TY  - JOUR
AU  - Druska,Viliam
AU  - Horrace,William C.
TI  - Generalized Moments Estimation for Panel Data
JF  - National Bureau of Economic Research Technical Working Paper Series
VL  - No. 291
PY  - 2003
Y2  - March 2003
UR  - http://www.nber.org/papers/t0291
L1  - http://www.nber.org/papers/t0291.pdf
N1  - Author contact info:
William Horrace
Center for Policy Research
426 Eggers Hall
Syracuse University
Syracuse, NY  13244-1020
Tel: 315/443-9061
Fax: 315/443-1081
E-Mail: whorrace@maxwell.syr.edu
AB  - This paper considers estimation of a panel data model with disturbances that are autocorrelated across cross-sectional units. It is assumed that the disturbances are spatially correlated, based on some geographic or economic proximity measure. If the time dimension of the data is large, feasible and efficient estimation proceeds by using the time dimension to estimate spatial dependence parameters. For the case where the time dimension is small (the usual panel data case), we develop a generalized moments estimation approach that is a straight-forward generalization of a cross-sectional model due to Kelejian and Prucha. We apply this approach in a stochastic frontier framework to a panel of Indonesian rice farms where spatial correlations are based on geographic proximity, altitude and weather. The correlations represent productivity shock spillovers across the rice farms in different villages on the island of Java. Test statistics indicate that productivity shock spillovers may exist in this (and perhaps other) data sets, and that these spillovers have effects on technical efficiency estimation and ranking.
ER  -