Measuring Commuting and Economic Activity inside Cities with Cell Phone Records / Gabriel E. Kreindler, Yuhei Miyauchi.

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Kreindler, Gabriel E

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Material type: Text

TextSeries: Working Paper Series (National Bureau of Economic Research) ; no. w28516.Publication details: Cambridge, Mass. National Bureau of Economic Research 2021.Description: 1 online resource: illustrations (black and white)Subject(s):

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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.

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Item type	Home library	Collection	Call number	Status	Date due	Barcode	Item holds
Working Paper	Biblioteca Digital	Colección NBER	nber w28516 (Browse shelf(Opens below))	Not For Loan

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February 2021.

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.