Do Employees Profit from Profit Sharing? Evidence from Canadian Panel Data Using panel data from a large sample of Canadian establishments, this paper examines whether employee earnings increase, decrease, or do not change in the period subsequent to adoption of profit sharing, relative to establishments that do not adopt profit sharing. Our research contributes to knowledge by utilizing longit...

We present a well-defined and characterized all-sky sample of classical Cepheids in the Milky Way, obtained by combining two time-domain surveys: Gaia DR2 (Gaia Collaboration et al. 2018) All-Sky Automated Survey for Supernovae (ASAS-SN; Shappee 2014). first use parallax variability information from to select ∼30,000 bright (G < 17) Cepheid candidates with MK − 1. then analyze their ASAS-SN V-b...

Results in the literature of classification models from microarray data often appear to be exceedingly good relative to most other domains of machine learning and clinical diagnostics. Yet array data are noisy, and have very small sample-to-variable ratios. What is the explanation for such exemplary, yet counterintuitive, classification performance? Answering this question has significant impli...

In developing a classification model for assigning observations of unknown class to one of a number of specified classes using the values of a set of features associated with each observation, it is often desirable to the classifier on a limited number of features. Mathematical programming (MP) discriminant analysis methods for developing classification models can be extended for feature select...

Roma Women in Athenian Firms: Do They Face Wage Bias? In the current study, we analyze the effect of having a Roma background on women’s wages. By utilizing the Athens Area Study random sample (2007-08) drawn from 16 multiethnic municipalities in which Roma live, we estimate that 66.1% of the wage differential between Roma and non-Roma female workers cannot be explained by differences in observ...

In random coefficients linear IV models, fixed effects averages of the individual-specific coefficients are biased in short panels due to the finite-sample bias of IV estimators. This paper introduces a new class of bias-corrected semiparametric estimators for panel models where the response to the regressors can be individual-specific in an unrestricted way. These estimators are based on momen...

MOTIVATION Two important questions for the analysis of gene expression measurements from different sample classes are (1) how to classify samples and (2) how to identify meaningful gene signatures (ranked gene lists) exhibiting the differences between classes and sample subsets. Solutions to both questions have immediate biological and biomedical applications. To achieve optimal classification ...

Selecting relevant and discriminative genes for sample classification is a common and critical task in gene expression analysis (e.g. disease diagnostic). It is desirable that gene selection can improve classification performance of learning algorithm effectively. In general, for most gene selection methods widely used in reality, an individual gene subset will be chosen according to its discri...

Sample selection models are important for correcting for the effects of nonrandom sampling in microeconomic data. This note is about semiparametric estimation using a series approximation to the selection correction term. Regression spline and power series approximations are considered. Consistency and asymptotic normality are shown, as well as consistency of an asymptotic variance estimator. J...

Accurate gender classification is useful in speech and speaker recognition as well as speech emotion classification, because a better performance has been reported when separate acoustic models are employed for males and females. Gender classification is also apparent in face recognition, video summarization, human-robot interaction, etc. Although gender classification is rather mature in a...