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Nonparametric Generalized Least Squares in Applied Regression Analysis

O'Hara, Michael E. - 2013

variants of heteroscedasticity robust standard error estimators (HRSEs) in an applied setting. Given myriad alternative HRSEs … various approaches to handling heteroscedasticity to data on professor rankings obtained from ratemyprofessor.com and find not … only heteroscedasticity to be prevalent but NPGLS and FGLS provide different insights and the statistical significance of …

Persistent link: https://www.econbiz.de/10013077989

Stochastic Nonparametric Envelopment of Data : Cross-Sectional Frontier Estimation Subject to Shape Constraints

Kuosmanen, Timo; Kortelainen, Mika - 2007

The field of production frontier estimation is divided between the parametric Stochastic Frontier Analysis (SFA) and the deterministic, nonparametric Data Envelopment Analysis (DEA). This paper explores an amalgam of DEA and SFA that melds a nonparametric frontier with a stochastic composite...

Persistent link: https://www.econbiz.de/10014050905

Orthogonality Conditions for Identification of Joint Production Technologies : Axiomatic Nonparametric Approach to the Estimation of Stochastic Distance Functions

Kuosmanen, Timo; Johnson, Andrew L; Parmeter, Christopher - 2015

The regression residual is commonly used as a productivity indicator. However, the observed input demands are endogenous if rational managers adjust their input use for inefficiency. A large stream of studies considers possible solutions to the endogeneity problem that require as little external...

Persistent link: https://www.econbiz.de/10014036140

Estimation and Inference for Heteroscedastic Systems of Equations

Duncan, Gregory M. - 2005

A method for estimation of heteroscedastic systems of equations that are more efficient than SUR and produce robust covariance matrices for parameter estimators is developed and applied to the Klein railroad data

Persistent link: https://www.econbiz.de/10014066062

Power Maximization and Size Control in Heteroskedasticity and Autocorrelation Robust Tests with Exponentiated Kernels

Sun, Yixiao - 2010

Using the power kernels of Phillips, Sun and Jin (2006, 2007), we examine the large sample asymptotic properties of the t-test for different choices of power parameter (rho). We show that the nonstandard fixed-rho limit distributions of the t-statistic provide more accurate approximations to the...

Persistent link: https://www.econbiz.de/10013148975

A New Asymptotic Theory for Vector Autoregressive Long-Run Variance Estimation and Autocorrelation Robust Testing

Sun, Yixiao; Kaplan, David M. - 2010

In this paper, we develop a new asymptotic theory of the long run variance estimator obtained by fitting a vector autoregressive model to the transformed moment processes in a GMM framework. In contrast to the conventional asymptotics where the VAR lag order p goes to infinity but at a slower...

Persistent link: https://www.econbiz.de/10014188745

Let's Fix it : Fixed-b Asymptotics Versus Small-b Asymptotics in Heteroscedasticity and Autocorrelation Robust Inference

Sun, Yixiao - 2010

In the presence of heteroscedasticity and autocorrelation of unknown forms, the covariance matrix of the parameter …

Persistent link: https://www.econbiz.de/10014188747

Consistent Hac Estimation and Robust Regression Testing Using Sharp Origin Kernels with No Truncation

Phillips, Peter C. B.; Sun, Yixiao; Jin, Sainan - 2003

A new family of kernels is suggested for use in heteroskedasticity and autocorrelation consistent (HAC) and long run variance (LRV) estimation and robust regression testing. The kernels are constructed by taking powers of the Bartlett kernel and are intended to be used with no truncation (or...

Persistent link: https://www.econbiz.de/10014088395

Addressing Spatial Heterogeneity in Regional Technical Efficiency

Ramajo, Julian - 2020

A new production-frontier specification is proposed when dealing with decision-making units whose efficiencies are correlated with the performances of the neighbors (spatial dependence), providing a bias reduction with respect to standard data envelopment analysis (DEA) methods. For the...

Persistent link: https://www.econbiz.de/10012839911

Stochastic Nonparametric Envelopment of Data : Combining Virtues of Sfa and DEA in a Unified Framework

Kuosmanen, Timo - 2006

The literature of productive efficiency analysis is divided into two main branches: the parametric Stochastic Frontier Analysis (SFA) and nonparametric Data Envelopment Analysis (DEA). This paper attempts to combine the virtues of both approaches in a unified framework. We follow the SFA...

Persistent link: https://www.econbiz.de/10014057860