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Traffic Noise in Georgia: Sound Levels and Inequality

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Using Lorenz-type curves, means tests, ordinary least squares, and locally weighted regressions (LWR), we examine the relative burdens of whites, blacks, and Hispanics in Georgia from road and air traffic noise. We find that whites bear less noise than either blacks or Hispanics and that blacks tend to experience more traffic noise than Hispanics. While every Metropolitan Statistical Area (MSA) showed that blacks experienced relatively more noise than average, such a result did not hold for Hispanics in roughly half of the MSAs. We find much heterogeneity across Census tracts using LWR. For most Census tracts, higher black and Hispanic population shares are associated with increased noise. However, 5.5 percent of the coefficients for blacks and 18.9 percent for Hispanics are negative, suggesting larger population shares are associated with less noise. The noise LWR marginal effects for black populations across most tracts in the state are consistent with diminishing marginal noise from additional black population, while those in Atlanta exhibit diminishing marginal noise for Hispanics. In many regions of the state where the potential for health-damaging noise exists, we find relatively high disproportionality in noise experienced by the black and Hispanic populations compared to the rest of the overall population. Our findings underscore the importance of using nonparametric estimation approaches to unveil spatial heterogeneity in applied urban and housing economics analyses.

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  • Jeffrey P. Cohen & Cletus C. Coughlin & Jonas C. Crews, 2018. "Traffic Noise in Georgia: Sound Levels and Inequality," Working Papers 2019-4, Federal Reserve Bank of St. Louis.
  • Handle: RePEc:fip:fedlwp:2019-004
    DOI: 10.20955/wp.2019.004
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    1. Jeffrey P. Cohen & Cletus C. Coughlin, 2012. "Chapter 12 Where does Airport Noise Fall? Evidence from Atlanta," Advances in Airline Economics, in: Pricing Behavior and Non-Price Characteristics in the Airline Industry, pages 275-295, Emerald Group Publishing Limited.
    2. Boyce, James K. & Zwickl, Klara & Ash, Michael, 2016. "Measuring environmental inequality," Ecological Economics, Elsevier, vol. 124(C), pages 114-123.
    3. Julii S. Brainard & Andrew P. Jones & Ian J. Bateman, 2006. "Exposure to Environmental Urban Noise Pollution in Birmingham, UK," Chapters, in: Ysé Serret & Nick Johnstone (ed.), The Distributional Effects of Environmental Policy, chapter 6, Edward Elgar Publishing.
    4. Anna Makles & Kerstin Schneider, 2016. "Quiet Please! Adverse Effects of Noise on Child Development," CESifo Working Paper Series 6281, CESifo.
    5. Aaron Swoboda & Tsegaye Nega & Maxwell Timm, 2015. "Hedonic Analysis Over Time And Space: The Case Of House Prices And Traffic Noise," Journal of Regional Science, Wiley Blackwell, vol. 55(4), pages 644-670, September.
    6. Daniel P. McMillen & John F. McDonald, 2004. "Locally Weighted Maximum Likelihood Estimation: Monte Carlo Evidence and an Application," Advances in Spatial Science, in: Luc Anselin & Raymond J. G. M. Florax & Sergio J. Rey (ed.), Advances in Spatial Econometrics, chapter 10, pages 225-239, Springer.
    7. Brooks Depro & Christopher Timmins & Maggie O'Neil, 2015. "White Flight and Coming to the Nuisance: Can Residential Mobility Explain Environmental Injustice?," Journal of the Association of Environmental and Resource Economists, University of Chicago Press, vol. 2(3), pages 439-468.
    8. Daniel P. McMillen & Christian L. Redfearn, 2010. "Estimation And Hypothesis Testing For Nonparametric Hedonic House Price Functions," Journal of Regional Science, Wiley Blackwell, vol. 50(3), pages 712-733, August.
    9. Hanneke Kruize & Peter Driessen & Pieter Glasbergen & Klaas (N.D.) Van Egmond & Ton Dassen, 2007. "Environmental equity in the vicinity of Amsterdam Airport: The interplay between market forces and government policy," Journal of Environmental Planning and Management, Taylor & Francis Journals, vol. 50(6), pages 699-726.
    10. A S Fotheringham & M E Charlton & C Brunsdon, 1998. "Geographically Weighted Regression: A Natural Evolution of the Expansion Method for Spatial Data Analysis," Environment and Planning A, , vol. 30(11), pages 1905-1927, November.
    11. Diana Weinhold, 2013. "The Happiness-Reducing Costs Of Noise Pollution," Journal of Regional Science, Wiley Blackwell, vol. 53(2), pages 292-303, May.
    12. Anna, Petrenko, 2016. "Мaркування готової продукції як складова частина інформаційного забезпечення маркетингової діяльності підприємств овочепродуктового підкомплексу," Agricultural and Resource Economics: International Scientific E-Journal, Agricultural and Resource Economics: International Scientific E-Journal, vol. 2(1), March.
    13. Robin R. Sobotta & Heather E. Campbell & Beverly J. Owens, 2007. "Aviation Noise And Environmental Justice: The Barrio Barrier," Journal of Regional Science, Wiley Blackwell, vol. 47(1), pages 125-154, February.
    14. Kopsch, Fredrik, 2016. "The cost of aircraft noise – Does it differ from road noise? A meta-analysis," Journal of Air Transport Management, Elsevier, vol. 57(C), pages 138-142.
    15. Yelena Ogneva-Himmelberger & Brian Cooperman, 2010. "Spatio-temporal Analysis of Noise Pollution near Boston Logan Airport: Who Carries the Cost?," Urban Studies, Urban Studies Journal Limited, vol. 47(1), pages 169-182, January.
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    Cited by:

    1. Tao Huang & Ta-Chien Chan & Ying-Jhen Huang & Wen-Chi Pan, 2020. "The Association between Noise Exposure and Metabolic Syndrome: A Longitudinal Cohort Study in Taiwan," IJERPH, MDPI, vol. 17(12), pages 1-14, June.
    2. Trudeau, Christopher & King, Nicholas & Guastavino, Catherine, 2023. "Investigating sonic injustice: A review of published research," Social Science & Medicine, Elsevier, vol. 326(C).
    3. Breidenbach, Philipp & Cohen, Jeffrey P. & Schaffner, Sandra, 2019. "Continuation of air services at Berlin-Tegel and its effects on rental prices," Ruhr Economic Papers 822, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.

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    More about this item

    Keywords

    traffic noise; Lorenz curves; nonparametric regressions;
    All these keywords.

    JEL classification:

    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • Q53 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Air Pollution; Water Pollution; Noise; Hazardous Waste; Solid Waste; Recycling
    • R41 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Transportation: Demand, Supply, and Congestion; Travel Time; Safety and Accidents; Transportation Noise

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