Measuring Commuting and Economic Activity inside Cities with Cell Phone Records

Gabriel E. Kreindler and Yuhei Miyauchi

No 28516, NBER Working Papers from National Bureau of Economic Research, Inc

Abstract: 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.

JEL-codes: C55 E24 R14 (search for similar items in EconPapers)
Date: 2021-02
New Economics Papers: this item is included in nep-geo, nep-mac, nep-tre and nep-ure
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Citations: View citations in EconPapers (9)

Published as Gabriel E. Kreindler, Yuhei Miyauchi; Measuring Commuting and Economic Activity Inside Cities with Cell Phone Records. The Review of Economics and Statistics 2021

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