This paper presents new econometric methods for the empirical analysis of individual labor market histories. The techniques developed here extend previous work on continuous time models in four ways: (1) A structural economic interpretation of these models is presented. (2) Time varying explanatory variables are introduced into the analysis in a general way. (3) Unobserved heterogeneity components are permitted to be correlated across spells. (4) A flexible model of duration dependence is presented that accommodates many previous models as a special case and that permits tests among competing specifications within a unified framework. We contrast our methods with more conventional discrete time and regression procedures. The parameters of continuous time models are in- variant to the sampling time unit used to record observations. Problems plague the regression approach to analyzing duration data which do not plague the likelihood approach advocated in this paper. The regression approach cannot be readily adopted to accommodate time varying explanatory variables. The functional forms of regression functions depend on the time paths of the explanatory variables. Ad hoc solutions to this problem can make exogenous variables endogenous to the model and so can induce simultaneous equations bias. Two sets of empirical results are presented. A major conclusion of the first analysis is that the discrete time Markov model widely used in labor market analysis is inconsistent with the data. The second set of empirical results is a test of the hypothesis that "unemployment" and "out of the labor force" are behaviorally different labor market states. Contrary to recent claims, we find that they are separate states for our sample of young men

In the last twenty years there has been an explosion of economic research on labour force dynamics. This book focuses on the methods by which behavioural theories of labour force dynamics have been empirically implemented.

This volume consists of papers presented at a conference on labor mar ket theory held in August 1982 at Sandbjerg - a manor house situated in S0nderjylland owned by University of Aarhus. The conference was ar ranged to mark the start of a labor market research project utilizing the first Danish longitudinal data set. The conference was meant to present a survey of the recent developments within labor market theory where unemployment at a given time is seen as a result of flows of in dividuals between the various labor market states. Consequently, al most all papers deal with aspects of transitions on the labor market. The first paper by Andersen discusses from a statisticians point of view how it is possible to analyze longitudinal data on labor market dynamics using statistical models for multivariate counting processes. Models including general calendar time specific intensities and models specifying the distribution of spell lengths as well as their combina tions are included. Finally it is demonstrated how the effect of exo genous, endogenous, and other time dependent variables can be model led. This paper does also contain an example of the application of the model.

In the last twenty years there has been an explosion of economic research on labor force dynamics; the movement of individuals between labor force states. This book focuses on the methods by which behavioral theories of labor force dynamics have been empirically implemented. Most attention is paid to the partial equilibrium two-state transitional model of job search behavior. That model is the foundation for much of our thinking about the nature of unemployment at both the individual and aggregate levels. Although the basic formulation has remained the same, approaches to the empirical implementation of such models has changed dramatically.

This paper proposes a hidden state Markov model (HMM) that incorporates workers’ unobserved labor market attachment into the analysis of labor market dynamics. Unlike previous literature, which typically assumes that a worker’s observed labor force status follows a first-order Markov process, the proposed HMM allows workers with the same labor force status to have different history-dependent transition probabilities. I show that the estimated HMM generates labor market transition probabilities that match those observed in the data, while the first-order Markov model (FOM) and its many-state extensions cannot. Even compared with the extended FOM, the HMM improves the fit of the empirical transition probabilities by a factor of 30. I apply the HMM to (1) calculate the long-run consequences of separation from stable employment, (2) study evolutions of employment stability across different demographic groups over the past several decades, (3) compare the dynamics of labor market flows during the Great Recession to those during the 1981 recession, and (4) highlight the importance of looking beyond distributions of current labor force status.

Selected papers from a conference held in honour of Professor Dale T. Mortensen upon the occasion of his 65th birthday. It includes papers on some of Professor Dale T. Mortensen's current research topics, as well as additional theoretical papers, and micro- and macro-econometric papers.