Data envelopment analysis (DEA) is an axiomatic, mathematical programming approach to productive efficiency analysis and performance measurement. This paper shows that DEA can be interpreted as a nonparametric least squares regression subject to shape constraints on production frontier and sign constraints on residuals. Thus, DEA can be seen as a nonparametric counter-part of the corrected ordi...

A serious practical problem with the ordinary least squares regression estimator is that it can have a relatively large standard error when the error term is heteroscedastic, even under normality. In practical terms, power can be poor relative to other regression estimators that might be used. This article illustrates the problem and summarizes strategies for dealing with it. Included are new r...

The method of Instrumental Variables is suggested as an alternative to traditional methods for estimating the reliability of mental test scores which avoids certain drawbacks of these methods. The consistency and efficiency of the instrumental variable method are examined empirically using data from the British National Child Development Study in an analysis of 16 year, 11 year and 7 year old s...

An eight-equation model embodies the hypothesis that cultural differences among ethnic-religious groups give rise to differences in psychological dispositions, which, though not directly observable, influence occupational achievement, directly or via educational attainment, while being subject to feedback from one or the other of these endogenous variables. Dispositions are reflected in three f...

Statistical literature has several methods for coping with multicollinearity. This paper introduces a new shrinkage estimator, called modified unbiased ridge (MUR). This estimator is obtained from unbiased ridge regression (URR) in the same way that ordinary ridge regression (ORR) is obtained from ordinary least squares (OLS). Properties of MUR are derived. Results on its matrix mean squared er...

Studies of intensive mothering suggest that fulfilling societal expectations of the “good mother” diminishes maternal psychological well-being; however, studies tend to focus on young mothers. We examine the association between intensive mothering and psychological well-being using a sample of mothers in midlife (n = 1,388) drawn from the 2004-2006 National Survey of Midlife Development in the ...

Existing dimension reduction (DR) methods such as ordinary least squares (OLS) and sliced inverse regression (SIR) often perform poorly in the presence of outliers. Ellipsoidal trimming can be used to create outlier resistant DR methods that can also give useful results when the assumption of linearly related predictors is violated. Theory for SIR and OLS is reviewed, and it is shown that sever...

In this paper, we propose a generative tracking method based on a novel robust linear regression algorithm. In contrast to existing methods, the proposed Least Soft-thresold Squares (LSS) algorithm models the error term with the Gaussian-Laplacian distribution, which can be solved efficiently. Based on maximum joint likelihood of parameters, we derive a LSS distance to measure the difference be...

A new technique for estimating countries’ de facto exchange rate regimes synthesizes two approaches. One approach estimates the implicit de facto basket weights in an ordinary least squares (OLS) regression of the local currency value rate against major currency values. Here the hypothesis is a basket peg with little flexibility. The second estimates the de facto degree of exchange rate flexibi...

Using panel data, this paper tests whether public and private capital have a positive and significant effect on aggregate output and labor productivity for Mexico during the 1960-2001 period. The richer information set made possible by the sectorial data enables this study to utilize the methodologically sound “group-mean” Fully Modified Ordinary Least Squares (FMOLS) procedure developed by Ped...