June 30, 2010
Keeping an eye on Europe
In June, a third of the economists in the Blue Chip panel of economic forecasters indicated that they had lowered their growth forecast over the next 18 months as a consequence of Europe's debt crisis. When pushed a little further, 31 percent said that weaker exports would be the channel through which this problem would hinder growth, while 69 percent thought that "tighter financial conditions" would be the channel through which debt problems in Europe could hit U.S. shores.
Tighter financial conditions also were mentioned by the Federal Open Market Committee in its last statement, where the committee noted, "Financial conditions have become less supportive of economic growth on balance, largely reflecting developments abroad."
In his speech today, Atlanta Fed President Dennis Lockhart identified the European sovereign debt crisis as one of the sources of uncertainty for the U.S. economy that he believes "have clouded the outlook." President Lockhart explicitly expressed his concern that Europe's "continuing and possibly escalating financial market pressures will be transmitted through interconnected banking and capital markets to our economy."
Negative effects from the European sovereign debt crisis can be transmitted to the U.S. economy through a number of financial channels, including higher risk premiums on private securities, a considerable rise in uncertainty, and sharply increased risk aversion. Another important channel is the direct exposure of the U.S. banking sector—both through holdings of troubled European assets and counterparty exposure to European banks, which not only have a substantial exposure to the debt-laden European countries but have also been facing higher funding costs. The LIBOR-OIS spread has widened notably (see the chart below), liquidity is now concentrated in tenors of one week and shorter, and the market has become notably tiered.
Banks in the most affected countries (Greece, Portugal, Ireland, Spain, and Italy) and other European banks perceived as having a sizeable exposure to those countries have to pay higher rates and borrow at shorter tenors. Although for now U.S. banks can raise funds more cheaply than many European financial institutions, some analysts believe that there's a risk that the short-term offshore dollar market may become increasingly strained, leading to funding shortages and, conceivably, forced asset sales.
Bank for International Settlements data through the end of December of last year show that the U.S. banking system's risk exposure to the most vulnerable EU countries appears to be manageable. U.S. banks' on-balance sheet financial claims vis-á-vis those countries, adjusted for guarantees and collateral, look substantial in absolute terms but are rather small relative to the size of U.S. banks' total financial assets (see the chart below). The exposure to Spain is the biggest, closely followed by Ireland and Italy. Overall, the five countries account for less than 2 percent of U.S. banks' assets.
U.S. exposure to developed Europe as a whole, however, is much higher at $1.2 trillion, so U.S. financial institutions may feel some pain if the European economy slows down markedly. How likely is a marked slowdown? It's difficult to determine, of course, but when asked about the largest risks facing the U.S. economy over the next year, the Blue Chip forecasters put "spillover effects of Europe's debt crisis" at the top of their list.
By Galina Alexeenko, economic policy analyst at the Atlanta Fed
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June 25, 2010
Increasing hours worked versus increasing hiring
The current recovery has been characterized by increasing production and sales without an associated expansion in employment. Part of the explanation for the lack of hiring has to do with increased productivity of workers (output per hour worked)—either by improved production methods or simply requiring more effort from staff per hour worked. Another reason why firms have been relatively slow to hire is that, in addition to slashing payrolls during the recession, many firms also cut the work hours of the remaining staff to levels well below prerecessionary norms. As a result, these firms have some scope to increase the hours worked by their current staff before hiring additional workers. This fact is evident in the often-cited increase during the recession in the number of people working part time for economic reasons (see here and here, for example). That number has remained relatively stable at around nine million people over the last year, but it is still more than twice its prerecessionary average.
Another perspective on the part-time issue can be gleaned from data on average work week obtained from the U.S. Bureau of Labor Statistics (BLS) Current Population Survey. Chart 1 shows the pattern of average weekly hours (not seasonally adjusted) for all nonfarm wage and salary workers during the period of January 2008 through May 2010. For ease of comparison, the chart is scaled to be relative to the 2002–07 average. Compared with prerecession levels, average hours worked declined during the recession although they really didn't begin falling until the second half of 2008. As of May 2010, average hours worked were still about 1.5 percent below the prerecession average but have been trending higher in recent months. (Note that the sharp drop in September 2009 is a quirk of Labor Day falling during the survey week and hence cutting the work week one day shorter than usual.) The fact that average hours worked has moved higher is an encouraging sign for employment growth going forward if the historical norm is any guide. Of course, a firm may need to hire new workers even when hours per worker are below average. For example, the decision to start an additional manufacturing production line will probably require hiring new staff even if existing staff on other lines are working fewer hours than usual.
The aggregate picture in Chart 1 masks considerable variation across industries. For example, Chart 2 shows the normalized average weekly hours reported by workers in the education and health services industries and in the financial industry. For these workers, although average hours worked per week declined mildly during the second half of 2009 weekly hours worked have since returned to prerecessionary levels. This performance suggests that, other things equal, additional demand for hours of work in these industries is likely to be met by additional hiring.
Chart 3 shows the evolution of average weekly hours reported by workers in the manufacturing and transportation/warehouse industries. In these industries, average hours worked began to decline in the fall of 2008, but they have recovered much of the decline in recent months and are now about 1 percent below their prerecession averages. As with the aggregate picture, the fact that average hours worked has been trending higher recently is encouraging news for future employment growth in these industries.
In contrast, Chart 4 shows the pattern of average hours reported by workers in the construction industry, the wholesale and retail trade industry, and the leisure and hospitality industry. For these workers, average weekly hours started to decline in the fall of 2008 and have shown no clear signs of recovery—still sitting some 3 percent to 4 percent below their prerecession averages and not trending higher. Thus, there appears to be more scope for firms in these industries to increase hours without necessarily having to hire additional workers.
This analysis does have some caveats. For one thing, it is based on worker-reported data about hours worked drawn from the BLS's Current Population Survey. An alternative would be the employer-reported measurements in the BLS's Establishment Survey.
Probably more importantly, this analysis uses the prerecession history as a guide to what is "normal." If, for example, firms decide to keep average weekly hours lower by increasing the use of part-time workers, then the fact that average hours are below prerecession levels does not imply that firms won't hire when demand increases. Some industries already make heavy use of part-time employment. For example, in May 2010 the reported average weekly hours by workers in the leisure and hospitality industry was 33.3 hours compared to 42 hours in manufacturing. Absent an offsetting increase in wage rates, a permanent shift toward increased part-time employment would lower a worker's income relative to full-time employment and probably result in an increased propensity for multiple job-holding by individuals and households.
By Amy Ellingson, economic analyst at the Atlanta Fed
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June 18, 2010
Another look at consumer sentiment and consumer spending
In the most recent economic forecasting survey by the Wall Street Journal, 23 percent of the surveyed economists said consumers spending more readily than anticipated is the biggest upside risk of their growth forecast for the second half of the year. So anything that can shed light on future spending habits is of particular interest. Two of the most commonly cited measures of consumer attitudes are the Conference Board's Consumer Confidence Index and the Thomson Reuters/University of Michigan's Index of Consumer Sentiment. A key question is, do these indicators improve consumption forecasts?
Previously, economic researchers have looked at the predictive power of these indexes for consumer spending, and they generally found that the ability of consumer confidence measures to predict consumer spending largely disappeared once some other measures of economic conditions were taken into account. One such example is a study by Sydney Ludvigson, which examined the forecasting record of these confidence measures through 2002 (for other examples, see here and here). Much has happened since then, of course, and a simple inspection of the two series reveals that both confidence measures fell fairly steadily starting in August 2007 until reaching near-record lows by June 2008. Therefore, a look at the more recent predictive track record of these indicators seems warranted.
For this examination, we conducted an out-of-sample forecasting experiment using a pair of statistical models (technically, Bayesian vector autoregression models). The first model predicts real personal consumption expenditures as a function of its own past values and past values of other variables such as real measures of stock market prices and disposable personal income. The second model includes all of these variables augmented by the two measures of consumer attitudes. At each point in time we use only the data that would have been available to forecast real consumption data anywhere from one to 12 months out. (For example, in the middle of February 2009, consumption data would have been available through December 2008 while some of the other variables would have been available through January or February 2009. The experiment is not "real time" in the sense that we use the latest vintage of data, which include revisions to the historical data that would not have been available to forecasters at the time.) Forecasts of consumption are made for the 1990–2003 period and then again for the period from 2004 to the present. The root mean squared forecast error is used to gauge the accuracy of the forecasts, with smaller numbers corresponding to smaller misses on average. As the accompanying chart shows, adding the two measures of consumer attitudes improves the forecast much more in the post-2003 sample than in the earlier period.
We experimented with some variations in specifications of the model, and we were unable to overturn the general finding that adding attitude measures to the model resulted in an improvement in forecasts in recent years. We found this fact intriguing and somewhat surprising.
A recent paper by Barsky and Solon argues that the Index of Consumer Sentiment reflects the public's awareness of economic conditions. In fact, the survey used to construct this index asks respondents about recent news they have heard related to changes in economic conditions. From August 2007 to June 2008, news of "unfavorable higher prices" was frequently mentioned in the survey. A study by James Hamilton showed that part of the deterioration in the Index of Consumer Sentiment during this period could be explained by rising energy prices. However, adding a measure of oil prices to our model did not overturn the basic finding of improved consumption spending forecasts in models that included measures of consumer attitudes.
It remains an open question why these measures of consumer attitudes have become more useful in recent years. A statistical anomaly, greater or more accessible news coverage of the economy, and a generally more aware public are all possibilities. If it is just luck, then time will eventually overturn the result. But if these consumer attitude indicators have become a more useful summary of a wide variety of developments in the economy, then their forecasting power will persist. Time and further research will help sort this out.
By Patrick Higgins, an economist at the Atlanta Fed
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June 11, 2010
Another view of the structural versus cyclical unemployment question
One of the key functions of labor markets is matching firms looking for workers who have particular attributes (or skills) with individuals looking for work who have those attributes. What economists have been worrying a lot about recently is the potential for a substantive mismatch between the skills of those looking for work and the skills that firms want. This type of labor reallocation friction is one of many potential structural problems affecting the U.S. labor market at present (see, for example, here, here, and here).
A 2003 New York Fed article by economists Erica Groshen and Simon Potter examined the issue of structural rigidities in labor markets during the recovery from the 2001 recession. Their idea was to identify the share of employment in industries that had either continued to lose or gain jobs on net after the recession versus the share of employment in industries that had responded cyclically (gaining jobs after having lost them during the recession or losing jobs after gaining them during the recession) to the recession. The New York Fed researchers used industry of employment as a proxy for industry-specific skills, though it's not a perfect measure. For example, the skills of construction workers are generally different from the skills of health care workers. The more often that employment is accounted for by industries that are continuing to gain or lose employees, the more the potential exists for skill mismatch going forward.
Using the first 12 months of the recovery as a basis, Groshen and Potter found that in the 1974–75 recession and the recessions of the early 1980s the share of employment in industries continuing recession employment trends was around 50 percent. That share increased to 57 percent for the 1990–91 recession and rose sharply to 79 percent for the 2001 recession. The researchers took these findings as evidence of structural change playing a more significant role in influencing the labor market recovery from the 2001 recession than earlier recessions saw.
Visually, this observation can be presented as a four-quadrant "bubble chart" that measures job growth during the recession on the horizontal axis and job growth in the first 12 months of recovery on the vertical axis (the size of the each bubble reflects the relative employment size of the industry). We replicated Groshen and Potter's work with minor data definitional changes and find that for the first 12 months of recovery from the 2001 recession 81 percent of employment was in industries continuing recession employment trends (the top right and bottom left quadrants in the chart).
Using the same approach as Groshen and Potter, how does the 2001 recession compare with the most recent recession? To make that determination, we used data available from the 11 months of recovery coming out of the most recent recession (assuming the recession ended in June 2009). We calculate that 65 percent of employment is in industries either still losing or gaining jobs. This share is less dramatic than the 2001 experience but a bit more than the 1990–91 experience.
The positioning of certain industries within the four quadrants is not too surprising given the nature of the most recent recession. For instance, construction and related industries are deep in the continued job-loss quadrant. In contrast, the temporary help sector has behaved procyclically. Jobs in federal government and health care have continued to grow, with the former boosted by temporary hiring of census workers. Of the 79 industries examined, about a third of them have landed in a different quadrant compared with the 2001 recession.
Of particular interest is the share of employment in industries that are continuing to lose jobs. For unemployed workers from those industries, there is less prospect of being reemployed in that industry and hence a greater chance that skill mismatch will be an issue for those workers. Interestingly, the share of employment in industries experiencing continued net losses is similar to that seen during the 2001 recession (45 percent versus 41 percent).
This most recent recession was especially deep, and the large share of unemployed workers reporting they were permanently separated from their employers suggests that many of those jobs in all likelihood will not come back. If new jobs come with different skill requirements, then skill mismatch could become a significant factor once labor demand increases. However, the relatively disappointing May private-sector payroll jobs numbers released last Friday and the improving but low level of job openings reported in the JOLTS data for April are reminders that weak labor demand is still the dominant factor inhibiting the overall employment recovery.
By Menbere Shiferaw, senior economic research analyst, and John Robertson, vice president and senior economist, both in the Atlanta Fed's research department
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June 03, 2010
The recovery: Job rich or job poor?
Gross domestic product (GDP) is growing, supported by strong labor productivity numbers and modest employment growth. Even after today's downward revision to first quarter labor productivity measures, growth in labor productivity in the business sector has averaged 5.6 percent over the last three quarters—more than twice the long-run average. Okun's law has underpredicted the rise in unemployment, and some commentators call for a jobless recovery. Today, Federal Reserve Bank of Atlanta President Dennis Lockhart gave a speech on the prospects for the future of employment and labor productivity that posed the question:
"… how long can firms ride this productivity growth before having to yield to new hiring to support greater activity?"
To provide some context, below is a chart that shows a decomposition of GDP growth during post-WWII recessions. This decomposition does not explain growth, but it does show the relative contribution of various factors such as average labor productivity, average hours worked, the unemployment rate, and other labor market variables.
Note: The decomposition is based on the identity.
Where Y is GDP, H is total hours worked from nonfarm payrolls, E* is employment from the nonfarm payroll survey, E is employment based on the household survey, L is labor force, and N is working age population.
As this chart shows, relatively high labor productivity growth during a recession is not a phenomenon isolated to the 2007–09 and 2001 recessions (for present purposes, the end of the most recent recession is identified with the trough in GDP in the second quarter of 2009). All recessions from WWII through 1970 also featured sizable growth in labor productivity. Notice also that these recessions experienced large declines in the employment rate (rise in the unemployment rate). Hence, the productivity gains were attributable to outsized reductions in hours rather than gains in output. The same also holds true of the 2007–09 recession. As President Lockhart noted:
"Many employers reacted to the downturn by aggressively cutting their workforces, reorganizing remaining workers, and cutting other costs."
Of course, the big question centers on the recovery. Specifically, does the outsized contribution from labor productivity during the last recession portend continued outsized gains (and hence subdued employment prospects) during the recovery and expansion as well?
Perhaps history can provide a guide. The next chart provides the same GDP decomposition, but this time for the first three quarters of the recovery (we chose three quarters to allow a common comparison across recoveries). This chart reflects at least two salient features. First, the fastest way to employment growth is faster GDP growth—recessions that are immediately followed by very strong GDP growth also tend to have strong employment growth. Second, productivity remains an important contributor to growth, and that contribution has been especially large during the early phases of the past three recessions.
President Lockhart's interpretation of these observations is that many employers:
"… have reacted to the upswing by holding employment at or near recession levels, seeking efficiencies in supply chains, investing in labor-saving automation, and generally tweaking their business models to operate more efficiently than before the recession. We've heard this story frequently in anecdotal accounts of our directors and business contacts across the Southeast.
"As long as efficiency and productivity gains can be achieved in this way, employers may remain hesitant to hire."
Going forward, President Lockhart concludes that:
"I do not expect the recent outsized productivity growth to continue indefinitely and become a new, permanently higher trend rate. Some degree of 'wait and see' behavior is at work and is no doubt reflected in the productivity numbers. With growing economic momentum, deferral of hiring will become riskier.
"Some employment gains should result as labor productivity levels out and falls back over time to something resembling the historic trend rate. But the pace of hiring is likely to be gradual. Current data on the use of part-time workers suggest that businesses have some scope to increase hours without hiring new full-time employees. And there are other, more structural obstacles to the rapid reemployment of the jobless. Some jobs in the construction sector and certain manufacturing industries are likely permanently lost, requiring some amount of migration of workers to other sectors. And, for a time, skill and geographic mismatches may frustrate employers willing to hire.
"Also, the weight of uncertainty about the future business environment makes a gradual pace of employment progress a reasonable assumption. I hear often from members of the business community that uncertainty regarding federal, state and local fiscal fundamentals and regulatory rules-of-the-game are feeding reticence to pull the trigger on new ventures, new hires and new investments. The recent European sovereign debt and banking pressures have added to uncertainty in financial markets.
"Sizing all this up, I expect recovery in the medium term to be neither jobless nor job rich."
The current Blue Chip consensus for second quarter GDP is about a 3.2 percent annual rate. Payroll employment expanded by an estimated 290,000 in April, and with an employment report out Friday that will likely feature very sizable gains (some forecasts calling for an addition of more than 500,000 jobs), the relative contribution of labor productivity to GDP growth in the second quarter is almost certain to decline sharply. However, most of the surge in May's number will be temporary U.S. Census workers, and this increase will reverse itself in pretty short order. Hence, it will probably take awhile to see how President Lockhart's forecast of continued modest employment growth pans out.
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