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Externalities of auto traffic congestion growth: Evidence from the residential property values in the US Great Lakes megaregion

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  • Jin, Jangik
  • Rafferty, Peter

Abstract

Traffic congestion is getting worse and commuting cost is getting higher in every major metropolitan area. In this study, we attempt to explore the negative externalities of traffic congestion focusing on housing prices. We use a unique transportation dataset, the National Performance Management Research Data Set (NPMRDS), which contains information on every 5 min travel time across the extensive region to measure traffic congestion at the local level. In order to estimate the effect of traffic congestion on residential property values, we use a dynamic hedonic price model with a monthly panel dataset. Our findings show that while there is no significant relationship between congestion growth and housing price growth in rural and non-metro areas, the effects of congestion growth on housing price growth in urban and metro areas are obvious. We verify that traffic congestion functions as a disamenity in a local neighborhood. Transportation policies that aim to relieve traffic congestion should consider that severe traffic congestion may have an adverse effect on local property values.

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  • Jin, Jangik & Rafferty, Peter, 2018. "Externalities of auto traffic congestion growth: Evidence from the residential property values in the US Great Lakes megaregion," Journal of Transport Geography, Elsevier, vol. 70(C), pages 131-140.
    • Handle: RePEc:eee:jotrge:v:70:y:2018:i:c:p:131-140
    DOI: 10.1016/j.jtrangeo.2018.05.022
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    4. Xueting Zhao & Liwei Hu & Xingzhong Wang & Jiabao Wu, 2022. "Study on Identification and Prevention of Traffic Congestion Zones Considering Resilience-Vulnerability of Urban Transportation Systems," Sustainability, MDPI, vol. 14(24), pages 1-23, December.

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