Two sides, but not of the same coin: digitalization, productivity and unemployment

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Oxana Krutova ◽  
Pertti Koistinen ◽  
Tuuli Turja ◽  
Harri Melin ◽  
Tuomo Särkikoski
Keyword(s):  
Total Factor Productivity ◽  
Job Loss ◽  
Labour Productivity ◽  
Research Problem ◽  
Quality Of Work Life ◽  
Macro Level ◽  
Factor Productivity ◽  
Content Type ◽  
Technological Unemployment ◽  
Factors Of Production

PurposeThis paper aims to examine how input from the digital restructuring of the workplace and productivity affects the risk of job loss and unemployment.Design/methodology/approachRelying on the concepts of technological unemployment and the productivity paradox as well as the theory of skills-biased technological change, the analysis incorporated micro-level individual determinants of job loss, macro-level economic determinants of input and the contribution from traditional (machinery and equipment) vs innovative (ICT) factors of production. The model has been also controlled for “traditional” indicators of “outsiderness” in the labour market. The Quality of Work Life Survey, which is a broad-based national interview survey produced by Statistics Finland, for 2018, the latest year available (N = 4,110) has been used in the analysis. Binomial logistic regression has been applied in order to estimate the effects of individual- and macro-level factors on the risk of job loss.FindingsThe results support arguments for the divergence between effects from labour- vs total-factor productivity on the risks of job loss, as well as the divergence between effects for temporary (layoff) vs permanent job loss (dismissal or unemployment). While the contribution from “traditional” factors of production to labour productivity potentially decreases the risk of permanent job loss, input from “innovative” factors of production on total-factor productivity potentially causes adverse effects (e.g. growing risks of permanent job loss).Originality/valueThe paper contributes to the theoretical discussion about technological unemployment and productivity by means of including two different concepts into a single econometric model, thus enabling examination of the research problem in an innovative way.

Does foreign direct investment spillover total factor productivity growth? A study of Indian drugs and pharmaceutical industry

2017 ◽  
Vol 24 (7) ◽  
pp. 1937-1955 ◽  
Author(s):  
Nitin Arora ◽  
Preeti Lohani
Keyword(s):  
Foreign Direct Investment ◽  
Pharmaceutical Industry ◽  
Total Factor Productivity ◽  
Direct Investment ◽  
Spillover Effect ◽  
Foreign Firms ◽  
Factor Productivity ◽  
Content Type ◽  
Domestic Firms ◽  
Tfp Growth

Purpose Foreign firms have certain advantages which may spillover to domestic firms in the form of improvements in total factor productivity (TFP) growth. The purpose of this paper is to empirically observe the presence of TFP spillovers of foreign direct investment (FDI) to domestic firms through analyzing source of TFP growth in Indian drugs and pharmaceutical industry. Design/methodology/approach This paper examines the sources of TFP spillovers of FDI in Indian drugs and pharmaceutical industry over the period 1999 to 2014. The data of 304 firms has been used for estimation of the growth rates of TFP and its sources under stochastic frontier analyses based Malmquist productivity index framework. For frontier estimation, the Wang and Ho (2010) model has been executed using translog form of production function. Findings The results show that there exists significant TFP spillover effect from the presence of foreign equity in drugs and pharmaceutical industry of India. The results also show that the major source of TFP fluctuations in the said industry is managerial efficiency that has been significantly affected by FDI spillover variables. In sum, the phenomenon of significant Intra-industry (horizontal) efficiency led productivity spillovers of FDI found valid in case of Indian drugs and pharmaceutical industry. Research limitations/implications The number of foreign firms is very less to imitate the significant impact of foreign investment on TFP growth of Indian pharmaceutical industry at aggregated level; and the Wang and Ho (2010) model is failing to capture direct impact of FDI on technological change under Malmquist framework. Practical implications Since, there exists dominance of domestic firms in Indian drugs and pharmaceutical industry, the planners should follow the policy which not only attract FDI but also benefit domestic firms; for example, developing modern infrastructure and institution which will further help domestic firms to absorb spillovers provided by the Multinational Corporations and also accelerate the growth and development of the economy. Social implications In no case, the foreign firms should dominate the market share otherwise the efficiency spillover effect will be negative and the domestic firms will be destroyed under the self-centric approach of foreign firms protected by the recent patent laws. Originality/value The study is a unique attempt to discuss the production structure and sources of TFP spillovers of FDI in Indian drugs and pharmaceutical industry with such a wide coverage of 304 firms over a period of 16 years under Wang and Ho (2010) model’s framework. The existing studies on TFP spillovers are using either a small sample size of firms or based upon traditional techniques of measuring spillover effects.

Silk Road Economic Belt strategy and industrial total-factor productivity

2019 ◽  
Vol 30 (1) ◽  
pp. 260-282 ◽  
Author(s):  
Jian Feng ◽  
Lingdi Zhao ◽  
Huanyu Jia ◽  
Shuangyu Shao
Keyword(s):  
Sustainable Development ◽  
Total Factor Productivity ◽  
Causal Effect ◽  
Silk Road ◽  
Factor Productivity ◽  
Positive Role ◽  
Content Type ◽  
Silk Road Economic Belt ◽  
The Difference

Purpose The purpose of this paper is to assess the effectiveness of the Silk Road Economic Belt (SREB) strategy and its role of industrial productivity in China. Design/methodology/approach To identify the causal effect of this strategy on industrial sustainable development, the authors first use the slacks-based measure model to calculate industries’ total-factor productivity (TFP) considered with CO2 emissions as undesirable output on the provincial level. Then, the authors use the PSM-DID method to identify the difference of TFPs between provinces and industries before and after the implementation of SREB strategy. Findings However, the authors find that there is no difference or even a relative decrease in TFPs of industries in target provinces after the implementation of the strategy, which reveals that the SREB strategy does not play a positive role of the industries’ sustainable development in years of 2014 and 2015. Originality/value The value of this result is to identify the short-term impact of SREB strategy and to seek for probable causes and appropriate solutions.

scholarly journals An Empirical Note on Productivity and Technological Diffusion in Nigeria, 1970-2000

2003 ◽  
Vol 15 (1) ◽  
Author(s):  
Ndem A. Ndiyo
Keyword(s):  
Total Factor Productivity ◽  
Productivity Growth ◽  
Technological Development ◽  
Knowledge Diffusion ◽  
Technological Knowledge ◽  
Technological Diffusion ◽  
Developing Economy ◽  
Factor Productivity ◽  
Empirical Note ◽  
Factors Of Production

The study analyses the longterm trend in knowledge diffusion and productivity growth in Nigeria, using a translog specification. The results indicate the need for technological upgrading and emphasized that policies designed to promote technological development should address the complementarities between ‘different factors of production. The article, thus, provides some support for the argument that total factor productivity (TFP), as a technological knowledge, can impact significantly on productivity in a developing economy like Nigeria.

scholarly journals Macroeconomic Dynamics of the Total Factor Productivity of the Russian Economy

2021 ◽  
Vol 17 (3) ◽  
pp. 799-813
Author(s):  
Sergey A. Mitsek
Keyword(s):  
Total Factor Productivity ◽  
Public Investment ◽  
Labour Productivity ◽  
Aggregate Demand ◽  
Factor Productivity ◽  
Export Prices ◽  
Russian Economy ◽  
Economic Trends ◽  
Total Productivity ◽  
Economic Growth Rates

The growth rate of Russia’s total productivity has been slowing down significantly since 2008. The majority of relevant publications either describe an economic methodology or specifically focus on labour productivity. However, economic growth rates, as well as community welfare, largely depend on total factor productivity. The paper aims to determine the reasons for the slowdown in the growth of total factor productivity after 2008. This negative dynamics was assessed using a macroeconomic econometric model and estimates for Russian regions and types of economic activity. Elasticity of dependent variables was calculated based on econometric equations as well as multipliers of exogenous variables presented in the model. Ordinary and rank correlations between the variables were also examined. The calculations revealed that the stagnation of total factor productivity was caused by the misallocation of resources across industries and regions, de crease in aggregate demand, increase in capital goods prices (primarily due to rouble devaluation) and a slowdown in digital economy development. In turn, these trends were influenced by a decline in public investment and export prices, as well as a slowdown in population growth and liquidity. Simultaneously, growth of the world economy contributed to the demand for Russian export goods, preventing a decrease in productivity. The findings can be used for forecasting Russian economic trends and developing relevant policy measures. Further research will examine the role of human capital, energy intensity, climate and institutional factors in increasing the total productivity.

Growth of Factor Inputs and Total Factor Productivity in Indian Public Sector Enterprises

1977 ◽  
Vol 2 (2) ◽  
pp. 121-133
Author(s):  
Bakul H. Dholakia
Keyword(s):  
Public Sector ◽  
Total Factor Productivity ◽  
Factor Productivity ◽  
The Public ◽  
Indian Economy ◽  
Factors Of Production ◽  
Factor Inputs ◽  
Better Than

The public sector undertakings in India have come under heavy criticism for inefficient management and low profitability. In view of the importance these undertakings command in the Indian economy, the author has done a detailed study of the productivity and efficiency of factors of production, and has concluded that the undertakings have, on the whole, performed better than the economy.

Resource misallocation of SMEs in Vietnamese manufacturing sector

2019 ◽  
Vol 26 (3) ◽  
pp. 290-303
Author(s):  
Phuong Thi Nguyen ◽  
Minh Khac Nguyen
Keyword(s):  
Developing Countries ◽  
Total Factor Productivity ◽  
Design Methodology ◽  
Large Scale ◽  
Manufacturing Sector ◽  
Factor Productivity ◽  
Content Type ◽  
Resource Misallocation ◽  
Productivity Decomposition ◽  
Enterprise Survey

Purpose The purpose of this paper is to examine resource misallocation among Vietnam’s small- and medium-sized enterprises (SMEs) in the manufacturing sector. The paper also aims to consider selective factors on reducing the level of resource misallocation in SMEs. Design/methodology/approach Resource misallocation and efficiency gains in total factor productivity (TFP) are assessed using Vietnam’s annual enterprise survey data for the period 2000–2015 and an appropriate productivity decomposition framework. Findings Resource misallocation is found to be higher among SMEs than large scale enterprises. TFP is found to 116.3 per cent greater if there is no resource misallocation among SMEs. Smaller scale, lower market concentration, trade liberalisation and corruption control are found to be associated with lower level of resource misallocation in SMEs. Research limitations/implications The major limitation of this study is that it has only decomposed misallocation of resources arising from output and capital distortions and that it focusses on selective factors contribution to reducing misallocation level in SMEs. Originality/value Resource misallocation is attracting attention in both developed and developing countries. However, knowledge about resource misallocation among SMEs is limited, particularly in the context of developing countries. This paper assesses the level of resource misallocation among SMEs in Vietnamese manufacturing sector.

Assessing the impact of knowledge management on total factor productivity

2019 ◽  
Vol 11 (1) ◽  
pp. 134-146 ◽  
Author(s):  
Mina Sami ◽  
Randa El Bedawy
Keyword(s):  
Knowledge Management ◽  
Total Factor Productivity ◽  
Current Literature ◽  
Organizational Level ◽  
Factor Productivity ◽  
Data Set ◽  
Content Type ◽  
Financial Indicator ◽  
Percent Increase ◽  
The Impact

Purpose The purpose of this paper is to examine the impact of knowledge management (KM) on the total factor productivity (TFP) at the organizational level in Egypt. Design/methodology/approach Using the novel available EC 2013 data set, which includes approximately 60,000 private organizations in Egypt, the paper explores the relationship between KM and TFP. For the purpose of dealing with endogeneity, the two-stage least squares econometric model has been implemented. Findings The study reveals that KM impacts positively the TFP of the Egyptian organizations. Conspicuously, each 10 percent increase in KM is associated with 9.3 percent increase in TFP. Originality/value The role of KM in the organizations has been under-researched globally, especially in Africa. This study contributes to the current literature by assessing the impact of KM on TFP, which represents the most comprehensive measure of the firm productivity; by implementing a novel instrumental variable in order to deal with endogeneity between KM and TFP; and by generating a more nuanced measure for the knowledge intensity that is not based on any financial indicator as in the most of the previous studies. Original findings can be highlighted from the paper as it demonstrates that the impact of KM is more important than proposed by the current literature. Conspicuously, the KM does not merely impact the customer satisfaction, the quality improvement and the profit margin, but it also impacts the TFP of the organizations.

Raising workers' quality is key to global productivity

2017 ◽  
Keyword(s):  
Total Factor Productivity ◽  
Computer Technology ◽  
Factor Productivity ◽  
Content Type ◽  
Information And Computer Technology ◽  
The 1960S ◽  
Investment Growth ◽  
Ageing Populations

Subject Total factor productivity. Significance The first estimates in the 1960s suggested that the growth of labour and capital inputs accounted for 20-30% of economic growth, implying that total factor productivity (TFP) improvements accounted for the remaining 70-80%. However, the skills embodied in labour and the technology embodied in capital can now be measured much more accurately. After these contributions are subtracted, the role of TFP in growth is reduced. Impacts Improvement in the quality of capital is closely tied to rising investment in capital, especially information and computer technology. If investment growth continues to slow, this will affect future output both through the volume of capital as well as its productive quality. Ageing populations and persistent ultra-low rates raise ‘secular stagnation’ fears; the future will depend on a better-educated workforce.

scholarly journals DOES ICT CAPITAL AFFECT ECONOMIC GROWTH IN THE EU-15 AND EU-12 COUNTRIES?

2014 ◽  
Vol 16 (2) ◽  
pp. 387-406 ◽  
Author(s):  
Jana Hanclova ◽  
Petr Doucek ◽  
Jakub Fischer ◽  
Kristyna Vltavska
Keyword(s):  
Economic Growth ◽  
Total Factor Productivity ◽  
Least Squares Method ◽  
Labour Productivity ◽  
The European Union ◽  
Factor Productivity ◽  
Average Growth ◽  
Capital Growth ◽  
Capital Services ◽  
The Eu

The paper examines economic growth in old and new member countries of the European Union (EU-15 and EU-12) during the years of 1994–2000 and 2001–2008 mainly due to changes in information and communication technology (ICT) capital development. The first group EU-15 is presented by old EU countries and the second group EU-12 is presented by new member countries that joined the EU in 2004–2007. The threefactor Cobb-Douglas production function is estimated through the panel general least squares method. The input factors that might influence the economic growth are labour, ICT capital services and non-ICT capital services. Since ICT capital growth data are not available for all selected economies, the groups of countries were reduced to EU-14 and EU-7. The estimated panel production functions confirmed that the average growth of GDP in the EU-7 countries was supported by the stable growth of labour quantity and ICT-capital and increasing total factor productivity. A short-term drop in non-ICT capital growth with follow-up stagnation was caused rather by lower labour productivity. The research discovered that the drop in GDP growth in the EU-14 countries was a result of the slower growth of non-ICT capital and total factor productivity and the stagnated growth of ICT capital with low elasticity, and showed that even the compensation of growth in labour quality did not prevent a decrease in total factor productivity and economic growth.

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