Структурные аспекты торговой политики России: тез. докл. к XX Апр. междунар. науч. конф. по проблемам развития экономики и общества, Москва, 9–12 апр. 2019 г.
The paper reviews the problem of persistent and growing role of non-tariff measures to be used in order to protect domestic producers in international trade. It notes the complexity this problem’s settlement at the international level, and the possibility of liberalization non-tariff barriers through the regional free trade agreements. Taking to account Russian’s foreign policy direction of international relations, the paper analyzes the level of non-tariff protection of the domestic market in Egypt as one of the possible future partners of the Eurasian Economic Union in a free trade agreement. Also the paper includes regression model calculation the impact of non-tariff measures on the export of goods from Russia to Egypt which based on the statistical data of the WTO and UNCTAD.
The scope of the paper is limited to several aspects of Britain’s economic relationship with the European Union after the departure from this bloc. Apart from general matters like the EU budget and the EU legislation, special attention is paid to economic and regulatory conditions of the EU single market as these aspects have been sensitive throughout the history of the European integration resulting in shaping some of the presented models, based on national economy priorities of the EU partners including those from the EFTA.
Taking into account crucial drawbacks of the Draft Withdrawal Agreement published on 14 November 2018, and the author’s view that it is unlikely to succeed, at least in the current wording, the paper provides solutions for the UK’s post-Brexit trade policy should it leave the EU with no deal.
We address the external effects on public sector efficiency measures acquired using Data Envelopment Analysis. We use the health care system in Russian regions in 2011 to evaluate modern approaches to accounting for external effects. We propose a promising method of correcting DEA efficiency measures. Despite the multiple advantages DEA offers, the usage of this approach carries with it a number of methodological difficulties. Accounting for multiple factors of efficiency calls for more complex methods, among which the most promising are DMU clustering and calculating local production possibility frontiers. Using regression models for estimate correction requires further study due to possible systematic errors during estimation. A mixture of data correction and DMU clustering together with multi-stage DEA seems most promising at the moment. Analyzing several stages of transforming society’s resources into social welfare will allow for picking out the weak points in a state agency’s work.