1. Accounting for Model Uncertainty and Natural Trading Partner Effects Trade Creation and Diversion Revisited: Christian HennTheo S. EicherChris Papageorgiou IMFUniversity of WashingtonIMF

2. 2 Road Map Reexamine PTAs’ impacts on trade flows Introduce New Methodology: Address Model Uncertainty Allow for Natural Trading Partners Generate New Results: Identify PTAs’ tangible benefits Identify individual PTA’s trade creation/diversion Highlight relevance of comprehensive approach

3. 3 A Brief History of Trade Flow Determinants Ricardo (Technology) Heckscher / Ohlin (Factor Endowments) Brander / Spencer / Krugman (IRS, Market Structure) Rivera Batiz / Romer / Young (Endogenous Growth) Melitz/Antras (Intra-Industry Cost Heterogeneity)

4. 4 Trade Flows and Trade Restrictions Trail Blazers: Static Models Kruger (1972), Findlay Wellisz (1982), Hillman (1982) Second Generation: Endogenous Protection Models Grossman Helpman (1995) etc. Preferential Trade Agreements (PTAs)

5. 5 Trade Flows and Trade Restrictions Preferential Trade Agreements (PTAs) Viner (1950) (Static Trade Creation/Diversion) Stepping Stones vs. Stumbling Blocks Krugman (1991, 1993) PTAs cannot be trade creating in the absence of intercontinental transport costs.  Prohibitive transport costs => PTA trade creation dominates  Finite transport costs => PTA trade diversion dominates Frankel, Stein and Wei (1995, 6, 8) model continuum of transport costs. The more remote trading partners are from the rest of the world, the more likely they are to form RTAs due to less potential trade diversion. The more “natural” trading partners are, the more likely an FTA will be formed by the countries’ governments due to more potential trade creation.

6. 6 Trade Flows and Trade Restrictions Stumbling Blocks Lobbies as stumbling blocks, b/c common external tariff (Panagranya & Findlay 1996) Diverting PTAs are politically more likely (GH 1995) Larger PTAs have monopoly power (Deardorff and Stern 1994) Given differences in factor endowments, trade with a few countries is sufficient to maximize gains from trade. Deardorff and Stern and Haveman (1994) PTA’s inhibit further multilateral tariff reduction, (Krishna 1998)

7. 7 Trade Flows and Trade Restrictions Stepping Stones (“complementary effect of pref. tariffs Bagwell Staiger 1998) preferential tariff induces trade diversion, which is costly, so external tariffs declines to compensate and shift imports back to their original source) PTAs allow lower external tariff b/c (tariff revenue competition, PTA free trade benefits allow for lower tariff revenues, so external tariff falls. RTA may promote external liberalization, Richardson 1993) Baldwin (1993, 1995, 1997) & Levy (1996)  Non-member exporters lobby forces joining if diversion is large  Larger PTAs shifts more power to the export lobby  Larger PTA even more attractive to join (more trade creation) PTA induced harmonization, allows new revenues that overcome trade fixed costs Freund (2000)

8. 8 PTA Effects Can Have Many Sources That Are Difficult to Disentangle Possible Scenarios: Among members: Trade Creation / Trade Diversion Between members: Trade Diversion / Open Block Between Non Members: Trade Diversion /Open Block Which Theory is Empirically Relevant? Which Effect(s) Dominate? How do we sift through the many models for evidence??

9. 9 PTA Effects Can Have Many Sources That Are Difficult to Disentangle Possible Scenarios: Among members: Trade Creation / Trade Diversion Between members: Trade Diversion / Open Block Between non members: Trade Diversion /Open Block Which Theory is Empirically Relevant? Which effect(s) dominate? How do we sift through the many models for evidence?? This is the DEFINITION of Models Uncertainty

10. 10 Model Uncertainty: Why do we care? Individual researchers typically emphasize a single model as they seek support for a particular regressor (the alternative is “Null Hypothesis”, or “no effect”) Inferences procedures based on a single model overstate the precision of the inferences  procedures do not account for the additional uncertainty surrounding the validity of model. standard errors understate uncertainty

13. 13 Previous Approach To Model Uncertainty In Trade Flow Empirics Ghosh and Yamarik (2004, JIE) First (and to date only) attempt to account for model uncertainty in trade flow / PTA estimation Use Extreme Bounds Analysis (EBA) (Leamer 1978, 1983, 1985)

14. 14 Previous Approach To Model Uncertainty In Trade Flow Theory Ghosh and Yamarik (2004, JIE) First (and to date only) attempt to account for model uncertainty in trade flow / PTA estimation Use Extreme Bounds Analysis (EBA) (Leamer 1978, 1983, 1985) Conclusion: No evidence of trade creation or diversion for any PTA! Relaxed extreme bounds pick up only trade diverting PTAs!!

15. 15 Extreme Bound Analysis -- Assessment -- Lack of Statistical Theory Backbone Reduce model space artificially to avoid running all regressions. (Why?) Why has each model (no matter how terrible) equal weight…? What is the robustness criterion? (see growth theory) How relevant is the analysis if the model space holds billions of models and the researcher searches only over less than 0.0000001% of the model space? Severe omitted variable bias Could be (and has been) considered data mining…

16. 16 Bayesian Model Averaging (BMA) BMA Intuition Model Selection: estimating the performance of different models in order to choose the best one. Model Averaging: average predictions from different models to achieve improved performance Posterior Estimate: weighted average over all models, where weights are given by model quality. BMA is a) theory based, b) based on objective criteria, and c) proof exists that BMA delivers best predictive performance (Raftery 1995)

17. 17 Bayesian Model Averaging: Quick details for the math hungry D is the data, M k is a model in some model space M, K is number of models,  is a quantity of interest Nice: priors largely wash out with 15000 observations posterior probability for model M k (the “weight”) is is the integrated likelihood (over all regressors) Posterior Mean

18. 18 Econometric Framework Basic Building Block: Gravity Equation Can be derived from a variety of trade models Deardorff (1998) Successful in explaining implied trade flows (Frankel Romer 1999) Zijt: proxies for trade costs / trade theory covariates

19. 19 Definition of PTA Dummies Trade Creation dummies (PTAij) 1 only if both trade partners are members of a respective PTA 0 otherwise Trade Diversion/Open Block Dummies (PTAi) 1 if one and only one trade partner is a member of a respective PTA 0 otherwise

20. 20 Trade Theory Covariates (Z ijt ) Geography Border, Remoteness, Landlocked, Island, Area Historical Ties Language, Common Colonizer, Colony Exchange Rate / Trade Policy Sachs dummy, Currency Union, Floating FX rate, FX volatility Factor Endowments / Development GDP p.c. Log Differences in GDP p.c. Education Population Density

21. 21 Data Identical to “no effect” data of Ghosh and Yamarik (2004) Avg Bilateral Trade Flows, 186 countries, 14,522 observations, 3,420 bilateral trade pairs, five-year intervals (1970-1995) 12 major PTAs: Europe: EU, EFTA, EEA Pacific Rim: APEC, ASEAN, NAFTA, ANZCERTA Latin America: CACM, CARICOM, LAIA, AP (Andean Pact), MERCOSUR

22. 22 European PTA Members

23. 23 Results: Europe Clear, strong open Block Effects.

24. 24 Pacific Rim PTA members

25. 25 Results: Pacific Rim     Now significant trade creation and diversion and open block PTA’s matter a lot! Puzzling high APEC… Large Trade Diversion for Nafta!

26. 26 Latin American PTA Membership

27. 27 Results: Latin America       Orthodox results of Strong trade creation And trade diversion In Latin America

28. 28 Summary part I Using: identical data statistically sound approach to model uncertainty considers all possible models (including best model) Derive quality-weighted averaged estimates We overturn the bleak “PTAs don’t matter“ results and show that several have trade creating, trade diverting and open block effects.

29. 29 Results: Control Variables Strong effects from gravity and other country specific Controls The only variables that do not receive support are - FLOAT - ED DIFF - ISLAND

30. 30 The Importance of Fixed Effects (Natural Trading Partners) Hummels and Levinsohn (1995) Trade is largely specific to country-pairs We may not know why, or cannot account for it with our covariates, no matter how many controls we include. We introduce country pair fixed effects Isolate whether countries trade a lot with each other because of PTA’s or because they are natural trading partners Cheng and Wall, 1999 (EU, Nafta, Mercsur); Egger and Pfaffermayr, 2003 (gravity only)

31. 31 The Importance of Fixed Effects (Natural Trading Partners) Introduce Country Pair Fixed Effects Example: similarities in economic and social institutions, such as corruption or rule of law, or simple economic infrastructure such as telecommunications. A concrete example would be France-Germany, with excellent transport links (unobserved) and a PTA (observed), vs. Afghanistan-Kazakhstan, with bad transport links (unobserved) and no PTA (observed). ij

32. 32 Europe Trade Effects Purged of Natural Trading Partner Effects Now EU is Trade Creating Strong Open Block Effect  

33. 33 Europe PTA Flows Purged of Natural Trading Partner Effects Only after controlling for natural trading pairs, the EU is Trade Creating EU countries naturally under-trade relative to the prediction of the standard gravity model. This “missing trade” is a standard feature of the basic gravity model, see e.g. Pollak (1996) or Rose (2004). EU Open Block Trade Creation does not survive but is simply due to similarities among trading partners

34. 34 Latin America PTA Flows Purged of Natural Trading Partner Effects Counterintuitive Effects Disappear All Effects are Natural Trading Partner Effects

35. 35 Pacific Rim PTA Flows Purged of Natural Trading Partner Effects    Counter Intuitive APEC Trade Creation vanishes AFTA and APEC Trade Creation confirmed NAFTA Trade Creation is maintained but smaller !

36. 36 Pacific Rim PTA Flows Purged of Natural Trading Partner Effects NAFTA 26% trade diversion?

37. 37 Trade Creation/Diversion Importance of Comprehensive Approach Most PTA Studies estimate Trade Creation for one/a few PTAs Marginal Effects (too diverse to average) vs Global Effects Most studies don’t distinguish Trade Creation/Open Block Example1: Two countries are in two different PTAs: what matters for trade flows is the Open Block effect / Trade Diversion of BOTH PTAs (70 countries, most high income countries are in PTAs) Example2: All countries (PTA or not) get open block effects from all other PTA’s. So: pairwise trade diversion may turn into multilateral trade creation!

38. 38 Trade Creation/Diversion Most PTA interactions are Trade Creating EVEN NAFTA trade can be trade creating with Nafta non members

39. 39 Conclusions 1) Address Model Uncertainty: obtain correct PTA’s effects: PTA’s do matter (!) 2) Purge Natural Trading Partner contamination. Eliminate Counterintuitive Results (!) Isolate actual PTA effects: (most PTA effects smaller) 3) Comprehensive Approach Identifies crucial interactions that can overcome “false trade diversion” (US / ASIA) Overwhelmingly, PTAs are stepping stones to freer trade