The Urban Blight Costs in Taiwan

Abstract

Urban blight is not only an eyesore for city residents, but also a threat to health, psychological well-being, and safety. It not only represents substantial economic decline, but also spreads through urban space. As well as the loss of personal property value, urban blight also harms public interests in the public domain. This study finds that danger and age are the two main factors of urban blight. Ignoring these two factors causes housing prices to fall. The decline in population due to long-term economic stagnation and the exodus of residents and industries, coupled with the long-term decline in income and spending on maintenance of old houses, has led to major visual and physical economic blight. This investigation adopts the hedonic model to analyze the correspondence of house prices with urban blight, based on real estate prices and related township variables announced by the government in Taiwan in 2017, and applies the spatial regression model to investigate the direct and indirect effects of real estate prices. The following conclusions can be drawn from the analytical results. 1. The spatial lag model finds that urban blight has a spatial spillover effect. 2. The government must not disregard the blight, due to its detrimental effect on housing prices and spatial diffusion effect. 3. The factors that affect the blight are age of residents, age of buildings, poverty, and danger.

Influence of the Cadastral Value of the Urban Land and Neighborhood Characteristics on the Mean House Mortgage Appraisal

“…The choice of the models herein employed is justified by the principle of parsimony: if the model shows good performance, the simpler, the better. In fact, all these models co-exist in the recent literature [18][19][20][21][22][23].…”

“…Comparisons have been made of hedonic models, estimated for home listing prices and purchase-sale house prices in Berlin [20] using characteristics of houses with the willingness-to-pay estimation. In Taiwan, hedonic models have been compared to spatial hedonic models [21] to analyze the urban blight effect on housing prices. The following have been employed as explanatory variables: old house, house age, household income, building material and elderly population per household.…”

Analyzing causes of urban blight using cognitive mapping and DEMATEL

“…Blight not only potentially triggers other issues, such as drug trafficking and prostitution, but also, unchecked, spreads quickly. Therefore, blight prevention and mitigation are crucial to reducing blight occurrences when it first appears (Ernst, 2008 ; Ferreira et al, 2018 ; Hu et al, 2021 ; Marques et al, 2018 ; Pires et al, 2018 ).…”