the undercounting can seriously mislead us as we try to understand the source of our livelihood.
But, more than services are being outsourced. Susan Houseman of the Upjohn Institute and her co-authors Matthew Dey and Anne Polivka of the Bureau of Labor Statistics find that U.S. manufacturing companies have also increasingly outsourced their “blue-collar” and production roles. They do this in an indirect way; they use temporary and leased workers (usually on-site) who are technically counted as employees of “employment services agencies.” Because these workers remain technically employees of the employment services agencies, the statistical counts of the work force of the companies that use employment services appear light, and declines in employment may be illusory, merely reflecting this outsourcing.
The number and size of employment services workers in the U.S. economy has grown rapidly over the past 16 years, easily outstripping overall payroll employment growth by a factor of six. And behind this growth, worker occupations in the employment services industry have been shifting toward industrial workers at the expense of office and administrative occupations. According to a survey by the American Staffing Association, 58 percent of customers engage temporary or contract workers to fill needs in industrial occupations.
In their research, Houseman and her co-authors draw on public databases to estimate the rapidly growing use of temporary and contract workers by manufacturing companies in the United States. They find that “the number of employment services workers assigned to manufacturing grew by about 1 million, from about 419,000 in 1989 to over 1.4 million in 2000.”
How does this practice affect the size of the U.S. manufacturing work force? Per the Houseman research, the outsized growth of temporary and contract workers by manufacturing companies implies that, rather than falling as reported, manufacturing employment actually grew by 1.4 percent in the U.S. between 1989 and 2000.
In researching why manufacturing firms use temporary workers, research by Yukako Ono and Daniel Sullivan finds that growing firms tend to take on temporary workers rather than permanent employees when they expect that their output may fall in the near future. By doing so, firms are spared the high costs of firing workers when they must curtail their production.
Because of such company behaviors, temporary or contract workers tend to be first hired and fired by companies during swings in national economic activity. During the 2001 recession, for example, the Houseman research finds that job declines in the manufacturing sector tended to be sharper than reported. Similarly, post-2001, manufacturers were more likely to hire workers from employment services agencies than to hire permanent workers, thereby understating recovery in manufacturing.
The miscounting also wreaks havoc with official productivity statistics. Since many measures of productivity are constructed as “output per worker,” an increasing tendency to undercount workers employed by manufacturers tends to overstate productivity growth in the manufacturing sector in comparison to many other industry sectors.
What are the regional differences in undercounting of manufacturing? We do not know this yet. However, if Midwest manufacturing companies behave like their national counterparts with respect to outsourcing of staff, Houseman’s findings for the nation imply that employment-services workers add 8.7 percent to direct-hire employment in Midwest manufacturing.
While we do not know that Midwest manufacturers outsource from employment service firms to the same extent as the nation, we do know that the employment services industry is very prominent in the Midwest. As measured by annual revenue, the nation’s top employment services corporation, Manpower, is headquartered in Milwaukee; the number two corporation is Kelly Services near Detroit.
More broadly, the chart below tracks the growth in “employment services” employees for both the U.S. and the East North Central region since 1990. The top chart indicates that the growth in these outsourced jobs has grown equally rapidly in comparison to the nation. Indiana and Michigan, ranking number first and fourth nationally in relative manufacturing concentration in 2005, experienced especially strong growth in employment services.
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The second chart indicates that the Midwest’s concentration of employees of the employment services industry has grown in relation to the U.S. Michigan has led the way, with a concentration that is now more than one-third greater than the U.S.
In examining hiring patterns from the employment services sector, Susan Houseman and her co-researchers are on to an important avenue in assisting the nation and the regions to understand the composition of their economies.
Following unprecedented home price appreciation nationwide in recent years, homeowners are much concerned about price reversal. In their current Economic Perspectives article, Chicago Fed economists Jonas Fisher and Saad Quayyum find that, on average, much of the recent surge in housing can be attributed to fundamentals such as rising income and favorable demographics, as well as innovations in home lending markets that have allowed renters to become homeowners. (Many of these innovations—such as interest-only loans and adjustable rate mortgages—were discussed in detail at the Chicago Fed’s Bank Structure Conference this spring. The proceedings of the conference were summarized in the September issue of the Chicago Fed Letter.)
While such arguments may provide some comfort to those who worry about the possibility of a bubble in average U.S. home prices, experiences and current conditions differ widely from place to place. Should Midwestern homeowners be more or less concerned about the cooling of residential real estate markets?
Senior Business Economist Mike Munley has been tracking home price developments in the Midwest. Mike reports that, on September 5, the Office of Federal Housing Enterprise Oversight (OFHEO) released its estimates for home price appreciation in the second quarter of 2006. The report included data on the national average of home price changes as well as state averages.
Home prices for the U.S. increased at a 4.8% annual rate between the first and second quarters, the slowest quarterly appreciation since the end of 1999 and just below the average since 1980. As measured year over year, U.S. home prices were up 10% from the second quarter of 2005, which was also slower than the rate of appreciation has been—it topped out at 14% in the middle of 2005.
Recent home price appreciation here in the Midwest has also slowed noticeably, and the long term back drop has been much less robust. For the most part, home prices in the Seventh District states have been increasing more slowly than the national average of home prices (see figure 1). On a year-over-year basis, price appreciation in every District state lagged behind the national average in the second quarter of 2006, and Michigan had the lowest appreciation of any state in the nation. In comparison to the first quarter, home values in Indiana and Michigan actually declined. (Maine, Massachusetts, and Ohio were the only other states with declines.) However, home values in Iowa managed to rise slightly faster than the national average.
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The city-level data told a similar story. Of the District MSAs (Metropolitan Statistical Areas) covered by OFHEO, only Michigan City-La Porte, IN, showed year-over-year appreciation (10.6%) faster than the national average. Of the bottom 20 MSAs in the U.S., 14 were in the Seventh District, and Ann Arbor, MI, was at the bottom with home prices, down 1.3% from a year ago.
The OFHEO home price data is only one of several sources of information about home prices for the U.S. and some cities. The National Association of Realtors (NAR) releases data on the median sale price of existing single-family homes. In general, the two data series tend to tell the same story—that is, the trends in both data series are similar over time. But, their results are often different in a given month (for regional and national data) or quarter (for city data). The NAR data tends to be more volatile. The NAR data set measures exactly what it sounds like: it is the price of the typical home sold during that quarter. Still, the median price depends on the mix of homes sold during that quarter. If, for example, a large number of inexpensive, starter homes were sold in the second quarter, this would lower the median sale price. By contrast, the OFHEO index is designed to track how the value of an individual home changes over time. OFHEO looks at the appraised value of homes each time a new mortgage is taken out—it is updated when a home gets sold or when the homeowner decides to refinance. OFHEO looks at the value of a large number of homes and is able to estimate the index quarterly. One drawback to the OFHEO index is that it only looks at home mortgages serviced by Fannie Mae and Freddie Mac, and those agencies only service mortgages that are less than $417,000—so the OFHEO index excludes most luxury housing.
The NAR publishes price breakdowns for regions and select metropolitan areas (but not states). In the second quarter of 2006, median home prices nationally were up 3.7% from a year earlier, while median sales prices in the Midwest (which includes the Seventh District, Ohio, and some plains states) were down 2.0%. Of the 24 District MSAs covered by the NAR, five (Chicago, Champaign, Milwaukee, Peoria, and Waterloo, IA) beat the national average, and 14 saw home sale prices down from a year ago. Although the NAR data are more volatile, this data series does confirm that home prices in the Midwest have been increasing more slowly than prices nationally.
There are a couple of reasons why home values have been rising more slowly in the Midwest than the rest of the country. Looking over the long term, the Midwest has generally seen slower home price appreciation since the early 1980s. As shown in figure 1, home values nationally have increased an average of 5.4% per year since then, whereas average appreciation in the District states has ranged from 3.5% in Iowa to 5.1% in Illinois. In part this difference reflects the slower population growth in the Midwest than in the rest of the nation. Since 1980, the U.S. population has increased an average of 1.1% per year, while population growth in Seventh District states has averaged only 0.4%. It follows that demand for housing in the District is not growing as rapidly, which in turn puts relatively less pressure on prices.