Measuring Commuting and Economic Activity inside Cities with Cell Phone Records
Gabriel Kreindler () and
Yuhei Miyauchi ()
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Gabriel Kreindler: Harvard University
Yuhei Miyauchi: Boston University
No WP2020-006, Boston University - Department of Economics - Working Papers Series from Boston University - Department of Economics
We show how commuting flows can be used to infer the spatial distribution of income within a city. We use a simple workplace choice model, which 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. Unlike machine learning approaches, our method does not require training data, yet achieves comparable predictive power. In an application, we show that hartals (transportation strikes) in Dhaka lower commuting, leading to 5-8% lower predicted income.
JEL-codes: C55 E24 R14 (search for similar items in EconPapers)
Pages: 44 pages
Date: 2019-02, Revised 2020-04
New Economics Papers: this item is included in nep-big, nep-geo, nep-mac, nep-pay and nep-ure
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Persistent link: https://EconPapers.repec.org/RePEc:bos:wpaper:wp2020-006
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