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For more than a decade, there has been an increased focus on the need for accountability and transparency about the value that United States and international higher education institutions add to students' knowledge and skills to help increase their economic productivity and career opportunities. This focus on accountability and transparency within the U.S. dates to 2005 when former US Secretary of Education Margaret Spellings established a Commission on the Future of Higher Education to develop a national strategy for higher education reform. This led to an increased focus on measuring value added within higher education institutions and using value-added scores to make institutional comparisons. This chapter presents a brief history of value added within the United States and presents high-level summaries of initiatives, assessments used to measure value added, and a review of how value added is measured. We also present challenges around methodology and interpretation of results. Lastly, we discuss some of the future directions in evaluating value added in higher education and areas for future research.

This paper presents the second-generation estimates for the Italian engineering industry in 1911, a year documented both by the customary demographic census, and the first industrial census. The first part of this paper uses the census data to estimate the industry’s value added, sector by sector; the second further disaggregates each sector by activity, and estimates the value added, employment, physical product, and metal consumption of each one. A third, concluding section dwells on the dependence of cross-section estimates on time-series evidence. Three appendices detail the specific algorithms that generate the present estimates; a fourth, a useful sample of firm-specific data.

The chapter analyses the international economic specialization of the Republic of Belarus based on the balance of payments and national statistics data by type of economic activity. It also demonstrates application of the customized Trade in Value Added methodology for analysis of the international economic specialization of Belarus. The methodology has been developed for the calculation of selected key figures for 2011–2016. Using of “Input–Output” tables to measure intersectoral relationships enabled assessment of the international trade not only in terms of prices of goods and services, but in terms of value added of each product. The analysis shows that the most important industries of the international economic specialization of Belarus are oil products, chemical products, food stuffs, equipment and vehicles, transport services, computer services. Domestic value added share of exports is about 60%, which corresponds to the level of such countries of Central and Eastern Europe as the Czech Republic, Slovakia, Estonia, Poland. Consequently, import intensity of exports accounts for about 40%. The results of the study have allowed to assess the interrelation between production, exports, and economic growth and to provide recommendations ensuring a deficit-free balance of payments.

Growth strategies exist, specifically for business divisions with a poor competitive position, by “orchestrating” value chains in external networks. The theory of competence development provides a basis for successfully developing new value architectures, since massive changes in a business division can take place only if they are based on durable competences. Four steps to orchestrating value chains can be deduced: (1) identifying changes in the value architecture as a possible growth strategy, (2) creating the organizational prerequisites for the deconstruction of value chains, (3) selling nonspecific value-added and (4) building networks around the core business that link (nonspecific) noncore activities to the firm.

This chapter does three things. First, it estimates regional gross domestic product (GDP) for three different geographical levels in Switzerland (97 micro regions, 16 labor market basins, and 3 large regions). Second, it analyzes the evolution of regional inequality relying on a heuristic model inspired by Williamson (1965), which features an initial growth impulse in one or several core regions and subsequent diffusion. Third, it uses index number theory to decompose regional inequality into three different effects: sectoral structure, productivity, and comparative advantage.

The results can be summarized as follows: As a consequence of the existence of multiple core regions, Swiss regional inequality has been comparatively low at higher geographical levels. Spatial diffusion of economic growth occurred across different parts of the country and within different labor market regions. This resulted in a bell-shaped evolution of regional inequality at the micro regional level and convergence at higher geographical levels. In early and in late stages of the development process, productivity differentials were the main drivers of inequality, whereas economic structure was determinant between 1888 and 1941. The poorest regions suffered from comparative disadvantage, that is, they were specialized in the vary sector (agriculture), where their relative productivity was comparatively lowest.

One of the most important economic processes in the world economy over the recent decades has been increasing fragmentation of international production that resulted in expansion of global value chains (GVCs). National economies started to get involved in GVCs in order to get value-added gains from this participation; Russia is not an exception. To analyze Russia’s GVCs participation, we need to adopt new statistical methodology based on input–output approach that allows estimating trade flows in terms of value added, including foreign and domestic value added as parts of gross exports. The author comes to the conclusion that Russia’s participation in GVCs was growing during the last decades mostly by forward participation connected with supply of oil and gas along GVC; moreover, Russia had net gains from this participation. Future trends in Russia’ involvement in GVCs can be described by two scenarios. The first one is based on expanding forward manufacturing participation in order to increase and diversify nonoil exports. This scenario is strongly supported by Russian Federation Ministry for Economic Development. The second scenario covers the continuation of mineral participation in GVCs that Russia implements till now. Both scenarios have their pro and contra. The author argues that the first scenario is better correlated with long-term economic interests and possibilities for sustainable development in Russia.

Due to the emergence of global production networks, trade statistics have became less accurate in describing the dependence of emerging Asia on external demand. This chapter analyses, using an update of the Asian International Input–Output (AIO) table, the interdependence of emerging Asian economies, the United States, the EU15, and Japan via trade and production linkages. According to the results, we do not find evidence of the decoupling of emerging Asia from the rest of the world. On the contrary, we find evidence on increasing trade integration, both globally and regionally. Nonetheless, our analysis indicates that emerging Asia's dependence on exports is only about one-third of its GDP, that is, well below the 50% exposure suggested by trade data. This finding can be explained by the high import content of exports in these economies, which is a result of the increasing segmentation of production across the region.