INCIDENCE AND CONSEQUENCES OF RISK‐TAKING BEHAVIOR IN TOURNAMENTS—EVIDENCE FROM THE NBA

We empirically explore the relevance and efficiency of risk‐taking behavior in tournaments. We use data from the National Basketball Association (NBA) and measure risk‐taking by the fraction of three‐point shots in basketball games. We examine how point differences between teams during games affect their subsequent risk‐taking behavior. It is found that teams that are trailing are more likely to increase their use of three‐point shots. We additionally analyze the consequences of this change in behavior. Enhanced risk‐taking is inefficient in the vast majority of cases and is only beneficial if a team is trailing by a rather large margin. We discuss possible explanations for these decision errors. (JEL M5, D81, J30)     

Attitudes of social work students towards older people

Demographic ageing is a challenge for many countries. Even though Turkey has a relatively younger demographic composition, the proportion of the older people (65+) within the population is rapidly increasing. Within this framework, older people are becoming more important clients for both social work students and social workers in Turkey. This study aims to reveal the attitudes of social work students towards older people and determine the various factors that affect their views on older persons. In the scope of the project, Kogan's Attitude Towards Old People Scale was applied to 419 social work undergraduate students at a university located in Central Anatolia. The findings showed that social work students scored a mean of 130.96 and they generally had positive attitudes towards older people. The correlation between year of study, gender and age was not statistically significant. However, having lived mostly in urban areas was positively correlated with the mean Kogan scores and this finding was found to be statistically significant. Exposure to personal contact with older people at both the personal and professional levels was influential in shaping attitudes about the older people.     

A Note on Exponentially Smoothed Seasonal Differences

Filtering economic time series can be justified if variations within a certain frequency interval are relevant for the problem at hand. It is shown here that exponential smoothing of seasonal differences provides a simple means of damping short oscillations, including seasonal ones.     

Subjective Recognition of Emotional Expressions in Face Transplant Patients

One of the most prevalent problems in face transplant patients is an inability to generate facial expression of emotions. The purpose of this study was to measure the subjective recognition of patients’ emotional expressions by other people. We examined facial expression of six emotions in two facial transplant patients (patient A = partial, patient B = full) and one healthy control using video clips to evoke emotions. We recorded target subjects’ facial expressions with a video camera while they were watching the clips. These were then shown to a panel of 130 viewers and rated in terms of degree of emotional expressiveness on a 7-point Likert scale. The scores for emotional expressiveness were higher for the healthy control than they were for patients A and B, and these varied as a function of emotion. The most recognizable emotion was happiness. The least recognizable emotions in Patient A were fear, surprise, and anger. The expressions of Patient B scored lower than those of Patient A and the healthy control. The findings show that partial and full-face transplant patients may have difficulties in generating facial expression of emotions even if they can feel those emotions, and different parts of the face seem to play critical roles in different emotional expressions.     

Separate Ratio Estimators for the Population Variance in Stratified Random Sampling

We propose separate ratio estimators for population variance in stratified random sampling. We obtain mean square error equations and compare proposed estimators about efficiency with each other. By these comparisons, we find the conditions which make proposed estimators more efficient than others. It has been shown that proposed classes of estimators are more efficient than usual unbiased estimator. We find that separate ratio estimators are more efficient than combined ratio estimators for population variance. The theoretical results are supported by a numerical illustration with original data. A simulation study is also carried out to investigate empirical performance of estimators.     

Ensuring Pareto Optimality by Referendum Voting

We consider a society confronting the decision of accepting or rejecting a list of (at least two) proposals. Assuming separability of preferences, we show the impossibility of guaranteeing Pareto optimal outcomes through anonymous referendum voting, except in the case of an odd number of voters confronting precisely two proposals. In this special case, majority voting is the only anonymous social choice rule which guarantees Pareto optimal referendum outcomes.     

Clustering the mixed panel dataset using Gower's distance and k-prototypes algorithms

ABSTRACT

Panel datasets have been increasingly used in economics to analyze complex economic phenomena. Panel data is a two-dimensional array that combines cross-sectional and time series data. Through constructing a panel data matrix, the clustering method is applied to panel data analysis. This method solves the heterogeneity question of the dependent variable, which belongs to panel data, before the analysis. Clustering is a widely used statistical tool in determining subsets in a given dataset. In this article, we present that the mixed panel dataset is clustered by agglomerative hierarchical algorithms based on Gower's distance and by k-prototypes. The performance of these algorithms has been studied on panel data with mixed numerical and categorical features. The effectiveness of these algorithms is compared by using cluster accuracy. An experimental analysis is illustrated on a real dataset using Stata and R package software.