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.     

Problem Gambling Associated with Violent and Criminal Behaviour: A Danish Population-Based Survey and Register Study

This study compares the number of criminal charges among problem gamblers (N = 384) and non-problem gamblers including non-gamblers (N = 18,241) and examines whether problem gambling is more strongly associated with income-generating crimes like theft, fraud and forgery than other types of crimes such as violent crimes. A cohort study was carried out, based on data from the Danish Health and Morbidity Surveys in 2005 and 2010, which were linked at the individual level with data from The Danish National Criminal Register. Multiple logistic regression analyses were used to determine the association between problem gambling and charges for different categories of crime. We found that problem gamblers had significantly higher odds of being charged than non-problem gamblers (adjusted odds ratio 1.5; 95 % confidence interval 1.1–1.9). The odds ratio for economic crime charges was 2.6 (1.5–4.5), for violence charges 2.2 (1.1–4.5), and for drug charges 3.7 (1.7–8.0). For road traffic charges the odds ratio was 1.3 (1.0–1.8). Hence, there was a strong association between problem gambling and being charged except for road traffic charges; however the association was not stronger for economic charges than for violence and drug charges.     

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 .