Job Finding Rate Research Articles

A Dynamic Analysis of Women’s Labour Force Participation in Urban India

AbstractThe introduction of the Periodic Labour Force Survey (PLFS) heralded a methodological innovation for the study of Indian labour, allowing the researcher to build panels tracking urban individuals over a year. Using two rounds of the PLFS covering the periods 2017–18 and 2018–19, we construct a pooled panel of urban Indian individuals aged 15–65 and focus on women’s experiences in the labour force. We find evidence of low dynamism in the Indian economy, with women facing significant difficulties regarding labour force participation. While a majority of women remain outside the labour force throughout the year, those who do participate face significant disadvantages. Job-finding rates for women are half that of men, indicating weak demand for women’s labour in the economy. Women face significant exits from both employment and unemployment, with nearly 18% of employed women leaving their jobs and moving to non-participation over the year. Women’s relative disadvantages persist even when age and education are considered, with the lowest job-finding rates seen for young and graduate women, and rates of labour force exit much higher than that of men. This paper highlights the importance of looking at demand side questions when it comes to examining women’s labour force participation.

Perceived returns to job search

This paper provides new evidence on workers’ perceptions of the returns to job search effort using hypothetical vignettes. This allows us to overcome limitations with survey data on realized behavior in which search effort and reservation wages may be endogenous to perceived job finding rates. The perceived job finding probability is nearly linear in hours searched and only slightly concave for most respondents. While workers are over-optimistic about the probability of receiving a job offer conditional on any search, they perceive the marginal return to additional search hours as positive but comparably low. Job seekers receiving an offer, update their perceived returns upwards, while the beliefs of unsuccessful searchers regress towards the direction of the mean. We find little evidence that novel aspects of the pandemic recession have fundamentally changed workers’ motivations for job search: that an existing job is expected to end or has unsatisfactory pay are the primary motives for on-the-job search. On the contrary, workers’ ability to do their tasks from home is not a strong predictor of job search nor a significant motive for switching occupations.

Returns to on-the-job search and wage dispersion

A wide class of models with On-the-Job Search (OJS) predict that workers gradually select into better jobs. We develop a simple method based on the expected number of job offers received that can be used to measure match quality, identify the wage offer distribution and estimate the contribution of OJS to wage dispersion and the increase in wages over the lifecycle. The method uses two sources of identification: (i) time variation in job-finding rates and (ii) individual variation in the time since the last layoff. Applying this method to the NLSY 79, we find that the standard deviation of the wage-offer distribution is 13% and that OJS accounts for 8% of the total wage dispersion and 30% of the wage-increase over the lifecycle.

Learning on the Job and the Cost of Business Cycles

We show that business cycles reduce welfare through a decrease in the average level of employment in a labor market search model with learning on the job and skill loss during unemployment. Empirically, unemployment and the job-finding rate are negatively correlated. Since new jobs are the product of these two from the employment transition equation, business cycles imply fewer new jobs. Learning on the job implies that the resulting decrease in employment reduces aggregate human capital. This reduces incentives to post vacancies, further decreasing employment and human capital. We quantify this mechanism and find large output and welfare costs of business cycles. (JEL D83, E23, E24, E32, J24, J63)

What Matters for Job Finding and Separation in the Long Run? Evidence from Labor Market Dynamics in New Zealand

We use the novel anonymized Household Labour Force Survey (HLFS) microdata to analyze job finding rates and job separation rates in New Zealand. We find that individual characteristics, including age, gender, ethnicity and education have a significant impact on job finding and separation rates, even after controlling for other factors. We use a decomposition approach to analyze how the effects of individual characteristics on job finding and separation rates contribute to heterogeneity in employment outcomes. Overall, we find that higher separation rates of young workers play a disproportionate role in explaining heterogeneity of employment outcomes across age groups, while differences in finding rates are somewhat more important in explaining differences by education level. Both finding and separation rate differences are important in explaining differences across ethnicities. We also find some heterogeneous response of worker groups to business cycle after controlling for other factors. The results underscore the importance of well-targeted labor market support policies.

Business cycle asymmetries and the labor market

This paper shows that a search and matching model with idiosyncratic training cost shocks can explain the asymmetric movement of the job-finding rate over the business cycle and the decline of matching efficiency in recessions. Large negative aggregate shocks move the hiring cutoff into a part of the training cost distribution with higher density. The position of the hiring cutoff in the distribution is disciplined by the empirical elasticity of the job-finding rate with respect to market tightness. Our model explains a large fraction of the matching efficiency decline during the Great Recession and generates state-dependent effects of policy interventions.

Moral Hazard Versus Liquidity and the Optimal Timing of Unemployment Benefits

Abstract We develop a novel way of identifying the liquidity and moral hazard effects of unemployment insurance exclusively from how job-finding rates respond to unemployment benefits that vary over an unemployment spell. We derive a sufficient statistics formula for the dynamically optimal level of unemployment benefits based on these two effects. Using a regression kink design (RKD) that simultaneously exploits two kinks in the schedule of unemployment benefits, we apply our method to Spain for the years 1992–2012 and find that moral hazard effects dominated liquidity effects, suggesting that Spanish unemployment benefits exceeded the optimal level in that period.

The Cyclicality of Immigrant Wages and Labour Market Flows: Evidence from Spain

Abstract This article studies the responses of real wages and labour market flows of immigrants in Spain for the period between 1999 and 2019. By using Labour Force Survey microdata, I examine the cyclicality of job-finding and job-separation rates for immigrants and natives over the long Spanish economic expansion and the sharp contraction. During the expansion, 1999–2007, the job-finding rate was higher for immigrants than for natives, but both rates converged to a lower level after the Great Recession took place in 2008. I also find that the impact of the crisis on the job-separation rate was more than three times as high for immigrants than for natives. By using longitudinal social security data, I find that wage cyclicality is higher for immigrants than for natives: a one percentage point increase in the unemployment rate is associated with a 0.61 and 0.85% drop in real wages for natives and immigrants, respectively. However, these differences only occur among low-tenure workers. This study provides novel empirical evidence to enrich macroeconomic theories on the interaction of economic cycles and the impact of immigration.

The ins and outs of Central European unemployment

ABSTRACT We examine the role of unemployment inflows and outflows in contributing to unemployment cyclicality in Czechia and Poland, using data from the European Union Statistics on Income and Living Conditions, and a three-state model of unemployment variance decomposition. We find that the labour market fluidity is higher in Poland than in Czechia, with Polish workers moving in and out of unemployment more frequently than their Czech counterparts. For both countries, the upward unemployment dynamics was during 2008–2011 driven by counter-cyclical increases in the job-separation rate, rather than by pro-cyclical declines in the job-finding rate. The inflow-outflow split was nonetheless more balanced in Czechia. The two economies further diverged across 2015–2018: Czech unemployment declined prevailingly due to diminishing job separations, while in Poland it was mostly due to improving job-finding prospects. This signals a deeper insider-outsider fragmentation of the Czech labour market, even during the period of economic expansion.

Nonlinearities and Workers' Heterogeneity in Unemployment Dynamics

This study demonstrates that nonlinearities, coupled with worker heterogeneity, make it possible to reconcile the Diamond–Mortensen–Pissarides model with the labor market dynamics observed in the United States. Nonlinearities, induced by firings and downward real wage rigidities, magnify adjustments in quantities, whereas heterogeneity concentrates them on the low-paid workers' submarkets. The model fits the job finding, job separation, and unemployment rates well. It also explains the Beveridge curve's dynamics and the cyclicality of the involuntary component of separations. The estimated dynamics of the aggregate shock that allows generating the US labor market fluctuations has a correlation with unemployment that changes of sign during the 80s. We also show that the differences in adjustment between submarkets predicted by the model are consistent with the data of job flows by educational attainment.

How effective are hiring subsidies in reducing long-term unemployment among prime-aged jobseekers? Evidence from Belgium

Abstract Hiring subsidies are widely used to create (stable) employment for the long-term unemployed. This paper exploits the abolition of a hiring subsidy targeted at long-term unemployed jobseekers older than 45 years of age in Belgium to evaluate its effectiveness in the short and medium run. Based on a triple-difference methodology, the hiring subsidy is shown to increase the job-finding rate by 13% without any evidence of spillover effects. This effect is driven by a positive effect on individuals with at least a bachelor's degree. However, the hiring subsidy mainly creates temporary short-lived employment: eligible jobseekers are not more likely to find employment that lasts at least 12 consecutive months compared with ineligible jobseekers.

Evidence on Job Search Models from a Survey of Unemployed Workers in Germany

Abstract The job-finding rate of unemployment insurance (UI) recipients declines in the initial months of unemployment and then exhibits a spike at the benefit exhaustion point. A range of theoretical explanations have been proposed, but those are hard to disentangle using data on job finding alone. To better understand the underlying mechanisms, we conducted a large text-message-based survey of unemployed workers in Germany. We surveyed 6,349 UI recipients twice a week for four months about their job search effort. The panel structure allows us to observe how search effort evolves in individuals over the unemployment spell. We provide three key facts: (i) search effort is flat early on in the UI spell, (ii) search effort exhibits an increase up to UI exhaustion and a decrease thereafter, (iii) UI recipients do not appear to time job start dates to coincide with the UI exhaustion point. A standard search model with unobserved heterogeneity struggles to explain the second fact, and a model of storable offers is not consistent with the third fact. The patterns are well captured by a model of reference-dependent job search or by a model with duration dependence in search cost.

Health, wealth, and informality over the life cycle

What is the impact of bad health on labor market trajectories, consumption, and wealth accumulation in a developing country characterized by a large informal sector and strong inequalities? We develop and estimate a heterogeneous agents model with two sectors to quantify the impact of health shocks and to disentangle the channels through which they affect wealth and consumption over the life cycle in South Africa. We show that the effects of health shocks are significant and strongly depend on the job status of individuals. For formal workers, bad health reduces labor efficiency, which translates into lower earnings. For informal workers and the non-employed, the shock lowers the job finding rate and increases job separation into non-employment, which results in a surge in non-employment spells. As the non-employed are more likely to be unhealthy, health shocks generate a vicious circle.

UI Generosity and Job Acceptance: Effects of the 2020 CARES Act

To provide economic relief following the onset of the COVID-19 pandemic, the U.S. CARES Act granted an extra $600 per week in unemployment insurance (UI) benefit payments from late March through July 2020. This unprecedented increase in UI generosity caused weekly benefit payments to exceed prior earnings for most recipients, raising concern that many would be unwilling to accept job offers, slowing the labor market recovery. To assess the impact of the UI supplement, we analyze the job acceptance decision in a dynamic framework in which job seekers weigh the value of a job against remaining unemployed, accounting for the perceived state of the labor market and expected weeks of UI benefits. We derive a reservation level of benefit payments at which an individual is indifferent between accepting and refusing a job offer at their prior wage. Calculating the reservation benefit and comparing it to imputed benefit payments for a wide range of U.S. workers suggests that only a small fraction would turn down an offer to return to work at their previous wage under the CARES Act expanded UI payments. We supplement this quantitative assessment of reservation benefits with direct empirical analysis of labor force transitions using matched Current Population Survey (CPS) data, linked to annual earning records from the CPS income supplement to form UI replacement rates. The results show moderate disincentive effects of the $600 supplemental payments on job finding rates and by extension small effects of the $300 weekly supplement available during 2021.

Job Specialization and Labor Market Turnover

This paper studies the decline in labor market turnover over recent decades, in particular, the job finding and separation rates. I analyze the role of an increase in specialization of jobs in accounting for this decline, where specialization is defined as the impact of mismatch on match productivity. Combining individual level data from NLSY79 and NLSY97 with data on skills from ASVAB and O*NET, I empirically estimate job specialization and show that the specialization has increased over time. To quantify the impact of this increasing specialization on labor market turnover, I build an equilibrium search and matching model with two-sided ex-ante heterogeneity and endogenous separations. The calibrated model shows that higher job specialization leads to a decline in both job finding and separation rates. As specialization increases, firms and workers become more selective in forming matches. Thus, well-matched firms and workers choose to remain in their matches longer, while bad matches get destroyed faster. Since higher specialization leads to an increase in the proportion of good matches in the economy, it results in a decline in the labor market turnover.

A Mixed Frequency BVAR for the Euro Area Labour Market

We introduce a Bayesian Mixed-Frequency VAR model for the aggregate euro area labour market that features a structural identification via sign restrictions. The purpose of this paper is twofold: we aim at (i) providing reliable and timely forecasts of key labour market variables and (ii) enhancing the economic interpretation of the main movements in the labour market. We find satisfactory results in terms of forecasting, especially when looking at quarterly variables, such as employment growth and the job finding rate. Furthermore, we look into the shocks that drove the labour market and macroeconomic dynamics from 2002 to early 2020, with a first insight also on the COVID-19 recession. While domestic and foreign demand shocks were the main drivers during the Global Financial Crisis, aggregate supply conditions and labour supply factors reflecting the degree of lockdown-related restrictions have been important drivers of key labour market variables during the pandemic.

The Geography of Unemployment

Unemployment rates differ widely across local labor markets. I offer new empirical evidence that high local unemployment emerges because of elevated local job losing rates. Local employers, rather than local workers, account for most of spatial gaps in job stability. I then propose a theory in which spatial differences in job loss arise endogenously, due to the spatial sorting of heterogeneous employers across local labor markets. Labor market frictions induce productive employers to over-value locating close to each other. The optimal policy incentivizes them to relocate to areas with high job losing rates, providing a rationale for commonly used place-based policies. I estimate the model using French administrative data. The estimated model accounts for over three fourths of the cross-sectional dispersion in unemployment rates, as well as for the respective contributions of job losing and job finding rates. Employers' inefficient location choices amplify spatial unemployment differentials five-fold. Both real-world and optimal place-based policies can yield sizable local and aggregate welfare gains.

Ui Generosity and Job Acceptance: Effects of the 2020 Cares Act

To provide economic relief following the onset of the COVID-19 pandemic, the U.S. CARES Act granted an extra $600 per week in unemployment insurance (UI) benefit payments from late March through July 2020. This unprecedented increase in UI generosity caused weekly benefit payments to exceed prior earnings for most recipients, raising concern that many would be unwilling to accept job offers, slowing the labor market recovery. To assess the impact of the UI supplement, we analyze the job acceptance decision in a dynamic framework in which job seekers weigh the value of a job against remaining unemployed, accounting for the perceived state of the labor market and expected weeks of UI benefits. We derive a reservation level of benefit payments at which an individual is indifferent between accepting and refusing a job offer at their prior wage. Calculating the reservation benefit and comparing it to imputed benefit payments for a wide range of U.S. workers suggests that only a small fraction would turn down an offer to return to work at their previous wage under the CARES Act expanded UI payments. We supplement this quantitative assessment of reservation benefits with direct empirical analysis of labor force transitions using matched Current Population Survey (CPS) data, linked to annual earning records from the CPS income supplement to form UI replacement rates. The results show moderate disincentive effects of the $600 supplemental payments on job finding rates and by extension small effects of the $300 weekly supplement available during 2021.

Worker Types, Job Displacement, and Duration Dependence

The composition of the workforce has implications for the earnings consequences of a job loss and patterns in the job-finding rate.

The Geography of Job Creation and Job Destruction

Spatial differences in labor market performance are large and highly persistent. Using data from the United States, Germany, and the United Kingdom, we document striking similarities in spatial differences in unemployment, vacancies, job finding, and job filling within each country. This robust set of facts guides and disciplines the development of a theory of local labor market performance. We find that a spatial version of a Diamond-Mortensen-Pissarides model with endogenous separations and on-the-job search quantitatively accounts for all the documented empirical regularities. The model also quantitatively rationalizes why differences in job-separation rates have primary importance in inducing differences in unemployment across space while changes in the job-finding rate are the main driver in unemployment fluctuations over the business cycle.