Curve of Correlation for Time Series

The curve of correlation is a measure of local correlation between two random variables X and Y at the point X = x of the support of this variable. This article studies this local measure using the theory of time series for bivariate and univariate stationary stochastic process. We suggest local polynomial estimators for time series observing their consistency both theoretically and through simulations. For this, different sizes of series, bandwidths, and kernels, besides lags and models’ configurations were used. Applications have also been made using the daily returns of two financial series.     

The Rationality of Under‐employing the Best‐performing Soccer Players

Abstract. This paper analyses the influence of sport performance (productivity) and other variables measuring the economic contribution of soccer players, upon the coach's decision of selecting a particular player. Using as dependent variable the proportion of time that individuals play in the Spanish professional soccer league, the paper concludes that players' economic market value does significantly affect the coach's choice, revealing the existence of other aims different from maximizing sport performance. We also examine the type of discrimination associated with lower chances of playing, which leads to smaller earnings and poorer career opportunities. The empirical evidence does not support discrimination due to nationality.     

On the Strong Consistency of Ridge Estimates

In this article, we establish strong consistency of the ridge estimates using extended results for the strong consistency of the least squares estimates in multiple regression models which discard the usual assumption of null mean value for the errors and only requires them to be i.i.d. with absolute moment of order r (0 < r ? 1).     

Pivotal Quantities Based on Sequential Data: A Bootstrap Approach

A bootstrap algorithm is provided for obtaining a confidence interval for the mean of a probability distribution when sequential data are considered. For this kind of data the empirical distribution can be biased but its bias is bounded by the coefficient of variation of the stopping rule associated with the sequential procedure. When using this distribution for resampling the validity of the bootstrap approach is established by means of a series expansion of the corresponding pivotal quantity. A simulation study is carried out using Wang and Tsiatis type tests and considering the normal and exponential distributions to generate the data. This study confirms that for moderate coefficients of variation of the stopping rule, the bootstrap method allows adequate confidence intervals for the parameters to be obtained, whichever is the distribution of data.     

A General Class of Estimators for the Linear Regression Model Affected by Collinearity and Outliers

In this article, a general class of estimators for the linear regression model affected by outliers and collinearity is introduced and studied in some detail. This class of estimators combines the theory of light, maximum entropy, and robust regression techniques. Our theoretical findings are illustrated through a Monte Carlo simulation study.     

Optimal Design of Acceptance Sampling Plans by Variables for Nonconforming Proportions When the Standard Deviation Is Unknown

This article presents an optimization-based approach for the design of acceptance sampling plans by variables for controlling nonconforming proportions when the standard deviation is unknown. The variables are described by rigorous noncentral Student’s t-distributions. Single and double acceptance sampling (AS) plans are addressed. The optimal design results from minimizing the average sampling number (ASN), subject to conditions holding at producer’s and consumer’s required quality levels. The problem is then solved employing a nonlinear programming solver. The results obtained are in close agreement with previous sampling plans found in the literature, outperforming them regarding the feasibility.     

The Significance of Education for Mortality Compression in the United States

Recent studies of old-age mortality trends assess whether longevity improvements over time are linked to increasing compression of mortality at advanced ages. The historical backdrop of these studies is the long-term improvement in a population's socioeconomic resources that fueled longevity gains. We extend this line of inquiry by examining whether socioeconomic differences in longevity within a population are accompanied by old-age mortality compression. Specifically, we document educational differences in longevity and mortality compression for older men and women in the United States. Drawing on the fundamental cause of disease framework, we hypothesize that both longevity and compression increase with higher levels of education and that women with the highest levels of education will exhibit the greatest degree of longevity and compression. Results based on the Health and Retirement Study and the National Health Interview Survey Linked Mortality File confirm a strong educational gradient in both longevity and mortality compression. We also find that mortality is more compressed within educational groups among women than men. The results suggest that educational attainment in the United States maximizes life chances by delaying the biological aging process.     

AN EXPERIMENTAL STUDY OF KIN AND ETHNIC FAVORITISM

Ethnic and kinship ties have long been viewed as potential catalysts for favoritism, and hence corruption. In experiments conducted in three countries, we recruit siblings, coethnics and strangers and vary the relationship(s) between the players of a game to observe how kin and ethnic ties influence the willingness of two players to benefit one another at the expense of a third party. We see universal sibling favoritism, but ethnic favoritism, and favoritism toward other in-group members (friends) varies. We argue this may be driven in part by kinship institutions, since favoritism is more common in societies with denser kin networks. ( JEL D9, C9, D73, J12)     

Do Cooperatives with Better Economic–Financial Indicators also have Better Socioeconomic Performance?

VOLUNTAS: International Journal of Voluntary and Nonprofit Organizations - The overall performance of cooperatives is related to economic–financial results and actions focused on benefits for...