Ageing, productivity and wages in Austria

Ageing, Productivity and Wages in Austria

Changes in industrial structure contribute to stagnant productivity of the entire economy and slowing economic growth. Usually, when a country’s economic development enters a mature stage, there is a deindustrialization phenomenon in which the share of manufacturing is transferred to the share of the service industries, and Korea has been fast in the employment sector since the 1990s. This phenomenon leads to a gap in productivity growth rates between manufacturing and service industries. Recently, concerns have been raised that the distribution of resources among industries is not smooth due to the decline in labor productivity and economic growth in the 2010s. Accordingly, this study analyzed the changes in productivity related to the trend of labor productivity and looked at the characteristics of the Korean economy, recognizing that it needs to increase productivity between industries and allocate resources efficiently in order for it to leap out of its low growth trend. In addition, panel analysis was conducted on how changes in industrial structure affect the share of employment and production. The main results are summarised as follows: First of all, the effects of labor productivity factor decomposition were greater than static and dynamic effects in all industries, manufacturing and service industries. This led to a rise in overall labor productivity due to technological innovation being more effective than by employment movement or inter-sector interactions from 1993 to 2019. In addition, the signs of static and dynamic effects showed different results from industry to industry, but the negative signs of dynamic effects showed a greater shift in employment from a highly productive industry to a lower industry. This is the result of Baumol’s structural burden assumption on the Korean economy. On the other hand, the manufacturing sector has been redistributed from less productive to higher industries as a result of static and dynamic effects among detailed industries, but the effectiveness has been low. The service industry had different results in static and dynamic effects. These results mean that employment shifts rapidly to highly productive industries, while employment shifts from fast-growing to slow industries. Next, according to panel analysis, the share of employment and production by industry are affected by labor productivity, labor income share, capital intensity, export dependence and import dependence. Labor productivity has a negative impact on employment, but it has a positive impact on production. In general, labor productivity and employment may be expected to increase employment in industries with high labor productivity, but in practice, the consequences of the share of employment were not. This is the result of Baumol's hypothesis in panel analysis. The increase in labor income share also led to an increase in household income, driving aggregate demand or economic growth. On the other hand, the capital intensity differs depending on whether capital and labor are alternatives or complementary, in which all industries and manufacturing industries are shown to have an inverse relationship between employment and production as capital and labor are alternatives. On the other hand, the service industry acted as a complementary relationship to attract employment. Foreign direct investment is expected to have a negative impact on employment and production as it replaces domestic production and exports, but only in the manufacturing and service industries have a positive impact on employment. These results may vary slightly by industry, but they can be interpreted as the result of qualitative changes in domestic industries, such as the spread of the fourth industry, technological innovation, advancement and convergence of major industries.

Maria Socorro Gochoco-Bautista: There is a difference between structural transformation in which the share of agriculture in total output declines over time, and structural transformation in which the share of agricultural sector employment to total employment declines over time as a country develops. The authors state that they would like to focus on the output side of structural adjustment (i.e., what happens to the sectoral shares of output rather than the sectoral shares of labor).I think that, as the focus of the paper is pro-poor growth, it is more important to talk about people and employment rather than output. Indeed, the authors define growth as pro-poor “if and only if poor people benefit in absolute terms, as reflected in an appropriate measure of poverty.” The paper by Loayza and Raddatz (2006) that the authors themselves cite argues that the labor intensity of the growing sector rather than which economic sector in particular is growing is more important.This leads to my suspicion that what makes growth pro-poor is the ability of growth to generate good jobs, and to ultimately reduce the share of agricultural employment to total employment as the economy undergoes structural transformation and develops. If this is the case, then I am afraid that the paper is unable to shed light on how to generate pro-poor growth, even though it is able to point to factors that may generate growth in the economy in general. Of course, because the demand for labor is derived from the demand for output, one would expect the demand for labor to increase in fast-growing sectors and reduce poverty. In Asia, however, we have generally seen that although output growth has been robust, the share of employment in agriculture relative to non-agriculture remains high, and we know that the quality jobs are not in agriculture and that the majority of the poor are in rural areas. Perhaps the employment elasticity of growth in the non-agricultural sector may be low especially if production there is relatively capital intensive. The authors do not give a measure of the labor intensity of the fast-growing non-agricultural sector relative to the agricultural sector.Where to focus reform proposals is important because this has a bearing on policy implications. It is important to take into account where the distortions in the economy are in the context of institutional limitations and which act to prevent growth from being pro-poor. For example, there are barriers to job creation and entry into high-paying jobs in the non-agricultural or industrial sector that act as a tax on the most progressive sector of the economy. This limits the ability of the industrial sector to absorb surplus labor from the rural sector and retards the shift from agricultural to non-agricultural growth. Evidence for these distortions exists. In urban centers, for example, the unemployment rate among those with tertiary education is higher than in those with only primary or secondary levels of education, and the employment rate of the less educated is higher in sectors where regulations are not binding. Such barriers in labor markets may account for gaps in labor productivity between agricultural and non-agricultural sectors. For pro-poor growth, I think that it is important to focus on the labor market and employment generation aspects of structural transformation.In the regression equation, agricultural growth and non-agricultural growth are both entered as regressors, but the two are related to each other. Growth in the agricultural sector makes growth in the non-agricultural sector possible by opening up non-farm employment opportunities, a point the authors make themselves. But because the focus of the paper is on output growth rather than employment growth potential, it is difficult to know with certainty whether growth in any sector is pro-poor.

Foreign Involvement and Firm Productivity: An Analysis for Indian Manufacturing, Service, Construction and Mining Sectors

This dissertation aims to integrate the post-keynesian approach to growth driven by exports with the structural change and productivity growth proposal of Therefore, we develop here a dynamic mathematical model that demonstrates the complementarity between these approaches, since the structural changes in favor of industry more than make up the loss of productivity of the service sector and agriculture, enhancing the longterm growth. Computer simulations presented here help understand the long-term dynamics of the proposed model and the effects of structural change on the evolution of per capita output of an economy. The model here proposed points that the long term per capita growth of the domestic economy depends on the real exchange rate, on the variation of the labor productivity of the productive sectors, variation of the employment share between sectors, labor productivity variation of the productive sectors, on the share of employment across sectors, on income from the rest of the world and the growth rate of wages. Presented computer simulations helps to understand the long term dynamics of the proposed model and the structural change effects on the evolution of output per capita of the Brazilian economy, as well as estimating hypothetical situations.It is observed, for Brazilian economy, that the country achieved a perverse productive specialization in the last five decades, where the industrial sector (with both high labor productivity and income elasticity of demand) lost power, as well as the primary sector. This fact gave rise to a large traditional service sector (with low labor productivity). This specialization has meant that the country had great restraint in the growth of productivity, negatively affecting their economic growth and development.

The vigorous growth of the Chinese economy together with its growing role in international trade has raised fears of deindustrialization among developing countries. This study draws on the large increase in the international trade exposure of the Brazilian economy from 2000 to 2012 to assess the impacts of trade on its manufacturing sector. In this period, import penetration increased by 25%, and at the same time, Chinas share of import penetration increased from 3% to 20%. Using household survey data that encompasses both formal and informal workers, this papers estimates indicate that higher import penetration reduces the employment level, the share of employment in the population, the hourly wage, the interindustry wage premium, and the share of informal employment. The industry-level results indicate that a rise in import penetration from either China or the rest of the world (ROW) reduced the employment level, hourly wage, and share of informal employment while increasing the interindustry wage premium. The worker-level results suggest that industry-level import penetration from China and the ROW raised workers wages and reduced the likelihood of their being informally employed. The state-level estimates imply that Chinese and ROW imports per worker initially reduced the employment level, the hourly wage, and share of informal employment, but these effects were reversed after 2008. Chinese imports per firm had a negative impact on the share of informal employment and a positive one on average years of schooling. Before 2008, Chinese imports per firm increased the share of workers with both high-school and college educations, and the net impact on both shares became negative after 2008. Estimates using actual imports per worker and per firm did not impact state-level labor-market outcomes. Finally, these effects were modulated by the labor intensity of the industry, the state-level initial share of manufacturing in the gross domestic product, the availability of a sea harbor in the state, and the implementation of the Nova Matriz Econmica policies in 2008.

Central American (CA) countries are considered to be part of the developing world. Their small and open economies have historically relied on the production and exports of agricultural products. In the last two decades, even though the share of agriculture in the GPD has declined significantly facing the surge in shares of manufacturing and service sectors, agriculture remains as one of the major economic activities in the CA countries. Agricultural sector employs a large portion of the economically active population and is an important source of income, particularly for rural and unskilled labor force. Significantly diversified economic performance has been observed among the seven CA countries during the past decades. Among them, Costa Rica and Panama are the most developed in terms of per capita GDP and outperformed the other five countries in various social-economic indicators, whereas Honduras and Nicaragua are the least developed. Identifying the sources contributing to observed differences among the CA countries has important implications for policy makers in their pursuit of economic growth. Therefore, this thesis attempts to examine two important issues for the seven CA countries – economic diversification and its link to economic growth as well as sectoral productivity differences – during the period 1990-2010. We first examine the economic diversification and its possible relation to economic growth. In the second part of the thesis, we then move to analyze the factors leading to differences in the labor productivity of industrial and agriculture sectors. According to Esanov (2012), economic diversification can be categorized into the product or export diversification. Both these two types of diversification are considered to enhance economic growth. To measure diversification, the trend of GDP composition by sector is used as a measure of product diversification while Herfindahl-Hirschman Index (HHI) is calculated to measure export diversification. The empirical results in this study suggest that the diversification strategy in the CA region is country-specific, Costa Rica and Panama experienced significant achievements while the other five countries seem to be lagged. Export diversification has been achieved mostly within the same agricultural sector but not among sectors; CA countries have introduced new export products into their export basket, but those new products mainly come from agricultural sector. In addition, the levels of diversification experienced by the CA countries are significantly lower compared to the developed economies. Based on regression analysis controlling for year and country specific unobserved characteristics, this study provides empirical evidence supporting the positive association of export diversification and per-capita-GDP growth. In the second part of the thesis, determinants contributing to observed differences in labor productivity between the industrial and agriculture sectors are analyzed through a two-stage regression model. The data collected indicates that, during 1990-2010, the level of labor productivity in the industrial sector has been higher and growing at a greater speed in comparison with the agricultural sector. A systematic review of the literature suggests that this sectoral productivity gap can be explained by variables such as physical capital investment, openness of the economy, foreign direct investment (FDI) as well as education (human capital). To test the hypothesis that those variables have a greater effect in industrial sector than in agricultural sector, which consequently implies a wider gap in labor productivity, a structural equation model is constructed. The specification in our econometric model explicitly considers possible problem of endogenous explanatory variable. The regression results suggest physical capital investments, openness and education are the major drivers to widen up the gap of labor productivity in the industrial and agriculture sectors. As a reasonable proxy for knowledge spilled into the CA countries from the developed countries, FDI is found to have a diminishing effect on productivity differences; it is a determinant of productivity differences at low level of FDI, but it reduces the productivity differences at large enough level of FDI inflow. Study sectoral labor productivity differences is of special significance in Central America, because these countries have labor-intensive economies and both agricultural and industry sectors together employ a large share of the economically active population. Due to its small share in the world economy, Central America has often been left out in researches on topics related to economic growth. To the best of our knowledge, there has not been previous literature on economic diversification and sectoral productivity differences in the CA countries as a whole. In this regard, this thesis fills in the gap and thus represents a significant complement to literature on the region.

In China, as in the Soviet Union and Eastern Europe, economic reform initiatives seek to increase productivity by introducing elements of market-oriented policies and institutions into an economy formerly dominated by state planning. Efforts to evaluate the impact of reform of Chinese industry have focused on the measurement of productivity change in state enterprises. This study expands the prior framework of analysis in several directions. Our investigation of productivity trends is not limited to state enterprises but includes quantitative comparisons with China's fast-growing collective industries, which contributed 36% of overall industrial output in 1988.1 Unlike previous studies, our analysis works with gross rather than net output. This permits us to investigate changes in the productivity of intermediate inputs, which occupy a large portion of total costs in Chinese industry, as well as labor and capital. To do this, we develop a "quasi-frontier" estimation procedure which seems appropriate for comparisons of total factor productivity based on Chinese industrial data. Finally, we offer a quantitative perspective on the extent to which reform efforts have moved industrial resource allocation toward patterns expected of a market system. The analysis confirms our previous finding, based on a restricted framework employing only labor, fixed capital, and net output, that multifactor productivity in state industry has risen substantially during

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This study aims to provide a comprehensive analysis of the impact of digital transformation on labor productivity in industrial enterprises. In the context of globalization and technological progress, the digitalization of industrial production has become a crucial factor in economic growth. Digital technologies–automation, artificial intelligence, big data analytics, cloud computing, and the industrial Internet of Things (IoT) are key tools for improving labor productivity. These technologies not only enhance production efficiency but also strengthen the competitiveness of enterprises, expanding their opportunities to enter global markets. The study examines international experiences in assessing the impact of digital transformation on labor productivity. Reforms implemented under Germany's "Industry 4.0" initiative, South Korea's digital strategies, and Singapore's "Smart City" program are analyzed, highlighting their effects on the industrial sector. In these countries, the adoption of digital technologies is considered a critical factor in increasing labor productivity. Additionally, the research explores the current state of digital transformation in Kazakhstan's industrial enterprises, identifying key barriers and opportunities. The main challenges of industrial digitalization in Kazakhstan are related to infrastructure limitations, a shortage of qualified personnel, and the low readiness of enterprises to adopt new technologies. Addressing these issues requires enhanced government support, the development of digital infrastructure, and the strengthening of enterprises' innovation potential. The findings of this study indicate that the effective implementation of digital transformation in Kazakhstan will become a vital component of national innovation development, positively impacting labor productivity and sustainable economic growth. The widespread adoption of digital technologies will enable industrial enterprises to optimize production processes, expand into new markets, and improve their competitiveness.

The structural-dynamic peculiarities of employment in the service industry are investigated. The facts that the service industry plays an increasing role in the economic growth of the countries and that the share of employed in the service industry in the countries with the developed market economy is 75–80% are emphasized. Therefore, Ukrainian economy has significant capacity for the employment increase in this industry. It is determined that the high share of employed in industries requiring highly skilled personnel indicates the development of innovative-technological economy sectors. It will promote the country’s GDP growth in future. The share of employment in such industries is defined to remain insignificant in Ukraine, as typical for to the countries with transition economies. The structure of employment in the service industry sectors in Ukraine and developed countries is determined to be distinctly different, although it provides Ukraine with additional opportunities to develop competitive sectors of service industry. It is revealed that the average weighted rate of employment growth has declined in 2018 in comparison with 2013 (81.59%), which is peculiar to the Ukrainian economy in general, where the 80.18 employment growth for the same period was caused by decline of economic activity in the country and was related to the unstable political situation and military actions, substantial inflation, declining foreign direct investment, etc. The formation of employment structure in service industry is influenced by transformation processes characteristic for the countries with transition economies. The evidence of effective development of service indusrtry is the growth of labor productivity. The significant share of employment in the region's service industry, along with low labour productivity, indicates the substantial shadowing of employment. In Ukraine, the level of informal employment is the highest in trade, transport and temporary accommodation sectors. At the same time, the growing share of employed in the industries with high added value like ICT, finances, healthcare, administrative and support services, scientific and professional activity, etc. indicates the efficient structural transformation of Ukrainian economy.

Recent work in the economic development literature has established sizable variations across nations in the relative wage for management, defined as the average wage for managers divided by the average wage for other workers, and provided evidence that the high relative wage for managers in lower income nations depresses productivity in those nations. This research explores if the same relationships exist solely across industries within the United States using an annual data set of 228 industries for years 2002–2020. As in the development literature, more variation is found across industries in the earnings for all other workers than for management, along with sizable variation across industries in the relative wage for management. Across the 228 industries in any year, the relative wage for management at the 10th/90th percentiles is near 2.0 and 3.2 respectively. Also, a robust positive link is found between managements’ employment share in an industry and the average wage of all other workers which is evidence of complementarity between management and the skill level of other workers in an industry. Lastly, evidence for nonlinearities over the sample period is found in the relationship between the growth rate of managements’ share of employment and labor productivity growth. Industries with lower rates of growth in managements’ share of employment exhibit a negative linkage with labor productivity growth, but this switches to a positive linkage with labor productivity growth for industries with higher growth rates for managements’ share of employment. Potential factors driving this result are discussed.

The industrial sector of the Republic of Croatia is subject to deindustrialization, which was globally recognized as early as in the 1960s. Such a situation is a challenge in terms of implementing new sources of economic growth and industrial production, with a particular emphasis on investing in research and development, education and their products. Since 2011, special emphasis has been placed on the need to implement the concept of Industry 4.0. The problem surveyed in this research derives from insufficient readiness of the Republic of Croatia to implement Industry 4.0, mainly resulting from its major orientation towards traditional industrial sectors and a low share of high value added activities, which is particularly visible through the share of high technology products in total exports. However, the Republic of Croatia is characterized by low levels of scientific research and innovative activities, which greatly slows down this process. The aim of the conducted research is to present the theoretical aspects of the process of deindustrialization and Industry 4.0, to make projections of the key indicators of deindustrialization and Industry 4.0 until 2025, and to propose scientifically based measures to be taken in the direction of securing digital transformation of the Croatian industry. The purpose of the conducted research is to analyse trends in the industrial sector in the Republic of Croatia and to determine the current state of the (de)industrialization process and the level of implementation of Industry 4.0. The research has showed that the process of deindustrialization in the Republic of Croatia is characterized by a reduction in the share of employment in the primary sector, by a growing employment in the secondary sector, and by a relative increase in industrial production and labour productivity. However, since 2015 there has been an increase in employment in the secondary sector, which is in contrast to the theoretical concepts of deindustrialization and indicates a new trend in the industrial sector. This situation is a challenge concerning the implementation of Industry 4.0, which requires increased investment in research and development and the improvement of knowledge and the ability of the population and their implementation in the economic sector. By analysing this segment of the Croatian economy, some progress has been made. Also, it has also been found that in some segments it significantly lags behind the EU levels.

Innovation, gender, and labour productivity: Small and medium enterprises in Vietnam

세계화가 빠르게 진전되면서 한국 기업들의 오프쇼어링 비중도 커지고 있다. 기존 연구들의 경우 오프쇼어링의 효과보다는 기업이 오프쇼어링을 선택하는 결정요인을 분석하는데 집중하고 있다. 따라서 본 논문은 오프쇼어링이 한국 기업의 생산성에 미친 영향에 대해 정량적으로 분석했다. 이를 위해 통계청의 기업활동조사를 기반으로 기업수준의 패널데이터를 이용해 합동 최소자승법과 고정효과 패널모형을 통해 분석했다. 기존 연구와는 달리 서비스업을 제조업과 구분하여 오프쇼어링의 영향을 추정하였으며, 두 산업 간의 결과를 비교하였다. 합동 최소자승법 결과에서는 전체 기업의 오프쇼어링 비중이 1% 증가할 때 노동생산성은 0.03% 증가하는 것으로 분석되었다. 그러나 고정효과 패널모형 결과의 경우, 오프쇼어링이 기업의 노동생산성에 주는 효과가 유의하게 추정되지 못했다. 모든 모형에서 오프쇼어링이 제조업 생산성에 긍정적 영향을 미치는 것으로 추정되었다. 서비스산업의 경우 고정효과 패널분석 결과에서 오프쇼어링이 생산성에 미치는 영향이 부정적으로 추정되었으나 유의하지는 않았다. 자본과 R&D비용 등 기업의 생산성에 영향을 주는 다른 설명변수들은 서울에 본사가 있는가 여부에 대한 더미변수를 제외하고 대부분 생산성 향상에 기여한다는 결과를 얻었다. As with fast growing globalization, Korean firms have increased their offshoring activities and more empirical research are needed to analyze the effect of offshoring on Korean firms' productivity. This study used "Survey of Business Activities", a firm-level panel data set surveyed by the Statistics Korea between 2006 and 2008, and estimated pooled OLS and Panel fixed effect model to examine the impact of offshoring on a firm's labor productivity. Unlike the previous studies on offshoring, we included in the analyses the firms in the service industry in addition to those in the manufacturing industry, and presented the comparative results. The results from pooled OLS model show that 1% increase in the share of offshoring output will lead to 0.03% increase in labor productivity. However, the results from Panel model show that the effects of offshoring on productivity is positive but statistically insignificant. Analyzing the manufacturing and the service sector separately, the main results based on Panel model can be summarized as follows: Offshoring has significant positive effects on firms' productivity in the manufacturing industry. Contrastingly, the impact of offshoring on firms' productivity in the service industry is estimated to be negative but statistically insignificant. Other than the share of offshoring output, most factors except headquarter location have positive effects on firms' productivity in both manufacturing and service industry.