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educational policy, education expansion, educational inequality, income inequality, Taiwan,

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In the present paper, we examine the relationship between wives' value of time and expenditures on food away from home (FAFH) in Taiwan between 1983 and 2000. An endogenous switching regression model is used to model the household's consumption decision on FAFH. The empirical results show that wives' value of time, household income, presence of young children and grandparents, and wives' educational attainment are important factors for both participation in consuming and amount spent on FAFH. The income elasticities of FAFH have increased from 0.09 to 0.17 over the sample period. Moreover, other things being equal, the level of spending on FAFH has also increased over time. The results suggest that there has been a structural change in the consumption pattern of FAFH by families in Taiwan.

Flood damage functions are necessary to ensure comprehensive flood-risk management. This study attempts to establish a residential flood-damage function through interviewing the residents living in the region where flood disasters occur frequently. Keelung River basin, near Taipei Metropolitan in Taiwan was selected as study area. Flood damages are related to the flood depths, which are the most commonly considered factor in previously published work. Ordinary least squares (OLS) regression was used to construct the flood-damage function at the beginning. Analytical results indicate that flood depth is the significant variable, but the spatial pattern of the residuals shows that residuals exhibit spatial autocorrelation. The Geographically Weighted Regression (GWR) Model was then applied to modify the traditional regression model, which cannot capture spatial variations, and to reduce the problem of spatial autocorrelation. The R-square value was found to increase from 0.15 to 0.24, and the spatial autocorrelation in the residuals was no longer evident. A modified OLS model with a dummy variable to capture the spatial autocorrelation pattern was also proposed for future applications. In conclusion, the residential flood damage is determined by flood depth and zone, and the GWR model not only captures the spatial variations of the affecting factors, but also helps to discover the independent variable to modify the traditional regression model.