scholarly journals Labor productivity gap between export and non-exporting firms in industrialization: The case of the Vietnamese manufacturing sector

Accounting ◽  
2020 ◽  
pp. 509-524
Author(s):  
Huu Trinh Nguyen ◽  
Thi Minh Thy Le ◽  
Thi Mai Huong Dang ◽  
Thanh Cuong Nguyen ◽  
Trung Dung Dang ◽  
...  
Keyword(s):  
Labor Productivity ◽  
Manufacturing Sector ◽  
Exporting Firms ◽  
Productivity Gap

scholarly journals Manufacturing and the Convergence Hypothesis: What the Long-Run Data Show

1993 ◽  
Vol 53 (4) ◽  
pp. 772-795 ◽  
Author(s):  
Stephen N. Broadberry
Keyword(s):  
United States ◽  
Structural Change ◽  
Labor Productivity ◽  
Manufacturing Sector ◽  
The United States ◽  
Industrialized Countries ◽  
Convergence Hypothesis ◽  
Technological Choice ◽  
Long Run ◽  
Productivity Gap

The commonly accepted chronology for comparative productivity levels, based on GDP data, does not apply to the manufacturing sector, which shows evidence of a much greater degree of stationarity of comparative labor productivity performance among the major industrialized countries of Britain, Germany, and the United States. These results for manufacturing suggest that convergence of GDP per worker must have occurred through trends in other sectors and through compositional effects of structural change. The persistent, large labor productivity gap between the United States and Europe cannot be explained simply by differences in capital per worker, but is related to technological choice.

International differences in labor productivity: Role of capital, technological level and resource rent

2016 ◽  
pp. 67-93 ◽  
Author(s):  
A. Zaytsev
Keyword(s):  
Labor Productivity ◽  
Developed Countries ◽  
Resource Rent ◽  
Per Capita Gdp ◽  
Technological Level ◽  
Per Capita ◽  
Oil Sector ◽  
Population Ratio ◽  
Gdp Gap ◽  
Productivity Gap

Using level accounting methodology this article examines sources of per capita GDP and labor productivity differences between Russia and developed and developing countries. It considers the role played by the following determinants in per capita GDP gap: per hour labor productivity, number of hours worked per worker and labor-population ratio. It is shown that labor productivity difference is the main reason of Russia’s lagging behind. Factors of Russia’s low labor productivity are then estimated. It is found that 33-39% of 2.5-5-times labor productivity gap (estimated for non-oil sector) between Russia and developed countries (US, Canada, Germany, Norway) is explained by lower capital-to-labor ratio and the latter 58-65% of the gap is due to lower technological level (multifactor productivity). Human capital level in Russia is almost the same as in developed countries, so it explains only 2-4% of labor productivity gap.

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 Kesenjangan Upah Antargender di Indonesia: Bukti Empiris di Sektor Manufaktur

2018 ◽  
pp. 1-21
Author(s):  
Martesa Husna Laili ◽  
Arie Damayanti
Keyword(s):  
Manufacturing Sector ◽  
Least Square ◽  
Seemingly Unrelated Regression ◽  
Wage Discrimination ◽  
Firm Level ◽  
Least Square Estimator ◽  
Exporting Firms ◽  
Unrelated Regression ◽  
Level Data ◽  
And Gender

Theoretically, in the labor market without discrimination, wages should be paid according to productivity. Unlike other studies that use worker level data, this study will identify gender wage discrimination using firm-level data. Using Industrial Survey Data in 1996 and 2006, the gender wage ratio and gender productivity ratio were estimated simultaneously using the nonlinear seemingly unrelated regression (NLSUR) with least square estimator. We find that there is wage discrimination against women in the manufacturing sector. After disaggregating the firms by trade orientation, we show that wage discrimination against women occurs in non-exporting firms. While in exporting firms there is no wage discrimination. ========================= Secara teori, di pasar kerja yang tidak ada diskriminasi, seharusnya upah dibayar sesuai dengan produktivitas. Berbeda dengan penelitian lain yang menggunakan data level pekerja, penelitian ini akan mengidentifikasi diskriminasi upah antargender dengan menggunakan data di level perusahaan. Dengan menggunakan data Industri Besar dan Sedang tahun 1996 dan 2006, rasio upah gender dan rasio produktivitas gender diestimasi secara simultan menggunakan metode non-linear seemingly unrelated regression (NLSUR) dengan estimator least square. Penelitian ini menemukan bukti ada diskriminasi upah terhadap perempuan di sektor manufaktur. Setelah mendisagregasi perusahaan berdasarkan status ekspor, diskriminasi upah terhadap perempuan ditemukan di perusahaan non-eksportir, sedangkan di perusahaan eksportir tidak ditemukan diskriminasi upah.

scholarly journals Factors Affecting Firm’s Annual Turnover in Selected Manufacturing Industries of India

2020 ◽  
Vol 2 (3) ◽  
pp. 33-59
Author(s):  
Ajay K. Singh ◽  
Bhim Jyoti
Keyword(s):  
Technology Transfer ◽  
Waste Management ◽  
Labor Productivity ◽  
Manufacturing Sector ◽  
Research Institutions ◽  
Skilled Workers ◽  
Factors Affecting ◽  
Quality Certification ◽  
Set Up ◽  
Annual Turnover

Purpose: This study makes a comparison of the manufacturing sector and its determinants for India and selected Asian countries. It examines the factors affecting the annual turnover of randomly selected 154 firms in seven different industries of the Indian manufacturing sector. Methods: In this study, the firm’s annual turnover is used as a dependent variable. Labor productivity, age, investment on plant & machinery, annual expenditure on marketing, total employees, production technology up-gradation, shortage of skilled workers, skills to improve the process, use of hi-tech tool and technique in production activities, technology transfer abilities, in-house R&D expertise, quality certification, foreign collaboration, waste management capabilities and building capacity of firms are used as independent variables. Regression coefficients of explanatory variables are assessed using linear, log-linear, and non-linear regression models. Results: The study concluded that the firm's annual turnover has a significant association with technological development related variables, labor productivity, age, technology transfer abilities, in-house R&D expertise, quality certification, and waste management practices of firms. Implications: It suggests that Indian policymakers need to adopt a strong IPRs, education, and S&T policy in research institutions. India needs to increase R&D expenditure and researchers in research institutions. Research institutions should collaborate with the existing industries to discover more technologies and innovations for the manufacturing sector. All research organizations must set up technology transfer offices to increase technology transfer and commercialization. Furthermore, India needs to set up hi-tech firms to face global challenges. Originality: It uses primary data of 154 firms which are collected from seven different industries across Indian states. Thus, the study substantially contributes to the existing literature.    Limitations: This study considers seven different industries that have high diversity in socio-economic, science & technological and IPRs related activities, technology transfer, commercialization of technology, and association with research institutions. Therefore, this study cannot provide policy suggestions for a specific industry.    

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