Marianna Kudlyak

In the pre-pandemic period, measures of consumer labor market perceptions correlated well with the aggregate unemployment rate. However, for more than a year during the pandemic, consumers perceived labor markets as much tighter than the high aggregate unemployment rate implied. In contrast, there is no such a departure from the historic relation if we use the jobless unemployment rate-unemployment for reasons other than temporary layoffs-as a measure of labor market tightness. Using a measure of the firm labor market perceptions from the National Federation of Independent Business, we find that during the post-pandemic period, firms perceived labor market as being tighter than what consumers perceived, given the historic relation between the two series. Furthermore, despite the vacancy-unemployment ratio was at its historic high levels during the post-pandemic period, our measure of firm perceptions signaled that the labor market was even tighter. In June-July 2024, the relations between consumer and firm perceptions and between various measures of labor market tightness are back to its pre-pandemic patterns.

We propose that the natural rate of unemployment may have an active role in the business cycle, in contrast to a widespread view that the rate is fairly smooth and at most only weakly cyclical. We demonstrate that the tendency to treat the natural rate as near-constant would explain the surprisingly low slope of the Phillips curve. We observe that evidence is weak about this basic point—the evidence neither comes close to rejecting the conventional view nor does it reject a very different view in which fluctuations in the natural rate are associated with a substantial fraction of cyclical volatility. We show that the natural rate may have closely tracked the actual rate during the long recovery that began in 2009 and ended in 2019. We explain how the common finding of research in the Phillips-curve framework of low—often extremely low—response of inflation to unemployment could be the result of fairly close tracking of the natural rate and the actual rate in recoveries. Our interpretation of the data contrasts to that of many Phillips-curve studies, that conclude that inflation has little relation to unemployment. But we also call attention to a recently growing body of research along New Keynesian lines that supports the credibility of the hypothesis of a strong relation between movements of the natural rate and actual rate of unemployment.

Existing literature documents that house prices respond to monetary policy surprises with a significant delay, taking years to reach their peak response. We present new evidence of a much faster response. We exploit information contained in listings for the residential properties for sale in the United States between 2001 and 2019 from the CoreLogic Multiple Listing Service Dataset. Using high-frequency measures of monetary policy shocks, we document that a one standard-deviation contractionary monetary policy surprise lowers housing list prices by 0.2–0.3 percent within two weeks—a magnitude on par with the effect on stock prices. House prices respond stronger to the surprises to future rates as compared to the surprise changes in the federal funds rate. Sale prices are mostly pre-determined by list prices and do not independently respond to monetary policy surprises.

Using a nationally-representative panel of consumer credit records for the US from 1999 to 2021, we document a positive correlation between child and parent homeownership. We propose a new causal mechanism behind this relationship: parents extract home equity to help finance their child’s home purchase. To identify the mechanism, we use fixed effect, event study, local projection and matching methods. We find that children whose parents extract equity: (i) are 60-80% more likely to become homeowners; (ii) have lower leverage at origination; and (iii) buy higher-valued homes and at a younger age. The effects are stronger when housing affordability is worse and children’s financial constraints are more likely to bind. Using a simple structural model, we find that in a counterfactual economy with no role for parental equity, intergenerational homeownership mobility increases.

Using a unique data set and a novel identification strategy, we estimate the effect of minimum wage increases on job vacancy postings. Using occupation-specific county-level vacancy data from the Conference Board’s Help Wanted Online for 2005-2018, we find that state-level minimum wage increases lead to substantial declines in existing and new vacancy postings in occupations with a larger share of workers who earn close to the prevailing minimum wage. We estimate that a 10 percent increase in the state-level effective minimum wage reduces vacancies by 2.4 percent in the same quarter, and the cumulative effect is as large as 4.5 percent a year later, in these occupations relative to the rest. The negative effect on vacancies is more pronounced for occupations where workers typically have lower educational attainment (high school or less) and in counties with higher poverty rates. We argue that our focus on vacancies versus on employment has a distinct advantage of highlighting a mechanism through which minimum wage hikes affect labor markets. Our finding of a negative effect on vacancies is not inconsistent with the wide range of findings in the literature about the effect of minimum wage change on employment, which is driven by changes in both hiring and separation margins.

Occupational specificity of human capital motivates an important role of occupational reallocation for the economy’s response to shocks and for the dynamics of inequality. We introduce occupational mobility, through a random choice model with dynamic value function optimization, into a multi-sector/multi-occupation Bewley-Aiyagari model with heterogeneous income risk, liquid and illiquid assets, price adjustment costs, and in which households differ by their occupation-specific skills. Labor income is a combination of endogenous occupational wages and idiosyncratic shock. Occupational reallocation and its impact on the economy depend on the transferability of workers’ skills across occupations and occupational specialization of the production function. The model matches well the statistics on income and wealth inequality, and the patterns of occupational mobility. It provides a laboratory for studying the short- and long-run effects of occupational shocks, automation and task encroaching on income and wealth inequality. We apply the model to the pandemic recession by adding an SIR block with occupation-specific infection risk and a ZLB policy and study the impact of occupational and aggregate labor supply shocks. We find that occupational mobility may tame the effect of the shocks but amplifies earnings inequality, as compared to a model without mobility.

Current unemployment, as of 2019Q4, is so low not because of unusually high job finding rates out of unemployment, but because of unusually low entry rates into unemployment. The unusually low entry rates, both from employment and from out of the labor force, reflect a long-run downward trend, and have lowered the unemployment rate trend over the recent decade. In fact, the difference between the current unemployment rate and unemployment rates at the two previous cyclical peaks in 2000 and 2007 is more than fully accounted for by the decline in its trend. This suggests that the current low unemployment rate does not indicate a labor market that is tighter than in 2000 or 2007.

We estimate trends in the labor force participation (LFP) and unemployment rates for demographic groups differentiated by age, gender, and education, using a parsimonious statistical model of age, cohort and cycle effects. Based on the group trends, we construct trends for the aggregate LFP and unemployment rate. Important drivers of the aggregate LFP rate trend are demographic factors, with increasing educational attainment being important throughout the sample and ageing of the population becoming more important since 2000, and changes of groups’ trend LFP rates, e.g. for women prior to 2000. The aggregate unemployment rate trend on the other hand is almost exclusively driven by demographic factors, with about equal contributions from an older and more educated population. Extrapolating the estimated trends using Census Bureau population forecasts and our own forecasts for educational shares, we project that over the next 10 years the trend LFP rate will decline to 61.1% from its 2018 value of 62.7%, and the trend unemployment rate will decline to 4.3% from its 2018 value of 4.7%.

We study the paths over time that individuals follow in the labor market, as revealed in the monthly Current Population Survey. Some people face much higher flow values from work than in a non-market activity; if they lose a job, they find another soon. Others have close to equal flow values and tend to circle through jobs, search, and non-market activities. And yet others have flow values for non-market activities that are higher than those in the market, and do not work. We develop a model that identifies and quantifies heterogeneity in dynamic individual behavior. Our model provides a bridge between research on monthly transition rates in the tradition of Blanchard and Diamond (1990) and research on economic dynamics in the tradition of Mortensen and Pissarides (1994). Our estimates discern 5 distinct types. Most unemployment comes from just two of those types. Low employment types frequently circle among unemployment, short-term jobs, and being out of the labor market. Short-term jobs play a role in the job-finding process related to the role of unemployment. These are stop-gap jobs for high-employment types and a part of circling for low-employment types. Because of their high job-finding rates, and despite their low flow values of non-work relative to work, the volatility of the future lifetime value that high-employment types derive from work and non-work is lower than for low-employment types.

We construct a novel measure of the duration of joblessness using the labor force status histories in the four-month CPS panels. For those out of the labor force (OLF) and the unemployed, the job finding rate declines with the duration of joblessness. This duration measure dominates other existing measures in the CPS for predicting transitions from non-employment to employment. For those OLF, the variation in job finding rates explained by the duration of joblessness is five times larger than the variation explained by the self-reported desire to work or reasons for not searching. For the unemployed, the job finding rate declines with the self-reported duration of unemployment only to the extent that this variable correlates with the duration of joblessness. The two duration measures are not equivalent, and the discrepancy between them is not a classification error. Instead, the self-reports of unemployment durations refer to how long the respondent looked for work, often disregarding short-term jobs or including periods of employment while searching. Using our novel measure, we provide new estimates of the duration distribution of the unemployed and reexamine current approaches to misclassification error in the CPS.

In the U.S. labor market unemployed individuals that are actively looking for work are more than three times as likely to become employed as those individuals that are not actively looking for work and are considered to be out of the labor force (OLF). Yet, on average, every month twice as many people make the transition from OLF to employment than do from unemployment. Based on these observations we have argued in Hornstein, Kudlyak, and Lange (2014) for an alternative measure of resource utilization in the labor market, a non-employment index, which is more comprehensive than the standard unemployment rate. In this article we show how the NEI fits into recent extensions of the matching function which is a standard macroeconomic approach to model labor markets with frictions, how it affects estimates of the extent of labor market frictions, and how these frictions have changed in the Great Recession.

We document novel, economically important correlations between children’s future credit risk scores, default, and homeownership status and their parents’ credit characteristics measured when the children are in their late teens. A one standard deviation higher parental credit risk score when the child is 19 is associated with a 24 percent reduction in the likelihood that the child goes bankrupt by age 29, a 36 percent lower likelihood of other serious default, a 35 point higher child credit score, and a 23 percent higher chance of the child becoming a homeowner. The linkages persist after controlling for parental income. The linkages are stronger in cities with lower intergenerational income mobility, implying that common factors might drive both. Existing measures of state-level educational policy have limited effects on the strength of the linkages. Evidence from a sample of siblings suggests that the linkages might be largely due to family fixed effects.

We introduce a simple representation of endogenous search effort into the standard matching function with job-seeker heterogeneity. Using the estimated augmented matching function, we study the sources of changes in the average employment transition rate. In the standard matching function, the contribution of matching efficiency is decreasing in the matching function elasticity. In contrast, for our matching function with variable search effort and small matching elasticity, search effort is procyclical, accounting for most of the transition rate volatility; and the decline of the aggregate matching efficiency accounts for a small part of the decline in the transition rate after 2007. For a large matching elasticity, search effort is countercyclical, and large movements in matching efficiency compensate for that; and the decline in the matching efficiency accounts for a large part of the decline in the transition rate after 2007. The data on employment transition rates provide evidence for endogenous search effort but do not separately identify cyclicality of search effort and matching elasticity.

wp2016-24_appendix.pdf – Supplemental Appendix

We use novel high-frequency panel data on individuals’ job applications from a job posting website to study how job seekers direct their applications over the course of a job search. We find that at the beginning of search there is sorting of applicants across vacancies by education. As the search continues, education becomes a weaker predictor of which job a job seeker applies for, and an average job seeker applies for jobs that are a first-week choice of less educated job seekers. The findings suggest that search is systematic, whereby a job seeker samples high-wage opportunities first and lower-wage opportunities later. The findings are consistent with the literature that documents declining reservation wages and provide evidence in favor of theories of job seekers’ learning.

I conduct an empirical investigation of the cyclicality of the price of labor. Firms employ workers up to the point where workers’ marginal revenue product equals the price of labor. If the labor market is a spot market, then the price of labor is the wage. But often workers are contracted for more than one period. The price of labor captures both the wage at the time of hiring and the impact of labor market conditions at the time of hiring on future wages. The price of labor and not wage is allocational for employment. Because it is not directly observed in the data, I construct the price of labor based on the behavior of individual wages and turnover. I find that a one percentage point increase in unemployment generates more than a 4.5% decrease in the price of labor. This cyclicality is three times higher than the cyclicality of individual wages and also noticeably higher than the cyclicality of the wages of newly hired workers. I conclude that the price of labor is very procyclical.

We compile a novel high-frequency, detailed geographic dataset on mass layoffs from U.S. state labor departments. Using recent advances in difference-in-difference estimation with staggered treatment, we find that locally-mandated stay-at-home orders issued March 16–22, 2020 triggered mass layoffs equal to half a percent of the population in just one week. Our findings contribute to explanations for why job loss in 2020 was catastrophic yet temporary.

An armamentarium comprises the resources assembled for a particular purpose, such as treating an illnesses or fighting a battle. A central bank uses its armamentarium to conduct monetary policy. The paper’s main points are (1) In a cyclical recovery, unemployment glides downward at a low rate. This rate was roughly uniform across historical recoveries since 1948. (2) In the recovery from 2009 through 2019, the natural rate of unemployment declined along with the actual unemployment rate, as evidenced by the fact that inflation was low and stable during that period. (3) The labor market during 2020 remained significantly tighter than total unemployment would suggest. (4) Low and steady inflation became firmly anchored during the expansion of 2009- 2019, but anchoring declined during the turbulence of the pandemic. The diminished anchoring of inflation may have been helpful in the disinflation that occurred in 2023.

In employment relationships, a wage is an installment payment on an implicit long-term agreement between a worker and a firm. The price of labor that impacts firm’s hiring decisions, instead, reflects the hiring wage as well as the impact of economic conditions at the time of hiring on future wages. Measured by the labor’s user cost, the price of labor is substantially more pro-cyclical than the new-hire wage or the average wage. The strong procyclicality of the price of labor calls for other forces for cyclical labor demand to explain employment fluctuations.

We estimate cyclicality in labor’s user cost allowing for cyclical fluctuations in the quality of worker-firm matches and wages that are smoothed within employment matches. To do so, we exploit a match’s long-run wage to control for its quality. Using 1980–2019 National Longitudinal Survey of Youth data, we identify three channels by which recessions affect user cost: they lower the new-hire wage and wages going forward in the match, but they also result in higher subsequent separations. We find that labor’s user cost is highly procyclical, increasing by more than 4% for a 1 percentage point decline in unemployment.

We use regional variation in the American Recovery and Reinvestment Act (2009-2012) to analyze the effect of government spending on consumer spending. Our consumption data come from household-level retail purchases in the Nielsen scanner data and auto purchases from Equifax credit balances. We estimate that a $1 increase in county-level government spending increases local non-durable consumer spending by $0.29 and local auto spending by $0.09. We translate the regional consumption responses to an aggregate fiscal multiplier using a multiregional, New Keynesian model with heterogeneous agents, incomplete markets, and trade linkages. Our model is consistent with the estimated positive local multiplier, a result that distinguishes our incomplete markets model from models with complete markets. At the zero lower bound, the aggregate consumption multiplier is twice as large as the local multiplier because trade linkages propagate the effect of government spending across regions.

Unemployment recoveries in the US have been inexorable. In the aftermath of a recession, unless another crisis intervenes, unemployment continues to glide down. Between 1948 and 2019, the annual reduction in the unemployment rate during cyclical recoveries was distributed around 0.1 log points per year. The economy seems to have an irresistible force toward restoring full employment. Occasionally, unemployment rises rapidly during an economic crisis, while most of the time, unemployment declines slowly and smoothly at a near-constant proportional rate. Similar properties hold for other measures of the US unemployment rate and for unemployment in emerging and advanced countries.

Potential workers are classified as unemployed if they seek work but are not working. The unemployed population contains two groups—those with jobs and those without jobs. Those with jobs are on furlough or temporary layoff. This group expanded tremendously in April 2020, at the trough of the pandemic recession. They wait out periods of non-work with the understanding that their jobs still exist and that they will be recalled. We show that the resulting temporary-layoff unemployment mostly dissipated by the end of 2020. Potential workers without jobs constitute what we call jobless unemployment. Shocks that elevate jobless unemployment have much more persistent effects. Historical major adverse shocks, such as the financial crisis in 2008, created mostly jobless unemployment and consequently caused extended periods of elevated unemployment. Jobless unemployment reached its pandemic peak in November 2020, at 4.9%, modest by historical standards, and has declined at a faster-than-historical pace since.

Even as the war in Ukraine continues, it is imperative to implement, post haste, a strategy to combat the substantial effects of the war on Ukrainian human capital. In this Policy Insight, the authors estimate the effect of the war on Ukraine’s human capital and identify key directions for rebuilding human capital in the country. This includes the quantity and quality of schooling for children, quality of higher education, training and retraining programmes for adults, assistance for people with physical and mental disabilities, post-deployment re-integration into the civilian sector, population growth and fertility, and the promotion of self-motivating mechanisms.

A remarkable fact about the historical US business cycle is that, after unemployment reached its peak in a recession, and a recovery begins, the annual reduction in the unemployment rate is stable at around one tenth of the current level of unemployment. We document this fact in a companion paper, Hall and Kudlyak (2020a). Here, we consider explanations for the surprising consistency of recoveries. We show that the evolution of the labor market from recession to recovery involves more than the direct effect of persistent unemployment of job-losers from the recession shock–unemployment during the recovery is above normal for people who did not lose jobs during the recession. We explore models of the labor market’s self-recovery that imply gradual working off of unemployment following a recession shock. We emphasize the feedback from high unemployment to the forces driving job creation. These models also explain why the recovery of market-wide unemployment is so much slower than the rate at which individual unemployed workers find new jobs. The reasons include the fact that the path that individual job-losers follow back to stable employment often includes several brief interim jobs.

The Ukrainian labour market not only needs to be rebuilt, it needs to be rebuilt better. The unprecedented challenges imposed by the reconstruction can only be faced by a
labour market that promotes participation and eases the reallocation of workers across jobs. This was not the case for the labour market in Ukraine before the bloody Russian
invasion. Reconstruction will therefore require a mix of emergency measures to deal with the legacies of the war and structural reforms to address pre-existing inefficiencies
of the labour market. In this chapter, we illustrate the challenges in light of experience of other European countries that have gone through military conflicts in the recent past
and propose strategies for action.

Among the challenges are that millions of workers (at least 10% of the labour force) will need to change jobs; the matching of vacancies and jobseekers will in many cases
involve repeated changes of residence due to the destruction of the housing stock and the mismatch between the regional profile of worker displacement and of firms relocation inherited from the war; former refugees, internally displaced people and war veterans, often injured and carrying with them the mental scars of the war, will have to be feintegrated in the labour market; a significantly larger fraction of the working age population than before the full-scale invasion will have to be mobilised to avoid bottlenecks in the recovery from the war; and immigrants from other countries will have to be integrated and involved in the reconstruction of the country.

The global COVID-19 pandemic has led to job loss of catastrophic proportions in the United States. This column looks at recoveries from recessions over past 70 years to assess how the US labour market might recover from this job loss of unprecedented magnitude. Remarkably consistent recoveries have occurred in the US after every recessionary shock that caused a spike in unemployment, and there are reasons to believe that the recovery from the current shock will be more rapid, because unemployment contains a much larger fraction of workers on temporary layoff than in previous recoveries. However, there is a great deal of uncertainty about the possible recovery rate.

Using household-level debt data over 2000-2012 and local variation in inequality, we show that low-income households in high-inequality regions (zip codes, counties, states) accumulated less debt relative to their income than low-income households in lower inequality regions. We also find evidence that low-income households face higher credit prices and reduced access to credit as inequality increases. We argue that these patterns are consistent with inequality tilting credit supply away from low-income households and toward high-income households, which may have long-run implications for outcomes like homeownership or entrepreneurship.

We use online job application data to study the relationship between search intensity and search duration. The data allow us to control for job seeker composition and the evolution of available job openings over the duration of search. We find that, within an individual search spell, search intensity declines continuously. We also find that longer-duration job seekers search more intensely throughout their search. They tend to be older, male, nonemployed, and live in areas with weaker labor markets. Our findings contradict standard assumptions of labor search models. We discuss how to reconcile the theory with our evidence.

Gertler and Gilchrist (1994) provide seminal evidence for the prevailing view that adverse shocks are propagated via credit constraints: small firms are affected more during tight credit periods than large firms. Under this view, the deep recession that followed the 2008 financial crisis is often interpreted as the propagation of the initial “credit shock.” Following Gertler and Gilchrist (1994)’s methodology, we study the behavior of small and large firms during episodes of credit disruption and extend the analysis to the 2008 financial crisis and NBER-dated recessions. We find that large firms’ short-term debt and sales contracted relatively more than those of small firms during the 2008 financial crisis and during most recessions since 1969. The results are robust to changes in the business cycle dating procedure. Using Compustat, we also find that during 2007–09 low financially dependent firms suffered more than high financially dependent firms. These results favor the view that a tightening of a financial or collateral constraint might not be a good representation of the 2007-09 crisis.

This article finds that in 2011, online job search was much more prevalent and significantly more effective in helping job seekers gain employment than about a decade earlier. Moreover, it shows that online job search data generally capture the aggregate patterns of the U.S. labor market. The authors discuss the advantages and disadvantages of using these data for research, and summarize related studies.

Aggregate wage growth has remained flat during the 2007-09 recession and its aftermath while unemployment has exhibited substantial swings. Does the low real aggregate wage growth during the recovery indicate a weak labor market beyond what is measured by the official unemployment rate? Aggregate wage growth reflects actual changes of workers’ wages, changes in the composition of workers, and changes in the composition of jobs. Some of these changes are related to underlying structural trends in the economy while others constitute the economy’s response to the business cycle shocks and are more indicative of cyclical resource utilization in the labor market. Consequently, it is important to look beyond the aggregate statistics to understand the behavior of real wages and its relation to the health of the labor market. In this article, we review recent literature that studies the changes in the components of the aggregate wage over time and, specifically, after the 2007-09 recession.

We study a new law that restricts credit to individuals under age 21. We first use a
difference-in-difference approach to estimate the effect of the law on credit card availability.
Following the passage of the law, individuals under age 21 are 8 percentage points (15 percent) less likely to have a credit card, have fewer cards, and, conditional on having a card at all, are 35 percent more likely to have a cosigned card. We then
use data from before the passage of the law to identify the characteristics of those individuals most likely to be affected by the Act.

Aggregate wage growth has remained flat during the 2007-09 recession and its aftermath while unemployment has exhibited substantial swings. Does the low real aggregate wage growth during the recovery indicate a weak labor market beyond what is measured by the official unemployment rate? Aggregate wage growth reflects actual changes of workers’ wages, changes in the composition of workers, and changes in the composition of jobs. Some of these changes are related to underlying structural trends in the economy while others constitute the economy’s response to the business cycle shocks and are more indicative of cyclical resource utilization in the labor market. Consequently, it is important to look beyond the aggregate statistics to understand the behavior of real wages and its relation to the health of the labor market. In this article, we review recent literature that studies the changes in the components of the aggregate wage over time and, specifically, after the 2007-09 recession.

The user cost of labor is the expected difference between the present discounted value of wages paid to a worker hired in the current period and that paid to a worker hired in the next period. Analogous to the price of any long-term asset, the user cost, not wage, is the relevant price for a firm that is considering adding a worker. I construct its counterpart in the data and estimate that it is substantially more procyclical than average wages or wages of newly hired workers. I demonstrate an application of the finding using the textbook search and matching model.

We construct a multi-sector search and matching model where the unemployed receives idiosyncratic productivity shocks that make working in certain sectors more productive than in the others. Agents must decide which sector to search in and face moving costs when leaving their current sector for another. In this environment, unemployment is associated with an additional risk: low future wages if mobility costs preclude search in the appropriate sector. This introduces a new role for unemployment benefits – productivity insurance while unemployed. For plausible parameterizations unemployment benefits increase per-worker productivity. In addition, the welfare-maximizing benefit level decreases as moving costs increase.

Using counterfactual exercises for the transition probabilities between full-time employment, part-time employment for economic reasons (PTER), part-time employment for noneconomic reasons (PTNER), unemployment, and out-of-the-labor-force similar to Shimer (2012), we find that, ceteris paribus, changes in the transition probabilities to and from PTER in the aftermath of the 2007-09 recession were mainly associated with changes in the composition of employment (full- versus part time, and PTER versus PTNER) instead of with changes in the distribution of individuals between employment and non-employment. Consequently, policymakers’ attention to PTER implies a broader definition of resource underutilization in the labor market than a simple extensive employment margin as captured by the standard unemployment rate. It brings attention to the intensive employment margin and the quality of employment. Since PTER workers’ share is highest in non-routine manual (typically, low-wage) occupations and given recent works on job polarization, it is a challenging task to disentangle cyclical versus structural factors behind an increased number of PTER workers after the 2007-09 recession.

In the U.S. labor market unemployed individuals that are actively looking for work are more than three times as likely to become employed as those individuals that are not actively looking for work and are considered to be out of the labor force (OLF). Yet, on average, every month twice as many people make the transition from OLF to employment than do from unemployment to employment. These observations on labor market transitions suggest that the standard unemployment rate and its extensions proposed by the Bureau of Labor Statistics are both too coarse and too narrow as measures of resource utilization in the labor market. These measures are too narrow since they exclude a large part of the population that is potentially employable, and they are too coarse since they assume the same labor force attachment for all nonemployed individuals. We construct a measure of resource utilization in the labor market, a nonemployment index, that is both comprehensive and accounts for differences in labor force attachment. Prior to 2007, the standard unemployment rate was highly correlated with our nonemployment index but, during the recession of 2007–09 and its aftermath, the standard unemployment rate overstated the extent of underutilization in the labor market.

We estimate a trend in the aggregate labor force participation rate using the age-gender and the birth cohort effects in the labor force participation rates of different demographic groups and the actual demographic composition of the population. We find that, in 2012, the aggregate labor force participation rate is close to its trend.

We provide an explanation of how inflation of the price of housing services is measured by the Bureau of Labor Statistics and describe alternative approaches. We then describe the contribution of inflation of the price of housing services to inflation in the consumer price index during the Great Recession and its aftermath. Finally, we examine new data series that provide additional information about the rental market for housing services and use this information to evaluate the direction of the pressure on housing services price inflation.

We conduct an accounting exercise of the changes in aggregate employment, unemployment, and out of labor force (OLF) among 25–64-year-old men from 1968–2010. We decompose the observed changes in these labor market outcomes into changes in the sociodemographic composition of the population and changes in the labor market outcomes of different sociodemographic groups. Using the results of the decomposition, we predict that the OLF-to-population ratio for men will increase to 16 percent in 2015, up from 14.7 percent in 2010.

We quantify the effect of recourse on default and find that recourse affects default by lowering the borrower’s sensitivity to negative equity. At the mean value of the default option for defaulted loans, borrowers are 30% more likely to default in non-recourse states. Furthermore, for homes appraised at $500,000 to $750,000, borrowers are twice as likely to default in non-recourse states. We also find that defaults are more likely to occur through a lender-friendly procedure, such as a deed in lieu, in states that allow deficiency judgments. We find no evidence that mortgage interest rates are lower in recourse states.

Search models of the labor market suggest that a significant determinant of job creation decisions by firms is the expected value of the initial and future real wages that firms have to pay to workers in newly formed employment relationships. Until recently, the focus of the empirical literature has been on the cyclical behavior of the current wage, but not on the cyclical behavior of the expected present discounted value of future wages within a match. This article reviews the empirical literature on the cyclicality of real wages of workers in continuing employment relationships, wages of newly hired workers, and a measure of wages that takes into account future wages within employment relationships. The existing evidence suggests that the real wage most relevant for job creation decisions appears to be quite flexible over the business cycle. Thus, the wage data do not support the rigidity necessary to generate the empirical volatility of unemployment in the standard search and matching model.

Recent monetary policy tightening has been noted as a possible contributor to the ongoing decline in house prices. However, the economic literature generally finds that it can take years for house prices to respond to monetary policy shocks. Using high-frequency data on list prices in the US, this column finds that house prices actually adjust to monetary policy shifts within a matter of weeks. Changes in house prices are largely driven by surprises in future rates rather than by surprises in the federal funds rate. This adjustment of house prices largely occurs through the mortgage rate channel of monetary policy.

Following early 2020 responses to the pandemic, labor force participation declined dramatically and has remained below its 2019 level, whereas the unemployment rate recovered briskly. We estimate the trend of labor force participation and unemployment and find a substantial impact of the pandemic on estimates of trend. It turns out that levels of labor force participation and unemployment in 2021 were approaching their estimated trends. A return to 2019 levels would then represent a tight labor market, especially relative to long-run demographic trends that suggest further declines in the participation rate.

Demographic forces have profoundly shaped the dynamics of U.S. labor force
participation and unemployment over the past forty years. Recognizing the
importance of these employment indicators for the conduct of monetary
policy, this Economic Brief explores how they have been influenced by the
U.S. population’s changing gender, educational, and age profile. Based on
the authors’ estimates, the trend U.S. unemployment rate will decline to 4.3
percent over the next ten years as the population continues to age and increase its educational attainment.

More than six years after the Great Recession
reached its trough, policymakers and researchers are still debating whether a full-blown, robust recovery in the labor market is under way. Although the unemployment rate declined from 10 percent in October 2009 to 5 percent in October 2015, some policymakers and researchers are concerned that other labor statistics are lagging the levels typically expected in the mature stages of an economic expansion. For example, several point to the number of workers who report working part time but would like to work full time. This number has been declining more slowly
than the level of unemployment. (See Figure 1.)

The female labor force participation (LFP) rate has dropped steadily since 2000, especially among single women. At the same time, the percentage of single women has grown as a share of the female population, a trend that has increased the impact of the single women’s LFP rate on the aggregate women’s LFP rate. An analysis of data from the Current Population Survey shows that a growing percentage of single women who are not in the labor force are going to school. Meanwhile, an increasing share of married women list retirement as the reason for no longer participating in the labor force.

During the current recovery, policymakers have debated whether slow wage growth indicates labor market “slack” that is not adequately reflected in the unemployment rate alone. The relationship—or lack thereof—between the unemployment rate and wage growth has challenged macroeconomists for decades. Empirical studies using micro data find that individual wages are procyclical, but attempting to use aggregate measures of wage growth to determine the level of “slack” in the labor market would be highly difficult and potentially misleading.

Unemployment rose dramatically during the 2007-09 recession, peaking at 10 percent in October 2009. It has fallen steadily since then, at times outpacing economists’ forecasts. In April, unemployment reached 6.3 percent, about two-thirds of the way back to its prerecession level. Such progress is often a sign of recovery, but some observers question whether the unemployment rate accurately measures resource utilization in the current labor market.

Young borrowers are conventionally considered the most prone to making financial mistakes. This has spurred efforts to limit their access to credit, particularly via credit cards. Recent research suggests, however, that young borrowers are actually among the least likely to experience a serious credit card default. One reason why people obtain credit cards early in life may be to build a strong credit history.

While there is a large body of theoretical work about the job search process, there is relatively little empirical evidence about important aspects of workers’ search behavior. A new database of online job posting data sheds light on how workers search for jobs.

Labor market research often focuses on transition rates between employment and unemployment without analyzing the effects of transition rates into and out of the labor force. Current Population Survey data permit analysis of transition rates among all three labor force statuses. A study at the Richmond Fed examines the role of labor force participation in the dynamics of the aggregate unemployment rate across the four most recent recessions. This research finds an increased role for transition rates between nonparticipation and unemployment during the Great Recession and recovery.

Do large firms and small firms behave differently when credit becomes more costly or harder to obtain? Past research has found that small firms are more likely to be credit-constrained and thus tend to be affected more negatively than large firms during such times. Recent findings from the 2007-2009 recession, however, raise questions about the roles of small and large firms during periods of tight credit.

Simply looking at unadjusted versions of traditional statistics may not be the best way to compare the state of the current economy to previous periods. When comparing recessions, it is important to account for demographic changes.

Many states give mortgage lenders strong legal means by which to pursue debt collection in the event of a mortgage default. In those states, probability of default is lower and the forms the default takes are often quite different from a costly conventional foreclosure.