Econometric analysis of productivity: Theory and implementation in R
- Authors
- Sickles, Robin C.; Song, WonHo; Zelenyuk, Valentin
- Issue Date
- Jan-2019
- Publisher
- Elsevier B.V.
- Keywords
- Bootstrapping; Data envelopment analysis; Index numbers; Nonparametric analysis; Panel data; Production (technical) efficiency; Stochastic frontier analysis
- Citation
- Handbook of Statistics, v.42, pp 267 - 297
- Pages
- 31
- Journal Title
- Handbook of Statistics
- Volume
- 42
- Start Page
- 267
- End Page
- 297
- URI
- https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/26420
- DOI
- 10.1016/bs.host.2018.11.007
- ISSN
- 0169-7161
1875-7448
- Abstract
- 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.
- Files in This Item
- There are no files associated with this item.
- Appears in
Collections - College of Business & Economics > School of Economics > 1. Journal Articles
![qrcode](https://api.qrserver.com/v1/create-qr-code/?size=55x55&data=https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/26420)
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.