Bo E. Honoré

This paper builds on Bonhomme (2012) to develop a method to systematically construct moment conditions for dynamic panel data logit models with fixed effects. After introducing the moment conditions obtained in this way, we explore their implications for identification and estimation of the model parameters that are common to all individuals, and we find that those common model parameters are estimable at root-n rate for many more dynamic panel logit models than has been appreciated by the existing literature. In the case where the model contains one lagged variable, the moment conditions in Kitazawa (2013, 2016) are transformations of a subset of ours. A GMM estimator that is based on the moment conditions is shown to perform well in Monte Carlo simulations and in an empirical illustration to labor force participation.

This paper introduces measures for how each moment contributes to the precision of parameter estimates in GMM settings. For example, one of the measures asks what would happen to the variance of the parameter estimates if a particular moment was dropped from the estimation. The measures are all easy to compute. We illustrate the usefulness of the measures through two simple examples as well as an application to a model of joint retirement planning of couples. We estimate the model using the UK-BHPS, and we find evidence of complementarities in leisure. Our sensitivity measures illustrate that the estimate of the complementarity is primarily informed by the distribution of differences in planned retirement dates. The estimated econometric model can be interpreted as a bivariate ordered choice model that allows for simultaneity. This makes the model potentially useful in other applications.

In this paper we specify and use a new duration model to study joint retirement in married couples using the Health and Retirement Study. Whereas conventionally used models cannot account for joint retirement, our model admits joint retirement with positive probability, allows for simultaneity and nests the traditional proportional hazards model. In contrast to other statistical models for simultaneous durations, it is based on Nash bargaining and it is therefore interpretable in terms of economic behavior. We provide a discussion of relevant identifying variation and estimate our model using indirect inference. The main empirical finding is that the simultaneity seems economically important. In our prefered specification the indirect utility associated with being retired increases by approximately 10% if one's spouse is already retired. By comparison, a defined benefit pension plan increases indirect utility by 20-30%. The estimated model also predicts that the indirect effect of a change in husbands' pension plan on wives' retirement dates is about 10% of the direct effect on the husbands