scholarly journals Measuring Productivity Change in U.S. Agriculture

1975 ◽  
Vol 7 (2) ◽  
pp. 69-75 ◽  
Author(s):  
Yao-Chi Lu
Keyword(s):  
Public Policy ◽  
Total Factor Productivity ◽  
Productivity Growth ◽  
Agricultural Production ◽  
Functional Form ◽  
Productivity Index ◽  
Productivity Change ◽  
Factor Productivity ◽  
Index Numbers ◽  
Increase Productivity

To understand the sources of change in productivity, that appropriate public policy and programs can be developed to increase productivity growth, a reliable and updated measure is needed. The term “productivity” discussed here refers to total factor productivity, or the ratio of value of total agricultural output to that of all inputs used in agricultural production.The first comprehensive work on the measurement of productivity change in U.S. agriculture was done by Loomis and Barton in 1961. Since then, this index has been updated annually as an offical USDA agricultural productivity index. The weakness of using index numbers lies in the arithmetic formula used. It implies a specific functional form of the production function that may not accurately describe the data. Thus, a need arises to consider an alternative estimate of productivity.

scholarly journals Total Factor Productivity Growth of Indian General Insurance Companies in the Recent Period: A Bootstrapped Approach

2019 ◽  
Vol 11 (1-2) ◽  
pp. 59-80
Author(s):  
Ram Pratap Sinha
Keyword(s):  
Private Sector ◽  
Total Factor Productivity ◽  
Productivity Growth ◽  
Malmquist Index ◽  
American Economic Review ◽  
Productivity Index ◽  
Insurance Companies ◽  
Productivity Change ◽  
Productivity Analysis ◽  
Factor Productivity

This study estimates Malmquist index of total factor productivity change of 14 major general insurers in India over the period 2009–10 to 2016–17 over 7 annual windows. The study decomposes total factor productivity index into its constituent components, using several approaches including Färe et al. (1989, Productivity Developments in Swedish Hospitals: A Malmquist Output Index Approach. Carbondale: Department of Economics, Southern Illinois University; 1992, Journal of Productivity Analysis 3(1): 85–101), Färe et al. (1994, American Economic Review 84(1): 66–83), Ray and Desli (1997, American Economic Review 87(5): 1033–39) and Wheelock and Wilson (1999, Journal of Money, Credit and Banking 31(2): 212–23). Furthermore, the study uses bootstrap data envelopment analysis (DEA) method to obtain bias-corrected point and interval estimates of Malmquist index and its components. Finally, the study makes a comparison of productivity performance between public and private sector insurers. The results indicate a modest growth in total factor productivity during the period contributed mainly by efficiency changes. The private sector insurers performed better than the public sector in terms of productivity growth. The variations in productivity performance indicate that insurer scale of activity can affect their performance. JEL Classification: G-23, C-61, D-21

scholarly journals Non-parametric decomposition of total factor productivity growth in yam production in North-Central Nigeria

2021 ◽  
pp. 91-98
Author(s):  
R.G. Isonguyo ◽  
M.A Ojo ◽  
A.J. Jirgi ◽  
E.S. Yisa
Keyword(s):  
Total Factor Productivity ◽  
Productivity Growth ◽  
Data Bank ◽  
Productivity Index ◽  
Productivity Change ◽  
Regression Result ◽  
Factor Productivity ◽  
Tobit Regression ◽  
North Central ◽  
Non Parametric

Abstract. Non-parametric analysis of total factor productivity change in yam production in North-Central Nigeria from 1992 to 2016 was carried out with the use of secondary data. The secondary production data of yam for that period were collected from Food and Agriculture Statistical (FAOSTAT) data bank. Malmquist Total Factor Productivity Index (MTFPI) based on Data Envelopment Analysis (DEA), was used to empirically analyse the total factor productivity of the yam, while Tobit regression was used to analyse the determinants of total factor productivity in the study area. The results of the MTFPI analysis reveal that yam contributed 1.4% of technical efficiency change to productivity growth over the period studied. The technological contributions to productivity growth regressed at 1.8%. The study revealed the productivity growth of yam to be 0.2%. Tobit regression result showed credit borrowed, government policy (Agricultural Transformation Agenda – ATA), capital, and labour to have significant and positive relationships with the productivity of the crop at either p≤0.05 or p≤0.001 level of probability, which implies that increase in them led to increase in the crop’s productivity. Capital-labour was statistically significant but negatively related to yam productivity at p≤0.01, which implied that utilization of labour in a greater proportion than capital led to reduction or regress in its productivity growth. The study recommends farmers’ training on farm practices and techniques to increase yam productivity. They should be encouraged to accept improved yam varieties from research institutes, properly allocate the production resources and adopt improved technology to achieve productivity growth in the study area.

scholarly journals A Dual Challenge in China’s Sustainable Total Factor Productivity Growth

2020 ◽  
Vol 12 (13) ◽  
pp. 5342
Author(s):  
Shaohua Zhang ◽  
Tzu-Pu Chang ◽  
Li-Chuan Liao
Keyword(s):  
Total Factor Productivity ◽  
Productivity Growth ◽  
Industrial Structure ◽  
Critical Issue ◽  
Sustainable Growth ◽  
Total Factor Productivity Growth ◽  
Productivity Index ◽  
Productivity Change ◽  
Factor Productivity ◽  
The Government

Since total factor productivity growth plays an essential role in China’s economic growth, the source of this growth has been a critical issue over the past decades. Hence, this paper applies an input slack-based productivity (ISP) index to investigate the contributors (i.e., labor and capital inputs) to China’s total factor productivity growth. The ISP index, combining the features of the directional distance function and Luenberger productivity index, can calculate the productivity change of each input factor under the total factor framework. According to the decomposition analyses, we find that China is confronting a dual challenge in total factor productivity growth: first, capital productivity growth exhibits a remarkable slowdown after the mid-1990s; second, although labor productivity continually expands, the relative labor efficiency among provinces has deteriorated since the 2000s. The results imply that the government should not only advocate upgrading industrial structure, but also consider balanced regional development policies for China’s sustainable growth.

scholarly journals Industry Efficiency and Total Factor Productivity Growth under Resources and Environmental Constraint in China

2012 ◽  
Vol 2012 ◽  
pp. 1-10 ◽  
Author(s):  
Feng Tao ◽  
Ling Li ◽  
X. H. Xia
Keyword(s):  
Energy Consumption ◽  
Total Factor Productivity ◽  
Environmental Efficiency ◽  
Pollutant Emissions ◽  
Productivity Index ◽  
Productivity Change ◽  
Factor Productivity ◽  
Energy And Environment ◽  
Capital Labor Ratio ◽  
Investment Capital

The growth of China's industry has been seriously depending on energy and environment. This paper attempts to apply the directional distance function and the Luenberger productivity index to measure the environmental efficiency, environmental total factor productivity, and its components at the level of subindustry in China over the period from 1999 to 2009 while considering energy consumption and emission of pollutants. This paper also empirically examines the determinants of efficiency and productivity change. The major findings are as follows. Firstly, the main sources of environmental inefficiency of China's industry are the inefficiency of gross industrial output value, the excessive energy consumption, and pollutant emissions. Secondly, the highest growth rate of environmental total factor productivity among the three industrial categories is manufacturing, followed by mining, and production and supply of electricity, gas, and water. Thirdly, foreign direct investment, capital-labor ratio, ownership structure, energy consumption structure, and environmental regulation have varying degrees of effects on the environmental efficiency and environmental total factor productivity.

scholarly journals Productivity Change of Microfinance Institutions in Bosnia and Herzegovina

2019 ◽  
Vol 14 (2) ◽  
pp. 23-33
Author(s):  
Velid Efendić ◽  
Nejra Hadžiahmetović
Keyword(s):  
Total Factor Productivity ◽  
Bosnia And Herzegovina ◽  
Malmquist Productivity Index ◽  
Productivity Index ◽  
Productivity Change ◽  
Microfinance Institutions ◽  
Factor Productivity ◽  
Strategic Objectives ◽  
Average Decrease ◽  
Recent Financial Crisis

Abstract The main aim of this paper is to investigate the productivity changes of microfinance institutions (MFIs) in Bosnia and Herzegovina (BiH) during and after the recent financial crisis. The study covers the period starting from 2008 until 2015. Using the Malmquist Productivity Index (MPI) over the sample of 10 MFIs and a balanced panel dataset of 80 observations, this study explores technical and technological change as well as total factor productivity (TFP) change. The empirical findings indicate a decline in TFP in most of the analyzed periods with an average decrease of 2.5%. The study reveals an average technological decline in the industry of 1.7%, while technical efficiency change is recorded at the level of -0.8%. Overall, crisis efficiency recovery occurred during the period between 2009 and 2013. However, due to technological inefficiencies, average total factor productivity change remains negative. Hence, policy makers need to enhance the technological progress in order to meet their strategic objectives in BiH MFIs.

AGRICULTURAL TOTAL FACTOR PRODUCTIVITY CHANGES IN THE NEW AND THE OLD EUROPEAN UNION MEMBERS

2015 ◽  
Author(s):  
Tomasz KIJEK ◽  
Anna NOWAK ◽  
Armand KASZTELAN ◽  
Artur KRUKOWSKI
Keyword(s):  
European Union ◽  
Technical Efficiency ◽  
Total Factor Productivity ◽  
Productivity Growth ◽  
Malmquist Productivity Index ◽  
Productivity Index ◽  
Factor Productivity ◽  
Technological Changes ◽  
Total Productivity ◽  
The Eu

The aim of this study was the evaluation of agricultural total factor productivity changes between new member countries which have acceded to EU after 2004 and so-called ‘old 15’ EU members. The analysis covered the years 2007–2013. The study is based on Malmquist productivity index divided into technological change and changes in technical efficiency. The results showed a slight increase in the agricultural total factor productivity in the EU countries in the years 2007–2013 (0.1 %, which mainly resulted from a slight increase in technical efficiency in agriculture(0.4 % ), while at the same time adverse technological changes. Among all the countries of the ‘old 15’, only Denmark, the Netherlands, Finland, United Kingdom and Sweden reported increased index of productivity. In the group of countries that joined the EU after 2004, the total productivity growth took place in such countries as Bulgaria, Cyprus, Czech Republic, Malta, Slovakia and Hungary. The reason for this increase was primarily changes in technical efficiency.

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