IDEAS home Printed from
   My bibliography  Save this paper

How Confident Can We Be In Cge-Based Assessments Of Free Trade Agreements?


  • Hertel, Thomas W.
  • Hummels, David
  • Ivanic, Maros
  • Keeney, Roman


With the proliferation of Free Trade Agreements (FTAs) over the past decade, demand for quantitative analysis of their likely impacts has surged. The main quantitative tool for performing such analysis is Computable General Equilibrium (CGE) modeling. Yet these models have been widely criticized for performing poorly (Kehoe, 2002) and having weak econometric foundations (McKitrick, 1998; Jorgenson, 1984). FTA results have been shown to be particularly sensitive to the trade elasticities, with small trade elasticities generating large terms of trade effects and relatively modest efficiency gains, whereas large trade elasticities lead to the opposite result. Critics are understandably wary of results being determined largely by the authors' choice of trade elasticities. Where do these trade elasticities come from? CGE modelers typically draw these elasticities from econometric work that uses time series price variation to identify an elasticity of substitution between domestic goods and composite imports (Alaouze, 1977; Alaouze, et al., 1977; Stern et al., 1976; Gallaway, McDaniel and Rivera, 2003). This approach has three problems: the use of point estimates as "truth", the magnitude of the point estimates, and estimating the relevant elasticity. First, modelers take point estimates drawn from the econometric literature, while ignoring the precision of these estimates. As we will make clear below, the confidence one has in various CGE conclusions depends critically on the size of the confidence interval around parameter estimates. Standard "robustness checks" such as systematically raising or lowering the substitution parameters does not properly address this problem because it ignores information about which parameters we know with some precision and which we do not. A second problem with most existing studies derives from the use of import price series to identify home vs. foreign substitution, for example, tends to systematically understate the true elasticity. This is because these estimates take price variation as exogenous when estimating the import demand functions, and ignore quality variation. When quality is high, import demand and prices will be jointly high. This biases estimated elasticities toward zero. A related point is that the fixed-weight import price series used by most authors are theoretically inappropriate for estimating the elasticities of interest. CGE modelers generally examine a nested utility structure, with domestic production substitution for a CES composite import bundle. The appropriate price series is then the corresponding CES price index among foreign varieties. Constructing such an index requires knowledge of the elasticity of substitution among foreign varieties (see below). By using a fixed-weight import price series, previous estimates place too much weight on high foreign prices, and too small a weight on low foreign prices. In other words, they overstate the degree of price variation that exists, relative to a CES price index. Reconciling small trade volume movements with large import price series movements requires a small elasticity of substitution. This problem, and that of unmeasured quality variation, helps explain why typical estimated elasticities are very small. The third problem with the existing literature is that estimates taken from other researchers' studies typically employ different levels of aggregation, and exploit different sources of price variation, from what policy modelers have in mind. Employment of elasticities in experiments ill-matched to their original estimation can be problematic. For example, estimates may be calculated at a higher or lower level of aggregation than the level of analysis than the modeler wants to examine. Estimating substitutability across sources for paddy rice gives one a quite different answer than estimates that look at agriculture as a whole. When analyzing Free Trade Agreements, the principle policy experiment is a change in relative prices among foreign suppliers caused by lowering tariffs within the FTA. Understanding the substitution this will induce across those suppliers is critical to gauging the FTA's real effects. Using home v. foreign elasticities rather than elasticities of substitution among imports supplied from different countries may be quite misleading. Moreover, these "sourcing" elasticities are critical for constructing composite import price series to appropriate estimate home v. foreign substitutability. In summary, the history of estimating the substitution elasticities governing trade flows in CGE models has been checkered at best. Clearly there is a need for improved econometric estimation of these trade elasticities that is well-integrated into the CGE modeling framework. This paper provides such estimation and integration, and has several significant merits. First, we choose our experiment carefully. Our CGE analysis focuses on the prospective Free Trade Agreement of the Americas (FTAA) currently under negotiation. This is one of the most important FTAs currently "in play" in international negotiations. It also fits nicely with the source data used to estimate the trade elasticities, which is largely based on imports into North and South America. Our assessment is done in a perfectly competitive, comparative static setting in order to emphasize the role of the trade elasticities in determining the conventional gains/losses from such an FTA. This type of model is still widely used by government agencies for the evaluation of such agreements. Extensions to incorporate imperfect competition are straightforward, but involve the introduction of additional parameters (markups, extent of unexploited scale economies) as well as structural assumptions (entry/no-entry, nature of inter-firm rivalry) that introduce further uncertainty. Since our focus is on the effects of a PTA we estimate elasticities of substitution across multiple foreign supply sources. We do not use cross-exporter variation in prices or tariffs alone. Exporter price series exhibit a high degree of multicolinearity, and in any case, would be subject to unmeasured quality variation as described previously. Similarly, tariff variation by itself is typically unhelpful because by their very nature, Most Favored Nation (MFN) tariffs are non-discriminatory in nature, affecting all suppliers in the same way. Tariff preferences, where they exist, are often difficult to measure- sometimes being confounded by quantitative barriers, restrictive rules of origin, and other restrictions. Instead we employ a unique methodology and data set drawing on not only tariffs, but also bilateral transportation costs for goods traded internationally (Hummels, 1999). Transportation costs vary much more widely than do tariffs, allowing much more precise estimation of the trade elasticities that are central to CGE analysis of FTAs. We have highly disaggregated commodity trade flow data, and are therefore able to provide estimates that precisely match the commodity aggregation scheme employed in the subsequent CGE model. We follow the GTAP Version 5.0 aggregation scheme which includes 42 merchandise trade commodities covering food products, natural resources and manufactured goods. With the exception of two primary commodities that are not traded, we are able to estimate trade elasticities for all merchandise commodities that are significantly different form zero at the 95% confidence level. Rather than producing point estimates of the resulting welfare, export and employment effects, we report confidence intervals instead. These are based on repeated solution of the model, drawing from a distribution of trade elasticity estimates constructed based on the econometrically estimated standard errors. There is now a long history of CGE studies based on SSA: Systematic Sensitivity Analysis (Harrison and Vinod, 1992; Wigle, 1991; Pagon and Shannon, 1987) However, to date, all of these studies have taken their parameter distributions "from the literature". None of these studies has been accompanied by an econometric study aimed at estimating the key parameters and their distributions at the relevant level of aggregation used in the CGE analysis. For this paper, we use the Gaussian Quadrature (GQ) approach to SSA, which has proven to be the most efficient and unbiased approach to systematically assessing the sensitivity of model results to parametric uncertainty (DeVuyst and Preckel, 1997; Arndt, 1996). We find that many of the results are qualitatively robust to uncertainty in the trade elasticities. In those cases where our findings are not robust, we explore the source of underlying uncertainty. In this way, the paper addresses the fundamental question: How Robust are CGE Analyses of Free Trade Agreements?

Suggested Citation

  • Hertel, Thomas W. & Hummels, David & Ivanic, Maros & Keeney, Roman, 2003. "How Confident Can We Be In Cge-Based Assessments Of Free Trade Agreements?," Working papers 28690, Purdue University, Center for Global Trade Analysis, Global Trade Analysis Project.
  • Handle: RePEc:ags:pugtwp:28690
    DOI: 10.22004/ag.econ.28690

    Download full text from publisher

    File URL:
    Download Restriction: no

    Other versions of this item:

    References listed on IDEAS

    1. Diao, Xinshen, 2001. "A Dynamic Evaluation of the Effects of A Free Trade Area of the Americas -An Intertemporal, Global General Equilibrium Model," Journal of Economic Integration, Center for Economic Integration, Sejong University, vol. 16, pages 21-47.
    2. Pagan, A R & Shannon, J H, 1987. "How Reliable Are ORAN I Conclusions?," The Economic Record, The Economic Society of Australia, vol. 63(180), pages 33-45, March.
    3. Timothy J. Kehoe, 2003. "An evaluation of the performance of applied general equilibrium models of the impact of NAFTA," Staff Report 320, Federal Reserve Bank of Minneapolis.
    4. McDougall, Robert, 2000. "A New Regional Household Demand System for GTAP," GTAP Working Papers 404, Center for Global Trade Analysis, Department of Agricultural Economics, Purdue University.
    5. Levinsohn, James, 1993. "Testing the imports-as-market-discipline hypothesis," Journal of International Economics, Elsevier, vol. 35(1-2), pages 1-22, August.
    6. McKitrick, Ross R., 1998. "The econometric critique of computable general equilibrium modeling: the role of functional forms," Economic Modelling, Elsevier, vol. 15(4), pages 543-573, October.
    7. Mary Hallward-Driemeier & Giuseppe Iarossi & Kenneth L. Sokoloff, 2002. "Exports and Manufacturing Productivity in East Asia: A Comparative Analysis with Firm-Level Data," NBER Working Papers 8894, National Bureau of Economic Research, Inc.
    8. McDougall, Robert, 2002. "A New Regional Household Demand System For Gtap," Technical Papers 28713, Purdue University, Center for Global Trade Analysis, Global Trade Analysis Project.
    9. Liu, Jing & Arndt, Channing, 2004. "Parameter Estimation and Measures of Fit in A Global, General Equilibrium Model," Journal of Economic Integration, Center for Economic Integration, Sejong University, vol. 19, pages 626-649.
    10. John Whalley, 1984. "Trade Liberalization among Major World Trading Areas," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262231204, September.
    11. Baldwin, Richard E. & Venables, Anthony J., 1995. "Regional economic integration," Handbook of International Economics, in: G. M. Grossman & K. Rogoff (ed.),Handbook of International Economics, edition 1, volume 3, chapter 31, pages 1597-1644, Elsevier.
    12. Arndt, Channing, 1996. "An Introduction To Systematic Sensitivity Analysis Via Gaussian Quadrature," Technical Papers 28709, Purdue University, Center for Global Trade Analysis, Global Trade Analysis Project.
    13. Hummels, David, 1999. "Toward a Geography of Trade Costs," Working papers 283448, Purdue University, Center for Global Trade Analysis, Global Trade Analysis Project.
    14. Harrison, Glenn W & Vinod, H D, 1992. "The Sensitivity Analysis of Applied General Equilibrium Models: Completely Randomized Factorial Sampling Designs," The Review of Economics and Statistics, MIT Press, vol. 74(2), pages 357-362, May.
    15. Chris M. Alaouze, 1977. "Estimates of the elasticity of substitution between imported and domestically produced goods classified at the input-output level of aggregation," Centre of Policy Studies/IMPACT Centre Working Papers o-13, Victoria University, Centre of Policy Studies/IMPACT Centre.
    16. Touhami Abdelkhalek & Jean-Marie Dufour, 1998. "Statistical Inference For Computable General Equilibrium Models, With Application To A Model Of The Moroccan Economy," The Review of Economics and Statistics, MIT Press, vol. 80(4), pages 520-534, November.
    17. DeVuyst, Eric A. & Preckel, Paul V., 1997. "Sensitivity analysis revisited: A quadrature-based approach," Journal of Policy Modeling, Elsevier, vol. 19(2), pages 175-185, April.
    18. Hummels, David, 1999. "Toward a Geography of Trade Costs," GTAP Working Papers 1162, Center for Global Trade Analysis, Department of Agricultural Economics, Purdue University.
    19. Chris M. Alaouze & John S. Marsden & John Zeitsch, 1977. "Estimates of the Elasticity of Substitution Between Imported and Domestically Produced Commodities at the Four Digit ASIC Level," Centre of Policy Studies/IMPACT Centre Working Papers o-11, Victoria University, Centre of Policy Studies/IMPACT Centre.
    20. Malcolm, Gerard, 1998. "Adjusting Tax Rates in the GTAP Data Base," GTAP Technical Papers 315, Center for Global Trade Analysis, Department of Agricultural Economics, Purdue University.
    21. Harrison, Glenn W. & Jones, Richard & Kimbell, Larry J. & Wigle, Randal, 1993. "How robust is applied general equilibrium analysis?," Journal of Policy Modeling, Elsevier, vol. 15(1), pages 99-115, February.
    22. Wigle, Randall M, 1991. "The Pagan-Shannon Approximation: Unconditional Systematic Sensitivity in Minutes," Empirical Economics, Springer, vol. 16(1), pages 35-49.
    23. Gallaway, Michael P. & McDaniel, Christine A. & Rivera, Sandra A., 2003. "Short-run and long-run industry-level estimates of U.S. Armington elasticities," The North American Journal of Economics and Finance, Elsevier, vol. 14(1), pages 49-68, March.
    24. Andrew B Bernard & J Bradford Jensen, 2001. "Exporting and Productivity: The Importance of Reallocation," Working Papers 01-02, Center for Economic Studies, U.S. Census Bureau.
    25. Malcolm, Gerard, 1998. "Adjusting Tax Rates In The Gtap Data Base," Technical Papers 28721, Purdue University, Center for Global Trade Analysis, Global Trade Analysis Project.
    26. Hertel, Thomas, 1997. "Global Trade Analysis: Modeling and applications," GTAP Books, Center for Global Trade Analysis, Department of Agricultural Economics, Purdue University, number 7685.
    27. Elena Ianchovichina & James Binkley & Thomas Hertel, 2000. "Procompetitive Effects of Foreign Competition on Domestic Markups," Review of International Economics, Wiley Blackwell, vol. 8(1), pages 134-148, February.
    28. David Hummels & Peter J. Klenow, 2005. "The Variety and Quality of a Nation's Exports," American Economic Review, American Economic Association, vol. 95(3), pages 704-723, June.
    Full references (including those not matched with items on IDEAS)

    More about this item


    International Relations/Trade;

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C68 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computable General Equilibrium Models


    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:ags:pugtwp:28690. 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: (AgEcon Search). 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.

    If CitEc recognized a 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.

    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.