IDEAS home Printed from https://ideas.repec.org/a/eee/jeborg/v196y2022icp278-293.html
   My bibliography  Save this article

Car accidents, smartphone adoption and 3G coverage

Author

Listed:
  • Hersh, Jonathan
  • Lang, Bree J.
  • Lang, Matthew

Abstract

This paper examines the relationship between smartphone use by drivers and traffic accidents in California between 2001 and 2013. In order to estimate smartphone use, we first show that widespread adoption of modern smartphones began in 2009 after the release of the iPhone 3G and T-Mobile G1. This information is combined with annual 3G coverage maps that are constructed from cellular tower information in a machine learning framework. In a difference-in-differences framework, we estimate the combined effect of smartphone adoption and 3G coverage along quarter-mile road segments. Controlling for census tract population density, road and year fixed effects, Poisson regression results show that there is a statistically significant increase in the traffic accident rate along a road segment when smartphone use becomes possible. Our preferred specification suggests smartphones caused accident rates to increase by 2.9 percent, resulting in 3500 additional accidents per year in California. Event study results rule out the possibility that our smartphone treatment is capturing a trend in the accident rate. The results are robust to a variety of specifications and consistent with individual-level studies showing that cell phone use leads to lower driving quality. The findings also provide guidance for policies aimed at reducing cell phone related accidents and distracted driving.

Suggested Citation

  • Hersh, Jonathan & Lang, Bree J. & Lang, Matthew, 2022. "Car accidents, smartphone adoption and 3G coverage," Journal of Economic Behavior & Organization, Elsevier, vol. 196(C), pages 278-293.
  • Handle: RePEc:eee:jeborg:v:196:y:2022:i:c:p:278-293
    DOI: 10.1016/j.jebo.2022.01.033
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167268122000464
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.jebo.2022.01.033?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Saurabh Bhargava & Vikram S. Pathania, 2013. "Driving under the (Cellular) Influence," American Economic Journal: Economic Policy, American Economic Association, vol. 5(3), pages 92-125, August.
    2. Palsson, Craig, 2017. "Smartphones and child injuries," Journal of Public Economics, Elsevier, vol. 156(C), pages 200-213.
    3. Scott Adams & McKinley L. Blackburn & Chad D. Cotti, 2012. "Minimum Wages and Alcohol-Related Traffic Fatalities among Teens," The Review of Economics and Statistics, MIT Press, vol. 94(3), pages 828-840, August.
    4. Christopher Carpenter & Carlos Dobkin, 2009. "The Effect of Alcohol Consumption on Mortality: Regression Discontinuity Evidence from the Minimum Drinking Age," American Economic Journal: Applied Economics, American Economic Association, vol. 1(1), pages 164-182, January.
    5. Gourieroux, Christian & Monfort, Alain & Trognon, Alain, 1984. "Pseudo Maximum Likelihood Methods: Theory," Econometrica, Econometric Society, vol. 52(3), pages 681-700, May.
    6. Rahi Abouk & Scott Adams, 2013. "Texting Bans and Fatal Accidents on Roadways: Do They Work? Or Do Drivers Just React to Announcements of Bans?," American Economic Journal: Applied Economics, American Economic Association, vol. 5(2), pages 179-199, April.
    7. Liu, Chenhui & Lu, Chaoru & Wang, Shefang & Sharma, Anuj & Shaw, John, 2019. "A longitudinal analysis of the effectiveness of California’s ban on cellphone use while driving," Transportation Research Part A: Policy and Practice, Elsevier, vol. 124(C), pages 456-467.
    8. Nikolaev, Alexander G. & Robbins, Matthew J. & Jacobson, Sheldon H., 2010. "Evaluating the impact of legislation prohibiting hand-held cell phone use while driving," Transportation Research Part A: Policy and Practice, Elsevier, vol. 44(3), pages 182-193, March.
    9. Goodman-Bacon, Andrew, 2021. "Difference-in-differences with variation in treatment timing," Journal of Econometrics, Elsevier, vol. 225(2), pages 254-277.
    10. Mara Faccio & John J. McConnell, 2018. "Death by Pokémon GO: The Economic and Human Cost of Using Apps While Driving," NBER Working Papers 24308, National Bureau of Economic Research, Inc.
    11. Kolko Jed D, 2009. "The Effects of Mobile Phones and Hands-Free Laws on Traffic Fatalities," The B.E. Journal of Economic Analysis & Policy, De Gruyter, vol. 9(1), pages 1-28, March.
    12. Gourieroux, Christian & Monfort, Alain & Trognon, Alain, 1984. "Pseudo Maximum Likelihood Methods: Applications to Poisson Models," Econometrica, Econometric Society, vol. 52(3), pages 701-720, May.
    13. Wilson, F.A. & Stimpson, J.P., 2010. "Trends in fatalities from distracted driving in the United States, 1999 to 2008," American Journal of Public Health, American Public Health Association, vol. 100(11), pages 2213-2219.
    14. Leandro Rocco & Breno Sampaio, 2016. "Are handheld cell phone and texting bans really effective in reducing fatalities?," Empirical Economics, Springer, vol. 51(2), pages 853-876, September.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. French, Michael T. & Gumus, Gulcin, 2018. "Watch for motorcycles! The effects of texting and handheld bans on motorcyclist fatalities," Social Science & Medicine, Elsevier, vol. 216(C), pages 81-87.
    2. Leandro Rocco & Breno Sampaio, 2016. "Are handheld cell phone and texting bans really effective in reducing fatalities?," Empirical Economics, Springer, vol. 51(2), pages 853-876, September.
    3. Wright, Nicholas A. & Dorilas, Ernest, 2022. "Do Cellphone Bans Save Lives? Evidence From Handheld Laws on Traffic Fatalities," Journal of Health Economics, Elsevier, vol. 85(C).
    4. Rahi Abouk & Scott Adams, 2013. "Texting Bans and Fatal Accidents on Roadways: Do They Work? Or Do Drivers Just React to Announcements of Bans?," American Economic Journal: Applied Economics, American Economic Association, vol. 5(2), pages 179-199, April.
    5. Erik Nesson & Vinish Shrestha, 2021. "The effects of false identification laws on underage alcohol‐related traffic fatalities," Health Economics, John Wiley & Sons, Ltd., vol. 30(9), pages 2264-2283, September.
    6. Anand, Vaibhav, 2022. "The Value of Forecast Improvements: Evidence from Advisory Lead Times and Vehicle Crashes," MPRA Paper 114491, University Library of Munich, Germany.
    7. Erik Nesson & Vinish Shrestha, 2016. "The Effects of False Identification Laws with a Scanner Provision on Underage Alcohol-Related Traffic Fatalities," Working Papers 2016-17, Towson University, Department of Economics, revised Apr 2020.
    8. Anderson, D. Mark & Sandholt, Sina, 2016. "Booster Seats and Traffic Fatalities among Children," IZA Discussion Papers 10071, Institute of Labor Economics (IZA).
    9. D. Mark Anderson & Sina Sandholt, 2019. "Are Booster Seats More Effective than Child Safety Seats or Seat Belts at Reducing Traffic Fatalities among Children?," American Journal of Health Economics, MIT Press, vol. 5(1), pages 42-64, Winter.
    10. J. Bradley Karl & Charles M. Nyce & Lawrence Powell & Boyi Zhuang, 2023. "How risky is distracted driving?," Journal of Risk and Uncertainty, Springer, vol. 66(3), pages 279-312, June.
    11. D. Mark Anderson & Benjamin Hansen & Daniel I. Rees, 2013. "Medical Marijuana Laws, Traffic Fatalities, and Alcohol Consumption," Journal of Law and Economics, University of Chicago Press, vol. 56(2), pages 333-369.
    12. Giuliani, Elisa & Martinelli, Arianna & Rabellotti, Roberta, 2016. "Is Co-Invention Expediting Technological Catch Up? A Study of Collaboration between Emerging Country Firms and EU Inventors," World Development, Elsevier, vol. 77(C), pages 192-205.
    13. Bettina Becker & Martin Theuringer, 2000. "Macroeconomic Determinants of Contingent Protection: The Case of the European Union," IWP Discussion Paper Series 02/2000, Institute for Economic Policy, Cologne, Germany.
    14. Hallin, Marc & La Vecchia, Davide, 2020. "A Simple R-estimation method for semiparametric duration models," Journal of Econometrics, Elsevier, vol. 218(2), pages 736-749.
    15. Barone-Adesi, Giovanni & Fusari, Nicola & Mira, Antonietta & Sala, Carlo, 2020. "Option market trading activity and the estimation of the pricing kernel: A Bayesian approach," Journal of Econometrics, Elsevier, vol. 216(2), pages 430-449.
    16. Silva João M. C. Santos & Tenreyro Silvana & Windmeijer Frank, 2015. "Testing Competing Models for Non-negative Data with Many Zeros," Journal of Econometric Methods, De Gruyter, vol. 4(1), pages 1-18, January.
    17. de Rassenfosse, Gaétan & Schoen, Anja & Wastyn, Annelies, 2014. "Selection bias in innovation studies: A simple test," Technological Forecasting and Social Change, Elsevier, vol. 81(C), pages 287-299.
    18. Gary King, 1989. "A Seemingly Unrelated Poisson Regression Model," Sociological Methods & Research, , vol. 17(3), pages 235-255, February.
    19. Jeff DeSimone & Daniel Grossman & Nicolas Ziebarth, 2023. "Regression Discontinuity Evidence on the Effectiveness of the Minimum Legal E-cigarette Purchasing Age," American Journal of Health Economics, University of Chicago Press, vol. 9(3), pages 461-485.
    20. Emilie Alberola & Julien Chevallier & Benoît Chèze, 2008. "The EU Emissions Trading Scheme : Disentangling the Effects of Industrial Production and CO2 Emissions on Carbon Prices," Working Papers hal-04140795, HAL.

    More about this item

    Keywords

    3G Coverage; Car accidents; Smartphones; Machine learning; Random forest;
    All these keywords.

    JEL classification:

    • R41 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Transportation: Demand, Supply, and Congestion; Travel Time; Safety and Accidents; Transportation Noise
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:jeborg:v:196:y:2022:i:c:p:278-293. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/jebo .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.