2 edition of Sources of variation in agricultural productivity found in the catalog.
Sources of variation in agricultural productivity
Sudhin K. Mukhopadhyay
|Statement||Sudhin K. Mukhopadhyay.|
|LC Classifications||HD2072 .M84|
|The Physical Object|
|Pagination||xii, 121 p. ;|
|Number of Pages||121|
|LC Control Number||76902965|
estimate agricultural productivity. o Identify research gaps and make recommendations. 3. Agricultural productivity in South Africa Historical overview Total agricultural productivity The trend of agricultural productivity in South Africa is traced back from Productivity Growth in World Agriculture: Sources and Constraints Vernon W. Ruttan P rior to the beginning of the twentieth century, almost all increases in crop and animal production occurred as a result of increases in the area cultivated. By the end of the century, almost all increases were coming.
Some sources of agricultural productivity are: Mechanization; High yield varieties, which were the basis of the Green revolution; Fertilizers: Primary plant nutrients: nitrogen, phosphorus and potassium and secondary nutrients such as sulfur, zinc, copper, manganese, calcium, magnesium and molybdenum on deficient soil; Education in management and entrepreneurial techniques to decrease fixed. The analysis of sources of variations in the level of agri cultural productivity require application of statistical methods. In thin roil \ ox 1 Hi in i)r ()\) Hun)u\i) b n agricultural productivity and a host of its social, economic and physical correlates.
It found that agriculture and food consumption are two of the most important drivers of environmental pressures, particularly habitat change, climate change, water use and toxic emissions. Agriculture is the main source of toxins released into the environment, including insecticides, especially those (—) European Union: The significant variation in pieces collected in Figure 1 is also noteworthy, as this is critical for obtaining precise estimates of the impact of ozone. Figures 2 and and3 3 further illustrate this variation both within and across workers. For Figure 2, we collapse the data to the worker level by computing each worker's mean daily productivity over by:
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The data sets are used to estimate and explain state level productivity and efficiency differences, and to test different approaches to productivity measurement.
The rise in agricultural productivity is the single most important source of economic growth in the U.S. farm sector, and the rate of productivity growth is estimated to be higher in agriculture than in the non-farm : Hardcover.
Sources of variation in agricultural productivity: a cross section time-series study in India. Agricultural Productivity: Measurement and Sources of Growth addresses measurement issues and techniques in agricultural productivity analysis, applying those techniques to recently published data sets for American agriculture.
The data sets are used to estimate and explain state level productivity and efficiency differences, and to test different approaches to productivity measurement. predicts the maximum attainable yields for each crop in a given area. Potential yields are a source of exogenous variation in agricultural productivity because they are a function of weather and soil characteristics, not of actual yields in Brazil.
In addition, the database reports potential yields under traditional and new agricultural. In this book we assemble a range of evidence from a range of sources with a view to developing an improved understanding of recent trends in agricultural productivity around the world. The fundamental purpose is to better understand the nature of the long-term growth in the supply of food and its principal determinants.
We pursue this purpose from two by: Advances in agricultural productivity have led to abundant and affordable food and fiber throughout most of the developed world. Public and private agricultural research has been the foundation and basis for much of this growth and development.
ERS data, research, and analyses quantify agricultural productivity improvements and the sources of improvement, in the U.S.
and. In the sample selected villages of the study area is more variation in the adoption of improved agricultural practices to ascertain level of agricultural development, the spatial variation is Author: Ankush Barakade.
Agricultural productivity change is explained by many factors. According to Hussain and Perera, () these factors include: Land and water related factors (such as farm/water course location, quality of land, sources of water, quality and quantity of water and timing of water application, etc.), Climatic factors (i.e.
rainfall, temperature, sunshine, frost, etc.), Agronomic factors such as. industry competitors. Productivity is quite lit-erally a matter of survival for businesses. How Micro-Level Productivity Variation and Persistence Has Influenced Research The discovery of ubiquitous, large, and per - sistent productivity differences has shaped research agendas in a number of fields.
Here are some examples of this influence. Low productivity in Indian agriculture may be attributed to low volume of governmental investment compared to the industrial sector. In the First Plan (), investment in the agricultural sector stood at 31 p.c. It declined gradually to 19 p.c.
by the Ninth Plan Period ( ). The data sets are used to estimate and explain state level productivity and efficiency differences, and to test different approaches to productivity measurement. The rise in agricultural productivity is the single most important source of economic growth in the U.S.
farm sector, and the rate of productivity growth is estimated to be higher in agriculture than in the non-farm sector. The results confirm that at the national level, technology (higher yield) was the main source of crop income growth during s, while rising prices and diversification emerged as the dominant sources of growth in agriculture during s.
Assessing and quantifying the sources of agricultural productivity across developing countries is the prime objective of the paper. 31 low and lower middle income countries from the Asian and. Agricultural Investment, Production Capacity and Productivity Lydia Zepeda.
This chapter provides an overview of current economic thinking on some aspects of agricultural investment and productivity, especially in the context of developing countries.
Abstract. This paper examines the contributions of public agricultural research, extension, and highway infrastructure to agricultural productivity of regions composed of Cited by: The Shifting Patterns of Agricultural Production and Productivity Worldwide Edited by Julian M.
Alston, Bruce A. Babcock, and Philip G. Pardey In this book we assemble a range of evidence from a range of sources with a view to developing an improved understanding of recent trends in agricultural productivity around the world. One conclusion based on the book’s research findings derives from the substantial spatial variation in agricultural productivity.
For areas with similar agricultural productivity growth trends and factors, what works well in one area can be used as the basis for formulating best-fit, location-specific agricultural policies, investments, and Manufacturer: International Food Policy Research Institute.
This paper explores the effects of agricultural productivity shocks on structural change. We exploit the invention of hybrid corn seed as an exogenous source of variation in US agricultural productivity. The technology significantly increased land productivity in counties suited to producing corn.
the agriculture patterns. The study attempted to measure the model of Coefficient of agricultural productivity in order to identify the pattern for spatial distribution of the productivity in 22 Municipalities in Libya. The coefficient of agricultural productivity is successful to determine the contrast that will be used when comparingFile Size: KB.
To identify the causal effects of the change in agricultural productivity brought by the new technology, we use two sources of exogenous variation in the profitability of technology adoption.
First, as the technology was invented and commercially introduced in the. Emissions on Agricultural Productivity and Household Welfare in Ethiopia induced variation in agricultural total factor productivity for the period – The simulation results indicate that CO 2 emissions negatively affect agricultural productivity and household Size: KB.Brazil as our source of cross-sectional variation in agricultural productivity.
Note that this empirical strategy relies on the assumption that goods can move across geographical areas of Brazil, but labor markets are local due to limited labor mobil-ity.
This research design allows us to investigate whether exogenous shocks to local.the sources of variation in agricultural productivity, defined as the aver-age value of crop output per hectare of arable land, in Rajasthan's 26 districts. (A district in India is an important political and administrative unit below the state level and over villages and tahsils.