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April 02, 2015
What Seems to Be Holding Back Labor Productivity Growth, and Why It Matters
The Atlanta Fed recently released its online Annual Report. In his video introduction to the report, President Dennis Lockhart explained that the economic growth we have experienced in recent years has been driven much more by growth in hours worked (primarily due to employment growth) than by growth in the output produced per hour worked (so-called average labor productivity). For example, over the past three years, business sector output growth averaged close to 3 percent a year. Labor productivity growth accounted for only about 0.75 percentage point of these output gains. The rest was due primarily to growth in employment.
The recent performance of labor productivity stands in stark contrast to historical experience. Business sector labor productivity growth averaged 1.4 percent over the past 10 years. This is well below the labor productivity gains of 3 percent a year experienced during the information technology productivity boom from the mid-1990s through the mid-2000s.
John Fernald and collaborators at the San Francisco Fed have decomposed labor productivity growth into some economically relevant components. The decomposition can be used to provide some insight into why labor productivity growth has been so low recently. The four factors in the decomposition are:
- Changes in the composition of the workforce (labor quality), weighted by labor's share of income
- Changes in the amount and type of capital per hour that workers have to use (capital deepening), weighted by capital's share of income
- Changes in the cyclical intensity of utilization of labor and capital resources (utilization)
- Everything else—all the drivers of labor productivity growth that are not embodied in the other factors. This component is often called total factor productivity.
The chart below displays the decomposition of labor productivity for various time periods. The bar at the far right is for the last three years (the next bar is for the past 10 years). The colored segments in each bar sum to average annual labor productivity growth for each time period.
Taken at face value, the chart suggests that a primary reason for the sluggish average labor productivity growth we have seen over the past three years is that capital spending growth has not kept up with growth in hours worked—a reduction in capital deepening. Declining capital deepening is highly unusual.
Do we think this sluggishness will persist? No. In our medium-term outlook, we at the Atlanta Fed expect that factors that have held down labor productivity growth (particularly relatively weak capital spending) will dissipate as confidence in the economy improves further and firms increase the pace of investment spending, including on various types of equipment and intellectual capital. We currently anticipate that the trend in business sector labor productivity growth will improve to a level of about 2 percent a year, midway between the current pace and the pace experienced during the 1995–2004 period of strong productivity gains. That is, we are not productivity pessimists. Time will tell, of course.
Clearly, this optimistic labor productivity outlook is not without risk. For one thing, we have been somewhat surprised that labor productivity has remained so low for so long during the economic recovery. Moreover, the first quarter data don't suggest that a turning point has occurred. Gross domestic product (GDP) in the first quarter is likely to come in on the weak side (the latest GDPNow tracking estimate here is currently signaling essentially no GDP growth in the first quarter), whereas employment growth is likely to be quite robust (for example, the ADP employment report suggested solid employment gains). As a result, we anticipate another weak reading for labor productivity in the first quarter. We are not taking this as refutation of our medium-term outlook.
Continued weakness in labor productivity would raise many important questions about the outlook for both economic growth and wage and price inflation. For example, our forecast of stronger productivity gains also implies a similarly sized pickup in hourly wage growth. To see this, note that unit labor cost (the wage bill per unit of output) is thought to be an important factor in business pricing decisions. The following chart shows a decomposition of average growth in business sector unit labor costs into the part due to nominal hourly wage growth and the part offset by labor productivity growth:
The 1975–84 period experienced high unit labor costs because labor productivity growth didn't keep up with wage growth. In contrast, the relatively low and stable average unit labor cost growth we have experienced since the 1980s has been due to wage growth largely offset by gains in labor productivity. Our forecast of stronger labor productivity growth implies faster wage growth as well. That said, a rise in wage growth absent a pickup in labor productivity growth poses an upside risk to our inflation outlook.
Of course, the data on productivity and its components are estimates. It is possible that the data are not accurately reflecting reality in real time. For example, colleagues at the Board of Governors suggest that measurement issues associated with the price of high-tech equipment may be causing business investment to be somewhat understated. That is, capital deepening may not be as weak as the current data indicate. In a follow-up blog to this one, my Atlanta Fed colleague Patrick Higgins will explore the possibility that the weak labor productivity we have recently experienced is likely to be revised away with subsequent revisions to GDP and hours data.
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March 06, 2015
Signs of Improvement in Prime-Age Labor Force Participation
This morning's job report provided further evidence of a stabilizing labor force participation (LFP) rate. After falling over 3 percentage points since 2008, LFP has been close to 62.9 percent of the population for the past seven months. Although demographics and behavioral trends explain much of the overall decline (our web page on LFP dynamics gives a full account), there is a cyclical component at work as well. In particular, the labor force attachment of "prime-age" (25 to 54 year olds) individuals to the labor force is something we're watching closely. Federal Reserve Bank of Atlanta President Dennis Lockhart noted as much in a February 6 speech:
Over the last few years, there has been a worrisome outflow of prime-age workers—especially men—from the labor force. I believe some of these people will be enticed back into formal work arrangements if the economy improves further.
There are signs that some of the prime-age individuals who had retreated to the margins of the labor market have been flowing back into the formal labor market.For one thing, LFP among prime-age individuals stopped declining 16 months ago for women and nine months ago for men. By our estimates, declining LFP in this age category accounts for about one-third of the overall decline in LFP since 2007, so 25- to 54-year-olds' decision to engage in the labor market has a big effect on the overall rate (see the chart). Even with an improving economy, however, a turnaround in LFP among prime-age individuals might not occur.
The reason an improving economy might not reverse the LFP trends is that LFP for both prime-age men and women had been on a longer-term downward trend even before the recession began, suggesting that factors other than the recession-induced decline in labor demand have been important. But the decline in the "shadow labor force"—the share of the prime-age population who say they want a job but are not technically counted as unemployed—demonstrates the cyclical nature of the labor market. For the last year and half, the share of these individuals in the labor force has been generally declining (see the chart).
Moreover, the job-finding success of the shadow labor force has improved. Although the 12-month flow into the official labor force has remained reasonably close to 50 percent, the likelihood of flowing into unemployment (as opposed to employment) rose during the recession. But during the past two years, that trend appears to be reversing (see the chart).
The ability of the prime-age shadow labor force to find work is improving at the same time that the LFP rate of the prime-age population is stabilizing. Taken together, this trend is consistent with improving job market opportunities and further absorption of the nation's slack labor resources.For a more complete analysis of long-term behavioral and demographic effects on LFP for the prime-age and non-prime-age populations, see our Labor Force Participation Dynamics web page, which now includes 2014 data.
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February 26, 2015
Are Shifts in Industry Composition Holding Back Wage Growth?
The last payroll employment report from the U.S. Bureau of Labor Statistics (BLS) included some relatively good news on wages. Private average hourly earnings rose an estimated 12 cents in January, the largest increase since June 2007. Even so, earnings were up only 2.2 percent over the last year versus average growth of 3.4 percent in 2007.
What accounts for the sluggish growth in average earnings? The average hourly earnings data for all workers is essentially the sum of the average earnings per hour within an industry weighted by that industry's share of employment. In this piece, Ed Lazear argues that a shift of the U.S. economy away from some high-paying industries to lower-paying industries may have contributed to dampened wage growth. Lazear specifically calls out the reduced share of employment in the relatively high-paying finance industry, at hospitals, and in the information sector as potential culprits. A shift in employment away from relatively high-wage jobs will put downward pressure on the growth in average wages.
To get some idea of the effect of industry composition on wages, I took the 2014 calendar year average wage for each industry group at the two-digit NAICS level and multiplied it by the share of employment in that industry in 2014 (admittedly, two-digit NAICS level of disaggregation is very coarse and masks a lot of potential shifts in job-types within industries). Summing across the industries gives an estimate of total average private hourly earnings in 2014. I then repeated the exercise, but using the 2007 industry shares of employment instead (see the chart).
Would average wages have been higher if we had the same mix of employment across industries as we had before the recession? The answer seems to be yes, but not much higher. If nothing had changed in the economy's industry employment mix since 2007, then average wages would have been about 12 cents higher.
This translates into a 16.8 percent increase in nominal wages between 2007 and 2014 versus a 16.2 percent increase if the actual industry employment shares where used, because the decline in the shares of employment in the relatively high paying industries Lazear cites has not been very large, and some higher-paying industries have seen growth. Moreover, some industries with below-average wages, such as retail trade, have experienced a decline in their share of employment as well.
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February 17, 2015
What's (Not) Up with Wage Growth?
In recent months, there's been plenty of discussion of the surprisingly sluggish growth in hourly wages. It certainly has the attention of our boss, Atlanta Fed President Dennis Lockhart, who in a speech on February 6 noted that
The behavior of wages and prices, in contrast, remains less encouraging, and, frankly, somewhat puzzling in light of recent growth and jobs numbers.
So what's up—or not up—with wage growth? Using samples of matched worker-level wage data from the U.S. Bureau of Labor Statistics' Current Population Survey, chart 1 plots the annual time series of median 12-month growth rates in per-hour wages. Like most wage growth measures, this chart indicates that wage growth has been gradually increasing since the end of the recession, but growth remains quite a bit lower than before the recession began. Prior to the recession, the median growth rate of wages was around 4 percent a year. This growth rate declined to 1.7 percent in 2010 (as the incidence of wage freezes become much more prevalent, as shown in this research) and increased to 2.5 percent in 2014. For comparison, the chart also shows the annual growth in the Employment Cost Index's measure of wages. The trends in the two measures are broadly similar.
A previous macroblog post discussed details about the method of constructing the median wage growth data.
It's well known that wage growth varies across job characteristics such as occupation, industry, and hours worked as well as across worker characteristics such as education and age. For example, younger workers tend to experience higher hourly wage growth than older workers (even though their hourly wage tends to be lower), and part-time workers tend to have lower wage growth than full-time workers. We thought it might be interesting to look at wage growth for various job and worker characteristics. Are there any bright spots where the median growth in wages has approached prerecession levels?
The answer seems to be no, at least not for the set of characteristics we examined.
The following charts plot the annual time series of the median 12-month growth rate in the wages of workers with a given characteristic (occupation, age, etc.). Chart 2 depicts workers across three broad occupation groups: general-services jobs, production-oriented occupations discussed in our last macroblog post, and a category encompassing managerial, professional, and technical occupations (labeled “professional” in the chart).
Chart 3 shows the median year-over-year wage growth of workers employed in goods-producing versus service-producing industries.
Chart 4 shows the median growth in the wages of individuals working full-time versus those working part-time.
Chart 5 shows the median wage growth of workers with less than an associate degree and those with at least an associate degree.
Chart 6 shows the median growth in the wages of individuals between 16 and 35 years of age, those 36 to 55 years of age, and those over 55 years of age.
We can sum up our findings by saying that median wage growth is higher for some characteristics than others, and the recent trend in wage growth is generally positive across characteristics. But none of the characteristic-specific median growth rates we looked at are close to returning to prerecession levels. Lower-than-normal wage growth appears to be a very widespread feature of the labor market since the end of the recession.
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February 12, 2015
Are We Becoming a Part-Time Economy?
Compared with 2007, the U.S. labor market now has about 2.5 million more people working part-time and about 2.2 million fewer people working full-time. In this sense, U.S. businesses are more reliant on part-time workers now than in the past.
But that doesn't necessarily imply we are moving toward a permanently higher share of the workforce engaged in part-time employment. As our colleague Julie Hotchkiss pointed out, almost all jobs created on net from 2010 to 2014 have been full-time. As a result, from 2009 to 2014, the part-time share of employment has declined from 21 percent to 19 percent and is about halfway back to its prerecession level.
But the decline in part-time utilization is not uniform across industries and occupations. In particular, the decline is much slower for occupations that tend to have an above-average share of people working part-time. This portion of the workforce includes general-service jobs such as food preparation, office and administrative support, janitorial services, personal care services, and sales.
The following chart compares the share of part-time employment for these general-service occupations with the share for production-type occupations (such as machine operators, fabricators, construction workers, and truck drivers).
The above chart suggests that if you talk to retailers or restaurateurs, they will say that they always relied pretty heavily on part-time workers. Their utilization increased during the recession, and it really hasn't changed much since then. But manufacturers or construction firms are more likely to say that part-time work is not that common, and although they did increase their utilization of part-time workers during the recession by quite a lot, things have been gradually returning to normal.
Why is the part-time share of employment declining more slowly in general-service occupations? The economy has been generating full-time general-service jobs at a much slower pace than in the past. Of the approximately 7.6 million full-time jobs created between 2010 and 2014, only about 17 percent have been in general-service occupations, versus about 32 percent of the 7.8 million full-time jobs created between 2003 and 2007. At the current rate of full-time job creation in general-service occupations, it would take more than 10 years for the part-time share of employment in general-service occupations to return to its prerecession average.
From the workers' perspective, a relevant question is whether these part-time utilization rates are desirable. Some people work part-time and do not currently want or are not available for full-time work (so-called part-time for noneconomic reasons, PTNER). Others are available and want full-time work but are working part-time because of slack business conditions or the unavailability of full-time jobs (so-called part-time for economic reasons, PTER). The following chart shows the share of employment in the general-service and production occupation groupings that is PTER and PTNER.
The chart indicates that most of the movement in the part-time share of employment is coming from people who want full-time work. In both cases, the share of involuntary part-time employment rose during the recession, but for general-service occupations it has been more persistent than for production jobs.
Why has the demand for full-time workers in general-service occupations been more subdued than for other jobs? As the following chart shows, wage growth for these occupations has been quite weak in the past few years, suggesting that employers have not been experiencing much tightness in the supply of workers to fill vacancies for these occupations. Presumably, then, the firms generally find it acceptable to have a greater share of part-time workers than in the past.
The overall share of the workforce employed in part-time jobs is declining and is likely to continue to decline. But the decline is not uniform across industries and occupations. Working part-time has become much more likely in general-service occupations than in the past—and a greater share of those workers are not happy about it.
By John Robertson, vice president and senior economist, and
Ellie Terry, an economic policy analysis specialist, both of the Atlanta Fed's research department
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December 23, 2014
Chances of Finding Full-Time Employment Have Improved
Today's sharp upward revision to the third-quarter GDP reading reinforces the view that the underlying strength of the U.S. economy has been sufficient to support more rapid improvement in the labor market. Last week we noted the solid and broad-based recent improvement in the involuntary part-time work (part-time for economic reasons or PTER) situation over the last year, noting significant declines in the stock of PTER workers across industrial sectors and occupational categories.
In this post we look at labor market improvement over the last year in terms of worker flows. Because the Current Population Survey is set up as a rotating panel, many of the people in the survey in any given month were in the survey a year earlier as well. This allows us to ask the question: if you were an unemployed prime-age individual (25–54 years old) or working PTER one year ago, what are you doing today? Have your chances of becoming employed full-time improved? Chart 1 shows the distribution of labor market outcomes of prime-age workers who were PTER one year earlier. Chart 2 shows the distribution of outcomes for those who were unemployed one year earlier. The data are 12-month moving averages to smooth out seasonal variation.
For both PTER workers and the unemployed, the chances of becoming employed full-time are up from a year earlier (and the chances of being unemployed are down). In November 2013 there was about a 45 percent chance of someone who was PTER a year earlier having a full-time job. In November 2014 that had improved to about a 48 percent chance. This full-time employment flow rate is still much lower than the prerecession average of around 55 percent, and the improvement appears to have stalled a bit in recent months, but it is a notable improvement from a year earlier nonetheless. For PTER workers, the picture along other dimensions is more mixed. The chances of becoming unemployed appear to have returned to around prerecession levels, which is good, but the likelihood of remaining PTER is still quite elevated.
For the unemployed, there has been an even more marked improvement in the full-time finding rate over the last year. In November 2013 there was around a 32 percent chance of someone who was unemployed a year earlier having a full-time job. In November 2014 the chances improved to close to 36 percent. Moreover, the improvement in the rate of finding full-time work is responsible for the similar-sized decline in the chances of remaining unemployed. The only negative here is that the likelihood of an unemployed worker becoming PTER, while low, remains elevated compared with before the recession.
All in all, we think these developments are encouraging and add to the view that the pace of labor market improvement has picked up over the last year.
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December 19, 2014
Exploring the Increasingly Widespread Decline in Involuntary Part-Time Work
We at the Atlanta Fed have been arguing for some time that the unusually large number and share of workers employed part-time but wanting full-time work (counted in the Current Population Survey as part-time for economic reasons, or PTER) partly reflects slack in the labor market that is not reflected in the official unemployment statistics. We are in good company. Chair Yellen reiterated this view in her prepared remarks during Wednesday’s Federal Open Market Committee press conference. The good news is that the stock of PTER workers has declined by around 900,000 during the last year compared with a decline of fewer than 200,000 in 2013. Moreover, the CPS data suggest the decline is primarily because these workers have either found full-time work or are no longer wanting full-time work (that is, are working part-time for noneconomic reasons), and not because they have become unemployed or have joined the ranks of the discouraged outside of the formal labor market. Even better news is that the recent decline has been very broad based (see the charts).
Up until about a year ago, the overall decline in the number of PTER workers was driven primarily by those in middle-skill occupations in goods-producing industries and, to a lesser extent, in services-producing industries. But during 2014, the decline is also evident in services-producing industries among PTER workers in both low- and high-skill occupations—two categories that had not seen any material decline in their PTER ranks since the end of the recession. (A previous macroblog post discussed the various occupational skill categories.) There is still a ways to go, but these developments are very encouraging.
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November 24, 2014
And the Winner Is...Full-Time Jobs!
Each month, the U.S. Census Bureau for the U.S. Bureau of Labor Statistics (BLS) surveys about 60,000 households and asks people 15 years and older whether they are employed and, if so, if they are working full-time or part-time. The BLS defines full-time employment as working at least 35 hours per week. This survey, referred to as both the Current Population Survey and the Household Survey, is what produces the monthly unemployment rate, labor force participation rate, and other statistics related to activities and characteristics of the U.S. population.
For many months after the official end of the Great Recession in June 2009, the Household Survey produced less-than-happy news about the labor market. The unemployment rate didn't start to decline until October 2009, and nonfarm payroll job growth didn't emerge confidently from negative territory until October 2010. Now that the unemployment rate has fallen to 5.8 percent—much faster than most would have expected even a year ago—the attention has turned to the quality, rather than quantity, of jobs. This scrutiny is driven by a stubbornly high rate of people employed part-time "for economic reasons" (PTER). These are folks who are working part-time but would like a full-time job. Several of my colleagues here at the Atlanta Fed have looked at this phenomenon from many angles (here, here, here, here, and here).
The elevated share of PTER has left some to conclude that, yes, the economy is creating a significant number of jobs (an average of more than 228,000 nonfarm payroll jobs each month in 2014), but these are low-quality, part-time jobs. Several headlines have popped up over the past year or so claiming that "...most new jobs have been part-time since Obamacare became law," "Most 2013 job growth is in part-time work," "75 Percent Of Jobs Created This Year  Were Part-Time," "Part-time jobs account for 97% of 2013 job growth," and as recently as July of this year, "...Jobs Report Is Great for Part-time Workers, Not So Much for Full-Time."
However, a more careful look at the postrecession data illustrates that since October 2010, with the exception of four months (November 2010 and May–July 2011), the growth in the number of people employed full-time has dominated growth in the number of people employed part-time. Of the additional 8.2 million people employed since October 2010, 7.8 million (95 percent) are employed full-time (see the charts).
The pair of charts illustrates the contribution of the growth in part-time and full-time jobs to the year-over-year change in total employment between January 2000 and October 2014. By zooming in, we can see the same thing from October 2010 (when payroll job growth entered consistently positive territory) to October 2014. Job growth from one month to the next, even using seasonally adjusted data, is very volatile.
To get a better idea of the underlying stable trends in the data, it is useful to compare outcomes in the same month from one year to the next, which is the comparison that the charts make. The black line depicts the change in the number of people employed each month compared to the number employed in the same month the previous year. The green bars show the change in the number of full-time employed, and the purple bars show the change in the number of part-time employed.
During the Great Recession (until about October 2010), the growth in part-time employment clearly exceeded growth in full-time employment, which was deep in negative territory. The current high level of PTER employment is likely to reflect this extended period of time in which growth in part-time employment exceeded that of full-time employment. But in every month since August 2011, the increase in the number of full-time employed from the year before has far exceeded the increase in the number of part-time employed. This phenomenon includes all of the months of 2013, in spite of what some of the headlines above would have you believe.
So, in the post-Great Recession era, the growth in full-employment is, without a doubt, way out ahead.
Author's note: The data used in this post, which are the same data used to generate the headlines linked above, reflect either full-time or part-time employment (total hours of work at least or less than 35 per week, respectively). They do not necessarily reflect employment in a single job.
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November 20, 2014
For Middle-Skill Occupations, Where Have All the Workers Gone?
Considerable discussion in recent years has concerned the “hollowing out of the middle class.” Part of that story revolves around the loss of the types of jobs that traditionally have been the core of the U.S. economy: so-called middle-skill jobs.
These jobs, based on the methodology of David Autor, consist of office and administrative occupations; sales jobs; operators, fabricators, and laborers; and production, craft, and repair personnel (many of whom work in the manufacturing industry). In this post, we don't examine why the decline in middle-skill jobs has occurred, just how those workers have weathered the most recent recession. But our Atlanta Fed colleague Federico Mandelman offers an explanation of why this has occurred.
So how have workers in middle-skill occupations fared during the last recession and recovery? Let's examine a few facts from the Current Population Survey from the U.S. Bureau of Labor Statistics.
Only employment in middle-skill occupations remains below prerecession levels
Chart 1 shows employment levels by skill category (using 12-month moving averages to smooth out the seasonal variation). From the end of 2007 to the end of 2009, the overall number of people working declined by more than 8 million. Middle-skill jobs were hit the hardest, declining about 10 percent from 2007 to 2009. As of September 2014, the level was still about 9 percent below the 2007 level. In contrast, employment in low-skill occupations is 7 percent above prerecession levels, and employment in high-skill occupations is about 8 percent higher than before the recession.
For full-time workers (working at least 35 hours a week at all jobs) the decline in middle-skill occupations is even more dramatic. From 2007 to 2009, the number of full-time workers whose main job was a middle-skill occupation fell more than 15 percent from 2007 to 2009 and is still about 11 percent below the level at the end of 2007.
Those in middle-skilled occupations were most likely to become unemployed
In the 2001 recession, the chances of being unemployed after one year were similar for those working full-time in middle- and low-skill occupations. During the most recent recession, the likelihood of becoming unemployed rose sharply for everyone, but much more sharply for those working in middle-skill occupations. At the recession's trough, almost 6 percent of people who were employed in middle-skill occupations one year earlier were unemployed, compared with about 3 percent of workers in high-skill occupations and 3.5 percent of workers in lower-skill occupations (see chart 2).
Underemployment has improved only slowly at all skill levels
The share of people who are working part-time involuntarily about doubled for workers in low-, middle-, and high-skill occupations. For middle-skill occupations, the share rose from around 1.7 percent to 4.3 percent and is currently around 2.4 percent. For low-skill occupations, involuntary part-time employment increased from 2.4 percent to 5 percent and was still 3.8 percent as of September 2014. And for those in high-skill occupations, the chances of becoming involuntarily part-time rose from 0.8 percent to 1.8 percent and are now back to about 1 percent (see chart 3).
Ready for some good news?
Those who held middle-skill jobs are more likely to obtain high-skill jobs than before the recession
Currently, of those in middle-skill occupations who remain in a full-time job, about 83 percent are still working in a middle-skill job one year later (see chart 4). What types of jobs are the other 17 percent getting? Mostly high-skill jobs; and that transition rate has been rising. The percent going from a middle-skill job to a high-skill job is close to 13 percent: up about 1 percent relative to before the recession. The percent transitioning into low-skill positions is lower: about 3.4 percent, up about 0.3 percentage point compared to before the recession. This transition to a high-skill occupation tends to translate to an average wage increase of about 27 percent (compared to those who stayed in middle-skill jobs). In contrast, those who transition into lower-skill occupations earned an average of around 24 percent less.
In summary, the number of middle-skill jobs declined substantially during the last recession, and that decline has been persistent—especially for full-time workers. Many of the workers leaving full-time, middle-skill jobs became unemployed, and some of that decline is the result of an increase in part-time employment. But others gained full-time work in other types of occupations. In particular, they are more likely than in the past to transition to higher-skill occupations. Further, the transition rate to high-skill occupations has gradually risen and doesn't appear directly tied to the last recession.
Authors' note: The middle-skill category of jobs consists of office and administrative occupations; sales; operators, fabricators, and laborers; and production, craft, and repair personnel. The other two broad categories of occupations are labeled high-skill and low-skill. High-skill occupations consist of managers, technicians, and professionals. Low-skill occupations are defined as those involving food preparation, building and grounds cleaning, personal care and personal services, and protective services.
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November 13, 2014
A Closer Look at Employment and Social Insurance
The Atlanta Fed's Center for Human Capital Studies hosted its annual employment conference on October 2–3, 2014, organized once again by Richard Rogerson of Princeton University, Robert Shimer of the University of Chicago, and the Atlanta Fed's Melinda Pitts. This macroblog post summarizes some of the discussions.
Social insurance programs in the United States and other developed countries represent a large and growing share of expenditures relative to gross domestic product (GDP). Assessing the costs and benefits of the diverse programs that make up the U.S. social insurance system is a key input into the design and implementation of effective programs. This conference featured seven papers that dealt with various aspects of this assessment. Although each program is designed to address specific issues and hence needs to be studied in the context of those issues, many of the same basic economic questions arise in each context. For example, what is the rationale for social insurance programs? Do they address inefficiencies, or are they mainly designed to redistribute from one group to another? Who benefits from specific programs? How do programs designed to achieve specific objectives distort economic outcomes? These are the questions that featured prominently in the conference.
A classic question in economics concerns the extent to which markets cannot achieve efficient outcomes without government intervention. It is well known that the so-called "invisible hand" can achieve efficient outcomes in a wide range of standard settings, but do these results extend to situations in which information asymmetries exist? In 1976, Michael Rothschild and Joseph Stiglitz's article "Equilibrium in Competitive Insurance Markets" suggested that in the presence of certain kinds of private information, insurance markets could not achieve efficient allocations. In fact, they argued that competitive equilibrium might not even exist in these settings. In "Adverse Selection Is Not a Justification for Social Insurance," Ed Prescott challenges this result and shows that competitive equilibrium exists and achieves efficient allocations in settings that include information problems such as Rothschild and Stiglitz's adverse selection problem. Key to this result is the presence of mutual insurance companies, and how this presence influences the contracts offered by insurance companies in equilibrium. In the Rothschild and Stiglitz environment, insurance companies were effectively agents with deep pockets that were outside the model.
Providing insurance to individuals in situations in which they face bad outcomes may distort individual behavior and lead to negative outcomes that outweigh the benefits of the insurance. This basic issue was addressed by three of the papers at the conference in three separate contexts. Jason Abaluck, Jonathan Gruber, and Ashley Swanson examined how prescription drug coverage through Medicare influences prescription drug usage; Hamish Low and Luigi Pistaferri studied the disability insurance (DI) system; and Bradley Heim, Ithai Lurie, and Kosali Simon examined whether the extension of health benefits to young adults as mandated by the Affordable Care Act (ACA) influenced the behavior of young adults.
In "Prescription Drug Use Under Medicare Part D: A Linear Model of Non-linear Budget Sets," Jason Abaluck, Jonathan Gruber, and Ashley Swanson study how prescription drug use responds to price changes associated with social insurance through Medicare. At the conference, Gruber discussed one key objective of their analysis: uncovering the elasticity of prescription drug use with respect to price. A large elasticity implies that providing insurance in the form of lower prices will distort behavior and lead to much higher drug use, and some recent papers have argued that this elasticity may be quite large. Their basic strategy is to study how changes in the details of Medicare coverage over time influenced individual choices. A novel feature of the estimation strategy is to take advantage of the fact that the marginal price people face depends on their overall annual expenditure on prescriptions, so that individuals can be sorted into groups based on histories of usage, interacted with changes in the details of coverage. A first key finding of this paper is that the elasticity is relatively small. A second key set of findings concerns the extent to which individual choices (in terms of plan selection and yearly expenditure conditional on plan choice) reflect departures from rationality, such as myopia or salience. The paper finds an important role for both of these effects.
Disability insurance (DI) represents a clear and classic example of the tension between insurance provision and insurance. While one would like to provide insurance to individuals who are unable to work, it can be difficult to assess the true ability of an individual to work, thereby creating the opportunity for people who are not disabled to also collect. Luigi Pistaferri addressed this issue in the paper he coauthored with Hamish Low, "Disability Insurance and the Dynamics of the Incentive-Insurance Tradeoff." This paper builds and estimates a structural model that incorporates labor supply, health shocks, earnings shocks, and the key details of the DI application process. The authors conduct various counterfactuals and assess the tension between insurance and incentives in the context of the U.S. DI program. Several results emerge. First, making the review process less strict would enhance welfare despite worsening incentives for people to misreport their health status. This is because the current system denies too many truly disabled individuals from collecting. But decreasing generosity would also increase overall welfare by decreasing the incentives for false collection.
One of the first measures of the Affordable Care Act (ACA) to be enacted was the provision that allowed dependent individuals to remain covered by their parents' healthcare plans until the age of 26. The paper by Bradley Heim, Ithai Lurie, and Kosali Simon, "The Impact of the Affordable Care Act Young Adult Mandate: Evidence from Tax Data," aims to assess the extent to which this provision has affected outcomes for young adults in terms of employment, wages, schooling, and marriage. As Simon described it at the conference, the novel aspect of this analysis is that it tracks outcomes using administrative IRS data, which affords a large sample size. The main empirical strategy is to compare the change in outcomes from before and after the provision was enacted for individuals below the age threshold with the change in outcomes for individuals just above the age threshold. The paper also reports estimates based on triple differencing that uses information on parental health insurance status. The main message from the analysis is that one cannot find robust, statistically significant effects of this ACA provision on outcomes for young individuals. One important qualification is that despite the large sample size, standard errors are still quite large, so that the analysis cannot rule out the possibility of economically significant effects.
Naoki Aizawa and Hanming Fang also considered the effects of the ACA in their paper "Equilibrium Labor Market Search and Health Insurance Reform." However, in contrast to the above papers that focus on how a particular program feature might influence individual choices, this paper focuses on how the creation of health insurance exchanges and the individual insurance mandate would affect the overall equilibrium in the labor market, taking into account the firms' decisions on whether to offer insurance and the wages that they offer to workers. In his presentation, Fang discussed building a structural equilibrium model of the labor market and estimating it using a variety of data sets. The authors find that the ACA will reduce the uninsured rate from about 20 percent to about 7 percent. But interestingly, the paper finds that the uninsured rate would drop even further if the employer mandate were dropped from the ACA. General equilibrium responses are key to understanding this result, illustrating the importance of studying these effects.
One of the rapidly growing social insurance programs is Medicaid. Mariacristina De Nardi, Eric French, and John Bailey Jones assess the benefits of this program in their paper "Medicaid Insurance in Old Age." As French described at the conference, this paper uses a structural approach to assess the extent to which households with different income and health status benefit from Medicaid. The analysis focuses on individuals from age 70 and forward using data from the Health and Retirement Study, emphasizing the risks that individuals face as a result of health shocks. Medicaid offers partial insurance against these shocks, particularly the large expenditures associated with nursing home care, and the paper assesses the value of this insurance for individuals in different positions in the wealth distribution at age 70. The paper has two main findings. First, the insurance value of Medicaid is substantial, and decreasing the size of the program would entail large welfare costs in excess of one dollar for every dollar of reduced spending. Second, expanding the size of the program would offer significant insurance value only to wealthy households. The authors conclude that in terms of managing the risks of the elderly, the current scope of Medicaid seems appropriate.
As the above discussion emphasizes, a critical input into the design and assessment of social insurance programs are data that allow us to reliably document the outcomes and groups that the insurance program wishes to help, as well as measure the efficacy of existing programs in achieving desirable outcomes. In the paper "Welfare Programs and Survey Misreporting: Implications for Income, Poverty and Disconnectedness," Bruce Meyer and Nikolas Mittag documented the serious shortcomings of several standard publicly available data sets when it comes to measuring the resources available to the poorer segments of the population. Meyer presented the paper at the conference, and it uses administrative data from New York State that allow them to link income and transfer data, both cash and in-kind, and compare the measures obtained using these administrative data with the measures obtained using data from the Current Population Survey (CPS), which is a standard source for publicly available data on the income distribution. The results are striking. Relative to analysis based on data from the CPS, analysis using administrative data shows better outcomes in terms of inequality and disconnectedness and yield larger effects from existing programs in terms of their ability to affect these outcomes.
Full papers or presentations for most of these papers are available on the Atlanta Fed's website.
By Melinda Pitts, director of the Atlanta Fed's Center for Human Capital Studies, Richard Rogerson of Princeton University, and Robert Shimer of the University of Chicago
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