IDEAS home Printed from
   My bibliography  Save this paper

Bargaining Power in Firm-to-Firm Relationships - ‎Two Methodologies to Detect Outliers in the Census Trade Data


  • Sebastian Heise


This note develops two methodologies to detect possibly incorrectly reported shipment values and quantities in the Longitudinal Foreign Trade Transactions Database (LFTTD). Both approaches seek to identify outliers in terms of unit values, defined as the ratio of value and quantity shipped. The first methodology examines trades in the far tails of the cross-sectional unit value distribution across importers or exporters, and highlights those trades that appear incompatible with a given U.S. firm's own transactions. The second approach identifies outliers as cases where a unit value jumps by an order of magnitude compared to a U.S. firm's transactions over the past two years. While both approaches reveal that outliers are relatively rare, the note highlights several cases where outliers were very large and possibly affected trade statistics. The note further presents distributions of outliers by value and discusses the countries and products that exhibit the largest shares of outliers. It also presents a number of examples to showcase that outliers identified by the two methodologies appear suspicious also to a human looking at the data. The note concludes with a discussion of the advantages and the disadvantages of the two approaches. The code files referenced in this file are available to Census employees and will hopefully be of use going forward.

Suggested Citation

  • Sebastian Heise, 2017. "Bargaining Power in Firm-to-Firm Relationships - ‎Two Methodologies to Detect Outliers in the Census Trade Data," CES Technical Notes Series 17-03, Center for Economic Studies, U.S. Census Bureau.
  • Handle: RePEc:cen:tnotes:17-03

    Download full text from publisher

    File URL:
    File Function: Abstract
    Download Restriction: CES Technical Notes may contain confidential data and, thereby, disclosure is prohibited. Researchers on approved projects (to apply for access, please see with the correct permissions can request full text notes from

    File URL:
    File Function: Confidential main document
    Download Restriction: Researchers need to have obtained appropriate permissions.

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

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:


    Access and download statistics


    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:tnotes:17-03. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Danielle H. Sandler). General contact details of provider: .

    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.

    We have no references for this item. You can help adding them by using 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.