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In this paper, we examine a number of indices used for measuring comparative advantages of a country in international trade for a good and propose the new net comparative advantage index that has several strong features. First, it reflects net trade, and that's why it is more theoretically grounded than indices calculated only from export data. Second, it is consistent with Kunimoto (1977) theoretical framework that is highly appreciated among trade economists. Third, it is not totally focused on a single commodity (that is, it takes world trade structure into consideration), unlike net export index. Fourth, it accounts for economic openness, using GDP as a scale variable. Fifth, it is hardly exposed to structural distortions. Finally, its sign is consistent with the sign of the net trade. We compare the new index with CEPII theoretically grounded econometric indicator and show that the proposed index has better empirical characteristics and is much easier to calculate and interpret. JEL Classification: F14.

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This paper estimates the capacity utilization rate for Russian manufacturing. We also propose a way to build continuous production capacity time series and indicators to describe the basic characteristics of production capacity. The data come from form 1-natura-BMoftheRussianFederalStateStatisticsService.Ourfindingsonthetrends andstructuralcharacteristicsofproductioncapacityareshowntobesignificantforeconomic policy since we found that in recent years capacities utilization rate in Russian manufacturing industry has been not extremely high and that there is a strong correlation notonlybetweencapacitiesutilizationrateandinflationratebutbetweencapacitiesutilization rate and capacities commissioning intensity as well. ©2017Non-profitpartnership"VoprosyEkonomiki".HostingbyElsevierB.V.Allrights reserved.

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T he article examines Russia's dependence on hightech imported goods. We improve the OECD hightechnology product classification by increasing the level of disaggregation, accounting for new goods, ensuring comparability over time, and differentiating goods by technological level on quite high levels of disaggregation. We describe the major trends in the world market for high-tech goods and identify the leading countries in each sector (most frequently, China, Germany, Republic of Korea, Switzerland, and Singapore) primarily by calculating net exports of high-tech goods in these sectors. We also assess Russian competitive positions in the global market for high-tech goods by sectors, applying the newly developed competitiveness index, and measure Russian dependence on high-tech goods imported from countries that recently imposed sanctions against Russia. We show that Russia's economy is highly dependent on imports of pharmaceutical goods and medical equipment, machinery and equipment (except nuclear reactors, fuel elements, engines and turbines), and electrical equipment. The sectors with most imports originating from 'sanctionimposing' countries are aircraft, medical and optical equipment, engines and turbines, and pharmaceutical goods. Computers and electronic equipment are at the opposite pole: in these sectors, China is the world leader and the key partner for Russia.

В статье с использованием методологии межотраслевого анализа уточняются представления о значимости отраслей в качестве потребителей и производителей промежуточной продукции и оценивается влияние интеграции в торговле товарами со странами Евразийского экономического союза (ЕАЭС) на выпуск и отдельные экономические показатели для России по видам деятельности. Показано, что структура выгод от торговой интеграции трансформируется при переходе к анализу в терминах добавленной стоимости: в химическом комплексе и машиностроении выгоды сокращаются, несмотря на сохранение лидирующих позиций этих отраслей, а в сфере услуг и промежуточных производствах, и прежде всего в добыче полезных ископаемых, - напротив, растут.

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