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This paper analyzes the performance of heteroskedasticity-and-autocorrelation-consistent (HAC) covariance matrix estimators in which the residuals are prewhitened using a vector autoregressive (VAR) filter. We highlight the pitfalls of using an arbitrarily fixed lag order for the VAR filter, and we demonstrate the benefits of using a model selection criterion (either AIC or BIC) to determine its lag structure. Furthermore, once data-dependent VAR prewhitening has been utilized, we find negligible or even counter-productive effects of applying standard kernel-based methods to the prewhitened residuals; that is, the performance of the prewhitened kernel estimator is virtually indistinguishable from that of the VARHAC estimator.
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This paper evaluates a class of endogenous job destruction models based on how well they explain the observed experiences of displaced workers. We show that pure reallocation models in which relationship-specific productivity drifts downward over time are difficult to reconcile with the evidence on postdisplacement wages and displacement rates. Pure reallocation models with upward drift can explain the evidence, but implausibly large and persistent negative productivity shocks are required to generate displacements. Combining upward drift with outside benefits or moral hazard as additional motives for displacement makes it possible to explain the evidence with much smaller shocks. Propagation of aggregate shocks, welfare implications of displacement, upgrade of relationships in lieu of displacement, and learning effects are also discussed.
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This paper develops a theoretical framework for analyzing contracting imperfections in long-term employment relationships. We focus chiefly on limited enforceability and limited worker liquidity. Inefficient severance of employment relationships, payment of efficiency wages, the relative response of wages and employment to business cycle shocks, and the propagation of these shocks are linked to the nature of contracting imperfections.
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