IDEAS home Printed from https://ideas.repec.org/
MyIDEAS: Log in (now much improved!) to save this paper

Quantitative Trade Models: Developments and Challenges

Listed author(s):
  • Timothy J. Kehoe
  • Pau S. Pujolas
  • Jack Rossbach

Applied general equilibrium (AGE) models, which feature multiple countries, multiple industries, and input-output linkages across industries, have been the dominant tool for evaluating the impact of trade reforms since the 1980s. We review how these models are used to perform policy analysis and document their shortcomings in predicting the industry-level effects of past trade reforms. We argue that, to improve their performance, AGE models need to incorporate product-level data on bilateral trade relations by industry and better model how trade reforms lower bilateral trade costs. We use the least traded products methodology of Kehoe et al. (2015) to provide guidance on how improvements can be made. We provide further suggestions on how AGE models can incorporate recent advances in quantitative trade theory to improve their predictive ability and better quantify the gains from trade liberalization.

If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

File URL: http://www.nber.org/papers/w22706.pdf
Download Restriction: Access to the full text is generally limited to series subscribers, however if the top level domain of the client browser is in a developing country or transition economy free access is provided. More information about subscriptions and free access is available at http://www.nber.org/wwphelp.html. Free access is also available to older working papers.

As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.

Paper provided by National Bureau of Economic Research, Inc in its series NBER Working Papers with number 22706.

as
in new window

Length:
Date of creation: Sep 2016
Publication status: published as Timothy J. Kehoe & Pau S. Pujolàs & Jack Rossbach, 2017. "Quantitative Trade Models: Developments and Challenges," Annual Review of Economics, vol 9(1), pages 295-325.
Handle: RePEc:nbr:nberwo:22706
Note: EFG ITI
Contact details of provider: Postal:
National Bureau of Economic Research, 1050 Massachusetts Avenue Cambridge, MA 02138, U.S.A.

Phone: 617-868-3900
Web page: http://www.nber.org
Email:


More information through EDIRC

No references listed on IDEAS
You can help add them by filling out this form.

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

When requesting a correction, please mention this item's handle: RePEc:nbr:nberwo:22706. 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: ()

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 references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link 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 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.

This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.