The purpose of this dissertation is to develop a methodology for the estimation of the appropriate welfare benefits in the presence of spillover externalities. The ability to capture influences of the not so easily observed variables allow spatial lag models to measure the direct and indirect spillover effects. The direct effect measures the value of the property in question and the indirect captures the influences of neighboring properties, through a spatial multiplier effect.Kim et al. (2003) through a path breaking approach estimated welfare benefits of air quality improvement. Their methodology captured spillover effects of amenity changes that lump both the direct and indirect multiplier effects. This approach motivated a wave of spatial hedonic studies employed for the valuation of non-market goods. Small and Steimetz (2008) however, argued that such approach is flawed in the context of welfare valuation. If the spatial multiplier captures pecuniary spillover effects, they hypothesized, and then welfare benefits are overestimated by the amount of the spatial multiplier. If, however, the spatial multiplier captures technological spillover effects then welfare changes is given by the reduced form of the spatial lag model effectively adding to the multiplier.Our contribution in this study is to propose a spatio-temporal methodological approach which allows for a richer dynamic specification when measuring spillover effects of residential amenity improvement. The contribution extends Small and Steimetz (2008) who provide a theoretical framework of our analysis, but lack empirical support. The contribution also extends Kim et al. (2003) who use spatial lag model to estimate the marginal willingness to pay for residential amenity improvement but do not disentangle the direct and indirect or spatial multiplier effects of the welfare benefit.Against this background this dissertation specifically deals with three important issues:1. To effectively measure price related (pecuniary) andwelfare (technological) related spillover effects withinspatial lag multiplier.2. To use GIS spatial association tools to identify spatialpatterns and perform exploratory spatial data analysis(ESDA) of the housing distribution in redevelopmentareas in data development stages and3. Use the decomposition methodology to compute andevaluate the effectiveness of spatially targetedredevelopment policy such as the one implemented byCity of Henderson.Empirical findings suggest that ignoring space leads to Marginal Willingness To Pay (MWTP) estimate that is about 4% larger than the direct effect but 6 % smaller than the multiplier effect obtained from spatial lag models. While spatial lag models estimate an indirect multiplier effect of $ 1.09 in house prices as a result of $1 amenity improvements only 8% can be attributed to technological effects, the rest are predominantly pecuniary. Therefore, u22correctu22 MWTP estimates for neighborhood quality would only include the direct effect and not the multiplier. In this case including the multiplier would overstate the estimates by 9%.These findings are in line with the existing literature on state programs which find spatially targeted redevelopment policies to be not as effective on welfare neighborhood indicators other than price. Although, Cityu27s HAP redevelopment program we believe grew in popularity its effectiveness on neighborhood quality indicators except price remain insignificant.
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