Economic Feasibility, General Economic Impact and Implications of a Free Trade Agreement Between the European Union and Georgia

This study of the feasibility, costs and benefits of a free trade agreement between the EU and Georgia was conducted from July 2007 to April 2008 under contrach with the European Commission. The first meeting in Brussels in September 2007 with staff members of Directorates-General for Trade, External Relations, Economic and Financial Affairs, Internal Market and Services, Competition, Enterprise and Industry proved indispensable in our work on this report. During mission to Tbilisi in October 2007 the consultations were held with a number of ministries, research institutes and business organizations. We greatly benefited from consultations with the Ministry of Economic Development, Standardization Office, UN Team Leader for Economic Development, State Minister for Reforms Coordination, Ministry of Energy, Office of Deputy State Minister for European and Euro Atlantic Integration, American Chamber of Commerce, Georgian Chamber of Commerce, IMF, World Bank, EBRD, GEPLAC – Georgian European Policy Legal Advice Centre, Wine Producers Association, Federation of Georgian Businessman. The European Commission Delegation to Georgia provided us with extensive information, consultation on key policy issues and organizational support, for which we are very grateful. Several authors contributed to this study. David Dyker is the author of the introductory section (chapter 2) and the analysis of services sectors (chapter 7). Michael Emerson is the author of section on regional integration scenarios (charter 3) and he also provided very valuable comments on all chapters in this study. Sveta Taran, Peter Holmes and Michael Gasiorek are the authors of chapter 4 employing the Sussex Framework to study the impact of a free trade agreement. Michael Gasiorek and Peter Holmes also provided valuable comments on the CGE modelling section. Evgeny Polyakov, Andrei Roudoi as well as Nino Chokheli and Giorgi Pertaia contributed to the chapter on the institutional and regulatory harmonization (chapter 5). The team from the Global Insight including Andre Jungmittag, Vicki Korchagin, Evgeny Polyakov and Andrei Roudoi supervised the implementation of the survey and completed the analysis of the survey results (chapter 6). Also the same team from Global Insight contributed chapter 10 on sensitive sectors. The implementation of the survey of NTBs was conducted by CASE-Transcaucasus under the supervision of Tamaz Asatiani. The analysis of FDI flows and their likely trends following an FTA was prepared by Malgorzata Jakubiak, while the estimation of the potential FDI flows was conducted by Alina Kudina (section 8.4). The CGE analysis (chapter 9) was written by Maryla Maliszewska, who also acted as the project manager and the editor of the study. Finally, conclusions are a collective work of all the authors. Sierz Naurodski and Elena Kozarzewska provided an excellent administrative support. I would like to take this opportunity to thank them all for their cooperation, valuable contributions and comments.European Neighborhood Policy, free trade agreement, institutional harmonization, EU, Georgia.

Fitting heavy-tailed mixture models with CVaR constraints

Standard methods of fitting finite mixture models take into account the majority of observations in the center of the distribution. This paper considers the case where the decision maker wants to make sure that the tail of the fitted distribution is at least as heavy as the tail of the empirical distribution. For instance, in nuclear engineering, where probability of exceedance (POE) needs to be estimated, it is important to fit correctly tails of the distributions. The goal of this paper is to supplement the standard methodology and to assure an appropriate heaviness of the fitted tails. We consider a new Conditional Value-at-Risk (CVaR) distance between distributions, that is a convex function with respect to weights of the mixture. We have conducted a case study demonstrating e˚ciency of the approach. Weights of mixture are found by minimizing CVaR distance between the mixture and the empirical distribution. We have suggested convex constraints on weights, assuring that the tail of the mixture is as heavy as the tail of empirical distribution