Big data, accessibility and urban house prices
نویسندگان
چکیده
Big data applications are attracting increasing interest among urban researchers. One unexplored question is whether the inclusion of big accessibility indices improves accuracy hedonic price models used for residential property valuation. This paper compares a index with an derived from regional travel demand model developed by local transportation planning agencies and traditional measures defined as distances to employment centres. Controls submarkets combined spatial autoregressive error also assessed tools capturing value location. Using single-family transactions Miami, Florida, metropolitan area, study’s main conclusion that measure does not add meaningful explanatory or predictive power. In contrast, outperforms other options considered.
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ژورنال
عنوان ژورنال: Urban Studies
سال: 2021
ISSN: ['2747-3619', '2747-3635']
DOI: https://doi.org/10.1177/0042098020982508