Measuring commuting and economic activity inside cities with cell phone records
Files
First author draft
Date
2021
Authors
Kreindler, Gabriel
Miyauchi, Yuhei
Version
First author draft
OA Version
Citation
G. Kreindler, Y. Miyauchi. 2021. "Measuring Commuting and Economic Activity inside Cities with Cell Phone Records" The Review of Economics and Statistics, pp.1-48. https://doi.org/10.1162/rest_a_01085
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.
Description
License
© 2021 by Gabriel E. Kreindler and Yuhei Miyauchi. All rights reserved. Short sections of text, not to exceed two paragraphs, may be quoted without explicit permission provided that full credit, including © notice, is given to the source.