Measuring Commuting and Economic Activity inside Cities with Cell Phone Records
Working Paper 28516
DOI 10.3386/w28516
Issue Date
We show how to use commuting flows to infer the spatial distribution of income within a city. A simple workplace choice model predicts a gravity equation for commuting flows whose destination fixed effects correspond to wages. We implement this method with cell phone transaction data from Dhaka and Colombo. Model-predicted income predicts separate income data, at the workplace and residential level, and by skill group. Unlike machine learning approaches, our method does not require training data, yet achieves comparable predictive power. We show that hartals (transportation strikes) in Dhaka reduce commuting more for high model-predicted wage and high-skill commuters.
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Copy CitationGabriel E. Kreindler and Yuhei Miyauchi, "Measuring Commuting and Economic Activity inside Cities with Cell Phone Records," NBER Working Paper 28516 (2021), https://doi.org/10.3386/w28516.