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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.
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.
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
November 10, 2014
Wage Growth of Part-Time versus Full-Time Workers: Evidence from the CPS
Last week, our Atlanta Fed colleagues Lei Fang and Pedro Silos highlighted the wage growth trends of full-time and part-time workers in recent years. Using data from the U.S. Census Bureau's Survey of Income and Program Participation (SIPP), they showed relatively weak growth in hourly wages of part-time workers between 2011 and 2013. The Current Population Survey (CPS)—administered jointly by the Census Bureau and the U.S. Bureau of Labor Statistics—also contains wage information and has data through September 2014. We thought it would be interesting to see if the CPS data revealed a similar post-recession pattern, and if the more recent data show any sign of improvement. The short answer is that they do.
The following chart displays the median year-over-year growth in hourly earnings of wage and salary earners (shown as quarterly averages). The wage data are constructed using a similar methodology to that outlined in this paper by our San Francisco Fed colleagues Mary Daly and Bart Hobijn. The orange line is the median year-over-year growth in the hourly wages of all workers. The green line is the median wage growth of workers who worked full-time in both the current month and 12 months earlier (it is close to the orange line because most workers work full-time hours). The blue line is the median wage growth of workers who were part-time in both periods. Note that the median part-time wage growth is less precisely estimated (and thus demonstrates relatively more quarter-to-quarter variation) than its full-time counterpart because the CPS's sample size of wages for part-time workers is much smaller than for full-time workers.
Despite the noisy nature of the part-time wage data, it seems clear that the median wage growth of people usually working part-time fell dramatically behind that of full-time workers between 2011 and 2013. This finding is consistent with that of Fang and Silos. Interestingly, the other period when median part-time wage growth slipped behind was during the sluggish labor market recovery following the 2001 recession, albeit much less dramatically than the recent episode.
The SIPP data used by Fang and Silos ended in mid-2013. The more recent CPS data suggest that overall wage growth has picked up during the last year and that the wage growth gap has closed a bit, which are encouraging findings. But the wage growth of part-time workers, as a group, continues to lag well behind that of full-time workers. The relatively low wage growth of part-time workers heightens the importance of the fact that the number of people working part-time—especially involuntarily part-time—remains elevated.
- And the Winner Is...Full-Time Jobs!
- For Middle-Skill Occupations, Where Have All the Workers Gone?
- A Closer Look at Employment and Social Insurance
- Wage Growth of Part-Time versus Full-Time Workers: Evidence from the CPS
- Wage Growth of Part-Time versus Full-Time Workers: Evidence from the SIPP
- Data Dependence and Liftoff in the Federal Funds Rate
- What's behind Declining Labor Force Participation? Test Your Hypothesis with Our New Data Tool
- On Bogs and Dots
- The Changing State of States' Economies
- What Kind of Job for Part-Time Pat?
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