Predicting marital satisfaction using prepare: a replication study*

This study clearly replicated the previous findings which demonstrated the predictive validity of PREPARE. Like the previous study, this longitudinal study was a 3-year follow-up of 179 couples who took PREPARE during their engagement. As in the initial longitudinal study, PREPARE predicted, with about 80% accuracy, couples who got divorced from those that were happily married. Also, the same linear trend in PREPARE scores was found (highest to lowest scores): happily married, unhappily married, cancelled/delayed marriage, and separated/divorced. This study further indicates the importance of the premarital period as the foundation for marriage and the ability of PREPARE to identify high-risk premarital couples who could benefit from premarital counseling. Premarital counseling could potentially help these high risk couples develop a more satisfying marriage.     

Dynamic capacity adjustments with reactive customers

In this paper we develop a behavioural model in which customers come and go based on their perception of waiting time (relative to other facilities) while managers gradually adjust the capacity of the facility based on their perception of demand. We explicitly account for the difference in access to information between existing and potential customers, which implies that the perception of potential customers lags the perception of current customers. We investigate the outcome of the interaction between these simultaneous dynamic decision processes, and in particular the impact of the lags created by the perception formation process and the time to implement desired changes in capacity. These multiple delays may result in customers and service provider being out of step: customers walk away just as the service provider manages to bring extra capacity online.     

IV Quantile Regression for Group‐Level Treatments,With an Application to the Distributional Effects of Trade

We present a methodology for estimating the distributional effects of an endogenous treatment that varies at the group level when there are group‐level unobservables, a quantile extension of Hausman and Taylor, 1981. Because of the presence of group‐level unobservables, standard quantile regression techniques are inconsistent in our setting even if the treatment is independent of unobservables. In contrast, our estimation technique is consistent as well as computationally simple, consisting of group‐by‐group quantile regression followed by two‐stage least squares. Using the Bahadur representation of quantile estimators, we derive weak conditions on the growth of the number of observations per group that are sufficient for consistency and asymptotic zero‐mean normality of our estimator. As in Hausman and Taylor, 1981, micro‐level covariates can be used as internal instruments for the endogenous group‐level treatment if they satisfy relevance and exogeneity conditions. Our approach applies to a broad range of settings including labor, public finance, industrial organization, urban economics, and development; we illustrate its usefulness with several such examples. Finally, an empirical application of our estimator finds that low‐wage earners in the United States from 1990 to 2007 were significantly more affected by increased Chinese import competition than high‐wage earners.     

Method Madness

I caution you not to expect a cookbook solution to your difficulty. I cannot tell you what to do in ten easy steps. Precious few successful career searches are conducted in so mechanical a fashion. You must decide the best sequence of events for yourself. —Howard Figler, The Complete Job Search Handbook     

A Mathematical Approach to Categorization and Labeling of Qualitative Data: the Latent Categorization Method

As text databases increasingly become available to researchers, the limits to human cognition are rapidly reached. Focusing on examining objective realities, this paper introduces the latent categorization method, a novel new research method for analysis of large and midsize data sets. This method clusters text artifacts and extracts the words that were most important in creating the clusters. Further, it demonstrates a set of techniques for extracting knowledge from a representative data set involving 6135 abstracts from a variety of business‐related journals .     

Hutterite fecundability by age and parity: Strategies for frailty modeling of event histories

Effective fecundability declines with age and parity. Furthermore, women differ in their effective fecundability: some women have persistently low or high monthly chances of live-birth conception. Estimates are presented concerning the magnitude of these effects in a natural-fertility population: 406 Hutterite women in North America who had 3,206 births, largely in the 1940s and 1950s. The estimates are based on models that incorporate the effects of persistent heterogeneity and that use the full information provided by multiple-spell duration data. In addition, hazards rather than probabilities are modeled, piecewise linear hazard functions are used, and age and parity effects are decomposed systematically. These methods permit the development of more elaborate models of changing fecundability and of heterogeneity in postpartum amenorrhea.