thesis

Time Aggregation Bias in Discrete Time Models of Aggregate Duration Data

Abstract

The paper focuses on the dynamics of unemployment in the Czech Republic over the period 1992-–2007. Unemployment dynamics are elaborated in terms of unemployment inflows and unemployment duration. The paper contributes to the literature dealing with discrete time models of aggregate unemployment duration data by accounting for time aggregation bias. Another innovation relates to the way we examine the impact of time-varying macroeconomic conditions on individual duration dependence and unemployment inflow composition. The estimation results suggest that both unobserved heterogeneity and individual duration dependence are present. The relative impact of the two factors on the aggregate duration dependence, however, changes over time. Next, seasonal effects on the individual hazard rate are detected. We do not find a significant role of macroeconomic influences. Finally, we demonstrate the profound influence of time aggregation of duration data on unemployment duration parameters for empirical data for France and the Czech Republic.Duration dependence, time aggregation bias, unemployment, unemployment duration.

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