@article{Hertel:28690,
      recid = {28690},
      author = {Hertel, Thomas W. and Hummels, David and Ivanic, Maros and  Keeney, Roman},
      title = {HOW CONFIDENT CAN WE BE IN CGE-BASED ASSESSMENTS OF FREE  TRADE AGREEMENTS?},
      address = {2003},
      number = {1237-2016-101395},
      series = {GTAP Working Paper No. 26},
      pages = {42},
      year = {2003},
      abstract = {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?},
      url = {http://ageconsearch.umn.edu/record/28690},
      doi = {https://doi.org/10.22004/ag.econ.28690},
}