HOW DESTRUCTIVE IS CREATIVE DESTRUCTION? EFFECTS OF JOB LOSS ON JOB MOBILITY,WITHDRAWAL AND INCOME

We analyze short and long‐term effects of worker displacement. Our sample consists of male workers displaced from Norwegian manufacturing plants. We find that displacement increases the probability of leaving the labor force by 31%. The drop‐out rate from the labor force is particularly high in the first years following displacement. The average earnings effects for those who remain in the labor force are moderate, a 3% loss relative to non‐displaced workers after seven years. Splitting displaced workers on within‐ and between‐firm movers, we find that the estimated earnings loss is entirely driven by between‐firm movers who experience a 3.6% loss. Transfers to other plants within multi‐plant firms upon displacement are quite common. Our results support the view that human capital is partly firm specific and partly industry specific. We find no evidence suggesting that human capital is plant specific.     

The role of the constant and linear terms in cointegration analysis of nonstationary variables

The autoregressive model for cointegrated variables is analyzed with respect to the role of the constant and linear terms. Various models for 1(1) variables defined by restrictions on the deterministic terms are discussed, and it is shown that statistical inference can be performed by reduced rank regression. The asymptotic distributions of the test statistics and estimators are found. A similar analysis is given for models for 1(2) variables with a constant term.     

Gaussian models for degradation processes-part I: Methods for the analysis of biomarker data

We present two stochastic models that describe the relationship between biomarker process values at random time points, event times, and a vector of covariates. In both models the biomarker processes are degradation processes that represent the decay of systems over time. In the first model the biomarker process is a Wiener process whose drift is a function of the covariate vector. In the second model the biomarker process is taken to be the difference between a stationary Gaussian process and a time drift whose drift parameter is a function of the covariates. For both models we present statistical methods for estimation of the regression coefficients. The first model is useful for predicting the residual time from study entry to the time a critical boundary is reached while the second model is useful for predicting the latency time from the infection until the time the presence of the infection is detected. We present our methods principally in the context of conducting inference in a population of HIV infected individuals.     

Stubbornness,Power, and Equilibrium Selection in Repeated Games with Multiple Equilibria

Axelord’s [(1970), Conflict of Interest, Markham Publishers, Chicago] index of conflict in 2 × 2 games with two pure strategy equilibria has the property that a reduction in the cost of holding out corresponds to an increase in conflict. This article takes the opposite view, arguing that if losing becomes less costly, a player is less likely to gamble to win, which means that conflict will be less frequent. This approach leads to a new power index and a new measure of stubbornness, both anchored in strategic reasoning. The win probability defined as power constitutes an equilibrium refinement which differs from Harsanyi and Selten’s [(1988), A General Theory of Equilibrium Selection in Games, MIT Press, Cambridge] refinement. In contrast, Axelrod’s approach focuses on preferences regarding divergences from imaginary outmost rewards that cannot be obtained jointly. The player who is less powerful in an asymmetric one-shot game becomes more powerful in the repeated game, provided he or she values the future sufficiently more than the opponent. This contrasts with the view that repetition induces cooperation, but conforms with the expectation that a more patient player receives a larger share of the pie.