دورية أكاديمية
LASSO for Stochastic Frontier Models with Many Efficient Firms
| العنوان: | LASSO for Stochastic Frontier Models with Many Efficient Firms |
|---|---|
| المؤلفون: | Horrace, William C, Jung, Hyunseok, Lee, Yoonseok |
| المصدر: | Center for Policy Research |
| بيانات النشر: | SURFACE at Syracuse University |
| سنة النشر: | 2022 |
| المجموعة: | Syracuse University Research Facility And Collaborative Environment (SUrface) |
| مصطلحات موضوعية: | Panel Data, Fixed-Effect Stochastic Frontier Model, Adaptive LASSO, L1 Regularization, Sign Restriction, Zero Inefficiency, Economic Policy, Economics, Public Affairs, Public Policy and Public Administration, Public Policy |
| الوصف: | We apply the adaptive LASSO (Zou, 2006) to select a set of maximally efficient firms in the panel fixed-effect stochastic frontier model. The adaptively weighted L1 penalty with sign restrictions for firm-level inefficiencies allows simultaneous estimation of the maximal efficiency and firm-level inefficiency parameters, which results in a faster rate of convergence of the corresponding estimators than the least-squares dummy variable approach. We show that the estimator possesses the oracle property and selection consistency still holds with our proposed tuning parameter selection criterion. We also propose an efficient optimization algorithm based on coordinate descent. We apply the method to estimate a group of efficient police officers who are best at detecting contraband in motor vehicle stops (i.e., search efficiency) in Syracuse, NY. |
| نوع الوثيقة: | text |
| وصف الملف: | application/pdf |
| اللغة: | English |
| العلاقة: | https://surface.syr.edu/cpr/416Test; https://surface.syr.edu/context/cpr/article/1416/viewcontent/wp248_accessible.pdfTest |
| الإتاحة: | https://surface.syr.edu/cpr/416Test https://surface.syr.edu/context/cpr/article/1416/viewcontent/wp248_accessible.pdfTest |
| حقوق: | http://creativecommons.org/licenses/by/4.0Test/ |
| رقم الانضمام: | edsbas.BDAAF38A |
| قاعدة البيانات: | BASE |
| الوصف غير متاح. |