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Accounting for Model Uncertainty and Natural Trading Partner Effects

Accounting for Model Uncertainty and Natural Trading Partner Effects. Trade Creation and Diversion Revisited:. Road Map . Reexamine PTAs’ impacts on trade flows Introduce New Methodology: Address Model Uncertainty Allow for Natural Trading Partners Generate New Results:

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Accounting for Model Uncertainty and Natural Trading Partner Effects

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  1. Accounting for Model Uncertainty and Natural Trading Partner Effects Trade Creation and Diversion Revisited:

  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. 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. 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. 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. 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. 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. 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. 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. 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 uncertaintysurrounding the validity of model. • standard errors understate uncertainty

  11. 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)

  12. 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 onlytrade diverting PTAs!!

  13. 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…

  14. 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)

  15. Bayesian Model Averaging:Quick details for the math hungry • posterior probability for model Mk (the “weight”) is • is the integrated likelihood (over all regressors) • Posterior Mean • D is the data, • Mk 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

  16. 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

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

  18. Trade Theory Covariates (Zijt) • 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

  19. Data • Identicalto “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

  20. European PTA Members

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

  22. Pacific Rim PTA members

  23. 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!    

  24. Latin American PTA Membership

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

  26. 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.

  27. 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

  28. 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)

  29. 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

  30. EuropeTrade Effects Purged of Natural Trading Partner Effects • Now EU is Trade Creating • Strong Open Block Effect  

  31. EuropePTA 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

  32. Latin AmericaPTA Flows Purged of Natural Trading Partner Effects • Counterintuitive Effects Disappear • All Effects are Natural Trading Partner Effects

  33. Pacific RimPTA 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

  34. Pacific RimPTA Flows Purged of Natural Trading Partner Effects • NAFTA 26% trade diversion?

  35. 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!

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

  37. 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

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