Nonlabor income measures of capital intensity versus capital stock measures in estimatingthe determinants of regional labor productivity differentials: The manufacturing sector

1983 ◽  
Vol 17 (1) ◽  
pp. 79-93 ◽  
Author(s):  
Ronald L. Moomaw
Keyword(s):  
Labor Productivity ◽  
Capital Stock ◽  
Manufacturing Sector ◽  
Capital Intensity ◽  
Regional Labor ◽  
Productivity Differentials

STRUCTURE, EMPLOYMENT AND PRODUCTIVITY GROWTH IN THE INDIAN UNORGANIZED MANUFACTURING SECTOR: AN INDUSTRY LEVEL ANALYSIS

2011 ◽  
Vol 56 (03) ◽  
pp. 349-376 ◽  
Author(s):  
S. N. RAJESH RAJ
Keyword(s):  
Labor Productivity ◽  
Technological Progress ◽  
Manufacturing Sector ◽  
Capital Intensity ◽  
Factor Productivity ◽  
Capital Productivity ◽  
Size Growth ◽  
Partial Factor Productivity ◽  
Partial Factor ◽  
Level Analysis

The paper analyzes the size, growth and productivity performance of the unorganized manufacturing sector in India during the 1978–1979 to 2000–2001 period. The study shows evidence of an increase in the size of the sector with a slowdown in the reforms period. Evidence indicates that the rate of growth varies widely across the two-digit industries but the variation in growth rate is smaller during the 1990s. Textiles and machinery goods were the fastest growing segments of India's unorganized manufacturing sector in the reforms period. The partial factor productivity approach shows that labor productivity has improved in 2000–2001 over 1978–1979 while capital productivity reported a decline in the same period. The sector, on the other hand, registered a fall in total factor productivity (TFP) during the reforms period. It is found that technological progress has been the main contributor to the growth in TFP in the prereforms period while technical regress contributed to the decline in TFP in the reforms period. A completely different picture is noticed since the mid-1990s when the sector made significant progress in TFP primarily attributed to technological progress which outweighed the decline in technical efficiency. It is also found that capital intensity is an essential factor augmenting labor productivity levels in the sector, which is important for improving the wages paid to the workers in the sector.

Digitalization, Industry Concentration, and Productivity in Germany

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Benjamin Ferschli ◽  
Miriam Rehm ◽  
Matthias Schnetzer ◽  
Stella Zilian
Keyword(s):  
Labor Productivity ◽  
Fixed Effects ◽  
Scale Effects ◽  
Manufacturing Sector ◽  
German Economy ◽  
Capital Intensity ◽  
Industry Concentration ◽  
Fixed Effects Model ◽  
Firm Level ◽  
Combining Data

Abstract This paper investigates the links of digitalization and industry concentration with labor productivity at the sectoral level in Germany. Combining data for digitalization and labor productivity from the EU KLEMS database with firm-level data from the CompNet and Orbis Bureau Van Dijk databases to construct industry concentration measures between 2000 and 2015, we show that (1) the German economy appears to have digitized since 2000, and (2) there is no clear-cut relationship between digitalization and market concentration at the industry level. Using a time and sector fixed effects model and controlling for capital intensity, however, we find evidence for (3) a positive effect of both lagged industry concentration and lagged digitalization on productivity at the sectoral level in Germany. This finding is robust to alternative measures of digitalization and industry concentration as well as to their interaction but sensitive to the sector sample and to scale effects from the capital intensity. We, therefore, cautiously conclude that recent technological change appears to have been labor-saving and that productivity-enhancing aspect of a partial “superstar firm” effect may be identified in the German economy, in particular in its manufacturing sector.

scholarly journals Women’s Economic Empowerment in Vietnam: Performance and Constraints of Female-Led Manufacturing SMEs

2021 ◽  
Vol 14 (6) ◽  
pp. 255
Author(s):  
MinhTam Bui ◽  
Trinh Q. Long
Keyword(s):  
Labor Productivity ◽  
Small And Medium Enterprises ◽  
Manufacturing Sector ◽  
Value Added ◽  
Medium Size ◽  
Formal Sector ◽  
Firm Level ◽  
Average Value ◽  
Significant Difference ◽  
Medium Enterprises

This paper identifies whether there was a performance difference among micro, small and medium enterprises (MSMEs) led by men and by women in Vietnam during the period 2005–2013 and aims to provide explanations for the differences, if any, in various performance indicators. The paper adopts a quantitative approach using a firm-level panel dataset in the manufacturing sector in 10 provinces/cities in Vietnam in five waves from 2005 to 2013. Fixed effect models are estimated to examine the influence of firm variables and demographic, human capital characteristics of owners/managers on firms’ value added, labor productivity and employment creation. We found that men led MSMEs did not outperform those led by women on average. Although the average value added was lower for female-led firms in the informal sector, the opposite was true in the formal sector where women tend to lead medium-size firms with higher value added and labor productivity. The performance disparity was more envisaged across levels of formality and less clear from a gender perspective. Moreover, while firms owned by businessmen seemed to create more jobs, firms owned by women had a higher share of female employees. No significant difference in business constraints faced by women and by men was found.

scholarly journals Intangible Assets and Labor Productivity Growth

Economies ◽  
2021 ◽  
Vol 9 (2) ◽  
pp. 82
Author(s):  
Carolina Hintzmann ◽  
Josep Lladós-Masllorens ◽  
Raul Ramos
Keyword(s):  
Labor Productivity ◽  
Productivity Growth ◽  
Intangible Assets ◽  
Manufacturing Sector ◽  
Intangible Asset ◽  
Labor Productivity Growth ◽  
Eu Member States ◽  
Different Types ◽  
European Economies ◽  
D Investment

We examine the contribution to labor productivity growth in the manufacturing sector of investment in different intangible asset categories—computerized information, innovative property, and economic competencies—for a set of 18 European countries between 1995 and 2017, as well as whether this contribution varies between different groups of countries. The motivation is to go a step further and identify which single or combination of intangible assets are relevant. The main findings can be summarized as follows. Firstly, all the three different categories of intangible assets contribute to labor productivity growth. In particular, intangible assets related to economic competences together with innovative property assets have been identified as the main drivers; specifically, advertising and marketing, organizational capital, research and development (R&D) investment, and design. Secondly, splitting the sample of European Union (EU) member states into three groups—northern, central and southern Europe—allows for the identification of a significant differentiated behavior between and within groups, in terms of the effects of investment in intangible assets on labor productivity growth. We conclude that measures promoting investment in intangibles at EU level should be accompanied by specific measures focusing on each country’s needs, for the purpose of promoting labor productivity growth. The obtained evidence suggests that the solution for the innovation deficit of some European economies consist not only of raising R&D expenditure, but also exploiting complementarities between different types of assets.

scholarly journals Labor Productivity and Foreign Direct Investment in the Indonesian Manufacturing Sector

2019 ◽  
Vol 8 (1) ◽  
pp. 9-22 ◽  
Author(s):  
Luhur Selo Baskoro ◽  
Yonsuke Hara ◽  
Yoshihiro Otsuji
Keyword(s):  
Foreign Direct Investment ◽  
Labor Productivity ◽  
Direct Investment ◽  
Social Protection ◽  
Manufacturing Sector ◽  
Random Effect ◽  
Effect Analysis ◽  
Positive Externalities ◽  
Random Effect Analysis

This paper investigates the determinants of foreign direct investment (FDI) inflow, focusing on the effect of labor productivity in the Indonesian manufacturing sector. Indonesia has the advantage of abundant labor supply in attracting FDI to bring positive externalities to its economy. Based on this background, this paper is aimed to study and to improve FDI inflow through a random effect analysis of 19 manufacturing industries from 2001 to 2014. The empirical result shows that labor productivity, wages, and export have become significant factors that attract FDI. FDI inflow in this sector tends to target non-labor industries. For the labor-intensive industries, the primary strategy is to increase labor quality through improvement in education, training, internship program, and worker certification. Improving research and development climate, and maintaining the quality of labor through health and social protection regulation can attain improvement in non-labor intensive industries.

scholarly journals Does wage reflect labor productivity? A comparison between Brazil and the United States

2018 ◽  
Vol 38 (4) ◽  
pp. 629-649 ◽  
Author(s):  
ALEXANDRE GORI MAIA ◽  
ARTHUR SAKAMOTO
Keyword(s):  
United States ◽  
Economic Development ◽  
Labor Productivity ◽  
Wage Differentials ◽  
The United States ◽  
Occupational Groups ◽  
Economic Cycles ◽  
Productivity Differentials ◽  
The Relationship ◽  
The U.S

ABSTRACT The study compares the relationship between wages and labor productivity for different categories of workers in Brazil and in the U.S. Analyses highlight to what extent the equilibrium between wages and productivity is related to the degree of economic development. Wages in the U.S. has shown to be more attached to labor productivity, while Brazil has experienced several economic cycles were average earnings grew initially much faster than labor productivity, suddenly falling down in the subsequent years. Analyses also stress how wage differentials, in fact, match productivity differentials for certain occupational groups, while for others they do not.

Wage-differentials and Their Determinants Across Industries in the Organized Manufacturing Sector of India

2020 ◽  
pp. 097215092091256
Author(s):  
Chandrima Ganguly ◽  
Joydeb Sasmal
Keyword(s):  
Wage Differentials ◽  
Manufacturing Sector ◽  
Wage Bargaining ◽  
Wage Determination ◽  
Farm Size ◽  
Total Employment ◽  
Annual Survey ◽  
Productivity Differentials ◽  
Specific Factors ◽  
Using Data

This article calculates the magnitude of wage differentials across industries in the organized manufacturing sector of India and identifies the major determinants of wage differentiation among the industries. Using data from Annual Survey of Industries in India for the period from 2000–2001 to 2015–2016, this study shows that mean wage is less in labour-intensive industries compared to the capital-intensive industries. The results of panel regression of annual average wage on various industry-specific factors show that productivity of labour is the most important factor in wage determination, and productivity largely depends on capital–labour ratio. The other significant factors in this regard are farm size, amount of profit and proportion of casual and female workers in total employment. Important policy implication of this study is that regulatory wage fixation and wage bargaining outcomes are not as significant as productivity differentials in explaining wage gaps across industries.

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