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Abstract
En 中文
In this paper I discuss economic processes that may give rise to spatial patterns in data, and explore the relative merits of alternative modeling approaches when data are spatially correlated. Specifically, I present an estimation scheme that allows for spatial random effects, and focus attention on cases in which such a framework may be preferred to the more general fixed effects framework that nests it. I use the models presented, together with information on the location of households in an Indonesian socio-economic survey, to test spatial relationships in Indonesian demand for rice.
Keywords:
SPATIAL CORRELATION
MORAN-I STATISTICS
RANDOM EFFECTS MODELS
FIXED EFFECTS MODELS
SUSENAS
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7.1
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3.0K
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4.3W
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