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Quasi-Experimental Methods in Environmental Economics: Opportunities and Challenges

Author

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  • Deschenes, Olivier

    () (University of California, Santa Barbara)

  • Meng, Kyle C.

    () (University of California, Santa Barbara)

Abstract

This paper examines the application of quasi-experimental methods in environmental economics. We begin with two observations: i) standard quasi-experimental methods, first applied in other microeconomic fields, typically assume unit-level treatments that do not spill over across units; (ii) because public goods, such as environmental attributes, exhibit externalities, treatment of one unit often affects other units. To explore the implications of applying standard quasi-experimental methods to public good problems, we extend the potential outcomes framework to explicitly distinguish between unit-level source and the resulting group-level exposure of a public good. This new framework serves as a foundation for reviewing and interpreting key papers from the recent empirical literature. We formally demonstrate that two common quasi-experimental estimators of the marginal social benefit of a public good can be biased due to externality spillovers, even when the source of the public good itself is quasi-randomly assigned. We propose an unbiased estimator for the valuation of local public goods and discuss how it can be implemented in future studies. Finally, we consider how to preserve the advantages of the quasi-experimental approach when valuing global public goods, such as climate change mitigation, for which no control units are available.

Suggested Citation

  • Deschenes, Olivier & Meng, Kyle C., 2018. "Quasi-Experimental Methods in Environmental Economics: Opportunities and Challenges," IZA Discussion Papers 11797, Institute for the Study of Labor (IZA).
  • Handle: RePEc:iza:izadps:dp11797
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    References listed on IDEAS

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    1. Michael Greenstone & Justin Gallagher, 2008. "Does Hazardous Waste Matter? Evidence from the Housing Market and the Superfund Program," The Quarterly Journal of Economics, Oxford University Press, vol. 123(3), pages 951-1003.
    2. Joshua D. Angrist & Jörn-Steffen Pischke, 2010. "The Credibility Revolution in Empirical Economics: How Better Research Design Is Taking the Con out of Econometrics," Journal of Economic Perspectives, American Economic Association, vol. 24(2), pages 3-30, Spring.
    3. James J. Heckman, 2010. "Building Bridges between Structural and Program Evaluation Approaches to Evaluating Policy," Journal of Economic Literature, American Economic Association, vol. 48(2), pages 356-398, June.
    4. Olivier Deschênes & Michael Greenstone, 2012. "The Economic Impacts of Climate Change: Evidence from Agricultural Output and Random Fluctuations in Weather: Reply," American Economic Review, American Economic Association, vol. 102(7), pages 3761-3773, December.
    5. repec:aea:aecrev:v:107:y:2017:i:10:p:2958-89 is not listed on IDEAS
    6. Kenneth Y. Chay & Michael Greenstone, 2003. "Air Quality, Infant Mortality, and the Clean Air Act of 1970," Working Papers 0406, Massachusetts Institute of Technology, Center for Energy and Environmental Policy Research.
    7. Alan Barreca & Karen Clay & Olivier Deschenes & Michael Greenstone & Joseph S. Shapiro, 2016. "Adapting to Climate Change: The Remarkable Decline in the US Temperature-Mortality Relationship over the Twentieth Century," Journal of Political Economy, University of Chicago Press, vol. 124(1), pages 105-159.
    8. Olivier Deschênes & Michael Greenstone & Joseph S. Shapiro, 2017. "Defensive Investments and the Demand for Air Quality: Evidence from the NOx Budget Program," American Economic Review, American Economic Association, vol. 107(10), pages 2958-2989, October.
    9. Anthony C. Fisher & W. Michael Hanemann & Michael J. Roberts & Wolfram Schlenker, 2012. "The Economic Impacts of Climate Change: Evidence from Agricultural Output and Random Fluctuations in Weather: Comment," American Economic Review, American Economic Association, vol. 102(7), pages 3749-3760, December.
    10. Grainger, Corbett A., 2012. "The distributional effects of pollution regulations: Do renters fully pay for cleaner air?," Journal of Public Economics, Elsevier, vol. 96(9-10), pages 840-852.
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    More about this item

    Keywords

    quasi-experimental methods; environmental economics; externalities;

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • H23 - Public Economics - - Taxation, Subsidies, and Revenue - - - Externalities; Redistributive Effects; Environmental Taxes and Subsidies
    • H41 - Public Economics - - Publicly Provided Goods - - - Public Goods
    • Q50 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - General
    • Q51 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Valuation of Environmental Effects
    • Q52 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Pollution Control Adoption and Costs; Distributional Effects; Employment Effects
    • Q53 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Air Pollution; Water Pollution; Noise; Hazardous Waste; Solid Waste; Recycling
    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming

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