Estimation of long-run inefficiency levels: a dynamic frontier approach

Cornwell, Schmidt, and Sickles (1990) and Kumbhakar (1990), among others, developed stochasticfrontier production models which allow firm specific inefficiency levels to change over time. These studies assumed arbitrary restrictions on the short-run dynamics of efficiency levels which have little theoretical justification. Further, the models are inappropriate for estimation of long-run efficiencies. We consider estimation of an alternative frontier model in which firmspecific technical inefficiency levels are autoregressive. This model is particularly useful to examine a potential dynamic link between technical innovations and production inefficiency levels. We apply our methodology to a panel of US airlines.     

Optimal designs for response functions with a downturn

In many toxicological assays, interactions between primary and secondary effects may cause a downturn in mean responses at high doses. In this situation, the typical monotonicity assumption is invalid and may be quite misleading. Prior literature addresses the analysis of response functions with a downturn, but so far as we know, this paper initiates the study of experimental design for this situation. A growth model is combined with a death model to allow for the downturn in mean doses. Several different objective functions are studied. When the number of treatments equals the number of parameters, Fisher information is found to be independent of the model of the treatment means and on the magnitudes of the treatments. In general, A- and D_A-optimal weights for estimating adjacent mean differences are found analytically for a simple model and numerically for a biologically motivated model. Results on c-optimality are also obtained for estimating the peak dose and the EC₅₀ (the treatment with response half way between the control and the peak response on the increasing portion of the response function). Finally, when interest lies only in the increasing portion of the response function, we propose composite D-optimal designs.     

On the historical determinants of third sector strength: A qualitative comparative analysis

This study proposes a theoretical explanation for the main causes of the third sector's strength. A Boolean comparative analysis based mainly on the theoretical frameworks of Rokkan and Esping-Andersen indicates that the combination of state-supported urban interests and Protestantism are necessary conditions. This result is very close to Max Weber's explanation of civil society which presupposes the facilitating role of the autonomous state. Thus, the empirical results are reinterpreted within the context of a Weberian explanatory framework. The implications of this endeavor within the historical context of developing countries are further explicated.     

It's More Than an M‐shape: The Political Economy of Female Non‐Standard Workers in the Republic of Korea

This study examines the re‐entrance of female workers into the Korean labor market. We highlight that women in their 40s have the highest rate of employment among all female workers and that a large proportion of these women are entering into non‐standard employment. In approaching this question, we examine the political economy of this phenomenon by first discussing the demand side of the Korean labor market using the gendering of the varieties of capitalism argument and then the supply side with the work–life balance argument. When examining re‐entrance into the labor market, women with general skills with lower education and higher education both found it more feasible to re‐enter the labor market as non‐standard workers. While work–life balance is a prominent reason for women's choice of opting out of the labor market, work–life balance choice mattered less for women re‐entering the labor market as non‐standard workers in their 40s and 50s but instead firmly based skill formation mattered more. In addition, the retail service industry is suggested to absorb a large number of female workers with lower skill levels who would have had difficulties in re‐entering other male‐oriented companies.     

Effects of correlation and missing data on sample size estimation in longitudinal clinical trials

In longitudinal clinical trials, a common objective is to compare the rates of changes in an outcome variable between two treatment groups. Generalized estimating equation (GEE) has been widely used to examine if the rates of changes are significantly different between treatment groups due to its robustness to misspecification of the true correlation structure and randomly missing data. The sample size formula for repeated outcomes is based on the assumption of missing completely at random and a large sample approximation. A simulation study is conducted to investigate the performance of GEE sample size formula with small sample sizes, damped exponential family of correlation structure and non‐ignorable missing data. Copyright © 2008 John Wiley & Sons, Ltd.     

Social affinity among top managerial executives of large corporations in Korea

Korea is a society subject to quite diverse social forces. Modernization should encourage reform, but the yoke of tradition restrains this tendency. This paper examines the patterns of preferential treatment of executives, based on family, school, and regional ties, by the owners of large Jaebol corporations in Korea. We found that about 21% of the total number of executive positions in the large corporations were occupied by individuals who had some type of family tie with the owners of the corporations. Also, there is a strong tendency of corporation owners to employ the executives of the same regional origin of birth as their own, but the affinity based on school ties was not as strong as that of regional origin. The findings of this study seem to support the arguments of previous studies that claimed a trust factor as a main cause of social similarity and affinity between the owners and executives in corporations.An earlier version of this paper was presented at the annual meetings of the American Sociological Association, August 17–22, 1987, Chicago, Illinois.     

Predictive Modeling and Categorizing Likelihoods of Quarantine Pest Introduction of Imported Propagative Commodities from Different Countries

The present study investigates U.S. Department of Agriculture inspection records in the Agricultural Quarantine Activity System database to estimate the probability of quarantine pests on propagative plant materials imported from various countries of origin and to develop a methodology ranking the risk of country–commodity combinations based on quarantine pest interceptions. Data collected from October 2014 to January 2016 were used for developing predictive models and validation study. A generalized linear model with Bayesian inference and a generalized linear mixed effects model were used to compare the interception rates of quarantine pests on different country–commodity combinations. Prediction ability of generalized linear mixed effects models was greater than that of generalized linear models. The estimated pest interception probability and confidence interval for each country–commodity combination was categorized into one of four compliance levels: “High,” “Medium,” “Low,” and “Poor/Unacceptable,” Using K‐means clustering analysis. This study presents risk‐based categorization for each country–commodity combination based on the probability of quarantine pest interceptions and the uncertainty in that assessment.     

Recognition of Facial Expressions of Negative Emotions in Romantic Relationships

Previous research has demonstrated that individuals who were accurate at recognizing facial expressions of emotions reported better relationships with family and friends. The purpose of the present study was to test whether the ability to recognize facial expressions of negative emotions predicted greater relationship satisfaction with their romantic relationships and whether this link was mediated by constructive responses to conflict. Participants currently involved in a romantic relationship completed a validated performance measure of recognition of facial expressions and afterwards reported on the responses they engaged in during conflict with their romantic partner and rated their romantic relationship satisfaction. Results showed that accurate recognition of facial expressions of negative emotions (anger, contempt, disgust, fear, and sadness) predicted less conflict engaging behaviors during conflict with their romantic partners (but not positive problem solving and withdrawal), which in turn predicted greater relationship satisfaction. The present study is the first to show that the ability to recognize facial expressions of negative emotions is related to romantic relationship satisfaction and that constructive responses to conflict such as less conflict engaging behaviors, mediate this process.     

Principal weighted logistic regression for sufficient dimension reduction in binary classification

Sufficient dimension reduction (SDR) is a popular supervised machine learning technique that reduces the predictor dimension and facilitates subsequent data analysis in practice. In this article, we propose principal weighted logistic regression (PWLR), an efficient SDR method in binary classification where inverse-regression-based SDR methods often suffer. We first develop linear PWLR for linear SDR and study its asymptotic properties. We then extend it to nonlinear SDR and propose the kernel PWLR. Evaluations with both simulated and real data show the promising performance of the PWLR for SDR in binary classification.