Productivity growth, technical efficiency, and technical change in China’s soybean production

2011 ◽  
Vol 6 (25) ◽  
Author(s):  
Wei SI
Keyword(s):  
Technical Efficiency ◽  
Productivity Growth ◽  
Technical Change ◽  
Soybean Production

PRODUCTIVITY GROWTH, TECHNICAL EFFICIENCY, AND RETURNS TO SCALE IN THE WASHINGTON STATE SAWMILL INDUSTRY

2005 ◽  
Vol 04 (03) ◽  
pp. 477-490 ◽  
Author(s):  
TED L. HELVOIGT ◽  
SHAWNA GROSSKOPF
Keyword(s):  
Technical Efficiency ◽  
Productivity Growth ◽  
Technical Change ◽  
Returns To Scale ◽  
Washington State ◽  
Productivity Index ◽  
Scale Efficiency ◽  
Data Envelopment ◽  
Sawmill Industry ◽  
Annual Decline

We employed data envelopment analysis (DEA) to examine the technical and scale efficiency of the sawmill industry of Washington State. We found that there is regional variation in the rate of technical efficiency and that for most years the industry in aggregate operated at a point of modest scale inefficiency. In addition, we examined the industry's rate of productivity growth and technical change between the early 1970s and late 1990s using the Malmquist input-oriented productivity index. We found that the industry experienced a modest average annual decline in productivity and technical change during the 1970s, but experienced strong productivity growth and technical change during the 1980s and 1990s.

Impact of Determinants of Industrial Development on Employment and Wages in Indian Manufacturing

2020 ◽  
pp. 18-30
Keyword(s):  
Technical Efficiency ◽  
Total Factor Productivity ◽  
Technical Change ◽  
Positive Impact ◽  
Manufacturing Sector ◽  
Factor Productivity ◽  
Firm Level ◽  
Employment Level ◽  
The Impact ◽  
Level Performance

ABSTRACT The present study was undertaken to explore the evolution of the impact of firm-level performance on employment level and wages in the Indian organized manufacturing sector over the period 1989-90 to 2013-14. One of the major components of the economic reform package was the deregulation and de-licensing in the Indian organized manufacturing sector. The impact of firm-level performance on employment and wages were estimated for Indian organized manufacturing sector in major sub-sectors in India during the period from 1989-90 to 2013-14 of the various variables namely profitability ratio, total factor productivity change, technical change, technical efficiency, openness (export-import), investment intensity, raw material intensity and FECI in total factor productivity index, technical efficiency, and technical change. The study exhibited that all explanatory variables except profitability ratio and technical change cost had a positive impact on the employment level. Out of eight variables, four variables such as net of foreign equity capital, investment intensity, TFPCH, and technical efficiency change showed a positive impact on wages and salary ratio and rest of the four variables such as openness intensity, technology acquisition index, profitability ratio, and technical change had negative impact on wages and salary ratio. In this context, the profit ratio should be distributed as per the marginal rule of economics such as the marginal productivity of labour and capital.

Productivity growth of Indonesian rice production: sources and efforts to improve performance

2018 ◽  
Vol 67 (9) ◽  
pp. 1792-1815 ◽  
Author(s):  
Joko Mariyono
Keyword(s):  
Technological Change ◽  
Technical Efficiency ◽  
Production Technology ◽  
Productivity Growth ◽  
Scale Effects ◽  
Allocative Efficiency ◽  
Rice Production ◽  
Content Type ◽  
Tfp Growth ◽  
Efficiency Effects

PurposeThe purpose of this paper is to investigate the productivity of rice production by decomposing the growth of total factor productivity (TFP) into four components: technological change, scale effects, technical and allocative efficiencies.Design/methodology/approachThis study employed an econometric approach to decompose TFP growth into four components: technological change, technical efficiency, allocative efficiency and scale effect. Unbalanced panel data used in this study were surveyed in 1994, 2004 and 2014 from 360 rice farming operations. The model used the stochastic frontier transcendental logarithm production technology to estimate the technology parameters.FindingsThe results indicate that the primary sources of TFP growth were technological change and allocative efficiency effects. The contribution of technical efficiency was low because it grew sluggishly.Research limitations/implicationsThis study has several shortcomings, such as very lowR2and the insignificant elasticity of labour presented in the findings. Another limitation is the limited time period panel covering long interval, which resulted in unbalanced data.Practical implicationsThe government should improve productivity growth by allocating more areas for rice production, which enhances the scale and efficiency effects and adjusting the use of capital and material inputs. Extension services should be strengthened to provide farmers with training on improved agronomic technologies. This action will enhance technical efficiency performance and lead to technological progress.Social implicationsAs Indonesian population is still growing at a significant rate and the fact that rice is the primary staple food for Indonesian people, the productivity of rice production should increase continually to ensure social security at a national level.Originality/valueThe productivity growth is decomposed into four components using the transcendental logarithm production technology based on farm-level data. The measure has not been conducted previously in Indonesia, even in rice-producing countries.

scholarly journals Technical Efficiency and Productivity Growth of Polish Crop Farms

2019 ◽  
Vol 298 (2) ◽  
pp. 95-125
Author(s):  
Jerzy Marzec ◽  
Andrzej Pisulewski ◽  
Artur Prędki
Keyword(s):  
Technical Efficiency ◽  
Productivity Growth ◽  
Efficiency And Productivity

scholarly journals Adoption of Improved Soybean Varieties and Differences in Technical Efficiency Between Improved and Local Soybean Varieties in Southern Shan State, Myanmar

2020 ◽  
Vol 12 (8) ◽  
pp. 55
Author(s):  
Ei Thazin Soe ◽  
Yoshifumi Takahashi ◽  
Mitsuyasu Yabe
Keyword(s):  
Technical Efficiency ◽  
Production Efficiency ◽  
Market Access ◽  
Study Data ◽  
Stochastic Production Frontier ◽  
Soybean Production ◽  
Government Organizations ◽  
Factors Influencing ◽  
Multi Stage ◽  
And Training

This study determined the factors influencing the adoption of improved soybean varieties and examined the technical efficiencies of improved and local soybean varieties production in Southern Shan State, Myanmar. For this study, data from a sample of 337 respondents were collected by employing a multi-stage random sampling method. Logit model was adopted to determine the factors influencing the adoption of improved soybean varieties. Additionally, a stochastic production frontier was used to examine technical efficiencies of improved and local soybean varieties. Results show that factors that positively and significantly influence the adoption of improved soybean varieties are education, market access, extension access and training access. Examination of technical efficiency reveals that labor, fertilizer, machinery, and use of pesticide and harvester are inputs that significantly contribute to improving production efficiency among the improved variety farmers while seeds, labor, and fertilizer are significant inputs of local soybean production. On average, the estimated yield of the improved soybean varieties is 1.51 t/ha, which is higher than the yield of local soybean varieties grown at 0.88 t/ha. It was also revealed that improved soybean varieties had a relatively higher level of mean technical efficiency (85.04%) than local varieties (70.13%) and significantly different at 1% level. The results show that improved soybean production is more efficient than local soybean production. Therefore, government and non-government organizations should improve and provide market access, efficient and effective extension services and training to encourage farmers to adopt improved soybean varieties.

Investment, Profitability, and Structural Change

2021 ◽  
pp. 113-130
Author(s):  
John Weiss ◽  
Hossein Jalilian
Keyword(s):  
Structural Change ◽  
Productivity Growth ◽  
Technical Change ◽  
Technological Advance ◽  
Historical Overview ◽  
Resource Reallocation ◽  
Dynamic Economy ◽  
And Shifts ◽  
Productivity Gains ◽  
Investment Choices

This chapter explores the links between profitability, investment, and structural change. This is examined for the case of India, using both a historical overview and regression analysis. In a Kaldorian dynamic economy, the reallocation of investment provides the driver for resource reallocation, allowing more productive and profitable activities to expand and less productive and less profitable activities to contract. Thus, investment choices drive structural change, productivity growth, technological advance, and ultimately profits. Investment in turn responds to expected profits, which are driven by technical change, related productivity gains, and shifts in demand. The relationships are thus circular and cumulative, with this chapter testing for the presence of such relationships.

Inventive Activity in the British Textile Industry, 1700–1800

1992 ◽  
Vol 52 (4) ◽  
pp. 881-906 ◽  
Author(s):  
Trevor Griffiths ◽  
Philip A. Hunt ◽  
Patrick K. O'Brien
Keyword(s):  
Eighteenth Century ◽  
Total Factor Productivity ◽  
Productivity Growth ◽  
Technical Change ◽  
Consumer Goods ◽  
Textile Industry ◽  
Industrial Development ◽  
Industrial Revolution ◽  
Factor Productivity ◽  
Inventive Activity

An analysis of innovations in the eighteenth-century British textile industry is the basis for an evaluation of aggregate studies of invention during the Industrial Revolution, derived from patent evidence alone. Disaggregation of the data challenges recent generalizations concerning the pace and pattern of technical change over the period. Discontinuities in the nature of invention, promoting an acceleration in total factor productivity growth, are traced to the 1790s. Prior to that date, industrial development conformed to a pattern of Smithian growth, as manufacturers diversified their output in response to an expanding domestic market for consumer goods.

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