Treatment Evaluation in the Presence of Sample Selection

Sample selection and attrition are inherent in a range of treatment evaluation problems such as the estimation of the returns to schooling or training. Conventional estimators tackling selection bias typically rely on restrictive functional form assumptions that are unlikely to hold in reality. This paper shows identification of average and quantile treatment effects in the presence of the double selection problem into (i) a selective subpopulation (e.g., working—selection on unobservables) and (ii) a binary treatment (e.g., training—selection on observables) based on weighting observations by the inverse of a nested propensity score that characterizes either selection probability. Weighting estimators based on parametric propensity score models are applied to female labor market data to estimate the returns to education.     

Marginal zero-inflated regression models for count data

Data sets with excess zeroes are frequently analyzed in many disciplines. A common framework used to analyze such data is the zero-inflated (ZI) regression model. It mixes a degenerate distribution with point mass at zero with a non-degenerate distribution. The estimates from ZI models quantify the effects of covariates on the means of latent random variables, which are often not the quantities of primary interest. Recently, marginal zero-inflated Poisson (MZIP; Long et al. [A marginalized zero-inflated Poisson regression model with overall exposure effects. Stat. Med. 33 (2014), pp. 5151–5165]) and negative binomial (MZINB; Preisser et al., 2016) models have been introduced that model the mean response directly. These models yield covariate effects that have simple interpretations that are, for many applications, more appealing than those available from ZI regression. This paper outlines a general framework for marginal zero-inflated models where the latent distribution is a member of the exponential dispersion family, focusing on common distributions for count data. In particular, our discussion includes the marginal zero-inflated binomial (MZIB) model, which has not been discussed previously. The details of maximum likelihood estimation via the EM algorithm are presented and the properties of the estimators as well as Wald and likelihood ratio-based inference are examined via simulation. Two examples presented illustrate the advantages of MZIP, MZINB, and MZIB models for practical data analysis.     

THE COMPETITIVE RETURNS TO THE GLOBAL SEARCH FOR TALENT: PROFESSIONAL SPORTS MARKETS AND FOREIGNERS

We examine the geographical and racial diversity of a market's labor supply. While the likely impact of expanding supply is to increase the level of productivity, it is not obvious what impact the expansion would have on the overall level of competition. If the added labor increases productivity differentials or are disproportionately populated on high achieving firms, then the likely result would be greater imbalance. We find that while increases in the foreign‐born component are associated with an increase in the overall level of competition, the impact has diminished across time. (JEL C22, D23, D30)     

PROVIDING GLOBAL PUBLIC GOODS: ELECTORAL DELEGATION AND COOPERATION

This study experimentally examines the effect of electoral delegation on providing global public goods shared by several groups. Each group elects one delegate who can freely decide on each group member's contribution to the global public goods. Our results show that people mostly vote for delegates who assign equal contributions for every group member. However, in contrast to standard theoretical predictions for our delegation mechanism, unequal contributions across groups drive cooperation down over time, and it decreases efficiency by almost 50% compared to the selfish benchmark. This pattern is not driven by delegates trying to exploit their fellow group members, as indicated by theory. It is driven by conditional cooperation of delegates across groups. Since one of the potential sources of the resulting inefficiency is the polycentric nature of global public goods provision together with other‐regarding preferences, we use the term P‐inefficiency to describe our finding. (JEL C92, D72, H41)     

Learning discrete decomposable graphical models via constraint optimization

Statistical model learning problems are traditionally solved using either heuristic greedy optimization or stochastic simulation, such as Markov chain Monte Carlo or simulated annealing. Recently, there has been an increasing interest in the use of combinatorial search methods, including those based on computational logic. Some of these methods are particularly attractive since they can also be successful in proving the global optimality of solutions, in contrast to stochastic algorithms that only guarantee optimality at the limit. Here we improve and generalize a recently introduced constraint-based method for learning undirected graphical models. The new method combines perfect elimination orderings with various strategies for solution pruning and offers a dramatic improvement both in terms of time and memory complexity. We also show that the method is capable of efficiently handling a more general class of models, called stratified/labeled graphical models, which have an astronomically larger model space.     

Emotional Transactions in the Paris Subway: Combining Naturalistic Videotaping,Objective Facial Coding and Sequential Analysis in the Study of Nonverbal Emotional Behavior

We report on what, to our knowledge, represents the first study of nonverbal emotional behavior in crowded public places combining naturalistic videotaping of situated activity, objective coding of facial movement, and sequential analysis of behavior. In the first part of the study we argue that passengers do not lose emotional sensitivity to physical contact as density (passengers per square meter) increases, which indicates that physical contact is experienced as a territorial intrusion regardless of crowdedness. In the second part of the study, we suggest that passengers resolve the emotions due to intrusive physical contacts through two interactional strategies involving facial movements usually interpreted as “expressions of emotions.” Since proxemic violations seem to represent a pervasive emotion elicitor, the protocol can be extended to other means of transportation and replicated in other locations. We conclude that the methodology provides an effective tool for theory-building in the study of nonverbal emotional behavior.     

Impacts of urban sprawl on species richness of plants,butterflies, gastropods and birds: not only built-up area matters

Urban growth is a major factor of global environmental change and has important impacts on biodiversity, such as changes in species composition and biotic homogenization. Most previous studies have focused on effects of urban area as a general measure of urbanization, and on few or single taxa. Here, we analyzed the impacts of the different components of urban sprawl (i.e., scattered and widespread urban growth) on species richness of a variety of taxonomic groups covering mosses, vascular plants, gastropods, butterflies, and birds at the habitat and landscape scales. Besides urban area, we considered the average age, imperviousness, and dispersion degree of urban area, along with human population density, to disentangle the effects of the different components of urban sprawl on biodiversity. The study was carried out in the Swiss Plateau that has undergone substantial urban sprawl in recent decades.Vascular plants and birds showed the strongest responses to urban sprawl, especially at the landscape scale, with non-native and ruderal plants proliferating and common generalist birds increasing at the expense of specialist birds as urban sprawl grew. Overall, urban area had the greatest contribution on such impacts, but additional effects of urban dispersion (i.e., increase of non-native plants) and human population density (i.e., increases of ruderal plants and common generalist birds) were found. Our findings support the hypothesis that negative impacts of urban sprawl on biodiversity can be reduced by compacting urban growth while still avoiding the formation of very densely populated areas.