Spousal Complementarity in Home Production

A bstract .   Economists have increasingly recognized the growing role of married women in the labor market by treating the labor supply decisions of married couples as joint decisions. However, they have yet to apply the same reasoning to home production. We build a more complete model of household time allocation that consists of a system of simultaneous equations estimating hours of labor supply and home production. Using data on white couples from Wave XXV of the Panel Study of Income Dynamics, we find that working wives act as if their husbands are substitutes for home production while other wives do not. Husbands' responses to their wives' behavior depends upon whether children are present.     

Serial Nonparticipation in Repeated Discrete Choice Models

We consider alternative econometric strategies for addressing serial nonparticipation, that is, repeated choice of the same alternative or same type of alternative across a series of choice occasions, in data typically analyzed within the repeated discrete choice framework. Single and double hurdle variants of the repeated discrete choice model are developed and applied to choice experiment and multisite seasonal recreation demand data. Our results suggest that hurdle models can generate significant improvements in statistical fit and qualitatively different policy implications, particularly in choice experiment applications where the proper treatment of serial nonparticipation is relatively more ambiguous.     

Competition,cooperation, and corporate culture

Cooperation between workers can be of substantial value to a firm, yet its level often varies substantially between firms. We show that these differences can unfold in a competitive labor market if workers have heterogeneous social preferences and preferences are private information. In our model, workers differ in their willingness to cooperate voluntarily. We show that there always exists a separating equilibrium in which workers self‐select into firms that differ in their monetary incentives as well as their level of worker cooperation. Our model highlights the role of sorting and worker heterogeneity in the emergence of heterogeneous corporate cultures. It also provides a new explanation for the coexistence of nonprofit and for‐profit firms.

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Fitting dynamic factor models to non-stationary time series

Factor modelling of a large time series panel has widely proven useful to reduce its cross-sectional dimensionality. This is done by explaining common co-movements in the panel through the existence of a small number of common components, up to some idiosyncratic behaviour of each individual series. To capture serial correlation in the common components, a dynamic structure is used as in traditional (uni- or multivariate) time series analysis of second order structure, i.e. allowing for infinite-length filtering of the factors via dynamic loadings. In this paper, motivated from economic data observed over long time periods which show smooth transitions over time in their covariance structure, we allow the dynamic structure of the factor model to be non-stationary over time by proposing a deterministic time variation of its loadings. In this respect we generalize the existing recent work on static factor models with time-varying loadings as well as the classical, i.e. stationary, dynamic approximate factor model. Motivated from the stationary case, we estimate the common components of our dynamic factor model by the eigenvectors of a consistent estimator of the now time-varying spectral density matrix of the underlying data-generating process. This can be seen as a time-varying principal components approach in the frequency domain. We derive consistency of this estimator in a “double-asymptotic” framework of both cross-section and time dimension tending to infinity. The performance of the estimators is illustrated by a simulation study and an application to a macroeconomic data set.