Measuring productivity and efficiency: a Kalman filter approach

Duygun, Meryem; Kutlu, Levent; Sickles, Robin

Abstract

In the Kalman filter setting, one can model the inefficiency term of the standard stochastic frontier composed error as an unobserved state. In this study a panel data version of the local level model is used for estimating time-varying efficiencies of firms. We apply the Kalman filter to estimate average efficiencies of U.S. airlines and find that the technical efficiency of these carriers did not improve during the period 1999-2009. During this period the industry incurred substantial losses, and the efficiency gains from reorganized networks, code-sharing arrangements, and other best business practices apparently had already been realized.

Citation

Duygun, M., Kutlu, L., & Sickles, R. (2016). Measuring productivity and efficiency: a Kalman filter approach. Journal of Productivity Analysis, 46(2), 155-167. https://doi.org/10.1007/s11123-016-0477-z

• Journal Article Type: Article
• Acceptance Date: Aug 1, 2016
• Online Publication Date: Sep 30, 2016
• Publication Date: Dec 8, 2016
• Deposit Date: Mar 16, 2017
• Publicly Available Date: Mar 16, 2017
• Journal: Journal of Productivity Analysis
• Print ISSN: 0895-562X
• Electronic ISSN: 1573-0441
• Publisher: Springer Verlag
• Peer Reviewed: Peer Reviewed
• Volume: 46
• Issue: 2
• Pages: 155-167
• DOI: https://doi.org/10.1007/s11123-016-0477-z
• Keywords: Kalman filter, Panel data, Airline productivity
• Public URL: https://nottingham-repository.worktribe.com/output/836048
• Publisher URL: https://link.springer.com/article/10.1007%2Fs11123-016-0477-z
• Additional Information: The final publication is available at Springer via http://dx.doi.org/10.1007/s11123-016-0477-z
• Contract Date: Mar 16, 2017