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The 1920s technological revolution and the crash of 1929: the role of RCA, DuPont, General Motors, and Union Carbide

Author

Listed:
  • Dimitra Papadovasilaki

    (Lake Forest College)

  • Federico Guerrero

    (University of Nevada)

  • Rattaphon Wuthisatian

    (Southern Oregon University)

  • Bhraman Gulati

    (Colorado State University)

Abstract

We study the role that RCA, DuPont, General Motors, and Union Carbide played in the 1927–1933 stock market boom and crash episode. We investigate whether a technological displacement took place and if the cycle was characterized by over-trading. The reasons we reexamine this episode is to contribute to the literature in the following ways: (1) The episode is studied using price and volume, daily data at the company level for the first time. (2) The paper introduces a methodological innovation and in contrast to previous literature, identifies technological displacement with the use of qualitative criteria rather than quantitative metrics. We display that the crash of 1929 originated in speculative activity revolving around a few companies that were the most innovative of the time, namely: RCA, DuPont, General Motors, and Union Carbide, and later extended to the rest of the stock market. These companies led the boom that preceded the crash, reinforcing the idea that radical technological innovations responsible for enhancing long-term prosperity can be the same ones that produce large financial cycles.

Suggested Citation

  • Dimitra Papadovasilaki & Federico Guerrero & Rattaphon Wuthisatian & Bhraman Gulati, 2022. "The 1920s technological revolution and the crash of 1929: the role of RCA, DuPont, General Motors, and Union Carbide," SN Business & Economics, Springer, vol. 2(5), pages 1-22, May.
    • Handle: RePEc:spr:snbeco:v:2:y:2022:i:5:d:10.1007_s43546-022-00208-3
    DOI: 10.1007/s43546-022-00208-3
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    References listed on IDEAS

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    1. Robert Z. Aliber & Charles P. Kindleberger, 2015. "Manias, Panics, and Crashes," Palgrave Macmillan Books, Palgrave Macmillan, edition 0, number 978-1-137-52574-1, December.
    2. Rappoport, Peter & White, Eugene N, 1994. "Was the Crash of 1929 Expected?," American Economic Review, American Economic Association, vol. 84(1), pages 271-281, March.
    3. Rappoport, Peter & White, Eugene N., 1993. "Was There a Bubble in the 1929 Stock Market?," The Journal of Economic History, Cambridge University Press, vol. 53(3), pages 549-574, September.
    4. Gili Yen & Cheng-few Lee, 2008. "Efficient Market Hypothesis (EMH): Past, Present and Future," Review of Pacific Basin Financial Markets and Policies (RPBFMP), World Scientific Publishing Co. Pte. Ltd., vol. 11(02), pages 305-329.
    5. Bradley Ewing & Mark Thompson & Mark Yanochik, 2007. "Using volume to forecast stock market volatility around the time of the 1929 crash," Applied Financial Economics, Taylor & Francis Journals, vol. 17(14), pages 1123-1128.
    6. DeJong, David N, et al, 1992. "Integration versus Trend Stationarity in Time Series," Econometrica, Econometric Society, vol. 60(2), pages 423-433, March.
    7. Ellen R. McGrattan & Edward C. Prescott, 2000. "Is the stock market overvalued?," Quarterly Review, Federal Reserve Bank of Minneapolis, vol. 24(Fall), pages 20-40.
    8. Burton G. Malkiel, 2003. "The Efficient Market Hypothesis and Its Critics," Working Papers 111, Princeton University, Department of Economics, Center for Economic Policy Studies..
    9. Ali Kabiri, 2014. "The Great Crash of 1929," Palgrave Studies in the History of Finance, Palgrave Macmillan, number 978-1-137-37289-5, February.
    10. Burton G. Malkiel, 2003. "The Efficient Market Hypothesis and Its Critics," Working Papers 111, Princeton University, Department of Economics, Center for Economic Policy Studies..
    11. Luboš Pástor & Pietro Veronesi, 2009. "Technological Revolutions and Stock Prices," American Economic Review, American Economic Association, vol. 99(4), pages 1451-1483, September.
    12. Tom Nicholas, 2008. "Does Innovation Cause Stock Market Runups? Evidence from the Great Crash," American Economic Review, American Economic Association, vol. 98(4), pages 1370-1396, September.
    13. repec:pri:cepsud:91malkiel is not listed on IDEAS
    14. Mathy, Gabriel P., 2016. "Stock volatility, return jumps and uncertainty shocks during the Great Depression," Financial History Review, Cambridge University Press, vol. 23(2), pages 165-192, August.
    15. Sirkin, Gerald, 1975. "The Stock Market of 1929 Revisited: A Note," Business History Review, Cambridge University Press, vol. 49(2), pages 223-231, July.
    16. Pierse, R. G. & Snell, A. J., 1995. "Temporal aggregation and the power of tests for a unit root," Journal of Econometrics, Elsevier, vol. 65(2), pages 333-345, February.
    17. Burton G. Malkiel, 2003. "The Efficient Market Hypothesis and Its Critics," Journal of Economic Perspectives, American Economic Association, vol. 17(1), pages 59-82, Winter.
    18. Jörg Breitung & Norman R. Swanson, 2002. "Temporal aggregation and spurious instantaneous causality in multiple time series models," Journal of Time Series Analysis, Wiley Blackwell, vol. 23(6), pages 651-665, November.
    19. De Long, J. Bradford & Shleifer, Andrei, 1991. "The stock market bubble of 1929: evidence from clsoed-end mutual funds," The Journal of Economic History, Cambridge University Press, vol. 51(3), pages 675-700, September.
    20. Marcellino, Massimiliano, 1999. "Some Consequences of Temporal Aggregation in Empirical Analysis," Journal of Business & Economic Statistics, American Statistical Association, vol. 17(1), pages 129-136, January.
    21. Donaldson, R Glen & Kamstra, Mark, 1996. "A New Dividend Forecasting Procedure That Rejects Bubbles in Asset Prices: The Case of 1929's Stock Crash," The Review of Financial Studies, Society for Financial Studies, vol. 9(2), pages 333-383.
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    More about this item

    Keywords

    Financial crisis; Great crash; 1929 Stock market crash; Technological displacement;
    All these keywords.

    JEL classification:

    • N20 - Economic History - - Financial Markets and Institutions - - - General, International, or Comparative
    • N12 - Economic History - - Macroeconomics and Monetary Economics; Industrial Structure; Growth; Fluctuations - - - U.S.; Canada: 1913-

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