Data Analytics for Business and Societal Challenges

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Paper Number

1695

Paper Type

Completed

Description

Urban air pollution induced by heavy transportation is among the most serious problems of the modern society. However, transportation decisions are endogenous to air quality, which makes it challenging to quantify the causal effect of transportation on air pollution. We aim to overcome this empirical difficulty by leveraging the spread of COVID-19 as instrumental variables and by combining a double/debiased machine learning approach with fixed effects ridge regression model. Collaborating with a famous Internet company which provides search engine and mobile mapping services, we collect a rich dataset including the number of COVID-19 cases, COVID-19-related search queries, public and private transportation, etc. We find that the effects of bus, rail, and private transportation would be significantly underestimated and those of taxi transportation would be overestimated without using instrumental variables. We also find the effects of transportation on different air pollutants are heterogeneous. Theoretical and managerial implications are provided.

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Dec 12th, 12:00 AM

COVID-19, Urban Transportation, and Air Pollution

Urban air pollution induced by heavy transportation is among the most serious problems of the modern society. However, transportation decisions are endogenous to air quality, which makes it challenging to quantify the causal effect of transportation on air pollution. We aim to overcome this empirical difficulty by leveraging the spread of COVID-19 as instrumental variables and by combining a double/debiased machine learning approach with fixed effects ridge regression model. Collaborating with a famous Internet company which provides search engine and mobile mapping services, we collect a rich dataset including the number of COVID-19 cases, COVID-19-related search queries, public and private transportation, etc. We find that the effects of bus, rail, and private transportation would be significantly underestimated and those of taxi transportation would be overestimated without using instrumental variables. We also find the effects of transportation on different air pollutants are heterogeneous. Theoretical and managerial implications are provided.

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