• Journal of the Korean Geographical Society
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• v.38 no.6
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• pp.906-921
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• 2003

This paper discusses the price effects of local growth controls on the housing markets of California jurisdictions in the late 1980s empirically. Particularly, based on spatial econometric modeling, the study focuses on the homebuilding constrained by growth controls which is one of the price effects. The modeling produces the California-wide generalizable results, differentiates among the individual effects of various growth controls on homebuilding, and covers spatial effects. Thereby, this study intends to supplement the existing work on the price effects of growth controls. The modeling results find that restrictive residential zoning had the effect of significantly restricting housing construction in the late 1980s. On the other hand, urban growth boundaries had the effect of accommodating homebuilding. Population growth or housing permit caps and adequate public facility ordinances had no significant effects on housing construction.

• Communications for Statistical Applications and Methods
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• v.29 no.3
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• pp.373-391
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• 2022

The distribution of observations in most econometric studies with spatial heterogeneity is skewed. Usually, a single transformation of the data is used to approximate normality and to model the transformed data with a normal assumption. This assumption is however not always appropriate due to the fact that panel data often exhibit non-normal characteristics. In this work, the normality assumption is relaxed in spatial mixed models, allowing for spatial heterogeneity. An inference procedure based on Bayesian mixed modeling is carried out with a multivariate skew-elliptical distribution, which includes the skew-t, skew-normal, student-t, and normal distributions as special cases. The methodology is illustrated through a simulation study and according to the empirical literature, we fit our models to non-life insurance consumption observed between 1998 and 2002 across a spatial panel of 103 Italian provinces in order to determine its determinants. Analyzing the posterior distribution of some parameters and comparing various model comparison criteria indicate the proposed model to be superior to conventional ones.