Recent discussions on the definition of growth in terms of welfare beyond GDP suggest that it is of urgent need to develop new approaches for measuring the economic performance of the firms and national economies. The new concepts should take into account simultaneously economic as well as social and environmental goals. We first discuss several approaches to productivity measures. Then we extend the Data Envelopment Analysis models for environment to measure the so called eco-efficiency and for social indicators to take into account the social performance. For an illustration, we perform the analysis of 30 European countries in the year 2010. In the last section we discuss the possibilities of inter-temporal analysis of proposed models and of their use in ex-ante evaluation of different policy scenarios.
In the present paper, we analyse the determinants of employment growth in V4 countries. While a standard approach relies on the parametric estimation of labour elasticity coefficients, we employ a novel approach based on structural decomposition analysis. This allows us to identify several determinants which mitigate the effects of economic growth on employment. We decompose the overall change in employment into the contribution of six factors: changes in labour productivity, changes in the import of intermediate products, changes in the structure of production, changes in the final demand structure by industries and by sectors, and a change in final demand volume. We show that besides the generally accepted influence of labour productivity growth on employment, other factors such as structural changes and changes in final demand played an important role in employment changes. These results shed some light on low labour elasticity in V4 countries and go beyond the simple labour productivity growth argument.
This paper provides detailed evidence on the extent of outsourcing and offshoring of manufacturing employment and value added using a regional subsystem input–output framework. The paper argues that direct employment and the value-added shares of manufacturing in the totals underestimate manufacturing’s importance. Jobs in manufacturing subsystems accounted for more than 25% of total worldwide employment, in contrast to just 15% recorded in direct statistics. In major developed countries, the level of intersectoral outsourcing reached its upper limit at the beginning of the new millennium. At the same time, the offshoring of activities interlinked with manufacturing has become the dominant driver of deindustrialisation in these countries. While direct manufacturing employment and intersectoral outsourcing declined between 2000 and 2014, offshoring experienced a significant increase of 6.5 percentage points, from 29% to 35.5% of the total employment generated under the G7 manufacturing subsystem. Furthermore, 84% of the value added that existed to meet the final demand for manufactured products in G7 countries remained in G7 countries, while most of the jobs needed to meet G7 final demand have been offshored to developing countries. The paper concludes that the importance of manufacturing subsystems for the world economy did not decline over 2000–14, but there was a significant shift of manufacturing activities and related services from G7 countries to China and other rapidly growing economies.
To understand the evolution of labor demand in European countries in the context of automation and other emerging technologies, we apply the decomposition developed by Acemoglu and Restrepo (2019) to European data. At the center of this framework is the task content of production-measuring the allocation of tasks to factors of production. By creating a displacement effect, automation shifts the task content of production against labor, while the introduction of new tasks in which labor has a comparative advantage increases the labor demand via the reinstatement effect. Contrary to the US experience, in a group of 10 European countries, the displacement effect of automation was completely counterbalanced by technologies that create new tasks in which labor has a comparative advantage. Furthermore, our crosscountry comparison reveals a substantial variation across countries. The cumulative change in the task content of production ranges from 6.2% in the United Kingdom to a strong negative effect, namely-7.6%, in Sweden. A part of the differences can be explained by the rate of adoption of industrial robots. We document a strong unconditional relationship between the change in robot density and the displacement effect. However, differences in the reinstatement effect remain unexplained.
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