Trade policy analysis: choosing the appropriate methodology Marc Bacchetta ERSD/WTO

Outline Research based policy making Criteria for choosing a methodology Key methodologies –Modelling assumptions –Required resources

Research based policy making Research based information on policies is needed at different stages of the policy making process –Proposal –Policy dialogue with stakeholders –Implementation

Dialogue Dialogue between researchers and policy stakeholders is crucial Researchers may help policy makers specify questions Researchers should guide the choice of appropriate methodologies

Methodology: the question Which approach is best suited to answer the question at stake given existing constraints ?

Choice of methodology is not necessarily straightforward The question should dictate the choice of a methodology... But there are various constraints: –Time and resources –Sunk costs (incl. familiarity with certain methodologies, institutional constraints) –Fashion

Key approaches Descriptive statistics Modelling approaches: –Ex ante vs ex post approaches –Econometric vs simulation models –Partial vs general equilibrium

Ex ante vs ex post approaches Ex ante simulation involves projecting the effects of a policy change on a set of economic variables of interest –Can answer “what if” questions Ex post approaches use historical data to conduct an analysis of the effects of past trade policy –Can answer “what if” questions if estimated parameters are used for simulation (which assumes that past relations continue to be relevant)

Econometric vs simulation models In econometric models, parameter values are estimated using statistical techniques –Parameter values come with confidence intervals –Parameter estimation is resource intensive –Results are specific to one country or group of countries In simulation models, parameters are typically drawn from a variety of sources and some are calibrated

Descriptive statistics (1) Trade flows analysis Example: assessment of trade patterns and/or trade performance Conceptual tools –Revealed comparative advantage, intra- industry trade, export diversification, etc. Empirical tools –Entropy indices, revealed comparative adv.

Trade performance and competitiveness assessment Trade in services Merchandise trade –Trade performance Growth and pattern in the direction of trade Composition of trade Export concentration and principal products –Competitiveness, specialization and complementarity International competitiveness of exports Export specialization Trade complementarity and intensity...

Indices Export specialization index Trade complementarity index –with

Descriptive statistics (2) Trade policy analysis Example: trade policy assessment Conceptual tools –Effective protection, non tariff barriers, bound and applied tariffs, tariff escalation, etc. Empirical tools –Averages, dispersion indices, coverage ratios, etc.

Trade policy assessments Trade policy reviews –Trade and investment regime –Trade policies by measure and by sector Tariff profiles NAMA tariff simulations

Econometric estimation of gravity equations Can be used to study the impact of trade policy variables on trade flows Example: effect of regional trade agreement Ex post: not well suited for making predictions No welfare effects

Econometric estimation of gravity equations Reasonable data requirements Reasonable entry costs Cost of econometric software package ? Importance of integrating theory with estimation

Econometric estimation of economic consequences of trade Example: assessment of the distributional effects of trade policy Ex post Variable level of econometric sophistication Variable data requirements

Partial equilibrium simulations Focuses on a specific market or product and ignores interactions with other markets Best suited for the analysis of sectoral policies, or when interactions with other markets are expected to be limited Allows to include more market relevant details than GE models Ex: assessing the welfare effect of a reduction of the tariff on wheat

Partial equilibrium simulations A number of partial equilibrium models have been developed to simulate international trade policy changes –Those include SMART, ATPSM, SWOPSIM Data requirements are manageable –Elasticities are crucial

General equilibrium simulations GE explicitly accounts for all the links between sectors of an economy – households, firms, governments and the rest of the world Imposes constraints s.t. income equals expenditure Trade off between detail and breadth of coverage Assesses effects of policy changes on aggregate and sectoral variables, including: –Income, production, employment, relative factor and product prices, etc.

General equilibrium simulations Single or multiple country models Highly intensive in data and parameters –SAM, behavioural parameters, elasticities –GTAP provides data and a simple model Entry cost is significant High risk of misinterpretation

Paper on Turkey Glenn Harrison, Thomas Rutherford and David Tarr (2003) “Trade Liberalization, poverty and Efficient Equity,” Journal of Development Economics, Vol. 71 (1), June 2003, Policy application—joining a Customs Union with the European Union (not membership). Small Open Economy model with 40 households, 20 rural and 20 urban. Economic Theory suggests that for developing countries trade liberalization should shift production toward labor intensive products. That should be pro-poor.

In Turkey the authors did not find this. They estimated that the poor lost. Why? They show that estimation of factor intensities is crucial to a sensible link between trade policy and poverty analysis. Input-Output tables notoriously fail to accurately report factor intensities. Capital’s share is a residual. In Agriculture, labor’s earnings are underreported, so it is the most capital intensive sector in IO tables. Services sectors are also problematical. In Turkey locomotives are reported as 100% labor; textiles are capital intensive.

Perverse results may be obtained if estimates are based on IO table factor intensities. The lesson learned for future applications is that factor intensities should be estimated outside of the input-output model. Perverse results may be obtained if estimates are based on IO table factor intensities. The lesson learned for future applications is that factor intensities should be estimated outside of the input-output model. The authors caution consumers of these models to ask producers how they have obtained the values of their factor intensities. The study identifies sectors where an increase in the tariff rates will increase the welfare of the poor. The authors caution, however, that political economy reasons suggest that these models should not be used for industrial policy to help the poor. Likely to be abused like the many other arguments to depart from tariff uniformity.

Partial vs general equilibrium models CGEPE Capturing economy wide linkagesX Consistency wrt budget constraintsX Capturing disaggregated effectsX Capturing complicated policy mechanismsX Use of timely dataX Capturing short and med. term effectsX Capturing long term effectsX Past performance in projecting impacts

Conflicting results Policy makers don’t like conflicting results In most cases different results reflect different assumptions Such differences are difficult to avoid What matters is the presentation of the results

References Piermartini, R. and R. Teh (2005) Demystifying modelling methods for trade policy, WTO Discussion Paper No. 10 Bowen, H.P., A. Hollander and J.-M. Viaene (1998) Applied international trade analysis, University of Michigan Press Abler, D. (2006) Approaches to measuring the effects of trade agreements, CATPRN Paper