دانلود مقاله ISI انگلیسی شماره 11763
ترجمه فارسی عنوان مقاله

مطالعات نظری و تجربی رشد بهره وری در اقتصاد کشاورزی - موارد چین و ایالات متحده

عنوان انگلیسی
Theoretical and Empirical Studies of Productivity Growth in the Agricultural Economics –– Cases of China and the United States
کد مقاله سال انتشار تعداد صفحات مقاله انگلیسی
11763 2012 7 صفحه PDF
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Physics Procedia, Volume 24, Part B, 2012, Pages 1475–1481

ترجمه کلمات کلیدی
اقتصاد جهانی - شاخص بهره وری ملکوئیست - بهینه سازی برنامه ریزی خطی - طبقه بندی تابع فاصله
کلمات کلیدی انگلیسی
World economy,Malmquist productivity index,Linear programming optimization,Distance function JEL Classifications
پیش نمایش مقاله
پیش نمایش مقاله  مطالعات نظری و تجربی رشد بهره وری در اقتصاد کشاورزی - موارد چین و ایالات متحده

چکیده انگلیسی

This article investigates agricultural productivity growth over several decades, emphasizing to a great extent the agricultural economic development condition for the nine agricultural divisions of the United States, and China's 27 provinces in terms of Malmquist productivity growth index. The paper sets up a technique to make use of two-stage linear programming method, based on sequential production technology, to estimate the most fitted and reliable distance functions in relevant agricultural sectors, and thus to compute the Malmquist productivity indexes. Especially, it proposes to decompose the productivity growth index into two major components, technical progress and efficiency improvement, and their sub-components, to study the sources of growth in productivity.

مقدمه انگلیسی

For several decades, the global agriculture experiences a persistent and rapid decline, to the most obvious contrary to the performances of other economic sectors that exhibits continuously fast development in recent years, the productivity growth of the agricultural sector, however, speeds relatively slow. Among them, the possible main reasons include increasingly resource scarcity, limited technological innovation,environmental degradation, and insufficient agricultural policy support. This article uses the linear programming technique to calculate the Malmquist productivity indexes based on the built-up technical frontiers, in order to investigate the total factor productivity growth of the two main greatest agricultural countries, China and the US, through several decades of years, and especially the function of their sub-components, technical efficiency and technological innovation, that increase the productivity, which in turn serves a reference basis as to raise the agricultural productivity and efficiency in the future.Traditional agricultural productivity researches rely heavily on productivity index approaches, such as those of Fisher, Tornqvist, that are incapable of disaggregating the total effect of agricultural productivity into changes in performance and changes in technology. Because these approaches mask some important factors that determine the measurement of productivity change over time. Besides,traditional techniques usually presume that production is always efficient. However, different from the traditional indexing procedures, Malmquist index with distance functions requires neither of the use of input prices nor that of output prices in its construction. This study examines the agricultural Malmquist productivity index using distance functions in estimating the total factor productivity. This approach allows for the decomposition of productivity growth into changes in technical efficiency over time (or catching-up) and shifts in technology over time(or technical change). Besides, it does not require presumption that production is always efficient.Furthermore, a non-parametric linear programming introduces in the second stage admits inefficient performances in technology.

نتیجه گیری انگلیسی

This paper examines the agricultural productivity growth of the two greatest agricultural countries in the world, the US and China, through several decades. In the study, it makes use of two-stage linear programming methods to estimate distance functions, and thus in turn to calculate Malmquist productivity indexes. In the programming, a sequential technique is conducted to define production sets, which have a desirable feature of smoothness and differentiability, proved to be the most reasonable and reliable method in estimating distance functions.According to our analysis, the US in general exhibits a positive growth in agricultural productivity over the examining time of 1960 to 1996. Although a decomposition analysis indicates that agricultural productivity growth in the US has been declining from 1960s to 1980s, their components of technological change contribute over 75% of the total productivity growth in each period of the four decades.On the other hand, agricultural productivity growth of China speeds relatively slow at an average rate of 0.11% in recent 30 years, far below an average of 3.5% growth rate in the US for a comparable time period, although the whole country’s economy develops rapidly in the same time. Moreover, of the less than 1% productivity growth, the scale efficiency predominantly accounts for more than 100% of the total factor productivity growth in the overall agricultural output value, which implicates the effect of technical efficiency contributable to productivity growth is degrading. Such result is a remarkable contrast to that of the US evidence.Finally, according to the study, State SD leads continuously the productivity technology of crop production during the reported time of four decades.However, few provinces in China exhibit a prevailing advantage in taking a lead of the country's agricultural productivity in the past 30 years.