Methodologies in the trade and poverty research Lucian Cernat International Trade Division

Outline T&P methodologies: –Simple: Econometric PE GE –Nested: Econometrics -> CGE CGE -> econometrics PE -> CGE PE -> econometrics

Econometrics Trade and growth –Empirical evidence is convincing, although disagreement persists –Problems with trade openess measurement –Causality from openess to growth difficult –Stops short of poverty impact analysis: Mainly at « poor country » level of analysis, e.g. Dollar and Kraay But also microeconometrics

Microeconometrics Directy poverty linkage based on econometric analysis of household surveys require few restrictions on parameters behavior of real households as opposed to representative households Can focus on more subtle effects of trade policies, e.g. child poverty, health, informal sector, labour markets, etc.

Balance-of-payments constraints (BPC) estimation of the income elasticity of demand for imports, and time series regressions of regions or individual countries in order to compare predicted and actual growth rates Unit roots tests and cointegration analysis to determine if there is a long-term common trend between export growth and GDP growth, and hence to test hypothesis of the BPC growth model

Partial equilibrium PE models to estimate price effects from trade reform Such price effects are then loosely interpreted in terms of welfare and poverty implications Major advantages: –simple, transparent, very relevant for trade policy makers and trade negotiators (often PE modelling conducted at tariff line level) Major disadvantage: –low accuracy on poverty impact

Partial equilibrium –> microanalysis Price and quantities estimates from partial equilibrium -> consumption and production bundles at household level Multicountry, multiproduct PE estimating trade changes at HS-6 digit level Then impact on prices of goods produced and consumed by the poor Impact on world demand of products sold by the poor –E.g. Kee, Nicita, Olarreaga (2007) estimates used in country studies (Ethiopia, Madagascar, Cambodia, etc).

General equilibrium Imposes income/expenditure and resource constraints. Takes into account linkages between markets, both product and factor markets (including feedback to the original market) market structure (im/perfect competition) production function representative household government behaviour substitutability between domestic and foreign products (Armington assumption) Investment and dynamics Model closure

General equilibrium for poverty analysis GE modeling with multiple representative households –aggregating households from a household survey into several representative households –major limitation: there can be large differences among the households in each representative household Individual Households Region 1Region n …… Informal UrbanRuralUrban Formal SkilledUnskilled Rural

GE for poverty analysis GE with “real” households from the household survey –First best option but very demanding –yet still possible, e.g. Rutherford et al (2005) Ultimate goal: individual level welfare and poverty analysis –Intermediary step: Gendering CGE modelling e.g.Fofana et al (2006)

Other options In between: “open loop” or “top down” –1st step: a single representative agent computable general equilibrium model -> estimated price changes –2 nd step: price changes -> microsimulation household model But ignores feedback effects of the quantity changes on the equilibrium prices

Other issues in CGE modelling macroeconomic closure for the GE model –Fixed gov’t spending –Gov’t income is fixed –Tariff revenue loss compensated by VAT Data reconciliation of ‘’super’’ SAMs –Household survey, enterprise data, IO tables, trade statistics, etc.

Other extensions Static vs. Dynamic –Comparative Static Analysis: compare initial and final steady-state more simple (theoretically, computationally) –Dynamic Analysis: also looks at the evolution from the initial to the final equilibrium: Other trade-related issues: –Imperfect competition –Climate Change –Trade and labour: migration, unemployment, etc

Modelling - caveats for policy makers Models provide a theoretically consistent, rigorous and quantitative way to evaluate different trade policies E.g. what is the poverty impact of specific Doha formulas in NAMA? But what if they don’t confirm the policymaker’s expectations? E.g. Uruguay Round estimates – cheque still in the mail? How about unintended consequences of major underlying assumptions and modelling choices? E.g. Doha estimates – wide range and declining gains

Conclusions Each modelling method has some value- added ‘’augmented ’’ CGE is gaining momentum Thanks. Any questions?