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.