@article{Evans:330913,
      recid = {330913},
      author = {Evans, David},
      title = {Identifying Winners and Losers in Southern Africa from  Global Trade Policy Reform: Integrating Findings From GTAP  and Poverty Case Studies},
      address = {2001},
      pages = {26},
      year = {2001},
      note = {Presented at the 4th Annual Conference on Global Economic  Analysis, Purdue University, USA},
      abstract = {The IFI's rely on twin propositions that poverty  alleviation is best pursued through increased growth, and  that trade liberalisation encourages growth and thereby  poverty alleviation. These aggregate propositions are not  disputed in this paper. Rather, the argument is made for  disaggregation to identify the winners and losers among the  poor in the short and medium run from further trade policy  liberalisation, both between and within countries.  Disaggregation is important on both equity grounds,  especially when the losers are among the poor. It is also  important on efficiency grounds particularly when designing  policies to help poor losers realise the opportunities for  gain from trade policy liberalisation in the longer run.  Two methodologies are frequently employed to assess the  linkages between trade and poverty. Country and sector case  studies dominate the literature. The key difficulty with  case studies is that it is not possible to deploy their  rich descriptive data in a consistent analytical framework.  It is usually not possible to construct a quantitative  counterfactual situation, for example the impact of a trade  policy change on the poor. Obtaining a counterfactual  through general equilibrium trade models has its own  catalogue of difficulties arising from data availability,  model assumptions and interpretation of results. The two  methodologies lie at extreme ends of a spectrum, but  insights from both can be mutually reinforcing. This paper  uses Zambia as an 'example' country to explore the  possibility of combining the rich poverty case study  material available for that country with the results for  Zambia of a multilateral trade model based on the GTAP  dataset and modelling software. It describes some of the  salient features of case studies of poverty in Zambia. A  common thread runs through all the case studies, that trade  policy reform in Zambia is likely to be pro-poor. This key  proposition is tested using the GTAP dataset and modelling  software. The GTAP database for 1997 is described including  an extension for Zambia to permit the analysis of poverty  impacts for four classes of households together with the  modelling strategy adopted for this exploratory study. It  then reports on the poverty impacts of a series of trade  policy experiments using the 1996 LCMS Survey for Zambia to  estimate headcount changes from: • Unilateral trade policy  reforms in Southern Africa that took place from 1992-4 up  to 1997. • A seven-country version of the SADC FTA. • A  'suppose' WTO Round. • A 'suppose' effective extension of  the EU/South Africa FTA into an EU/SADC7 FTA through Least  Developed Country access into the EU through negotiations  about to begin. Zambian households are disaggregated into  four groups so that GTAP aggregate household results can be  disaggregated to real post-tax income changes in each of  the four household groups in post simulation calculations.  A key finding is that regionally ii based trade policy  reforms have a neutral or adverse impact on household  income distribution compared with possible major trade  policy reforms under the WTO. However, the final headcount  poverty impacts of the international trade policy reforms  are offset by the lower income responsiveness of the  poverty impacts in the poorest rural households. Whilst  these findings are suggestive, the research strategy on the  modelling side using both the GTAP dataset and runGTAP as  computing software has a number of important limitations.  On the data side, for Southern Africa applications, the  standardised GTAP dataset throws away too much useful  information for trade and poverty analysis that is  available in the underlying MERRISA SAMs upon which the  Southern Africa dataset for GTAP was built. This is most  notable for household aggregation, factor aggregation at  the low income or subsistence end, margins aggregation,  rudimentary treatment of government income and expenditure.  On the runGTAP modelling side, satisfactory resolution of  the database problems poses serious programming problems.  The above suggests an alternative trade and poverty  research strategy in which the CGE model and country case  study interface is first explored with country models  without the constraints of the standard GTAP dataset  aggregation. An obvious choice for a starting model is the  standard model Loefgren, Harris and Robinson (2001). At a  later point, such country models could be tied into a  global model using the GTAP dataset for scenario  calculations using a common sectoral classification to  complete the bottom-up strategy for the analysis of trade  and poverty impacts.},
      url = {http://ageconsearch.umn.edu/record/330913},
}