November 14, 2013
Atlanta Fed's Jobs Calculator Drills Down to the States
In March 2012, the Federal Reserve Bank of Atlanta launched its Jobs Calculator, an application that illustrates the relationship between the unemployment rate, growth in payroll employment, the labor force participation rate, and a few other variables to boot. Most notably, it tells us how many jobs need to be created to achieve a specific unemployment rate within a given period of time. This tool has turned out to be a useful one for anchoring discussions about national employment growth and unemployment among policy makers and the media.
However, the national employment situation masks significant differences in state labor markets. For example, at the trough of the business cycle (June 2009), the national unemployment rate was 9.5 percent, but it ranged from 4.2 percent in North Dakota to 15.2 percent in Michigan. State policy makers, in managing the dynamics of their own employment situation, need to know the data on a state level.
We are pleased to announce that the Atlanta Fed recently unveiled the state-level Jobs Calculator. The same tool that has been used for national discussions is now available for state-level analyses (see the figure below).
Not only does this state tab allow a quick overview of the historical employment growth in each state (see, for example, Alabama's historical employment growth in the figure below), but it also has the same functionality as the national Jobs Calculator. (Because of the recent partial government shutdown, the data are updated only through August; state-level employment data for October will be available November 22.)
Like the national Jobs Calculator, the state-level version allows the user to input a target unemployment rate, choose the number of months desired to hit the target rate, and find out how many new jobs are required per month to get there. But the calculator is flexible enough to allow other interesting experiments as well.
Consider the case of Florida. During the recession, Florida experienced a significant decline in its population growth. It has gone from a high of about 0.2 percent growth per month (roughly 2.4 percent per year) to its current 0.115 percent growth per month (about 1.38 percent per year; see the figure below). Suppose policy makers in Florida want to know how a return to prerecession population growth might affect the number of jobs needed to maintain its current unemployment rate over the next 12 months. (Note that as of August, the unemployment rate in Florida was 7 percent.)
The calculator's default settings always answer the question, “How many jobs per month does it take to maintain today's unemployment rate over the next 12 months?” To answer our hypothetical policy makers' question, all they would have to do is enter a prerecession monthly population growth rate of 0.2 percent into Florida's state Jobs Calculator, leaving everything else the same. Given the current data in hand, we would discover that Florida would need to generate about 6,000 more jobs per month at the higher population growth than at the current—and lower—population growth to stabilize the unemployment rate at 7 percent.
The data behind the state-level Jobs Calculator come from the U.S. Census Bureau's Establishment Survey, the same data used for the national Jobs Calculator, combined with the Local Area Unemployment Statistics (LAUS) programs run by each state. The LAUS contain the regional and state employment statistics that are consistent with data from the Census Bureau's Current Population Survey. State-level population estimates are provided by the U.S. Census Bureau (and are described in more detail here). You'll note that the LAUS data, especially for very small states, look more erratic than national or larger states' numbers—the unfortunate consequence of small sample sizes.
LAUS data are generally issued about the third Friday of each month following the reference month, which means that the state-level Jobs Calculator statistics will be updated about two weeks after the national Jobs Calculator. The schedule of release dates is available from the U.S. Bureau of Labor Statistics.
By Julie Hotchkiss, a research economist and policy adviser in the Atlanta Fed's research department
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October 09, 2013
Delving into Labor Markets
Though never far from the headlines, the Federal Reserve's dual mandate comes front and center again with the announcement today of President Obama's nomination of Fed Vice Chair Janet Yellen as the next chair of the Board of Governors. Inevitably, analysis will turn to discussions of who is a hawk and who is a dove, who cares relatively more about inflation, and who cares relatively more about growth and employment.
That's unfortunate, because such characterizations really do miss the point. The debate among different policymakers is not about whether person A is more concerned about jobs and unemployment than person B, but about legitimate and longstanding conversations about what accounts for the performance of labor markets and what role monetary policy might have in the event that performance is judged to be subpar.
As it happens, the Atlanta Fed's most recent contribution to this discussion came last week in the form of the annual employment conference sponsored by the Bank's Center for Human Capital Studies. Organized, as in past years, by Richard Rogerson (Princeton University), Robert Shimer (University of Chicago), and Melinda Pitts (Federal Reserve Bank of Atlanta), the conference explored the causes of the continued weak labor market recovery in the United States. The existing literature has suggested a number of possibilities: wage rigidities, mismatch between workers' skills and the skills required by new jobs, extended unemployment insurance benefits and other government policy changes, and firms' reorganizing and asking workers to do more. The papers sought to analyze and document the importance of these factors for the slow recovery.
One notable policy change in the recent recession was the unprecedented expansion of unemployment insurance (UI) benefits to as long as 99 weeks for a very large fraction of UI-eligible workers. Did this increase play an important role in high levels of unemployment? Two papers from the conference addressed this question from different perspectives. "Do Extended Unemployment Benefits Lengthen Unemployment Spells? Evidence from Recent Cycles in the U.S. Labor Market," by Henry S. Farber and Robert G. Valetta, assessed the extent to which extended UI benefits result in higher unemployment because workers choose to remain unemployed longer. They find a statistically significant effect of longer UI durations on the duration of unemployment spells, but they conclude that the overall contribution to the unemployment rate was less than half a percentage point. Because the aggregate unemployment rate rose by more than 5 percent, this effect accounts for less than 10 percent of the overall increase.
"Unemployment Benefits and Unemployment in the Great Recession: The Role of Macro Effects," by Marcus Hagedorn, Fatih Karahan, Iourii Manovskii, and Kurt Mitman, offered a different perspective. The authors look at the evolution of unemployment rates in counties that are adjacent but lie in different states. They use the fact that the timing of extended benefits occurs at different times across states to identify the effect of extended UI durations on country-level unemployment. They find that the effects are sufficiently large that the increase in UI duration can account for virtually all of the increase in unemployment.
While seemingly at odds, the results of these two studies are consistent. The first paper shows that the decrease in the job-finding rate for workers with relatively longer benefits did not increase that much compared with the rate for workers with shorter-duration benefits, holding the overall unemployment rate constant. The second paper argues that the job-finding rate decreases for everyone when benefits are extended. The authors find that when some workers have access to longer-duration UI benefits, being unemployed is not as painful for them, which puts upward pressure on wages. To the extent that firms cannot target their job openings toward workers without access to UI, firms may be less likely to create jobs, making it harder for all workers to get job offers. The impact on uninsured workers may be as large as the impact on insured workers, and so the microeconomic estimates in Farber and Valetta will not necessarily uncover UI's total impact on the unemployment rate.
The possible role of wage rigidities has figured prominently in many accounts of the large increase in unemployment during the recent recession. Two papers considered the importance of this explanation. "Wage Adjustment in the Great Recession," by Michael Elsby, Donggyun Shin and Gary Solon, used microdata from the U.S. Census Bureau's Current Population Survey to examine the extent to which wages are sticky. The paper finds that there has been less response in average real wages during the recent recession than in previous recessions, perhaps suggesting that real wage rigidity contributed to the large increase in unemployment. However, they also show that wages at the individual level are really quite flexible. Specifically, relatively few individuals have zero nominal wage growth from one year to the next, and many people experience decreases in nominal wage rates.
A key issue in the theoretical literature is the extent to which wage stickiness affects new hires versus existing workers. In "How Sticky Wages in Existing Jobs Can Affect Hiring," authors Mark Bils, Yongsung Chang and Sun-Bin Kim show that even if wages for new hires are completely flexible, they may nonetheless have large effects on unemployment fluctuations when one allows for an "effort decision" for existing workers. This decision means that in response to negative shocks, firms require existing workers to expend more effort given that their wage is fixed, decreasing the need to hire new workers. The authors show that this effect is quantitatively significant and can come close to resolving the unemployment volatility puzzle, which relates to the large fluctuations in unemployment relative to productivity.
An empirical regularity that has appeared in the last few years is an outward shift in the Beveridge curve, which relates the unemployment rate to the level of vacancies. One interpretation of this upward shift is that the matching of unemployed workers and vacancies has worsened. Yet there is a lot of variety in the job-search effort by workers with different characteristics, such as the length of unemployment, whether they are on temporary layoff, and so on. In "Measuring Matching Efficiency with Heterogeneous Jobseekers," Robert Hall and Sam Schulhofer-Wohl devise a method for incorporating this heterogeneity into the analysis and show that there has indeed been a decrease in the matching rate for workers during the last few years. It will be important for future research to determine how much this decrease reflects a decline in search intensity or whether the lower job-finding rates represent a decrease for a given level of search intensity.
Related to the two issues of nominal rigidities and mismatch, in the paper "Labor Mobility within Currency Unions," Emmanuel Farhi and Ivan Werning study the role of labor mobility in diminishing the effects associated with nominal rigidities. For example, some researchers have suggested that a key difference between the apparent success of the United States relative to the euro zone is U.S. labor is more mobile. Farhi and Werning argue that one should not assume the mobility necessarily reduces the effects of nominal rigidities. In particular, they conclude that mobility eases the effects of nominal rigidities only if goods markets are well integrated.
Two papers focused on the nature of worker mobility across firms in the recent recession. In "Worker Flows over the Business Cycle: The Role of Firm Quality," Lisa Kahn and Erika McEntarfer examine recent changes in flows of workers between firms that offer jobs of differing quality. They find that that lower-quality firms decreased both hiring and separations by large and equal amounts, whereas high-quality firms have much smaller declines in both hiring and separations. The net result is that the fraction of workers in lower-quality jobs tends to increase during recessions.
In closely related work, "Did the Job Ladder Fail after the Great Recession?" by Giuseppi Moscarini and Fabien Postel-Vinay, uses data from the U.S. Bureau of Labor Statistics' Job Openings and Labor Turnover Survey (JOLTS) to study the hiring and separation patterns across firms of different sizes. They determine that the pattern of firm growth across size classes was different during this recession than in previous recessions. In particular, they find that following the Lehman Brothers collapse, smaller firms actually fared worse than larger firms, perhaps because financing constraints had more severe consequences for smaller firms.
As the provisions in the Affordable Care Act (ACA) take effect in the coming months, there may be large effects not only on the market for health care but also on the labor market. In particular, the ACA will implicitly introduce taxes and subsidies that will differ across firms and workers of different types. In "Effects of the Affordable Care Act on the Amount and Composition of Labor Market Activity," Trevor Gallen and Casey Mulligan develop a framework to think about how these provisions will influence labor market outcomes across different sectors and worker types, and they use a calibrated version of the model to quantify the effects. The authors predict that the ACA will substantially reduce the return to market work for low-skilled individuals and that a large number of individuals who currently receive health insurance through their employers will end up purchasing insurance through the exchanges established as part of the ACA.
The conference also featured a presentation by Ed Lazear, "The New Normal? Productivity and Employment during the Recession and Recovery." The talk highlighted three themes from Lazear's recent research. First, productivity did not decline in the recent recession—as it typically had done in previous recessions—perhaps reflecting that workers expend more effort during periods of high unemployment since they fear unemployment more in a weak labor market. Second, the unemployment rate is a less useful indicator of the overall state of the labor market during the current recovery (in recent years the decline in the unemployment rate has not been accompanied by an increase in the employment-to-population ratio, since labor force participation has declined). The third theme is that the deterioration in labor market outcomes during the recent recession should be interpreted as cyclical rather than structural and, hence, a labor market recovery is likely once GDP growth is stronger.
We certainly wouldn't claim that the conference put to rest any of the relevant questions that will confront the Federal Open Market Committee and its new chair going forward. But we do believe that continuing to support the dissemination of the type of research presented at this conference gives us a fighting chance.
By Richard Rogerson of Princeton University and Robert Shimer of the University of Chicago, both advisers to the Atlanta Fed's Center for Human Capital Studies, and Melinda Pitts, director of the Atlanta Fed's Center for Human Capital Studies
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September 23, 2013
The Dynamics of Economic Dynamism
Earlier today, Atlanta Fed President Dennis Lockhart gave a speech at the Creative Leadership Summit of the Louise Blouin Foundation. He posed the questions: Is the economic dynamism of the United States declining? Is America losing its economic mojo? He observed:
“... we see a picture in which fewer firms are expanding, and each expanding firm is adding fewer new jobs on average than in the past. Fewer firms are shrinking, and each is downsizing by less on average. Fewer people are being laid off or are quitting their job, and firms are hiring fewer people. In other words, the employment dynamics of the U.S. economy are slower.
The decline in job creation and destruction was also the theme of this recent macroblog post by Mark Curtis, which featured some pretty nifty dynamic charts of trends in job creation and destruction by industry and geography.
Identifying the policy implications of these slower dynamics requires careful diagnosis of the causal factors underlying the trends. The cutting edge of economic research looking at this issue was featured at the 2013 Comparative Analysis of Enterprise Data Conference hosted last week by the Atlanta Census Research Data Center (ACRDC), which is housed at the Atlanta Fed and directed by one of our senior research economists, Julie Hotchkiss. Through the ACRDC, qualified researchers in Atlanta and around the Southeast can perform statistical analyses on non-public Census microdata.
The agenda and papers presented at the conference are located here. Some of the papers, I think, were particularly relevant to what President Lockhart discussed. A few examples:
“Reallocation in the Great Recession: Cleansing or Not?” by Lucia Foster and Cheryl Grim of the Center for Economic Studies at the U.S. Census Bureau and John Haltiwanger at the University of Maryland looked at the so-called “cleansing hypothesis,” in which recessions are not only periods of outsized job creation and destruction, but they are also periods in which the reallocation is especially productivity enhancing. They find that while previous recessions fit this pattern reasonably well, they do not see this kind of activity in the most recent recession. In fact, they find that in the manufacturing sector, the intensity of reallocation fell rather than rose (because of the especially sharp decline in job creation), and the reallocation that did occur was less productivity enhancing than in prior recessions.
“How Firms Respond to Business Cycles: The Role of Firm Age and Firm Size,” by Javier Miranda, Teresa Fort, John Haltiwanger and Ron Jarmin, looked at the varying impact of recessions on firms by size and age. They show that young businesses (which are typically small) exhibit very different cyclical dynamics than small/older businesses and are more sensitive to the cycle than larger/older businesses. The paper also explores explanations for the finding that young/small businesses were hit especially hard during the last recession. They identify the collapse in housing prices as a primary culprit, with the decline in job creation at young firms especially pronounced in states with a large drop in housing prices.
As a side note, although not presented at the conference, “The Secular Decline in Business Dynamism in the U.S.,” a new paper by Ryan Decker, John Haltiwanger, Ron Jarmin and Javier Miranda, analyzes the overall secular decline in job reallocation across industries. They find that changes in industry composition (the decline in manufacturing and rise of service industries) are not driving the decline. Instead, the primary driver seems to be the decline in the pace of entrepreneurship and the accompanying decline in the share of young firms in the economy.
Finally, Steve Davis, from the University of Chicago, talked about his joint research with John Haltiwanger, Kyle Handley, Ron Jarmin, Josh Lerner and Javier Miranda on private equity in employment dynamics, Private equity critics claim that leveraged buyouts bring huge job losses. Davis shows that private-equity buyouts are followed by a decline in net employment at these firms relative to controls (similar firms that were not targets of a buyout). However, that net change pales compared with the amount of gross job creation and destruction that typically occurs within the target firm after the buyout. In particular, he finds that in addition to reducing employment at its existing establishments, including by selling some establishments to other firms, jobs are created at new establishments within the firm via acquisition and the opening of new establishments. Moreover, they show that this reallocation is generally productivity enhancing for the firm. Although the data used in the study go only through the mid-2000s, it seems reasonable to infer from the findings that the decline in private equity deals during and since the last recession has contributed to the overall lower level of employment dynamics in this recovery.
The Comparative Analysis of Enterprise Date Conference was an excellent representation of the type of high-quality research being conducted on questions that go to the heart of the cyclical-versus-structural debate about the future course of the U.S. economy. While this is an exciting and important time for researchers in this field, it is troubling to learn that the programs that collect the data used in these types of studies are being trimmed because of federal budget cuts.
By John Robertson, vice president and senior economist in the Atlanta Fed’s research department
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September 17, 2013
The ABCs of LFPR
As the Federal Open Market Committee (FOMC) meets amid much speculation about the next steps for monetary policy, it does so in in the context of an August 2013 Employment Situation report that was generally viewed as a mixed bag. The employment numbers undershot the consensus among most market observers, while the unemployment rate edged down again. But even the drop in the unemployment rate—a cumulative 0.8 percentage point over the past 12 months—failed to impress everyone. Martin Feldstein, for instance:
The official unemployment rate has declined sharply (to 7.3% last month from 10% in October 2009) only because so many people have stopped looking for work or are working part-time.
Part of what Professor Feldstein is referring to, of course, is the labor force participation rate (LFPR), which measures the share of the adult population that is in the labor force. LFPR includes those who are employed and those who are unemployed but looking for a job, but not those who are unemployed and are not looking for a job (which includes retirees and discouraged workers).
We generally refrain from direct commentary about issues related to monetary policy in the time surrounding FOMC meetings. I won't break with that tradition but am more than happy to highlight a resource that can help you draw your own conclusions about all things having to do with the labor market, including the LFPR.
Our Center for Human Capital Studies' Federal Reserve Human Capital Compendium is a collection of Federal Reserve System research published on topics related to employment, unemployment, and workforce development. Our latest update offers several entries that address the LFPR and its implications for the labor market. Two recent additions:
Will a Surge in Labor Force Participation Impede Unemployment Rate Improvement? Researchers at the Richmond Fed concluded that, in the short run, the LFPR and the unemployment rate are negatively correlated. This conclusion is derived from the fact that unemployed participants in the labor force are more likely to leave the labor force than those who are employed. Also, movement from unemployed non-participant to employed participant (basically skipping the unemployed-participant phase) is more likely in an improving labor market. They concluded that movements in the LFPR lag six months behind movements in the unemployment rate.
Cyclical versus Secular: Decomposing the Recent Decline in U.S. Labor Force Participation. Researchers at the Federal Reserve Bank of Boston found that since 2008, the decline in the LFPR largely reflects demographic effects of an aging population. Furthermore, the cyclical response of the LFPR during the latest recession and recovery period has been smaller than expected, so the unemployment rate would have been three-quarters of a percent lower if the LFPR had followed historical norms. They conclude that going forward, the unemployment rate should give an accurate read on labor market conditions and that further cyclical declines in the LFPR are unlikely if the labor market continues to improve.
But much more information on the LFPR and other topics including wages and earnings, outsourcing, and productivity is available. If you're looking for something to do while you await the FOMC's decision, one option is building a little human capital of your own with our Human Capital Compendium.
By Whitney Mancuso, a senior economic analyst in the Atlanta Fed's research department
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September 13, 2013
Job Reallocation over Time: Decomposing the Decline
One of the primary ways an economy expands is by quickly reallocating resources to the places where they are most productive. If new and productive firms are able to quickly grow and unproductive firms can quickly shrink, then the economy as a whole will experience faster growth and the many benefits (such as lower unemployment and higher wages) that are associated with that growth. Certain individuals may experience unemployment spells from this reallocation, but economists, starting with Joseph Schumpeter, have found that reallocation is associated with economic growth and wage growth, particularly for young workers.
Recently, a number of prominent economists such as John Haltiwanger have expressed concern that falling reallocation rates in the United States are a major contributor to the slow economic recovery. One simple way to quantify the speed of reallocation is to examine the job creation rate—defined as the number of new jobs in expanding firms divided by the total number of jobs in the economy—and the destruction rate, defined likewise but using the number of jobs lost by contracting firms. Chart 1 plots both the creation and the destruction rates of the U.S. economy starting in 1977. These measures track each other closely with creation rates exceeding destruction rates during periods of economic growth and vice versa during recessions. The most recent recession saw a particularly sharp decline in job creation (you can highlight the creation rate by clicking on the line), but it is clear this decline is part of a larger trend that far predates the current period. A decline in these rates could indicate less innovation or less labor market flexibility, both of which are likely to retard economic growth. Feel free to explore the measures for yourself using the figure’s interactivity.
To better understand these important trends we create a common variable called reallocation, which is defined as total jobs created plus total jobs destroyed, divided by total jobs in the economy. This formula creates one measure that describes how quickly jobs are moving from shrinking firms to expanding firms. Using data from the U.S. Census Bureau’s Business Dynamic Statistics, we examine differences in this variable across sectors and across states. Furthermore, using some basic data visualization tools, we can see how reallocation has evolved over time across these dimensions.
Chart 2 plots reallocation rates by industry from 1977 to 2011. The plot highlights the reallocation rate for all industries, but you can also select or deselect any industry to more clearly view how it has changed over time. Scrolling over the lines allows you to view the exact rates by industry in any time period. A few interesting patterns emerge. First, sectors have different levels of job reallocation in the cross section. Manufacturing stands out as having particularly low reallocation rates, probably the result of the large fixed-cost capital requirements required in production. Second, not all industries experienced sharp declines during this period. If you highlight the finance, insurance, and real estate sector, it is evident that reallocation rates actually increased for this sector until the most recent recession. Retail and construction, on the other hand, have experienced steady and significant declines during the past 35 years.
Chart 3 maps reallocation rates across states for the year 1977. This figure provides us with a cross sectional view of geographical differences in reallocation rates. States with the highest reallocation rates are dark brown, and states with the lowest rates are light brown. You can click through the years to visually capture how these rates have changed overtime for each state. Compare the color of the map in 1977 with the color in 2011. Scroll the mouse over any state to view that state’s reallocation rate in the particular year.
As with industries, states display clear cross sectional differences in their reallocation rates. The highest rates are found in western states, Florida, and Texas, and the lowest are in the Midwest. Scrolling through the years shows that the decline in reallocation rates is common to the entire country.
Overall, these figures display a stark trend. The economy is reallocating jobs at much slower rates than 20 or even 10 years ago, and this decline is, with only a few exceptions, common across states and industries. Economists are just now starting to explore the causes of this trend, and a single, compelling explanation has yet to emerge. But some explanation is clearly in order and clearly important for economic policymakers, monetary and otherwise.
By Mark Curtis, a visiting scholar in the Atlanta Fed's research department
Please note that the charts and maps in this post were updated and improved on November 27, 2013.
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August 16, 2013
GDP, Jobs, and Growth Accounting
The latest on productivity, from the Associated Press via USA Today:
U.S. worker productivity accelerated to a still-modest 0.9% annual pace between April and June after dropping the previous quarter.
The second-quarter gain...reversed a decline in the January-March quarter, when the Labor Department's revised numbers show productivity shrank at a 1.7% annual pace.
Labor costs rose at a 1.4% annual pace from April through June, reversing a revised 4.2% drop the previous quarter.
Productivity measures output per hour of work. Weak productivity suggests that companies may have to hire because they can't squeeze more work from their existing employees....
Productivity growth has been weaker recently, rising 1.5% in 2012 and 0.5% in 2011.
Annual productivity growth averaged 3.2% in 2009 and 3.3% in 2010. In records dating back to 1947, it's been about 2%.
Though not quite in the category of spectacular—and coming off revisions that if anything made things look weaker than previously thought—last quarter's uptick is a welcome development. Earlier this week, in a speech to the Atlanta Kiwanis club, Atlanta Fed President Dennis Lockhart laid out several scenarios with materially different implications for how the GDP and employment picture might play out over the next several years:
As a matter of arithmetic, healthy employment growth coupled with tepid GDP growth implies weak labor productivity growth. And in fact, productivity growth in recent quarters has been significantly below historical norms.
[I] believe that the recent low growth of productivity is probably just a temporary downdraft after the rather strong productivity growth when the economy emerged from recession.
If productivity growth rebounds to more typical levels, the coincidence of job gains at a pace of around 190,000 per month in recent months and GDP growth below 2 percent cannot persist. Again, it's a matter of arithmetic. Either GDP growth will rise to levels consistent with recent employment growth, or employment growth will fall to levels more consistent with the weak GDP data we've been witnessing.
I've got a working assumption on this question, and it is captured in the Atlanta Fed's baseline forecast for the second half of this year and 2014. This outlook calls for a pickup in real GDP growth over the balance of 2013, with a further step-up in economic activity as we move into 2014.
You can get a sense of this outlook by considering the output of one particular model that we use here at the Atlanta Fed. The model, which is purely statistical, gives us a view into how productivity, GDP, employment, and the unemployment rate might move together (along with other labor market variables like labor force participation and average hours worked). Here is the bottom line of an exercise that assumes GDP growth through 2015 comes in at about the central tendency of the projections from the Federal Reserve's June 2013 Summary of Economic Projections.
For this exercise, we have adjusted the 2013 growth forecast down slightly due to the weaker-than-expected growth in the first half of the year. Additionally, we have plugged in assumptions for productivity growth—1.5 percent per quarter (SAAR), the average gain over the past eight years—and nonfarm business output growth. We then let the model forecast the remaining variables, all of which are for the labor market:
The model forecasts employment gains in the neighborhood of what the economy has been generating over the past several years, and a steadily declining unemployment rate.
Now consider two "stall" scenarios in which GDP growth fails to get beyond 2.3 percent. The first of these scenarios is the one noted in the Lockhart Kiwanis speech, with productivity recovering but job growth falling off the pace:
From a policy perspective, this one may not cause too much handwringing about the appropriate course of action. The weak GDP growth is accompanied by a failure to make the type of progress on the unemployment rate that the FOMC has clearly articulated as the necessary condition for adjustments in policy rates:
[T]he Committee decided to keep the target range for the federal funds rate at 0 to 1/4 percent and currently anticipates that this exceptionally low range for the federal funds rate will be appropriate at least as long as the unemployment rate remains above 6-1/2 percent, inflation between one and two years ahead is projected to be no more than a half percentage point above the Committee's 2 percent longer-run goal, and longer-term inflation expectations continue to be well anchored.
Absent unforeseen issues with inflation, staying the course would seem to be in order.
But there is a second stall scenario in which productivity and GDP growth remain tepid, even as labor market indicators improve:
The difference in this experiment is that the expectations of those that President Lockhart referred to in his speech as the "innovation pessimists" are correct. Recent weakness in productivity growth reflects a fall in trend productivity growth. In this case, essentially identical labor market outcomes would nonetheless correspond to an economy that can't seem to hit "escape" velocity.
If it is clear that this configuration of outcomes is associated with a structural break in productivity growth, an argument against monetary policy stimulus would have some weight. After all, in most cases we don't expect the tools of monetary policy to fix structural efficiency problems.
But, alas, such clarity rarely arrives in real time. The experiments above give some sense of how difficult it can be to discover the right branch to follow on the policy decision tree.
By Dave Altig, executive vice president and research director of the Atlanta Fed
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August 09, 2013
Myth and Reality: The Low-Wage Job Machine
In the wake of the July employment report released last week, an interesting graphic appeared in a Wall Street Journal article with the somewhat distressing title "Low Pay Clouds Job Growth." The graphic juxtaposed average wages by sector (as of July 2013) with changes in the numbers of jobs created by sector (from July 2011 through July 2013). I've reproduced that chart below, with a few enhancements:
For the 17 sectors, the red circles represent the five sectors with the lowest average wage as of July. The green circles represent the five sectors with the highest average wages, and the blue circles represent those with average wages between the high and low groups. The size of each of the circles in the chart represents the share of employment in that sector during the July 2011 to July 2013 period.
The clear implication of the article is that things are even worse than you think:
Employers added a seasonally adjusted 162,000 jobs in July, the fewest since March, the Labor Department said Friday, and hiring was also weaker in May and June than initially reported. Moreover, more than half the job gains were in the restaurant and retail sectors, both of which pay well under $20 an hour on average.
That situation may indeed be something worth worrying about, but if so it is nothing new. The following chart shows the percentages of job gains sorted by low-wage, middle-wage, and high-wage sectors for each of the U.S. expansion periods dating back to 1970:
I've dated the current recovery from March 2010: the month that employment gains turned positive. It should also be noted that the cross-recovery comparisons are not quite apples-to-apples given changes in the way sectoral employment is reported by the U.S. Bureau of Labor Statistics. (There are only 11 sectors, for example, in the recovery periods prior to 1991.)
But I don't think this materially alters the basic picture: The lowest-wage sectors have consistently produced 40 percent to 50 percent of the job gains in recent recoveries. Though the percentage was slightly higher in July, it was not materially so. And this recovery does not look at all unusual when taken as a whole.
What is more striking—at least relative to the earlier recoveries in the chart—is the growing disparity between the average wages across sectors, as this animation clearly illustrates:
Importantly, the animation also clearly illustrates that the growing wage disparity is a trend, not a unique feature of the postcrisis period. There are lots of interesting things being written about the reasons for this trend, and it is a vitally important topic. But I'm pretty sure the answers to the important policy questions lie well beyond the current business cycle.
By Dave Altig, executive vice president and research director of the Atlanta Fed
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August 02, 2013
What a Difference a Month Makes? Maybe Not Much
By most accounts, the July employment report released this morning was something of a disappointment, perhaps more because it fell short of expectations than for any absolute signal it sends about the state of the economy. To be sure, the 162,000 net jobs created in July were below June’s 12-month average, which itself ticked down a bit as a result of negative revisions to the May and June statistics.
“Ticked down a bit” is the operative phrase, as the average monthly jobs gain from May 2012 through June 2013 now registers at 189,000 as opposed to the 191,000 reported last month. With this month’s new data, the 12-month average gains (from June 2012 to July 2013) clock in at 190,000 jobs per month, still right on the trend that has prevailed over the past couple of years. In other words, not much has changed in the longer view of things.
Our interests here at macroblog run to the policy implications, of course. Not too surprisingly, focal points are 1) the 7 percent unemployment rate neighborhood that Chairman Bernanke has associated with Federal Open Market Committee forecasts of what will prevail around the time that the Fed’s current asset purchase program might be ending and 2) the benchmark 6 1/2 percent unemployment that the statement following this week’s FOMC meeting continued to identify as the earliest possible point at which adjustments to the Committee’s interest rate target will be considered.
Following last month’s employment report I offered up calculations from the Atlanta Fed’s Jobs Calculator™ regarding the dates at which these unemployment thresholds might be reached, under the assumptions that jobs gains average 191,000 per month going forward, the participation rate remains constant at the reported June level, and there will be no change in the relationship between employment statistics from the payroll (or establishment) survey (whence comes the headline jobs number) and the employment statistics from the household survey (statistics used to calculate the unemployment rate). All of these figures change month to month, so it may be useful to update that exercise with current statistics (with last month’s calculations noted parenthetically):
Not much change there. In fact, the unemployment rates in these calculations fall a little faster than last month’s calculations suggested, in part due to the ancillary assumptions on participation rates and the payroll-employment /household-employment ratio.
In the spirit of pessimism—an economist’s university-given right—I’ll ask: what if the latest 162,000-job-gain number is closer than the trailing 12-month average to what we will experience going forward? Easiest enough to explore:
I will leave it to you to decide whether the differences imply important policy distinctions.
Side note: For a broader look at labor market conditions, take a look at the Atlanta Fed’s spider chart, updated as of today’s employment report.
By Dave Altig, executive vice president and research director of the Atlanta Fed
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July 05, 2013
A Quick Independence Day Weekend, Post-Employment Report Update
From what I gather, a lot of people took notice of this statement, from Chairman Bernanke’s June 19 press conference:
If the incoming data are broadly consistent with this forecast, the Committee currently anticipates that it would be appropriate to moderate the monthly pace of purchases later this year. And if the subsequent data remain broadly aligned with our current expectations for the economy, we would continue to reduce the pace of purchases in measured steps through the first half of next year, ending purchases around midyear. In this scenario, when asset purchases ultimately come to an end, the unemployment rate would likely be in the vicinity of 7 percent, with solid economic growth supporting further job gains, a substantial improvement from the 8.1 percent unemployment rate that prevailed when the Committee announced this program.
That 7 percent assessment to which the Chairman was referring comes, of course, from the outlook summarized in the Summary of Economic Projections, published following the June 18–19 meeting of the Federal Open Market Committee.
Here are the unemployment forecasts specifically:
The highlighted numbers represent the “central tendency” projections for the average fourth quarter unemployment rate in 2013, 2014, and 2015 (in blue) and the “longer run” (in green). Naturally enough, getting to a 6.5 percent to 6.8 percent unemployment rate in the fourth quarter of 2014 is pretty likely to imply the unemployment rate crossing 7 percent sometime around roughly the middle of next year.
So, how do things look after the June employment report? As is our wont, we turn to our Jobs Calculator to answer such questions, and come up with the following. If the U.S. economy creates 191,000 jobs per month (the average for the past 12 months), and the labor force participation rate stays at 63.5 percent (its June level), and all the other important assumptions (such as the ratio of establishment survey to household survey employment) remain the same, then the economy’s schedule looks like this:
Note also the implication of this statement...
[T]he Committee decided to keep the target range for the federal funds rate at 0 to 1/4 percent and currently anticipates that this exceptionally low range for the federal funds rate will be appropriate at least as long as the unemployment rate remains above 6-1/2 percent , inflation between one and two years ahead is projected to be no more than a half percentage point above the Committee's 2 percent longer-run goal, and longer-term inflation expectations continue to be well anchored.
...which certainly aids in understanding this information, from the last Summary of Economic Projections:
I will leave it to the principals to articulate whether today’s report materially changes anything contained in last month’s projections. In the meantime, enjoy your weekend.
By Dave Altig, executive vice president and research director of the Atlanta Fed
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June 10, 2013
Casting a Web over Jobs Data
Writing in the Wall Street Journal prior to the U.S. Bureau of Labor Statistics' Friday release of the May employment data, Ed Lazear (Stanford professor and former chair of George W. Bush's Council of Economic Advisers) made a plea for an expansive interpretation of labor market conditions:
...when Friday's jobs report is released, the unemployment rate and the number of new jobs will come in for close scrutiny. Then again, they always attract the most attention. Even the Federal Reserve focuses on the unemployment rate...
Yet the unemployment rate is not the best guide to the strength of the labor market, particularly during this recession and recovery. Instead, the Fed and the rest of us should be watching the employment rate. There are two reasons.
First, the better measure of a strong labor market is the proportion of the population that is working, not the proportion that isn't…
Second...There is another highly relevant measure that captures what is going on in the economy. "U6" counts those marginally attached to the workforce—including the unemployed who dropped out of the labor market and are not actively seeking work because they are discouraged, as well as those working part time because they cannot find full-time work...
The striking deficiency in jobs is borne out by the Bureau of Labor Statistics' Job Openings and Labor Turnover Survey. Despite declining unemployment rates, the number of hires during the most recent month (March 2013) is almost the same as it was in January 2009, the worst month for job losses during the entire recession (4.2 million then, 4.3 million now).
Faithful readers of macroblog will recognize that, contrary to the narrow focus that Professor Lazear suggests preoccupies the Federal Reserve, one of the Fed's consistent themes has been to cast our intellectual nets over a broad swath of labor market indicators. In fact, one of our favorite blog topics over the past six months has been the construction of "spider charts" to visualize the status of the labor market beyond what can be gleaned from simply looking at the standard unemployment and employment statistics.
Internally, these spider charts have become one of our primary tools for evaluating the status of the labor market. Because we have also found this tool to be an effective means of communicating the overall labor market picture, we are pleased to announce that the labor market spider chart has been added to our portfolio of labor market tools available on the Atlanta Fed's Center for Human Capital Studies' web pages (a portfolio that includes the Jobs Calculator and the Human Capital Compendium, which is a repository of human capital-related products from throughout the Federal Reserve System). The spider chart is presented both in simple levels that were first introduced in macroblog on January 13, 2013, as well as in rates, which were discussed in macroblog last April.
As we have mentioned before, the spider chart contains four groups of labor market indicators:
- Employer behavior includes indicators related to the hiring activities of employers.
- Confidence includes indicators of employer and worker confidence in the labor market.
- Utilization includes measures related to available labor resources.
- Leading indicators shows data that typically provide insight into the future direction of overall labor market activity.
The inner circle of the chart represents the labor market conditions that existed when the unemployment rate peaked in the fourth quarter of 2009. The outer circle represents the labor market conditions that existed just before the recession began.
A section on the website titled Indicators explains the details behind each of the variables included in the groups noted above, and another section, Surveys, details the data sources. A Frequently Asked Questions section offers details on the construction of the indicators and the reference points, as well as the rationale for this approach and answers to other questions that have arisen.
The spider chart allows one to chart the progress on all these dimensions using the most recent three months of data, compared to that level (or rate) for the same time period over the last three years, while the reference points remain fixed. So one could have a spider chart that shows just the data for the three-month period ending in May 2013, or a chart that encompasses the data for May 2013, May 2012, and May 2011.
The increase in the unemployment rate in last Friday's jobs report, amid an otherwise strong report that included a 175,000 increase in payroll employment, supports this strategy of using a variety of indicators to monitor labor market conditions rather than to simply focus on the unemployment rate. The increase in the labor force participation rate this month worked to drive up the unemployment rate, but by all other accounts this was a solid report. In fact, all seven of the indicators from the employment situation report release increased from the April readings in both the "levels" and "rates" spider charts.
Our current focus is still on the recovery of the labor market, and as long as this is the case, we will use the information in these charts to help us determine if the labor market has achieved substantial improvement. When the labor market has turned a corner into expansion, we will reevaluate our tools and determine a more appropriate way to monitor the labor market. But, for now, rest assured that our policy deliberations are not stuck in a single-indicator rut.
By M. Melinda Pitts, director, Center for Human Capital Studies, and
Patrick Higgins, senior economist, both in the Atlanta Fed's research department
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