A solution for multicollinearity in stochastic frontier production function models
Bibliographic Data
| ID | 11149953 |
|---|---|
| Authors | Elkin Castaño (Universidad de Antioquia) |
| Year | 2017 |
| Issue | 86 |
| Pages | 9-23 |
| Publication date | 2017-01-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Lecturas de Economía (JOURNAL) |
| Journal identifiers | ISSN: 0120-2596 • E-ISSN: 2323-0622 |
| Publisher | Universidad de Antioquia (PUBLISHER • CO) |
| DOI | 10.17533/udea.le.n86a01 |
| OpenAlex | W2588292072 |
| Language | EN |
| References cited | 15 |
This paper considers the problem of collinearity among inputs in a stochastic frontier production model, an issue that has received little attention in the econometric literature. To address this problem, a principal-component-based solution is proposed, which allows carrying out a joint interpretation of technical efficiency and the technology parameters of the model. Applications of the method to simulated and real data show its usability and effective performance
Collinearity · Component (thermodynamics · Econometric model · Econometrics · Economics · Frontier · Function (biology · Function model · Interpretation (philosophy · Machine learning · Mathematical optimization · Microeconomics · Multicollinearity · Principal component analysis · Production (economics · Production–possibility frontier · Regression analysis · Statistics · Usability · Work in process · Artificial Intelligence · Computer Science · Economic Growth and Productivity · Efficiency Analysis Using DEA · Fiscal Policy and Economic Growth · Mathematics
| Highly cited | No |
|---|