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Air pollution and mobility in the Mexico City Metropolitan Area, what drives the COVID-19 death toll?

Author

Listed:
  • Carlos Vladimir Rodríguez-Caballero

    (Mexico Autonomous Institute of Technology (ITAM) and CREATES)

  • J. Eduardo Vera-Valdés

    (Aalborg University and CREATES)

Abstract

This paper analyzes the relation between air pollution exposure and the number of deaths due to COVID-19 in the Mexico City Metropolitan Area. We test if short- and long-term exposure to air pollution is associated with a higher number of deaths due to the pandemic. Our results show that long-term exposure to particle matter of ten micrometers and smaller are associated with a higher death toll due to the pandemic. Nonetheless, in the short-term, the effect of air pollution on the number of deaths is less pronounced. Once we control for the short-term commonality among municipalities, contemporaneous air pollution exposure is no longer significant. Moreover, we show that the extracted unobservable common factor is highly correlated to mobility. Thus, our results show that mobility seems to be the main driver behind the number of deaths in the short-term. These results are particularly revealing given that the Metropolitan Area did not experience a decrease in air pollution during COVID- 19 inspired lockdowns. Thus, this paper highlights the importance of implementing policies to reduce mobility and air pollution to mitigate health risks due to the pandemic. Mobility constraints can reduce the number of deaths due to COVID-19 in the short-term, while pollution policies can reduce health risks in the long-term.

Suggested Citation

  • Carlos Vladimir Rodríguez-Caballero & J. Eduardo Vera-Valdés, 2020. "Air pollution and mobility in the Mexico City Metropolitan Area, what drives the COVID-19 death toll?," CREATES Research Papers 2020-15, Department of Economics and Business Economics, Aarhus University.
  • Handle: RePEc:aah:create:2020-15
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    References listed on IDEAS

    as
    1. Kapetanios, G. & Pesaran, M. Hashem & Yamagata, T., 2011. "Panels with non-stationary multifactor error structures," Journal of Econometrics, Elsevier, vol. 160(2), pages 326-348, February.
    2. M. Hashem Pesaran, 2006. "Estimation and Inference in Large Heterogeneous Panels with a Multifactor Error Structure," Econometrica, Econometric Society, vol. 74(4), pages 967-1012, July.
    3. Ergemen, Yunus Emre & Velasco, Carlos, 2017. "Estimation of fractionally integrated panels with fixed effects and cross-section dependence," Journal of Econometrics, Elsevier, vol. 196(2), pages 248-258.
    4. Juan Carlos Parra-Alvarez & Hamza Polattimur & Olaf Posch, 2020. "Risk Matters: Breaking Certainty Equivalence," CREATES Research Papers 2020-02, Department of Economics and Business Economics, Aarhus University.
    5. Guerra, Erick, 2015. "The geography of car ownership in Mexico City: a joint model of households’ residential location and car ownership decisions," Journal of Transport Geography, Elsevier, vol. 43(C), pages 171-180.
    6. M. Hashem Pesaran, 2003. "Estimation and Inference in Large Heterogenous Panels with Cross Section Dependence," CESifo Working Paper Series 869, CESifo.
    7. Jushan Bai, 2009. "Panel Data Models With Interactive Fixed Effects," Econometrica, Econometric Society, vol. 77(4), pages 1229-1279, July.
    8. Phillips, Peter C.B. & Sul, Donggyu, 2007. "Bias in dynamic panel estimation with fixed effects, incidental trends and cross section dependence," Journal of Econometrics, Elsevier, vol. 137(1), pages 162-188, March.
    9. Moon, H.R.Hyungsik Roger & Perron, Benoit, 2004. "Testing for a unit root in panels with dynamic factors," Journal of Econometrics, Elsevier, vol. 122(1), pages 81-126, September.
    10. Jushan Bai & Serena Ng, 2004. "A PANIC Attack on Unit Roots and Cointegration," Econometrica, Econometric Society, vol. 72(4), pages 1127-1177, July.
    11. Mikkel Bennedsen, 2020. "Designing a sequential testing procedure for verifying global CO2 emissions," CREATES Research Papers 2020-01, Department of Economics and Business Economics, Aarhus University.
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    More about this item

    Keywords

    COVID-19; Pollution; Morbidity; Spreading; Mobility;
    All these keywords.

    JEL classification:

    • Q53 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Air Pollution; Water Pollution; Noise; Hazardous Waste; Solid Waste; Recycling
    • Q28 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - Government Policy
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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