IDEAS home Printed from https://ideas.repec.org/p/cge/wacage/729.html
   My bibliography  Save this paper

Did Tariffs Make American Manufacturing Great? New Evidence from the Gilded Age

Author

Listed:
  • Klein, Alexander

    (University of Sussex, CEPR and CAGE)

  • Meissner, Christopher M.

    (University of California, Davis and NBER)

Abstract

We study the relationship between tariffs and labor productivity in US manufacturing between 1870 and 1909. Using highly disaggregated tariff data, state-industry data for the manufacturing sector, and a novel identification strategy, results show that tariffs reduced labor productivity. Tariffs also generally reduced the average size of establishments within an industry but raised output prices, value-added, gross output, employment, and the number of establishments. We also find evidence of heterogeneity in the association between tariffs and value added, gross output, employment, and establishments across groups of industries. We conclude that tariffs may have reduced labor productivity in manufacturing by weakening import competition and by inducing entry of smaller, less productive domestic firms. Our research also reveals that lobbying by powerful and productive industries may have been at play. The era’s high tariffs are unlikely to have helped the US become a globally competitive manufacturer.

Suggested Citation

  • Klein, Alexander & Meissner, Christopher M., 2024. "Did Tariffs Make American Manufacturing Great? New Evidence from the Gilded Age," CAGE Online Working Paper Series 729, Competitive Advantage in the Global Economy (CAGE).
    • Handle: RePEc:cge:wacage:729
    as

    Download full text from publisher

    File URL: https://warwick.ac.uk/fac/soc/economics/research/centres/cage/manage/publications/wp729.2024.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Douglas A. Irwin, 2017. "Clashing over Commerce: A History of US Trade Policy," NBER Books, National Bureau of Economic Research, Inc, number irwi-2, March.
    2. Allen, Robert C., 2014. "American Exceptionalism as a Problem in Global History," The Journal of Economic History, Cambridge University Press, vol. 74(2), pages 309-350, June.
    3. Djogbenou, Antoine A. & MacKinnon, James G. & Nielsen, Morten Ørregaard, 2019. "Asymptotic theory and wild bootstrap inference with clustered errors," Journal of Econometrics, Elsevier, vol. 212(2), pages 393-412.
    4. James Foreman-Peck, 2019. "An American and European technological difference: The early motor car power source," Business History, Taylor & Francis Journals, vol. 61(7), pages 1158-1174, October.
    5. Huberman, Michael & Meissner, Christopher M. & Oosterlinck, Kim, 2017. "Technology and Geography in the Second Industrial Revolution: New Evidence from the Margins of Trade," The Journal of Economic History, Cambridge University Press, vol. 77(1), pages 39-89, March.
    6. Papke, Leslie E. & Wooldridge, Jeffrey M., 2008. "Panel data methods for fractional response variables with an application to test pass rates," Journal of Econometrics, Elsevier, vol. 145(1-2), pages 121-133, July.
    7. John W. Kendrick, 1961. "Productivity Trends in the United States," NBER Books, National Bureau of Economic Research, Inc, number kend61-1, March.
    8. Carter,Susan B. & Gartner,Scott Sigmund & Haines,Michael R. & Olmstead,Alan L. & Sutch,Richard & Wri (ed.), 2006. "The Historical Statistics of the United States 5 Volume Hardback Set," Cambridge Books, Cambridge University Press, number 9780521817912, January.
    9. Sibylle H. Lehmann & Kevin H. O'Rourke, 2011. "The Structure of Protection and Growth in the Late Nineteenth Century," The Review of Economics and Statistics, MIT Press, vol. 93(2), pages 606-616, May.
    10. repec:ucp:bkecon:9780226398969 is not listed on IDEAS
    11. Djogbenou, Antoine A. & MacKinnon, James G. & Orregaard Nielsen, Morten, 2018. "Asymptotic Theory and Wild Bootstrap Inference with Clustered Errors," Queen's Economics Department Working Papers 274725, Queen's University - Department of Economics.
    12. Helen Hunter, 1955. "Innovation, Competition, and Locational Changes in the Pulp and Paper Industry: 1880-1950," Land Economics, University of Wisconsin Press, vol. 31(4), pages 314-327.
    13. Joseph H. Davis, 2004. "An Annual Index of U. S. Industrial Production, 1790–1915," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 119(4), pages 1177-1215.
    14. José Luis Montiel Olea & Carolin Pflueger, 2013. "A Robust Test for Weak Instruments," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 31(3), pages 358-369, July.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Brian D. Varian, 2025. "Effective Rates of Protection in an Industrialising, Settler Economy: Estimates for Victoria (Australia) in 1880," CEH Discussion Papers 02, Centre for Economic History, Research School of Economics, Australian National University.

    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. Wenjie Wang & Yichong Zhang, 2021. "Wild Bootstrap for Instrumental Variables Regressions with Weak and Few Clusters," Papers 2108.13707, arXiv.org, revised Jan 2024.
    2. MacKinnon, James G., 2023. "Fast cluster bootstrap methods for linear regression models," Econometrics and Statistics, Elsevier, vol. 26(C), pages 52-71.
    3. Wang, Wenjie, 2021. "Wild Bootstrap for Instrumental Variables Regression with Weak Instruments and Few Clusters," MPRA Paper 106227, University Library of Munich, Germany.
    4. Wang, Wenjie & Zhang, Yichong, 2024. "Wild bootstrap inference for instrumental variables regressions with weak and few clusters," Journal of Econometrics, Elsevier, vol. 241(1).
    5. Schnitzlein, Charles & Chelley-Steeley, Patricia & Steeley, James M, 2024. "Conflicting versus reinforcing private information, information aggregation, and the time series properties of asset prices," Journal of Banking & Finance, Elsevier, vol. 169(C).
    6. James G. MacKinnon & Morten Ørregaard Nielsen & Matthew D. Webb, 2023. "Fast and reliable jackknife and bootstrap methods for cluster‐robust inference," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(5), pages 671-694, August.
    7. Costa-Font, Joan & Vilaplana-Prieto, Cristina, 2022. "Health shocks and housing downsizing: How persistent is ‘ageing in place’?," Journal of Economic Behavior & Organization, Elsevier, vol. 204(C), pages 490-508.
    8. David Roodman & James G. MacKinnon & Morten Ørregaard Nielsen & Matthew D. Webb, 2019. "Fast and wild: Bootstrap inference in Stata using boottest," Stata Journal, StataCorp LLC, vol. 19(1), pages 4-60, March.
    9. Solórzano Diego & Dixon Huw, 2020. "The Relationship Between Nominal Wage and Price Flexibility: New Evidence," Working Papers 2020-20, Banco de México.
    10. Iscan Talan, 2010. "How Much Can Engel's Law and Baumol's Disease Explain the Rise of Service Employment in the United States?," The B.E. Journal of Macroeconomics, De Gruyter, vol. 10(1), pages 1-43, September.
    11. Djogbenou, Antoine A. & MacKinnon, James G. & Orregaard Nielsen, Morten, 2018. "Asymptotic Theory and Wild Bootstrap Inference with Clustered Errors," Queen's Economics Department Working Papers 274725, Queen's University - Department of Economics.
    12. Ritschl, Albrecht & Sarferaz, Samad & Uebele, Martin, 2008. "The U.S. business cycle, 1867-1995: Dynamic factor analysis vs. reconstructed national accounts," SFB 649 Discussion Papers 2008-066, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    13. James G. MacKinnon, 2019. "How cluster‐robust inference is changing applied econometrics," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 52(3), pages 851-881, August.
    14. Lee, Sunyoung, 2025. "Did recreational marijuana legalization increase crime in the long run?," International Review of Law and Economics, Elsevier, vol. 82(C).
    15. Hilt, Eric & Jaremski, Matthew & Rahn, Wendy, 2022. "When Uncle Sam introduced Main Street to Wall Street: Liberty Bonds and the transformation of American finance," Journal of Financial Economics, Elsevier, vol. 145(1), pages 194-216.
    16. Liyu Dou & Pengjin Min & Wenjie Wang & Yichong Zhang, 2025. "An Improved Inference for IV Regressions," Papers 2506.23816, arXiv.org.
    17. Yuya Sasaki & Yulong Wang, 2022. "Non-Robustness of the Cluster-Robust Inference: with a Proposal of a New Robust Method," Papers 2210.16991, arXiv.org, revised Jan 2025.
    18. Dario Tortarolo & Guillermo Cruces & Gonzalo Vazquez-Bare, 2023. "Design of partial population experiments with an application to spillovers in tax compliance," IFS Working Papers W23/17, Institute for Fiscal Studies.
    19. Hansen, Bruce E. & Lee, Seojeong, 2019. "Asymptotic theory for clustered samples," Journal of Econometrics, Elsevier, vol. 210(2), pages 268-290.
    20. Giulio Cornelli & Magdalena Erdem & Egon Zakrajsek, 2024. "CEO turnover risk and firm environmental performance," BIS Working Papers 1190, Bank for International Settlements.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    JEL classification:

    • F13 - International Economics - - Trade - - - Trade Policy; International Trade Organizations
    • F15 - International Economics - - Trade - - - Economic Integration
    • N11 - Economic History - - Macroeconomics and Monetary Economics; Industrial Structure; Growth; Fluctuations - - - U.S.; Canada: Pre-1913
    • O14 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Industrialization; Manufacturing and Service Industries; Choice of Technology
    • O47 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Empirical Studies of Economic Growth; Aggregate Productivity; Cross-Country Output Convergence

    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:cge:wacage:729. 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: Jane Snape (email available below). General contact details of provider: https://edirc.repec.org/data/dewaruk.html .

    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.