Dynamics Of Productivity Growth Research Articles

Are pro‐productivity policies fit for purpose?

AbstractIn this paper we examine productivity trends, drivers of productivity growth and pro‐productivity policies across the G‐20 economies since 1970. While we find distinctly different productivity growth dynamics between G‐20 economies and over time, one common observation is a widely shared slowdown in labour productivity growth since the 2010s underpinned by lower (or even negative) total factor productivity growth. Moreover, the growth in capital per worker hour has also begun to level off. We develop a typology of pro‐productivity policies and argue that policies for investment and technological change need strengthening to support a revival of productivity growth. Such policies should include a balanced approach to stronger technological progress and more rapid diffusion; a strengthening of investment, especially in intangibles and public services; and greater attention for human capital. We also argue for stronger institutions and capabilities that allow for dynamic learning about pro‐productivity policies across countries and over time.

Clustering Analysis of Energy Consumption in the Countries of the Visegrad Group

The main purpose of this paper is to assess energy consumption with a breakdown into main sectors of the countries that belong to the Visegrad Group. The specific objectives aim to determine changes in energy absorption, its productivity, structure by sectors and to show the similarities of the Visegrad Group countries to the other EU states in terms of the sectoral energy absorption structure. All members of the Visegrad group, i.e., Poland, Hungary, Slovakia and the Czech Republic, were purposefully selected for the study as of 31 December 2018. The research period covered the years 1990–2018. The sources of gathered information were the literature on the subject and OECD data. The following methods were used for the analysis and presentation of materials: explanations, tabular and graphical depictions, descriptive statistics, dynamics indicators, and cluster analysis performed with the following methods: k-means, hierarchical agglomerative clusters and DIvisive ANAlysis (DIANA). There is a limited number of previous studies on the relationship between the national level of economic development and energy consumption in different sectors of industry. Additionally, there are no such analytical projects concerning EU states. The article fills the research gap in this area. It was established that the dynamics of productivity growth over the nine years (2010–2018) was similar in the countries of the Visegrad group and on average for the EU. This means that the members of the Visegrad group did not actually improve their energy efficiency as compared to the EU average. The reason may be the increasingly faster implementation of modern technologies in developed economies of Western Europe as compared to the developing countries, which include the members of the Visegrad group. The conversion of the economy had a very large impact on changing the structure of energy absorption by sector. Industry and agriculture lost their importance. On the other hand, the transport and service sectors benefited. As a result of the cluster analysis, all EU (European Union) states were divided into four groups. Poland, the Czech Republic, and Hungary found themselves in one group, along with most Western European countries. This may mean that the economies of these states have become unified with highly developed economic systems. Slovakia found itself in the group of states with a greater importance of industry. The study complements the contribution to the theory. From a practical point of view, it shows the impact of economic transformation on changes in energy consumption in individual sectors, which may be a model of transition in this area.

Dynamics of productivity growth in Indian dairy products manufacturing industry

The study assesses the total factor productivity of dairy products manufacturing industry of the year 2009–13 using stochastic frontier production approach. The study concludes that the change in total value of output of industry is due to adoption of efficient and best practices by processors. The TFP growth of dairy industry is 4.3% mainly driven by technical change over time. Temporarily, the dairy industry is moving towards overcoming the constraints in TFP growth. There is more need to augment capital which is energy efficient and accordingly capacity building of emerging skill sets in the industry.

A two-sector Kaleckian model of growth and distribution with endogenous productivity dynamics

This study extends a two-sector Kaleckian model of output growth and income distribution by incorporating endogenous labour productivity growth. The model is composed of investment goods and consumption goods production sectors. The impact of a change in wage and profit shares on capacity utilisation and output growth rates at the sectoral and aggregate levels are identified. The study reveals short-run cyclical capacity utilisation rates and productivity growth dynamics. Even if the short-run steady state is stable, the capital accumulation rate in the consumption goods sector must decrease more than that in the investment sector for long-run stability. When simultaneous rises in profit shares in both the sectors affect long-run aggregate economic growth differently at a steady state, the distributional interests between the same class in different sectors may hamper the long-run economic growth. A policy message is that the effect of income distribution on industrial output growth is not always beneficial. These phenomena are specific to two-sector models and cannot be observed when using conventional aggregate growth models.

Tendencies of innovative development of the Russian Federation

Today in Russia there is a definite situation in the field of innovative development, characterized by a number of distinctive features. In a dynamic environment of industrial production and entrepreneurship, the need for the formation and development of non-proprietary resources is beyond doubt. The dynamics of productivity growth, the development of new high-tech production systems, the growth of the patent base in enterprises, trends in innovative development in general in the sector of the economy and large-scale production.The state of development of the economic system, depending on the structure of the innovation development of the subjects. At the same time, the innovative development of companies is manifested both in investments in advanced production technologies and in the production of high-tech products. The purpose of the scientific article is to analyze the innovative development in the Russian Federation.The goal necessitated the following tasks:1. To analyze the indirect indicator of innovation development – the volume of domestic expenditures on research and development in the context of country adaptability;2. To analyze the innovation activity of organizations by districts of the Russian Federation;3. To produce a factor analysis of indicators on the innovative development of the Russian Federation;4. Formulate recommendations for improving innovation activities in Russia.The article used modern methods and tools for integrated analysis based on the systematization and structuring of thematic material. So, in the article in which you will find information about what is happening in Russia.The above studies have become conclusions and recommendations regarding the features of the innovative development of the Russian Federation, recommendations for improving innovation activities in the Russian Federation.Significance is expressed in the practical possibility of using the results of research results.

Industry regulation, competition, and the dynamics of productivity growth: evidence from China’s iron and steel industry

This study aims to investigate the characteristics of the efficient evolution of China’s iron and steel industry against the backdrop of limited openness and regulation and to discuss the important effects of regulatory policy and total factor productivity (TFP) of China’s iron and steel industry. The method adopted the Cobb–Douglas production function combined with a semi-parametric method to decompose productivity. This study based on the micro-level dataset of iron and steel enterprises in the database of China’s industrial enterprises between 1998 and 2007 that investigated the intrinsic correlation among corporate entry and exit, market competition of existing enterprises, and TFP growth in the iron and steel industry. The results of the research show that the entry-exit would promote the growth of the aggregate productivity, while the low efficiency of resource allocation would significantly inhibit the TFP growth. The basic conclusion is that, with substantial government intervention in enterprise investments, marketcompetition may not promote optimal resource allocation efficiency in China’s iron and steel industry, but make the allocation less efficient.

Introduction: New Directions in Productivity Analysis

Today, economists acknowledge the basic relationship between productivity growth and improvements in living standards and all agree about the need to provide a more accurate assessment of productivity gain across time and space. But, beyond this basic consensus, the stream of empirical productivity analysis is certainly one of the most vividly debated in the economic literature. Since the surge of growth accounting exercises in the 1950’s, each decade witnessed important controversies which lead to new developments and further improvements. In the last decade, these renewals have been profound and motivated by three main sources. Firstly, the resumption of productivity growth in the 1990s after the productivity slowdown of the 1970s and 1980s provoked controversies among policymakers and researchers, and forced economists to reexamine the fundamental question of measurement techniques (Hulten et al. , 2001). Secondly, the important contribution of Philippe Aghion and Peter Howitt’s 1992 paper opened up new directions for empirical productivity analysis. In formalizing aggregate productivity growth as the outcome of a process of creative destruction, they invited us to explore the correlation between productivity growth and the endogenous flow of firm entry and exit and the endogenous rate of capital obsolescence. Thirdly, the new and growing availability of large scale longitudinal firmlevel datasets, provided radically new ways to connect micro-and aggregate productivity growth dynamics. Following on the pioneering micro-