​​Estimation of Total Factor Productivity Growth of Major Pulse Crops in Rajasthan, India

Author(s):  
Devendra Kumar Verma ◽  
Hari Singh ◽  
S.S. Burark ◽  
Jitendra Suman ◽  
Priyanka Lal

Background: Pulses, supplemented with cereals, provide a perfect mix of vegetarian protein of high biological value. The productivity of pulses in India is less than half of the productivity levels in the USA and Canada. Present investigation was aimed to Total Factor Productivity (TFP) growth in three pulse crops in the state of Rajasthan from 2000-01 to 2017-18. Methods: In the current study, the Tornqvist Theil Index was used to compute the total output index, total input index and total factor productivity index. The Tornqvist Index is exact for the homogenous translog production function that can deliver a second order approximation to an arbitrary twice differentiable homogenous production function. The translog function does not require perfect substitutes for inputs. If the relative price of input increases, the producer decreases its use (substituting other inputs) until all marginal productivities are proportional to the new prices. Result: The results of this study has indicates low TFP in Gram (0.98%) despite a 59.23 per cent share in the total pulse output of the state. The annual compound growth rate of TFP of black gram increased at the rate of 1.11 per cent per annum (moderate growth) and the contribution of TFP to output growth was low; at about 41.63. Whereas, the compound growth rate of TFP of annual green gram crop increased at the 2.38 per cent per annum (high growth) while its TFP to output growth was about 66.43 per cent. The real cost of production of gram, black gram and green gram crop increased by 0.77, 1.49 and 1.57 per cent per annum, respectively.

Cereal crops provide essential nutrients and energy in the everyday human diet through direct human consumption and meat production since they comprise a major livestock feed. In the current study, the Tornqvist Theil Index was used to compute the total output index, total input index, and total factor productivity index. The Tornqvist Index is exact for the homogenous translog production function that can deliver a second-order approximation to an arbitrary twice differentiable homogenous production function. This study has indicated moderate TFP in wheat (1.45percent), and the contribution of TFP to output growth was high, about 87 percent for wheat in Rajasthan state. The annual compound growth rate of the TFP of barley increased at the rate of 1.65 percent per annum (moderate growth), and the contribution of TFP to output growth was average, at about 63.47. In comparison, the compound growth rate of TFP of annual maize crop increased at 1.80 percent per annum (moderate growth), while its TFP to output growth was about 73.09 percent. The annual compound growth rate of the TFP of bajra increased by 2.56 percent per year. The contribution of TFP to output growth was 61.29 percent for bajra in Rajasthan. The real cost of production of barley and maize increased by 0.88 and 1.59 percent, which decreased for wheat and bajra by -0.93 and -0.21 percent per annum, respectively. It was revealed that in the bajra crop, Rajasthan state showed good performance of TFP growth among the selected cereal crops. The technology, including agronomical practices, plant protection measures, and mechanization, helped to sustain TFP growth in the bajra crop.


Author(s):  
Jorge Benzaquen

Purpose The purpose of this paper is to propose and analyze a model to obtain a total factor productivity of an industry through quantitative empirical analysis in order to determine the joint contribution of the production and technology function, and the change and technical progress. The case of the Peruvian large shipbuilding industry between the years 1969 and 1990 was considered for the analysis of the proposed model. The large shipbuilding in Peru finished in 1992 and has restarted in 2014. The importance of the study lies in the fact that the analysis is focused on an industry which is resurfacing, and in this regards, the study of the first production period will yield more and accurate information to make decisions regarding its future development. Design/methodology/approach One way of considering the several effects of technical progress, in line with Sato (1970) such as growth and bias, is to specify a production function maintaining the linear homogeneity property, such as: Y(t)=F [A(t)K(t), B(t)L(t)], where Y(t) is the aggregate product over a period of time (t); K(t) is the capital; L(t) is the labor; and A(t) and B(t) are the efficiencies or augmentations of K(t) and L(t), respectively. Based on the regression analysis data, the value of σ can be estimated to a residual growth rate (Kennedy and Thirlwall, 1972) that allows assessing the technical knowledge that is not attributable to the factors’ efficiency grains: TCTR = T ˙ / T − ( α ( A ˙ / A ) + β ( B ˙ / B ) ) . This last expression measures the residual technological growth rate (TCTR, by its Spanish acronym). Findings The results of the analysis of the large shipbuilding at SIMA-Callao during the given period (22 years of operation, between 1969 and 1990) show that the necessary installed capacity and the technological knowledge was available in order to develop a complex industrial process in the South Pacific region, thus, contributing to the sector’s growth in the country. The evolution of the shipbuilding activities coincides with the GDP expansion and decline periods in Peru. According to the results, the total factor productivity increased during 1969-1976, 1979-1982, and 1986-1987 periods and it has been confirmed that the contribution of the efficiencies of the production factors were inversely related to the economies of scale and output growth. Practical implications The analysis is based on the activities carried out throughout 22 years of operations in SIMA-Callao shipyards (1969-1990). The data regarding the product, labor, imported materials costs, local material costs, direct expenses, wages, and man-day costs was obtained from several sources within the shipyard. Direct expenses correspond to classification, inspections, administrative expenses (dock, quality control, equipment rental, etc.), drawings, technical data, insurance, and materials freight. Additionally, the sources of information are project construction contracts, annual expenses reports, and man-day cost quarterly reports of the shipbuilding area. The man-day cost includes salary, social benefits, and the company’s functional cost. Originality/value There are different ways to obtain productivity index. In this case, the authors used the stated model. In addition, based on this experience, this can be applied to other industries.


2021 ◽  
Author(s):  
Mateus C. R. Neves ◽  
Felipe De Figueiredo Silva ◽  
Carlos Otávio Freitas

In this working paper, we estimate agricultural total factor productivity (Ag TFP) for South American countries over the period 19692016 and identify how road density affect technical efficiency. In 2015, Colombia, Peru, Venezuela, Ecuador, and Bolivia, the Andean countries, had 205,000; 166,000; 96,000; 89,000; and 43,000 kilometers of roads, respectively. A poor-quality and limited road network, along with inaccessibility to markets, might limit the ability of farms to efficiently manage production inputs, raising technical inefficiency. We find that the Ag TFP growth rate per year for South American countries, on average, is 1.5%. For the Andean countries, we find an even smaller growth rate per year of 1.4% on average. Our findings suggest that higher road density is associated with lower technical inefficiency.


Agro Ekonomi ◽  
2016 ◽  
Vol 24 (2) ◽  
pp. 2
Author(s):  
Sri Widodo

The total factor productivity became an interesting concept in the measurement of productivity growth. Productivity is a ratio of output to input. The most common measurement of productivity is single factor productivity or partial productivity such as of land, labor, or capital.A total (factor) productivity is a productivity of all factors of production where the factors are aggregated. In cross-sectional studies this total productivity is a ratio of actual to potential output where the potential output is estimated from ther frontier production function. One of the methods to estimate this frontier function is by using linear programming technique.The total productivity does not always coincide with a single factor productivity of land (yield), that in the study area the larger farms tend to have higher total productivity than yield


2016 ◽  
Vol 21 (Special Edition) ◽  
pp. 33-63 ◽  
Author(s):  
Rashid Amjad ◽  
Namra Awais

This paper reviews Pakistan’s productivity performance over the last 35 years (1980–2015) and identifies factors that help explain the declining trend in labor productivity and total factor productivity (TFP), both of which could have served as major drivers of productivity growth – as happened in East Asia and more recently in India. A key finding is that the maximum TFP gains and their contribution to economic growth are realized during periods of high-output growth. The lack of sustained growth and low and declining levels of investment appear to be the most important causes of the low contribution of TFP to productivity growth, which has now reached levels that should be of major concern to policymakers vis-à-vis Pakistan’s growth prospects.


Author(s):  
Rakesh Kumar ◽  
B.C. Sharma ◽  
Neetu Sharma ◽  
Brij Nanadan ◽  
Akhil Verma ◽  
...  

Background: Maize-wheat is the predominant cropping system of dryland ecology of Jammu region, but due to their comparatively higher input requirements especially of nutrients and water under the fragile ecology of these dry lands an untenable threat has been posed to their factor productivities. Therefore, all cropping sequences that suit and sustain better on the natural resources of the dryland ecosystems for a longer period of time needs to be explored.Methods: The treatments consisted of two oilseeds i.e. mustard) and gobhi sarson and two pulse crops i.e. chickpea and field pea taken during rabi were followed by two oilseed i.e. soybean and sesame and two pulse crops i.e. green gram and black gram grown during kharif. The experiment was laid out in randomized block design with four replications.Result: Significantly higher chickpea equivalent yield of green gram was observed with field pea- green gram sequence (10.26 q/ha) which was at par with the chickpea – green gram and field pea - black gram system. The available nitrogen status was significantly influenced and recorded highest (166.82kg/ha) under field pea- green gram system. Further overall nutrient mining by this system was quite low as compared to other systems.


2011 ◽  
Vol 16 (2) ◽  
pp. 184-203 ◽  
Author(s):  
Alessio Moro

In this paper I show that the intensity at which intermediate goods are used in the production process affects aggregate total factor productivity (TFP). To do this, I construct an input–output model economy in which firms produce gross output by means of a production function in capital, labor, and intermediate goods. This production function is subject, together with the standard neutral technical change, to intermediates-biased technical change. Positive (negative) intermediates-biased technical change implies a decline (increase) in the elasticity of gross output with respect to intermediate goods. In equilibrium, this elasticity appears as an explicit part of TFP in the value added aggregate production function. In particular, when the elasticity of gross output with respect to intermediates increases, aggregate TFP declines. I use the model to quantify the impact of intermediates-biased technical change for measured TFP growth in Italy. The exercise shows that intermediates-biased technical change can account for the productivity slowdown observed in Italy from 1994 to 2004.


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