ISSUES IN SPATIAL DATA ANALYSIS
讨论了空间数据分析中模型设定错误导致估计偏差的问题，比较了非参数、半参数方法、固定效应估计量和处理效应估计量的优缺点，对从事空间计量研究的学者有参考价值。
ABSTRACT Misspecified functional forms tend to produce biased estimates and spatially correlated errors. Imposing less structure than standard spatial lag models while being more amenable to large datasets, nonparametric and semiparametric methods offer significant advantages for spatial modeling. Fixed effect estimators have significant advantages when spatial effects are constant within well-defined zones, but their flexibility can produce variable, inefficient estimates while failing to account adequately for smooth spatial trends. Though estimators that are designed to measure treatment effects can potentially control for unobserved variables while eliminating the need to specify a functional form, they may be biased if the variables are not constant within discrete zones.