scholarly journals What's the big deal?: the effect of corporate reforms on manufacturing productivity in Korea

2005 ◽  
Author(s):  
◽  
Hojong Kang
Keyword(s):  
Productivity Growth ◽  
Plant Size ◽  
Factor Productivity ◽  
Data Set ◽  
Before And After ◽  
Interaction Term ◽  
Manufacturing Productivity ◽  
Plant Level ◽  
Positive Effect ◽  
Do So

Although Korea has achieved striking economic success during last four decades, following the 1997-98 foreign exchange crisis, Korea's economy was in urgent need of restructuring amid a series of corporate bankruptcies and a paralyzing credit crunch. In this paper using an unpublished plant-level panel data set, I explore changes in total factor productivity and its growth before and after the crisis. In order to do so, I sort out eight industries that were most likely affected by the "Big Deal Program". The results suggest the Big Deal had a positive and significant effect on TFP levels. Bigger plants in Big Deal industries had differentially higher TFP levels However, these results are not robust to the bigger plants classified as being in the top 5% in terms of K/L ratio. Unlike the results for TFP levels, coefficient for the three variable interaction term ( DiTt[arrow][tau] Spt ) are all positive and significant with the plant-size specification. It means the bigger plants in eight Big Deal industries have more productivity growth even though they have lower TFP levels than the smaller plants after the reform. Depending on the plant-size specifications, the Big Deal program had a positive effect on the bigger plants in the Big Deal industries of 0.1 to 1.39 percents.

scholarly journals The Decline of British Manufacturing, 1973–2012: The Role of Total Factor Productivity

2019 ◽  
Vol 247 ◽  
pp. R19-R31 ◽  
Author(s):  
Richard Harris ◽  
John Moffat
Keyword(s):  
Total Factor Productivity ◽  
Productivity Growth ◽  
Intangible Assets ◽  
Factor Productivity ◽  
Tfp Growth ◽  
Manufacturing Productivity ◽  
Plant Level

This paper uses plant-level estimates of total factor productivity covering 40 years to examine what role, if any, productivity has played in the decline of output share and employment in British manufacturing. The results show that TFP growth in British manufacturing was negative between 1973 and 1982, marginally positive between 1982 and 1994 and strongly positive between 1994 and 2012. Poor TFP performance therefore does not appear to be the main cause of the decline of UK manufacturing. Productivity growth decompositions show that, in the latter period, the largest contributions to TFP growth come from foreign-owned plants, industries that are heavily involved in trade, and industries with high levels of intangible assets.

Comparative analysis of efficiency and productivity growth in Canadian regional boreal logging industries

2003 ◽  
Vol 33 (9) ◽  
pp. 1653-1660 ◽  
Author(s):  
Atakelty Hailu ◽  
Terrence S Veeman
Keyword(s):  
Total Factor Productivity ◽  
Productivity Growth ◽  
Productive Efficiency ◽  
Set Covering ◽  
Data Envelopment Analysis Model ◽  
Factor Productivity ◽  
Data Set ◽  
Term Survival ◽  
Positive Effects ◽  
Logging Industry

The Canadian boreal logging industry has attracted little or no attention from economic researchers in spite of its importance for the competitiveness and long-term survival of other forest-based industries. This article uses a panel data set covering the period from 1977 to 1995 to analyze technical efficiency, technical change, and total factor productivity growth in the logging industries for six boreal provinces. The production technology is represented using a data envelopment analysis model. A transitive measure of productivity change that combines technical progress and changes in the degree of productive efficiency is computed. The empirical investigation reveals that logging activities in the boreal region are characterized by substantial efficiency differentials among the regions. Results from a Tobit analysis of efficiency differentials indicate that forest resource characteristics such as forest density and proportion of hardwood production were found to have positive effects. There was also evidence of significant positive scale effects. Engineering construction per area seems to be negatively related to efficiency. Total factor productivity in the boreal logging industry progressed at an average annual rate of 1.56%.

scholarly journals Total Factor Productivity Changes in Japanese Small and Medium-Sized Enterprises in 1982–2016: Suggestive Indications of an IT Revolution?

2020 ◽  
Vol 19 (3) ◽  
pp. 21-37
Author(s):  
Yoko Konishi ◽  
Takashi Saito
Keyword(s):  
Information And Communication Technology ◽  
Communication Technology ◽  
Productivity Growth ◽  
The United States ◽  
Factor Productivity ◽  
Japanese Firms ◽  
Technology Revolution ◽  
Before And After ◽  
Information And Communication ◽  
It Revolution

Since the information technology revolution in 2000, businesses worldwide have adopted information and communication technology (ICT) and big data. Recent studies attribute the origin of productivity growth in Europe and the United States to the depth of ICT utilization. We investigate whether that is the case in Japan. We measure the productivity of five manufacturing and eleven services industries in Japan and observe how it changed before and after 2000. Our results suggest that productivity increased for providers of ICT products but not for providers of ICT services. Moreover, productivity rose after 2000 in seven services industries that are users of ICT. Japanese firms are predominantly small and medium-sized and we conclude that the productivity findings for western countries are also observed for Japanese small and medium-sized enterprises.

scholarly journals Knowledge Spillover and R&D in Manufacturing Enterprises

2021 ◽  
Vol 3 (6) ◽  
Author(s):  
Ting Yang ◽  
Bing Gao ◽  
Kejin Xie
Keyword(s):  
Knowledge Spillovers ◽  
Spillover Effect ◽  
Manufacturing Industries ◽  
Significant Positive Effect ◽  
Factor Productivity ◽  
Manufacturing Enterprises ◽  
City Regions ◽  
The Mean ◽  
Interaction Term ◽  
Positive Effect

Based on the database of Chinese industrial industries, a model is constructed to empirically analyze the interaction between knowledge spillovers and R&D in manufacturing industries; the mean productivity values of county and city regions have a significant positive effect on firms' R&D, which gradually decreases; an interaction term between the number of neighboring firms and the average total factor productivity of industries in different regional scopes is added, and the greater the number of neighboring firms in the neighborhood, the greater the spillover effect on research and development. In order to increase the innovation input of companies, they need to be given the space to fully exchange ideas.

scholarly journals Productivity Dynamics and Rural Industrialization in India

2019 ◽  
Vol 32 (1) ◽  
pp. 23-46
Author(s):  
Takahiro Sato ◽  
Aradhna Aggarwal
Keyword(s):  
Panel Data ◽  
Total Factor Productivity ◽  
Productivity Growth ◽  
Rural Areas ◽  
Manufacturing Sector ◽  
Aggregate Productivity ◽  
Factor Productivity ◽  
Rural Industrialization ◽  
Plant Level ◽  
Productivity Dynamics

Since the late 1990s, industrialization in India has been driven by the rural organized manufacturing sector. This paper examines the effects of firms’ dynamics on rural industrialization in India, using plant-level panel data, to investigate the characteristics of rural industrialization in India in recent years. In particular, the paper focuses on productivity differences among continuing, entering, and exiting firms. The results show that both labour and total factor productivity of the organized manufacturing sector in rural areas increased during 2000–2006 and the aggregate productivity growth is supported by the productivity growth of the continuing firms, the entry of productive firms, and the exit of less-productive firms. The paper can conclude that firms’ productivity dynamics contributed to the current rural industrialization in India. JEL: O14, O47, O53

scholarly journals Total Factor Productivity Growth in Pakistan: An Analysis of the Agricultural and Manufacturing Sectors

2009 ◽  
Vol 14 (Special Edition) ◽  
pp. 1-16 ◽  
Author(s):  
Azam Amjad Chaudhry
Keyword(s):  
Total Factor Productivity ◽  
Productivity Growth ◽  
Average Rate ◽  
Output Growth ◽  
Production Functions ◽  
Gdp Growth ◽  
Factor Productivity ◽  
Manufacturing Sectors ◽  
Manufacturing Productivity ◽  
East Asian Economies

This paper uses Cobb-Douglas and translog production functions to calculate total factor productivity (TFP) in Pakistan over the period 1985 – 2005, first for the manufacturing and agricultural sectors individually, then for the economy as a whole. In manufacturing, productivity increased at an average of 2.4% per year with output growth being driven mainly by increases in capital. Despite the limitations of the available agricultural data, we have determined that productivity has grown at an average rate of 1.75% per year in this sector. The major drivers of growth in agriculture have been increases in labor and TFP. These estimates of sectoral TFP put Pakistan at par or above average as compared to other developing countries, but lagging behind the East Asian economies. For the economy as a whole, TFP has increased at an average rate of only 1.1% a year in Pakistan, resulting in almost three quarters of GDP growth attributed to increases in labor and the capital stock.

scholarly journals Competition, selection, and productivity growth in the Chilean manufacturing industry

2020 ◽  
Vol 29 (3) ◽  
pp. 877-892
Author(s):  
Roberto Álvarez ◽  
Aldo Gonzalez
Keyword(s):  
Productivity Growth ◽  
Manufacturing Industry ◽  
Factor Productivity ◽  
Manufacturing Plants ◽  
Tfp Growth ◽  
Key Driver ◽  
Quantitative Impact ◽  
The Impact ◽  
Firm Selection ◽  
Positive Effect

Abstract Competition is considered as a key driver of productivity growth. However, the empirical evidence on its impact is scant in developing countries. Using information from manufacturing plants for the period 1995–2007, we analyze the impact of competition on firm selection and productivity growth in Chile. Our results indicate that competition has a positive effect on total factor productivity (TFP) growth, especially for laggard firms. We find weaker evidence that competition affects the probability of exit for low-productivity firms. In general, these results for productivity growth are robust to alternative methodologies for calculating productivity and to the inclusion of other variables that may affect firms’ TFP growth. We find support for Schumpeterian forces, but the quantitative impact is small.

scholarly journals Capital Obsolescence and Agricultural Productivity*

2020 ◽  
Vol 136 (1) ◽  
pp. 505-561
Author(s):  
Julieta Caunedo ◽  
Elisa Keller
Keyword(s):  
Labor Productivity ◽  
Productivity Growth ◽  
Agricultural Labor ◽  
Data Set ◽  
Agricultural Labor Productivity ◽  
Country Differences ◽  
Cross Country ◽  
Rich Countries ◽  
Price Differences ◽  
Do So

Abstract This article argues that accounting for capital-embodied technology greatly increases the importance of capital in explaining cross-country differences in agricultural labor productivity. To do so, we draw on a novel data set of agricultural capital prices. We document that new capital is more expensive in richer countries, both in absolute terms and relative to old capital. A model of endogenous adoption of capital of different quality links these price differences to the path of capital-embodied technology. In particular, our model recovers the level of embodied technology from the price of new capital and the growth rate of embodied technology from the price of new capital relative to old capital. We then measure the stocks of quality-adjusted capital in agriculture for a sample of 16 countries at different stages of development. We find that adjusting for differences in quality almost doubles the importance of capital in accounting for cross-country differences in agricultural labor productivity: from 21% to 37%. In addition, improvements in capital quality have been an important source of agricultural labor productivity growth over the past 25 years, accounting for 21% and 35% of the productivity growth in poor and rich countries, respectively.

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