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Semiparametric Efficient Estimation of AR(1) Panel Data Models

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Author Info
Byeong Park (Seoul National University)
Robin C. Sickles (Rice University)
Leopold Simar (Universite Catholique de Louvain)

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Abstract

This study focuses on the semiparametric efficient estimation of random effect panel models containing AR(1) disturbances. We also consider such estimators when the effects and regressors are correlated (Hausman and Taylor, 1981). One motivation for such a model is the need to estimate a stochastic frontier distance function, isolate the fixed effects estimates, and interpret transformations of them as firm-specific relative efficiencies (Schmidt and Sickles, 1984). In markets in which regulatory constraints have been lessened or done away with, these market shocks may not be adjusted to immediately and may induce a serial correlation pattern in within firm variations. In the banking industry, whose productivity we analyze over the 1980's and 1990's, these aspects of semiparametric efficient estimation become important in order to resolve questions concerning the proper measurement of financial deregulation's impact on productivity. We introduce two semiparametric efficient estimators that make minimal assumptions on the distribution of the random errors, effects, and the regressors and that provide semiparametric efficient estimates of the slope parameters and of the effects. Our estimators extend the previous work of Park and Simar (1995), Park, Sickles, and Simar (1998), and Adams, Berger, and Sickles (1998).

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Paper provided by Econometric Society in its series Econometric Society World Congress 2000 Contributed Papers with number 1510.

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Date of creation: 01 Aug 2000
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Handle: RePEc:ecm:wc2000:1510

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Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
  1. Joel L. Horowitz & Marianthi Markatou, 1993. "Semiparametric Estimation Of Regression Models For Panel Data," Econometrics 9309001, EconWPA. [Downloadable!]
  2. Arellano, Manuel & Bover, Olympia, 1995. "Another look at the instrumental variable estimation of error-components models," Journal of Econometrics, Elsevier, vol. 68(1), pages 29-51, July. [Downloadable!] (restricted)
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  3. Adams, Robert M & Berger, Allen N & Sickles, Robin C, 1999. "Semiparametric Approaches to Stochastic Panel Frontiers with Applications in the Banking Industry," Journal of Business & Economic Statistics, American Statistical Association, vol. 17(3), pages 349-58, July.
  4. Robinson, Peter M, 1988. "Root- N-Consistent Semiparametric Regression," Econometrica, Econometric Society, vol. 56(4), pages 931-54, July. [Downloadable!] (restricted)
  5. Horowitz, Joel L & Markatou, Marianthi, 1996. "Semiparametric Estimation of Regression Models for Panel Data," Review of Economic Studies, Blackwell Publishing, vol. 63(1), pages 145-68, January. [Downloadable!] (restricted)
  6. Schmidt, Peter & Sickles, Robin C, 1984. "Production Frontiers and Panel Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 2(4), pages 367-74, October.
  7. Cornwell, Christopher & Schmidt, Peter & Sickles, Robin C., 1989. "Production Frontiers With Cross-Sectinal And Time-Series Variation In Efficiency Levels," Working Papers 89-18, C.V. Starr Center for Applied Economics, New York University. [Downloadable!]
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  8. Park, B.U. & Simar, L., 1992. "Efficient Semiparametric Estimation in Stochastic Frontier Model," Papers 9201, Catholique de Louvain - Institut de statistique.
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  9. Park, B. & Sickles, R.C. & Simar, L., 1993. "Stochastic Frontiers: A Semiparametric Approach," Papers 9303, Catholique de Louvain - Institut de statistique.
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  10. Hans M. Amman & David A. Kendrick, . "Computational Economics," Online economics textbooks, SUNY-Oswego, Department of Economics, number comp1, March. [Downloadable!]
  11. Allen N. Berger & Anil K. Kashyap & Joseph Scalise, 1995. "The Transformation of the U.S. Banking Industry: What a Long, Strange Trip It's Been," Center for Financial Institutions Working Papers 96-06, Wharton School Center for Financial Institutions, University of Pennsylvania.
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  1. Byeong Park & Seuck Song, 2007. "Comments on: Panel data analysis—advantages and challenges," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer, vol. 16(1), pages 47-51, May. [Downloadable!] (restricted)
  2. Kuosmanen, Timo, 2006. "Stochastic Nonparametric Envelopment of Data: Combining Virtues of SFA and DEA in a Unified Framework," Discussion Papers 11864, MTT Agrifood Research Finland. [Downloadable!]
  3. Kortelainen, Mika, 2008. "Estimation of semiparametric stochastic frontiers under shape constraints with application to pollution generating technologies," MPRA Paper 9257, University Library of Munich, Germany. [Downloadable!]
  4. Byeong U. Park & Robin C Sickles & Léopold Simar, 2002. "Semi parametric efficient estimation of dynamic panel data models," 10th International Conference on Panel Data, Berlin, July 5-6, 2002 C6-1, International Conferences on Panel Data. [Downloadable!]
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  5. Robin Sickles, 2007. "Comments on: Panel data analysis—advantages and challenges," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer, vol. 16(1), pages 31-32, May. [Downloadable!] (restricted)
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