Working Inflow, Outflow, and Churning

Linked employer-employee data from the Finnish business sector is used in an analysis of worker turnover. The data is an unbalanced panel with over 219 000 observations in the years 1991-97. The churning (excess worker turnover), worker inflow (hiring), and worker outflow (separation) rates are explained by various plant and employee characteristics in type 2 Tobit models where the explanatory variables can have a different effect on the probability of the flow rates to be non-zero and on the magnitude of the flow rate when it is positive. Most of the characteristics are defined as 5-group categorical variables defined for each industry separately in each year. We compare the Tobit results to OLS estimates, and also use weighting by plant employment. It turns out that weighted OLS results are fairly close to Tobit results. The probabilities of observing non-zero churning, inflow, and outflow rates increase with plant size. The magnitudes of the non-zero churning and inflow rates depend positively on size, but the magnitude of outflow rate negatively. High-wage plants have low turnover, whereas plants with large within-plant variation in wages have high turnover. Average tenure of employees has a negative impact on turnover. High plant employment growth increases churning and separation but reduces hiring in the next year. We also control various other plant and average employee characteristics like average age and education, shares of women and homeowners, foreign ownership, ownership changes, and regional unemployment.http://deepblue.lib.umich.edu/bitstream/2027.42/39997/3/wp611.pd

The effects of workforce composition, labor turnover, and the qualities of entering and exiting workers on productivity growth

This study identifies and analyzes the effects of firms’ workforce composition, labor turnover, and the qualities of entering and exiting employees on consequent changes in their productivity. Using register data provided by Statistics Netherlands, we examine the productivity dynamics of Dutch manufacturing firms between the years 2002 and 2005. The regression results illustrate that changes in firm productivity are not only determined by the composition of the firm’s current workforce and the degree of labor turnover, but also by the characteristics of the workers who enter and exit the firm. Firms benefit from the inflow of employees previously employed with other firms in the same industry, and with highly productive firms, whereas the inflow of workers from non-employment has a negative effect on their new employers’ productivity growth. Furthermore, the outflow of workers into non-employment, and to highly productive firms positively affects their old employers’ productivity growth, while the exit of workers who leave for firms in the same industry, and of those who simultaneously relocate (across long distances) has a negative effect.workforce composition; labor turnover; job mobility; employee mobility; productivity growth

Is Inter-Firm Labor Mobility a Channel of Knowledge spillovers? Evidence from a Linked Employer-Employee Panel

An employer-employee panel is used to study whether the movement of workers across firms is a channel of unintended diffusion of R&D-generated knowledge. Somewhat surprisingly, hiring workers from others' R&D labs to one's own does not seem to be a significant spillover channel. Hiring workers previously in R&D to one's non-R&D activities, however, boosts both productivity and profitability. This is interpreted as evidence that these workers transmit knowledge that can be readily copied and implemented without much additional R&D effort.Labor Mobility, R&D Spillovers, Profitability, Linked Employer-Employee Data

Long run relationship between entry and exit: time series evidence from Turkish manufacturing industry

This paper investigates the long run relationship between entry and exit using aggregate annual data from the Turkish manufacturing industry for the period 1968-2001. The time series properties of the data imply that simple OLS regressions may yield spurious results. We employ both bivariate and multivariate models to test for Granger causality. Utilizing relatively new time series techniques, we find that exit Granger causes entry in the long run, but not vice versa. However, unlike many empirical findings in the literature, past exit has a negative effect on entry. Entrants seem to be put off by past exit in the long run. Hence, our results do not seem to support the replacement effect in the Turkish manufacturing industry in general. None of the other variables included in the multivariate analysis has significant effects on entry or exit. The generalized impulse responses between entry and exit confirm Granger causality results.

Working Inflow, Outflow, and Churning

Linked employer-employee data from the Finnish business sector is used in an analysis of worker turnover. The data is an unbalanced panel with over 219 000 observations in the years 1991-97. The churning (excess worker turnover), worker inflow (hiring), and worker outflow (separation) rates are explained by various plant and employee characteristics in type 2 Tobit models where the explanatory variables can have a different effect on the probability of the flow rates to be non-zero and on the magnitude of the flow rate when it is positive. Most of the characteristics are defined as 5-group categorical variables defined for each industry separately in each year. We compare the Tobit results to OLS estimates, and also use weighting by plant employment. It turns out that weighted OLS results are fairly close to Tobit results. The probabilities of observing non-zero churning, inflow, and outflow rates increase with plant size. The magnitudes of the non-zero churning and inflow rates depend positively on size, but the magnitude of outflow rate negatively. High-wage plants have low turnover, whereas plants with large within-plant variation in wages have high turnover. Average tenure of employees has a negative impact on turnover. High plant employment growth increases churning and separation but reduces hiring in the next year. We also control various other plant and average employee characteristics like average age and education, shares of women and homeowners, foreign ownership, ownership changes, and regional unemployment.worker turnover, churning, employer-employee data

Regional Matching Frictions and Aggregate Unemployment

The study shows that a stochastic frontier approach applied to regional level data offers a convenient and interesting method to examine how regional differences in matching efficiency and structural factors contribute to aggregate unemployment. The study finds notable and time-wise stable differences in the matching efficiency across travel-to-work areas in Finland. If all areas were as efficient as the most efficient one, the number of hires would increase about 40 per cent. This would decrease the aggregate unemployment rate from the current 8.5 percent level to 6.0 per cent. If all the areas shared the same structural characteristics as the most favourable area, the aggregate unemployment rate would drop to 7.1 per cent.

Job disamenities, job satisfaction, quit intentions, and actual separations: putting the pieces together

We analyze the potential role of adverse working conditions at the workplace in the determination of employees’ quit behavior. Our data contain both detailed information on perceived job disamenities, job satisfaction, and quit intentions from a cross-section survey and information on employees’ actual job switches from longitudinal register data that can be linked to the survey. Reduced-form models show that employees facing adverse working conditions tend to have greater intentions to switch jobs and search for new matches more frequently. Multivariate probit models point out that job dissatisfaction that arises in adverse working conditions is related to job search and this in turn is related to actual job switches

Age and productivity: evidence from linked employer employee data

In most Western, industrialised countries the workforce is ageing rapidly. In order to assess the possible consequences of an ageing workforce, this paper measures the impact of changes in the age structure of establishments on productivity using representative linked employer-employee panel data. We take into account that the levels as well as the changes in the age structure of establishments and their production are likely to be simultaneously determined and apply dynamic GMM methods. We find that establishment productivity increases with the share of employees until the age of 50-55 and only decreases slightly afterwards. Our findings suggest that previous estimations are biased because they either do not take into account endogeneity, time dependencies, or crucial information correlated with age shares and productivity. Large standard deviations point to important variation in the age productivity profile among establishments. --ageing workforce,age,productivity,LEED,system GMM

Job disamenities, job satisfaction, quit intentions, and actual separations: putting the pieces together

We analyze the potential role of adverse working conditions at the workplace in the determination of employees’ quit behavior. Our data contain both detailed information on perceived job disamenities, job satisfaction, and quit intentions from a cross-section survey and information on employees’ actual job switches from longitudinal register data that can be linked to the survey. Reduced-form models show that employees facing adverse working conditions tend to have greater intentions to switch jobs and search for new matches more frequently. Multivariate probit models point out that job dissatisfaction that arises in adverse working conditions is related to job search and this in turn is related to actual job switches.working conditions; job satisfaction; on-the-job search; job separation; quits