Generalized moments estimation for spatial panel data: Indonesian rice farming

Viliam Druska, William C Horrace

Research output: Contribution to journalArticle

62 Scopus citations

Abstract

We consider estimation of a panel data model where disturbances are spatially correlated in the cross-sectional dimension, based on geographic or economic proximity. When the time dimension of the data is large, spatial correlation parameters may be consistently estimated. When the time dimension is small (the usual panel data case), we develop an estimator that extends the cross-sectional model of Kelejian and Prucha. This approach is applied in a stochastic frontier framework to a panel of Indonesian rice farms where spatial correlations represent productivity shock spillovers, based on geographic proximity and weather. These spillovers affect farm-level efficiency estimation and ranking.

Original languageEnglish (US)
Pages (from-to)185-198
Number of pages14
JournalAmerican Journal of Agricultural Economics
Volume86
Issue number1
DOIs
StatePublished - Feb 2004

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Keywords

  • Autocorrelation
  • Economic spillovers
  • Productivity
  • Stochastic frontiers

ASJC Scopus subject areas

  • Agricultural and Biological Sciences (miscellaneous)
  • Economics and Econometrics

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