Econometric analysis of productivity: Theory and implementation in R

Citations

SCOPUS

9

초록

Our chapter details a wide variety of approaches used in estimating productivity and efficiency based on methods developed to estimate frontier production using stochastic frontier analysis (SFA) and data envelopment analysis (DEA). The estimators utilize panel, single cross section, and time series data sets. The R programs include such approaches to estimate firm efficiency as the time-invariant fixed effects, correlated random effects, and uncorrelated random effects panel stochastic frontier estimators, time-varying fixed effects, correlated random effects, and uncorrelated random effects estimators, semiparametric efficient panel frontier estimators, factor models for cross-sectional and time-varying efficiency, bootstrapping methods to develop confidence intervals for index number-based productivity estimates and their decompositions, DEA and Free Disposable Hull estimators. The chapter provides the professional researcher, analyst, statistician, and regulator with the most up to date efficiency modeling methods in the easily accessible open source programming language R. © 2019 Elsevier B.V.

키워드

BootstrappingData envelopment analysisIndex numbersNonparametric analysisPanel dataProduction (technical) efficiencyStochastic frontier analysis
제목
Econometric analysis of productivity: Theory and implementation in R
저자
Sickles, Robin C.Song, WonhoZelenyuk, Valentin
DOI
10.1016/bs.host.2018.11.007
발행일
2019-01
유형
Article in Press
저널명
Handbook of Statistics
42
페이지
267 ~ 297