Analyzing Regional Economic Indicators from Transportation Network Analytics

Authors: Song Gao, University of Wisconsin-Madison, Yunlei Liang, University of Wisconsin-Madison, Yuhao Kang, University of Wisconsin-Madison, YUQI GAO*,
Topics: Economic Geography, Transportation Geography, Spatial Analysis & Modeling
Keywords: spatial networks, transportation geography, economic geography, GIS
Session Type: Paper
Day: 4/7/2019
Start / End Time: 2:00 PM / 3:40 PM
Room: Cleveland 1, Marriott, Mezzanine Level
Presentation File: No File Uploaded


Utilizing a novel dataset of the entry and exit record of vehicles at toll gates in three Chinese provinces, we attempt to establish the relevance of mid-distance land transportation pattern to regional economic variables. The dataset contains traffic volume and freight volume (passenger volume) information of all cargo trucks (passenger cars) registered and aggregated by entry-station-and-exit-station pairs over a period of one year for four years. We device standard measurement of betweeness centrality to analyze the observed transportation network. Expectedly, the centrality measurement has a high correlation with city income level. We investigate other political, economic and geographic factors that may explain the variation in cities’ centrality. We estimate a gravity model based on traffic volume between pairs of cities for each province separately as well as for the whole sample. We discuss the implication of the estimated coefficient from the simple gravity model. We suggest a more complex model that takes into account road quality, local output, production linkage based on economic model in order to shed some light on the efficiency of the current transportation network. We conclude that transportation records like ours contain valuable information concerning labor mobility, urban planning and place-based policy.

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