IDEAS home Printed from https://ideas.repec.org/p/cen/wpaper/20-28.html
   My bibliography  Save this paper

Identifying U.S. Merchandise Traders: Integrating Customs Transactions with Business Administrative Data

Author

Listed:
  • Fariha Kamal
  • Wei Ouyang

Abstract

This paper describes the construction of the Longitudinal Firm Trade Transactions Database (LFTTD) enabling the identification of merchandise traders - exporters and importers - in the U.S. Census Bureau’s Business Register (BR). The LFTTD links merchandise export and import transactions from customs declaration forms to the BR beginning in 1992 through the present. We employ a combination of deterministic and probabilistic matching algorithms to assign a unique firm identifier in the BR to a merchandise export or import transaction record. On average, we match 89 percent of export and import values to a firm identifier. In 1992, we match 79 (88) percent of export (import) value; in 2017, we match 92 (96) percent of export (import) value. Trade transactions in year t are matched to years between 1976 and t+1 of the BR. On average, 94 percent of the trade value matches to a firm in year t of the BR. The LFTTD provides the most comprehensive identification of and the foundation for the analysis of goods trading firms in the U.S. economy.

Suggested Citation

  • Fariha Kamal & Wei Ouyang, 2020. "Identifying U.S. Merchandise Traders: Integrating Customs Transactions with Business Administrative Data," Working Papers 20-28, Center for Economic Studies, U.S. Census Bureau.
    • Handle: RePEc:cen:wpaper:20-28
    as

    Download full text from publisher

    File URL: https://www2.census.gov/ces/wp/2020/CES-WP-20-28.pdf
    File Function: First version, 2020
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. John Cuffe & Nathan Goldschlag, 2018. "Squeezing More Out of Your Data: Business Record Linkage with Python," Working Papers 18-46, Center for Economic Studies, U.S. Census Bureau.
    2. Christoph E. Boehm & Aaron Flaaen & Nitya Pandalai-Nayar, 2019. "Input Linkages and the Transmission of Shocks: Firm-Level Evidence from the 2011 Tōhoku Earthquake," The Review of Economics and Statistics, MIT Press, vol. 101(1), pages 60-75, March.
    3. Bethany DeSalvo & Frank F. Limehouse & Shawn D. Klimek, 2016. "Documenting the Business Register and Related Economic Business Data," Working Papers 16-17, Center for Economic Studies, U.S. Census Bureau.
    4. Christopher Ordowich & David Cheney & Jan Youtie & Andrea Fernández-Ribas & Philip Shapira, 2012. "Evaluating the Impact of MEP Services on Establishment Performance: A Preliminary Empirical Investigation," Working Papers 12-15, Center for Economic Studies, U.S. Census Bureau.
    5. Timothy Dunne & J. Bradford Jensen & Mark J. Roberts, 2009. "Producer Dynamics: New Evidence from Micro Data," NBER Books, National Bureau of Economic Research, Inc, number dunn05-1, March.
    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. Richard Beem & Christopher Goetz & Martha Stinson & Sean Wang, 2022. "Business Dynamics Statistics for Single-Unit Firms," Working Papers 22-57, Center for Economic Studies, U.S. Census Bureau.
    2. Basker, Emek & Kamal, Fariha, 2021. "Recall and response: Relationship adjustments to adverse information shocks," European Economic Review, Elsevier, vol. 139(C).
    3. Melissa C. Chow & Teresa C. Fort & Christopher Goetz & Nathan Goldschlag & James Lawrence & Elisabeth Ruth Perlman & Martha Stinson & T. Kirk White, 2021. "Redesigning the Longitudinal Business Database," NBER Working Papers 28839, National Bureau of Economic Research, Inc.

    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. Basker, Emek & Kamal, Fariha, 2021. "Recall and response: Relationship adjustments to adverse information shocks," European Economic Review, Elsevier, vol. 139(C).
    2. Andrea Coveri & Claudio Cozza & Leopoldo Nascia & Antonello Zanfei, 2020. "Supply chain contagion and the role of industrial policy," Economia e Politica Industriale: Journal of Industrial and Business Economics, Springer;Associazione Amici di Economia e Politica Industriale, vol. 47(3), pages 467-482, September.
    3. Kurz, Christopher & Senses, Mine Z., 2016. "Importing, exporting, and firm-level employment volatility," Journal of International Economics, Elsevier, vol. 98(C), pages 160-175.
    4. Kyle Handley & Fariha Kamal & Ryan Monarch, 2020. "Rising Import Tariffs, Falling Export Growth: When Modern Supply Chains Meet Old-Style Protectionism," Working Papers 676, Research Seminar in International Economics, University of Michigan.
    5. Pol Antràs & Davin Chor, 2021. "Global Value Chains," NBER Working Papers 28549, National Bureau of Economic Research, Inc.
    6. Fariha Kamal & Jessica McCloskey & Wei Ouyang, 2022. "Multinational Firms in the U.S. Economy: Insights from Newly Integrated Microdata," BEA Working Papers 0202, Bureau of Economic Analysis.
    7. Joseph Staudt & Yifang Wei & Lisa Singh & Shawn Klimek & J. Bradford Jensen & Andrew Baer, 2019. "Automating Response Evaluation for Franchising Questions on the 2017 Economic Census," NBER Chapters, in: Big Data for Twenty-First-Century Economic Statistics, pages 209-227, National Bureau of Economic Research, Inc.
    8. Fariha Kamal & Jessica McCloskey & Wei Ouyang, 2022. "Multinational Firms in the U.S. Economy: Insights from Newly Integrated Microdata," Working Papers 22-39, Center for Economic Studies, U.S. Census Bureau.
    9. Fariha Kamal & Asha Sundaram & Cristina J. Tello-Trillo, 2020. "Family-Leave Mandates and Female Labor at U.S. Firms: Evidence from a Trade Shock," Working Papers 20-25, Center for Economic Studies, U.S. Census Bureau.
    10. C.J. Krizan, 2015. "Statistics on the International Trade Administration's Global Markets Program," Working Papers 15-17, Center for Economic Studies, U.S. Census Bureau.
    11. John M. Abowd & Ian M. Schmutte & Lars Vilhuber, 2018. "Disclosure Limitation and Confidentiality Protection in Linked Data," Working Papers 18-07, Center for Economic Studies, U.S. Census Bureau.
    12. Alexandre Janiak & Paulo Santos Monteiro, 2011. "Inflation and Welfare in Long‐Run Equilibrium with Firm Dynamics," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 43(5), pages 795-834, August.
    13. Lawless, Martina & Siedschlag, Iulia & Studnicka, Zuzanna, 2017. "Expanding and diversifying the manufactured exports of Irish-owned enterprises," Research Series, Economic and Social Research Institute (ESRI), number BKMNEXT335, June.
    14. Vasco M. Carvalho & Alireza Tahbaz-Salehi, 2019. "Production Networks: A Primer," Annual Review of Economics, Annual Reviews, vol. 11(1), pages 635-663, August.
    15. Stephen J. Redding & David E. Weinstein, 2017. "Aggregating from Micro to Macro Patterns of Trade," NBER Working Papers 24051, National Bureau of Economic Research, Inc.
    16. Jose Asturias & Emin Dinlersoz & John Haltiwanger & Rebecca Hutchinson, 2021. "Business Applications as Economic Indicators," Working Papers 21-09, Center for Economic Studies, U.S. Census Bureau.
    17. Andrew B. Bernard & J. Bradford Jensen & Stephen J. Redding & Peter K. Schott, 2018. "Global Firms," Journal of Economic Literature, American Economic Association, vol. 56(2), pages 565-619, June.
    18. Alessandra Bonfiglioli & Rosario Crinò & Gino Gancia, 2018. "Firms and Economic Performance: A view from Trade," Working Papers 1034, Barcelona School of Economics.
    19. Daniel Fackler & Claus Schnabel & Joachim Wagner, 2013. "Establishment exits in Germany: the role of size and age," Small Business Economics, Springer, vol. 41(3), pages 683-700, October.
    20. David Baqaee & Emmanuel Farhi, 2020. "Nonlinear Production Networks with an Application to the Covid-19 Crisis," NBER Working Papers 27281, National Bureau of Economic Research, Inc.

    More about this item

    Keywords

    trade transactions; matching; machine learning;
    All these keywords.

    JEL classification:

    • F00 - International Economics - - General - - - General
    • F10 - International Economics - - Trade - - - General
    • F14 - International Economics - - Trade - - - Empirical Studies of Trade

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:cen:wpaper:20-28. 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: Dawn Anderson (email available below). General contact details of provider: https://edirc.repec.org/data/cesgvus.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.