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Nighttime Light Pollution and Economic Activities: A Spatio-Temporal Model with Common Factors for US Counties

Author

Listed:
  • Bresson, Georges

    (University of Paris 2)

  • Etienne, Jean-Michel

    (Université Paris-Sud)

  • Lacroix, Guy

    (Université Laval)

Abstract

Excessive nighttime light is known to have detrimental effects on health and on the environment (fauna and flora). The paper investigates the link between nighttime light pollution and economic growth, air pollution, and urban density. We propose a county model of consumption which accounts for spatial interactions. The model naturally leads to a dynamic general nesting spatial model with unknown common factors. The model is estimated with data for 3071 continental US counties from 2012–2019 using a quasi-maximum likelihood estimator. Short run and long run county marginal effects emphasize the importance of spillover effects on radiance levels. Counties with high levels of radiance are less sensitive to additional growth than low-level counties. This has implications for policies that have been proposed to curtail nighttime light pollution.

Suggested Citation

  • Bresson, Georges & Etienne, Jean-Michel & Lacroix, Guy, 2023. "Nighttime Light Pollution and Economic Activities: A Spatio-Temporal Model with Common Factors for US Counties," IZA Discussion Papers 16342, Institute of Labor Economics (IZA).
    • Handle: RePEc:iza:izadps:dp16342
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    References listed on IDEAS

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    1. Seung C. Ahn & Alex R. Horenstein, 2013. "Eigenvalue Ratio Test for the Number of Factors," Econometrica, Econometric Society, vol. 81(3), pages 1203-1227, May.
    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. Alexei Onatski, 2010. "Determining the Number of Factors from Empirical Distribution of Eigenvalues," The Review of Economics and Statistics, MIT Press, vol. 92(4), pages 1004-1016, November.
    4. M. Hashem Pesaran, 2007. "A simple panel unit root test in the presence of cross-section dependence," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(2), pages 265-312.
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    More about this item

    Keywords

    nighttime light pollution; air pollution; GDP; satellite data; space-time panel data model;
    All these keywords.

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • Q53 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Air Pollution; Water Pollution; Noise; Hazardous Waste; Solid Waste; Recycling

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