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A spatial analysis of real estate prices and public transportaion in the greater Los Angeles area

Posted on:2015-04-23Degree:M.SType:Thesis
University:University of Southern CaliforniaCandidate:Yu, DanqingFull Text:PDF
GTID:2479390020951946Subject:Biology
Abstract/Summary:
The city of Los Angeles is renowned for its traffic. In recent years, the city has been re-investing in public transportation in order to curb the gridlock and mitigate other detrimental side effects of an automobile dependent society such as air pollution and stress. With the introduction of new rail lines and better bus service, the city has seen an increase in public transportation ridership of 5.7% between 2012 and 2014. That increase is primarily due to greater use of the metro rail service, with the total number of trips growing 14.2% since 2012.;While improving public transportation has many benefits, there are effects on the housing and rental markets that are not as well understood. Furthermore, the complex relationships between real estate prices, access to public transportation and ridership are highly spatially dependent. In this study, these relationships were examined through the use of spatial autoregressive models that included predictor variables for type of commuting (public transportation or driving), length of commute, distance to public transportation, housing characteristics, and demographics. We found that the relationship between median house value and distance to public transportation was dependent upon the spatial scale of the neighbourhood being examined. On a highly local scale (<1km on average), median house prices increased by ;As public transportation options continue to grow and become more readily available in the Los Angeles metropolitan area, there will be several changes to the real estate market. While house prices appear to be lower in very close proximity to public transportation, renters tend to attach a premium to living near metro rail and bus lines.
Keywords/Search Tags:Public, Los angeles, Real estate, Prices, Spatial
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