This document summarizes a study that estimated technical efficiency in Ghana's agricultural sector from 1976-2007 and investigated factors that influence the estimates. The key findings were:
1) Ghana's agriculture exhibited decreasing returns to scale and overuse of land relative to other inputs like fertilizer and machinery.
2) Technical efficiency in Ghana's agriculture was estimated to be 79%, meaning there is a 21% gap between actual and potential output.
3) None of the hypothesized variables tested (e.g. education, infrastructure) were found to statistically explain the technical efficiency estimates.
Technical efficiency in agriculture in ghana analyses of determining factorsAlexander Decker
This document summarizes a journal article that estimates technical efficiency in Ghana's agricultural sector from 1976-2007 and investigates factors that influence the estimated efficiencies. The study finds decreasing returns to scale and that land is negatively related to output while fertilizer and machinery are positively related. The estimated level of inefficiency is 21% with decreasing returns to scale. No hypothesized variables for explaining technical efficiency were found to be statistically significant. The study calls for decreasing land use relative to other inputs to improve efficiency.
Analysis of food crop output volatility in agricultural policy programme regi...Alexander Decker
The document analyzes food crop output volatility in Nigeria under different agricultural policy programs from 1961 to 2009. It finds that the Pre-Operation Feed the Nation period (1961-1976) and Structural Adjustment Programme period (1986-1993) exhibited the highest volatility for most crops, while the Operation Feed the Nation period (1976-1979) and Green Revolution period (1980-1985) showed the most stable outputs. The mean outputs generally increased across policy periods since 1961 and were highest during the Post Structural Adjustment period (1994-2009). Statistical analysis confirms that the policy programs influenced crop outputs and their volatilities, though the impacts varied inconsistently across crops and regimes. The study recommends formulating specific crop policy packages as
Farmer's Agribusiness Training Course: Module 1 Lesson 3 Supplementary Readin...PiLNAfrica
The objectives of this paper are threefold: (1) to assess the direction and magnitude of changes in agricultural productivity in Kenya in the last 25 years for five of the most important agricultural provinces in Kenya, with particular focus on the period since the initiation of agricultural policy adjustment in the 1990s; (2) to identify the major factors affecting changes in crop productivity; and (3) to identify cost-effective strategies likely to promote future agricultural intensification and productivity growth in Kenya's crop sector in the post-reform period.
Case Study to Investigate the Adoption of Precision Agriculture in Nigeria Us...Premier Publishers
This study investigated the adoption of precision farming (PF) technology with research into the possible implementation of the technology for increased productivity in a maize plantation in Nigeria. The research understands the nature of the challenges and highlights the possibility of implementing PF technology to Nigerian Agriculture. The methodology uses simple image analysis with fuzzy classification to determine the degree of spatial and temporal variability of the field to develop a treatment plan for an equally fertile and fully productive yield. The results showed that implementing precision agriculture (PA) will yield high productivity with the aid of remote sensing to obtain an aerial view of the farm. Simple PA technologies, such as using the information to determine and test soil nutrient availability to enable land preparation to obtain a uniform field, can help make the managerial decision on the farm efficiently. There is a great chance to optimize production on the field, minimise input resources, cost and maximising profit while preserving the natural environment. By using machine vision technology with fuzzy logic for decision making, not only the shape, size, colour, and texture of objects can be recognised but also numerical attributes of the objects or scene being imaged.
This document is the preface and table of contents for the "Pocket Book of Agricultural Statistics 2014" published by the Government of India's Ministry of Agriculture. It provides an overview of the publication, which contains statistical tables on key indicators related to Indian agriculture. These include socio-economic data, government outlays and expenditures, labor and poverty statistics, agricultural land use, production and yields of major crops and horticulture, livestock, inputs and costs, prices and procurement, consumption, international comparisons, and agricultural emissions. The preface notes that additional useful data from other sources have been included in this edition.
Status of Agricultural Food Sector: Basis for A Proposed Continuity PlanIJAEMSJORNAL
This study described the status of agriculture in the province of Nueva Ecija. It determined the current situation of the farming business in Nueva Ecija in terms of agricultural land use, its statistical profile on agriculture, crops grown by cities and municipalities and the presence of support agencies in maintaining the continuous development of farming and other forms of agriculture therein. Based on its agriculture profile, land, mostly irrigated shares the biggest portion in terms of its usage for food production. Rice, corn, onion and tomatoes are the major crops being grown in cities and municipalities. Findings revealed that rice and corn share the biggest in domestic consumption. For support agencies, bank and business agencies are found in support for farmers while the government mostly provides seminars. It was also revealed that other seeds for crops are introduced as a farmer’s option and lesser in choosing for an investment in their income. As their contingency plan, farmers opt to sell and engage in driving rather than farming during lean months. Pest attacks constitute the main problem encountered by farmers, while seeding management is a priority. The above findings point to certain sustainability that requires improvement and a continuity plan to match up with the continuous supply of goods from the farms to the demands of an increasing population for its consumption.
1) The document discusses the impact of economic reforms on the growth of agriculture in India. It notes that while agriculture's share of GDP has declined since the 1950s, it still accounts for around 14% of GDP and provides over 50% of employment.
2) It summarizes the 12th Five Year Plan's goal of 4% annual agricultural growth. It also outlines various strategies proposed to boost agricultural output, such as improving water management, promoting animal husbandry and fisheries, and increasing access to credit.
3) The document analyzes factors that have both positively and negatively impacted agricultural growth. Higher GDP growth and globalization helped increase public investment and credit to agriculture. However, structural issues around land and water
China's agricultural sector has grown significantly over the past 30 years, with agricultural GDP growing 4-5 times the population growth rate. Institutional reforms, investments in agricultural technology, and market liberalization policies have driven this growth. However, China still faces challenges regarding small farm sizes, rural labor mobility, and improving its agricultural research and extension systems to better serve farmers. Future prospects include growing imports of land-intensive goods and exports of labor-intensive products as China's agriculture continues integrating with global markets.
Technical efficiency in agriculture in ghana analyses of determining factorsAlexander Decker
This document summarizes a journal article that estimates technical efficiency in Ghana's agricultural sector from 1976-2007 and investigates factors that influence the estimated efficiencies. The study finds decreasing returns to scale and that land is negatively related to output while fertilizer and machinery are positively related. The estimated level of inefficiency is 21% with decreasing returns to scale. No hypothesized variables for explaining technical efficiency were found to be statistically significant. The study calls for decreasing land use relative to other inputs to improve efficiency.
Analysis of food crop output volatility in agricultural policy programme regi...Alexander Decker
The document analyzes food crop output volatility in Nigeria under different agricultural policy programs from 1961 to 2009. It finds that the Pre-Operation Feed the Nation period (1961-1976) and Structural Adjustment Programme period (1986-1993) exhibited the highest volatility for most crops, while the Operation Feed the Nation period (1976-1979) and Green Revolution period (1980-1985) showed the most stable outputs. The mean outputs generally increased across policy periods since 1961 and were highest during the Post Structural Adjustment period (1994-2009). Statistical analysis confirms that the policy programs influenced crop outputs and their volatilities, though the impacts varied inconsistently across crops and regimes. The study recommends formulating specific crop policy packages as
Farmer's Agribusiness Training Course: Module 1 Lesson 3 Supplementary Readin...PiLNAfrica
The objectives of this paper are threefold: (1) to assess the direction and magnitude of changes in agricultural productivity in Kenya in the last 25 years for five of the most important agricultural provinces in Kenya, with particular focus on the period since the initiation of agricultural policy adjustment in the 1990s; (2) to identify the major factors affecting changes in crop productivity; and (3) to identify cost-effective strategies likely to promote future agricultural intensification and productivity growth in Kenya's crop sector in the post-reform period.
Case Study to Investigate the Adoption of Precision Agriculture in Nigeria Us...Premier Publishers
This study investigated the adoption of precision farming (PF) technology with research into the possible implementation of the technology for increased productivity in a maize plantation in Nigeria. The research understands the nature of the challenges and highlights the possibility of implementing PF technology to Nigerian Agriculture. The methodology uses simple image analysis with fuzzy classification to determine the degree of spatial and temporal variability of the field to develop a treatment plan for an equally fertile and fully productive yield. The results showed that implementing precision agriculture (PA) will yield high productivity with the aid of remote sensing to obtain an aerial view of the farm. Simple PA technologies, such as using the information to determine and test soil nutrient availability to enable land preparation to obtain a uniform field, can help make the managerial decision on the farm efficiently. There is a great chance to optimize production on the field, minimise input resources, cost and maximising profit while preserving the natural environment. By using machine vision technology with fuzzy logic for decision making, not only the shape, size, colour, and texture of objects can be recognised but also numerical attributes of the objects or scene being imaged.
This document is the preface and table of contents for the "Pocket Book of Agricultural Statistics 2014" published by the Government of India's Ministry of Agriculture. It provides an overview of the publication, which contains statistical tables on key indicators related to Indian agriculture. These include socio-economic data, government outlays and expenditures, labor and poverty statistics, agricultural land use, production and yields of major crops and horticulture, livestock, inputs and costs, prices and procurement, consumption, international comparisons, and agricultural emissions. The preface notes that additional useful data from other sources have been included in this edition.
Status of Agricultural Food Sector: Basis for A Proposed Continuity PlanIJAEMSJORNAL
This study described the status of agriculture in the province of Nueva Ecija. It determined the current situation of the farming business in Nueva Ecija in terms of agricultural land use, its statistical profile on agriculture, crops grown by cities and municipalities and the presence of support agencies in maintaining the continuous development of farming and other forms of agriculture therein. Based on its agriculture profile, land, mostly irrigated shares the biggest portion in terms of its usage for food production. Rice, corn, onion and tomatoes are the major crops being grown in cities and municipalities. Findings revealed that rice and corn share the biggest in domestic consumption. For support agencies, bank and business agencies are found in support for farmers while the government mostly provides seminars. It was also revealed that other seeds for crops are introduced as a farmer’s option and lesser in choosing for an investment in their income. As their contingency plan, farmers opt to sell and engage in driving rather than farming during lean months. Pest attacks constitute the main problem encountered by farmers, while seeding management is a priority. The above findings point to certain sustainability that requires improvement and a continuity plan to match up with the continuous supply of goods from the farms to the demands of an increasing population for its consumption.
1) The document discusses the impact of economic reforms on the growth of agriculture in India. It notes that while agriculture's share of GDP has declined since the 1950s, it still accounts for around 14% of GDP and provides over 50% of employment.
2) It summarizes the 12th Five Year Plan's goal of 4% annual agricultural growth. It also outlines various strategies proposed to boost agricultural output, such as improving water management, promoting animal husbandry and fisheries, and increasing access to credit.
3) The document analyzes factors that have both positively and negatively impacted agricultural growth. Higher GDP growth and globalization helped increase public investment and credit to agriculture. However, structural issues around land and water
China's agricultural sector has grown significantly over the past 30 years, with agricultural GDP growing 4-5 times the population growth rate. Institutional reforms, investments in agricultural technology, and market liberalization policies have driven this growth. However, China still faces challenges regarding small farm sizes, rural labor mobility, and improving its agricultural research and extension systems to better serve farmers. Future prospects include growing imports of land-intensive goods and exports of labor-intensive products as China's agriculture continues integrating with global markets.
This document discusses trends in high-value agriculture in India. It notes a shift from grains to higher-value commodities like fruits, vegetables, dairy and meat due to rising incomes, urbanization, and trade policies. Exports of high-value products like fruits and vegetables have grown significantly. Contract farming has allowed small farmers to access high-value domestic and export markets. Overall high-value agriculture provides opportunities for commercialization and income growth for smallholders through arrangements like contract farming. The document analyzes crop area and production data and makes recommendations to promote diversification and infrastructure to support high-value agriculture.
The document analyzes the growth and instability of foodgrain production in Odisha, India over a 20-year period from 1995-1996 to 2014-2015 at the state and district level. It finds that while total foodgrain production experienced no growth in the first decade, the second decade saw impressive growth for all crops, especially other cereals which grew at 7.7% annually. At the district level, most districts also saw higher growth rates for paddy, other cereals, pulses and total foodgrains in the second decade compared to the first. However, some districts still experienced negative or low growth for certain crops. The study also found that instability or risk in foodgrain production decreased at the state level in the second
Technical efficiency of rural women farmers in borno state, nigeria.Alexander Decker
This document summarizes a study that examined the technical efficiency of rural women farmers in Borno State, Nigeria. Key findings include:
1) Rural women farmers in the study area had high levels of illiteracy (59.4%), did not belong to cooperatives (89.8%), had little contact with agricultural extension services (72%), and low access to credit (89.4%).
2) The mean technical efficiency of respondents was 0.5754, while the most efficient farmer achieved a technical efficiency of 0.9994.
3) Factors found to reduce technical inefficiency (and thus increase efficiency) included higher education levels, more off-farm income, more time spent farming, older
Effects of Rice Liberalization Law on Rice Production, Farmers’ Wages and Gov...IJAEMSJORNAL
- The document analyzes the effects of the Rice Liberalization Law on rice production, farmers' wages, and government budgets in Nueva Ecija, Philippines.
- Quantitative analysis using time series data from 2010-2019 finds that government budgets have a significant positive effect on rice production, while low production negatively impacts farmers' wages and income.
- The study aims to determine if liberalizing rice trade through the Rice Liberalization Law significantly impacted the current rice market situation in Nueva Ecija.
Technical efficiency of cowpea production in osun state, nigeriaAlexander Decker
- The study analyzed the technical efficiency of 200 cowpea farmers in Osun State, Nigeria using a
stochastic production frontier function.
- The results found the mean technical efficiency level was 66%, indicating room for improvement.
- Age, household size, and farming experience reduced technical inefficiency, while gender and education
increased inefficiency.
- The findings suggest cowpea farmers could increase output with existing inputs and technology by improving
their technical efficiency.
11.technical efficiency of cowpea production in osun state, nigeriaAlexander Decker
This document analyzes the technical efficiency of cowpea farmers in Osun State, Nigeria. It finds that the mean technical efficiency level was 66%, meaning on average farmers were producing 66% of potential output. Factors like age, household size, and farming experience reduced technical inefficiency, while gender and education increased inefficiency. The study concludes there is room for improving efficiency to boost cowpea output through better use of available resources.
This document summarizes the key topics and findings from the book "Agricultural Transformation in Nepal: Trends, Prospects and Policy Options". It discusses Nepal's agricultural sector challenges including lower and fluctuating growth, declining productivity, and rising imports. However, it also notes prospects like shifting diets driving demand, commercialization, and emerging value chains. The way forward involves ensuring food security through technology adoption, increasing public and private investment, promoting diversification, and developing domestic and regional value chains. Strengthening infrastructure, quality standards, contract farming and trade opportunities can help realize the agriculture sector's potential.
Agricultural productivity growth and incidence of povertyAlexander Decker
This study analyzed agricultural productivity growth and poverty in Africa from 1971-2009 using Malmquist Total Factor Productivity indices and human development indices. The results showed that on average, agricultural productivity in Africa grew 0.2% per year, with 22 countries experiencing growth primarily due to technological changes. However, some countries like Congo and Somalia experienced declines in productivity due to factors like war and civil unrest. Overall, Africa saw a 2.1% upward shift in production frontiers but a 1.8% decline in efficiency. The analysis also found a positive relationship between agricultural productivity growth and reductions in poverty.
Analysis of Technical, Economic and Allocative Efficiencies of CassavaProduct...IOSR Journals
This document analyzes the technical, economic, and allocative efficiencies of cassava production in Taraba State, Nigeria. It finds that the average technical, allocative, and economic efficiencies were 88.7%, 85.6%, and 82.5% respectively, indicating that farmers were relatively efficient. The major factors influencing cassava output were found to be farm size, family labor, hired labor, fertilizer use, household size, education level, and source of farm financing. To improve efficiency, the study recommends encouraging more intensive farming practices rather than continued expansion of land for cassava production and improving farmer knowledge through education and training.
IFPRI South Asia researchers Devesh Roy, Ruchira Boss, Mamata Pradhan and Manmeet Ajmani presented ‘Understanding the landscape of pulse policy in India and implications for trade’ to the Global Pulse Federation. The paper examines Indian policy around production, consumption and trade. The need for pulse trade policy in India to be supportive of Domestic priorities focused on serving interest of both India’s farmers and consumers.
Land reforms, labor allocation and economic diversity: evidence from Vietnam ...anucrawfordphd
This document summarizes and discusses a paper examining the impact of land fragmentation on economic diversity of farm households in Vietnam. The paper developed a theoretical model and used empirical analysis of panel data from 2004-2006 to show that land consolidation can reduce farm labor supply and increase non-farm income by releasing labor. The discussant provided consideration on further interpreting the model and empirical approach, addressing potential endogeneity, and exploring impacts across different household groups and additional outcome measures.
Input Structure Effect of Total Factor Productivity Growth of Animal HusbandryDr. Amarjeet Singh
This paper uses the input-output panel data of China's animal husbandry industry from 1997 to 2017, based on the total factor decomposition framework of total factor productivity (TFP), and uses the Hicks-Moorsteen index completely decompose the growth of animal husbandry TFP. By measuring the effect of mixed efficiency on the development of TFP in animal husbandry and then evaluating the input structure effect of TFP growth in animal husbandry. The results show that the impact of input structure on the TFP growth of animal husbandry has also changed from negative to positive. From 1997 to 2007, the input structure of the Huanghuaihai region alone contributed to the growth of TFP in animal husbandry, and the rest of the region was the opposite. From 2008 to 2017, the input structure of the Mengxin Plateau region hindered the growth of TFP in animal husbandry, while the rest of the region was the opposite.
7.[55 64]impact of input and output market development interventions in ethiopiaAlexander Decker
This study evaluated the impact of input and output market development interventions by the Improving Productivity and Market Success (IPMS) project in Ethiopia. The interventions aimed to improve agricultural markets, increase marketed surplus, and make households more market-oriented. The study used survey data and propensity score matching to compare participant and non-participant households in Alaba and Dale districts. The results showed that the interventions positively impacted institutional changes like increased credit availability and quality of extension services. Participants had significantly higher rates of credit receipt and marketed surplus compared to non-participants. The interventions also increased farmer organization by supporting the establishment of cooperatives. The study concluded that expanding these types of market development interventions could help Ethiopia achieve its growth and poverty
11.impact of input and output market development interventions in ethiopiaAlexander Decker
This study evaluated the impact of input and output market development interventions by the Improving Productivity and Market Success (IPMS) project in Ethiopia. The interventions aimed to improve agricultural markets, increase marketed surplus, and make households more market-oriented. The study used survey data and propensity score matching to compare participant and non-participant households in Alaba and Dale districts. The results showed that the interventions positively impacted institutional changes like increased credit availability and quality of extension services. Participants had significantly higher rates of credit receipt and marketed surplus compared to non-participants. The interventions also increased farmer organization by supporting the establishment of cooperatives. The study concluded that expanding these types of market development interventions could help Ethiopia achieve its growth and poverty
This study analyzed factors that influence farmers' adoption of record-keeping methods in central and southern Chile. The researchers conducted surveys of 211 farmers and estimated a probit model with the dependent variable being whether farmers kept digital records. The results showed that higher education levels, younger age, membership in a technology transfer group or management center, leasing land, and higher personal risk tolerance were statistically significant predictors of adopting digital record-keeping. The model had good predictive power for different farmer groups.
11.productivity and resource use efficiency in tomato and watermelon farmsAlexander Decker
This study examines productivity and resource use efficiency in tomato and watermelon farms in Ghana. The value of output for watermelon farms was higher than for tomato farms, due to differences in output prices and input costs. It cost more to produce a hectare of tomato (GH¢704.59) than watermelon (GH¢509.03), but tomato yields per hectare were lower (GH¢480.37 vs GH¢1738.68 for watermelon). Factors like land, labor, and experience influenced tomato output value, while land, non-farm activity, and training impacted watermelon output. Marginal values for land and labor exceeded market prices, indicating inefficient resource use for both crops
Productivity and resource use efficiency in tomato and watermelon farmsAlexander Decker
This document summarizes a study that examined productivity and resource use efficiency in tomato and watermelon farms in Ghana. The study found that the value of output for watermelon was higher than for tomato, due to differences in output prices and input costs. Analysis of factors affecting output value found that for tomato, land, labor and experience were significant, while for watermelon, land, non-agricultural activity and training were significant. Marginal values for land and labor were higher than market prices, indicating inefficient use of those resources for both crops. Fertilizer use for tomato and capital use for watermelon did not significantly impact output values, showing underutilization of those inputs. The results have implications for
Determinants of seed cotton output evidence from the northern region of ghanaAlexander Decker
This document summarizes a study that analyzed the factors influencing seed cotton output in Ghana's Northern Region. 200 cotton farmers were surveyed using multi-stage random sampling. An augmented Cobb-Douglas production model was used for analysis. The results showed farmer's education, experience, farm size, fertilizer use, labor, location, extension contact and farmer group size were significant determinants of output. The estimation also showed decreasing returns to scale of 0.824. The relevance of input factors calls for policies focusing on timely provision of quality inputs.
Agriculture Public Expenditure Workshop organized by the Strengthening National Comprehensive Agricultural Public Expenditure in Sub-Saharan Africa Program
Dar es Salaam, June 2013
Accra, Ghana, April 13-14, 2011
Analysis of resource use efficiency in smallholder mixed crop livestock agric...Alexander Decker
This document analyzes the resource use efficiency of smallholder mixed crop-livestock farmers in central Ethiopia. It finds that on average, farmers are 26% technically inefficient, 32% allocatively inefficient, and 50% economically inefficient in their production of major crops like teff, wheat, and chickpeas. A regression analysis finds that livestock ownership and off-farm work reduce inefficiency, while large family size and association membership increase inefficiency. The study suggests improving integrated livestock and crop systems, promoting off-farm activities, and reforming farmers' associations to boost efficiency.
Assessment of budgetary allocation to agricultural sector and its effect on a...Alexander Decker
This document summarizes a study that assessed the budgetary allocation to agriculture in Rivers State, Nigeria from 1999-2010 and its effect on agricultural output. The study found:
1) Agricultural output of crops like cassava, yam, oil palm and plantain showed little to no growth over the 12-year period despite over 21 billion naira being allocated to agriculture.
2) The highest percentage of the state budget allocated to agriculture was 9.56% in 2005, with over 1 billion naira allocated in most years except 2002, 2003, 2006-2008 and 2010.
3) There was a very poor relationship between budgetary allocations and agricultural output, as the allocations did
This document discusses trends in high-value agriculture in India. It notes a shift from grains to higher-value commodities like fruits, vegetables, dairy and meat due to rising incomes, urbanization, and trade policies. Exports of high-value products like fruits and vegetables have grown significantly. Contract farming has allowed small farmers to access high-value domestic and export markets. Overall high-value agriculture provides opportunities for commercialization and income growth for smallholders through arrangements like contract farming. The document analyzes crop area and production data and makes recommendations to promote diversification and infrastructure to support high-value agriculture.
The document analyzes the growth and instability of foodgrain production in Odisha, India over a 20-year period from 1995-1996 to 2014-2015 at the state and district level. It finds that while total foodgrain production experienced no growth in the first decade, the second decade saw impressive growth for all crops, especially other cereals which grew at 7.7% annually. At the district level, most districts also saw higher growth rates for paddy, other cereals, pulses and total foodgrains in the second decade compared to the first. However, some districts still experienced negative or low growth for certain crops. The study also found that instability or risk in foodgrain production decreased at the state level in the second
Technical efficiency of rural women farmers in borno state, nigeria.Alexander Decker
This document summarizes a study that examined the technical efficiency of rural women farmers in Borno State, Nigeria. Key findings include:
1) Rural women farmers in the study area had high levels of illiteracy (59.4%), did not belong to cooperatives (89.8%), had little contact with agricultural extension services (72%), and low access to credit (89.4%).
2) The mean technical efficiency of respondents was 0.5754, while the most efficient farmer achieved a technical efficiency of 0.9994.
3) Factors found to reduce technical inefficiency (and thus increase efficiency) included higher education levels, more off-farm income, more time spent farming, older
Effects of Rice Liberalization Law on Rice Production, Farmers’ Wages and Gov...IJAEMSJORNAL
- The document analyzes the effects of the Rice Liberalization Law on rice production, farmers' wages, and government budgets in Nueva Ecija, Philippines.
- Quantitative analysis using time series data from 2010-2019 finds that government budgets have a significant positive effect on rice production, while low production negatively impacts farmers' wages and income.
- The study aims to determine if liberalizing rice trade through the Rice Liberalization Law significantly impacted the current rice market situation in Nueva Ecija.
Technical efficiency of cowpea production in osun state, nigeriaAlexander Decker
- The study analyzed the technical efficiency of 200 cowpea farmers in Osun State, Nigeria using a
stochastic production frontier function.
- The results found the mean technical efficiency level was 66%, indicating room for improvement.
- Age, household size, and farming experience reduced technical inefficiency, while gender and education
increased inefficiency.
- The findings suggest cowpea farmers could increase output with existing inputs and technology by improving
their technical efficiency.
11.technical efficiency of cowpea production in osun state, nigeriaAlexander Decker
This document analyzes the technical efficiency of cowpea farmers in Osun State, Nigeria. It finds that the mean technical efficiency level was 66%, meaning on average farmers were producing 66% of potential output. Factors like age, household size, and farming experience reduced technical inefficiency, while gender and education increased inefficiency. The study concludes there is room for improving efficiency to boost cowpea output through better use of available resources.
This document summarizes the key topics and findings from the book "Agricultural Transformation in Nepal: Trends, Prospects and Policy Options". It discusses Nepal's agricultural sector challenges including lower and fluctuating growth, declining productivity, and rising imports. However, it also notes prospects like shifting diets driving demand, commercialization, and emerging value chains. The way forward involves ensuring food security through technology adoption, increasing public and private investment, promoting diversification, and developing domestic and regional value chains. Strengthening infrastructure, quality standards, contract farming and trade opportunities can help realize the agriculture sector's potential.
Agricultural productivity growth and incidence of povertyAlexander Decker
This study analyzed agricultural productivity growth and poverty in Africa from 1971-2009 using Malmquist Total Factor Productivity indices and human development indices. The results showed that on average, agricultural productivity in Africa grew 0.2% per year, with 22 countries experiencing growth primarily due to technological changes. However, some countries like Congo and Somalia experienced declines in productivity due to factors like war and civil unrest. Overall, Africa saw a 2.1% upward shift in production frontiers but a 1.8% decline in efficiency. The analysis also found a positive relationship between agricultural productivity growth and reductions in poverty.
Analysis of Technical, Economic and Allocative Efficiencies of CassavaProduct...IOSR Journals
This document analyzes the technical, economic, and allocative efficiencies of cassava production in Taraba State, Nigeria. It finds that the average technical, allocative, and economic efficiencies were 88.7%, 85.6%, and 82.5% respectively, indicating that farmers were relatively efficient. The major factors influencing cassava output were found to be farm size, family labor, hired labor, fertilizer use, household size, education level, and source of farm financing. To improve efficiency, the study recommends encouraging more intensive farming practices rather than continued expansion of land for cassava production and improving farmer knowledge through education and training.
IFPRI South Asia researchers Devesh Roy, Ruchira Boss, Mamata Pradhan and Manmeet Ajmani presented ‘Understanding the landscape of pulse policy in India and implications for trade’ to the Global Pulse Federation. The paper examines Indian policy around production, consumption and trade. The need for pulse trade policy in India to be supportive of Domestic priorities focused on serving interest of both India’s farmers and consumers.
Land reforms, labor allocation and economic diversity: evidence from Vietnam ...anucrawfordphd
This document summarizes and discusses a paper examining the impact of land fragmentation on economic diversity of farm households in Vietnam. The paper developed a theoretical model and used empirical analysis of panel data from 2004-2006 to show that land consolidation can reduce farm labor supply and increase non-farm income by releasing labor. The discussant provided consideration on further interpreting the model and empirical approach, addressing potential endogeneity, and exploring impacts across different household groups and additional outcome measures.
Input Structure Effect of Total Factor Productivity Growth of Animal HusbandryDr. Amarjeet Singh
This paper uses the input-output panel data of China's animal husbandry industry from 1997 to 2017, based on the total factor decomposition framework of total factor productivity (TFP), and uses the Hicks-Moorsteen index completely decompose the growth of animal husbandry TFP. By measuring the effect of mixed efficiency on the development of TFP in animal husbandry and then evaluating the input structure effect of TFP growth in animal husbandry. The results show that the impact of input structure on the TFP growth of animal husbandry has also changed from negative to positive. From 1997 to 2007, the input structure of the Huanghuaihai region alone contributed to the growth of TFP in animal husbandry, and the rest of the region was the opposite. From 2008 to 2017, the input structure of the Mengxin Plateau region hindered the growth of TFP in animal husbandry, while the rest of the region was the opposite.
7.[55 64]impact of input and output market development interventions in ethiopiaAlexander Decker
This study evaluated the impact of input and output market development interventions by the Improving Productivity and Market Success (IPMS) project in Ethiopia. The interventions aimed to improve agricultural markets, increase marketed surplus, and make households more market-oriented. The study used survey data and propensity score matching to compare participant and non-participant households in Alaba and Dale districts. The results showed that the interventions positively impacted institutional changes like increased credit availability and quality of extension services. Participants had significantly higher rates of credit receipt and marketed surplus compared to non-participants. The interventions also increased farmer organization by supporting the establishment of cooperatives. The study concluded that expanding these types of market development interventions could help Ethiopia achieve its growth and poverty
11.impact of input and output market development interventions in ethiopiaAlexander Decker
This study evaluated the impact of input and output market development interventions by the Improving Productivity and Market Success (IPMS) project in Ethiopia. The interventions aimed to improve agricultural markets, increase marketed surplus, and make households more market-oriented. The study used survey data and propensity score matching to compare participant and non-participant households in Alaba and Dale districts. The results showed that the interventions positively impacted institutional changes like increased credit availability and quality of extension services. Participants had significantly higher rates of credit receipt and marketed surplus compared to non-participants. The interventions also increased farmer organization by supporting the establishment of cooperatives. The study concluded that expanding these types of market development interventions could help Ethiopia achieve its growth and poverty
This study analyzed factors that influence farmers' adoption of record-keeping methods in central and southern Chile. The researchers conducted surveys of 211 farmers and estimated a probit model with the dependent variable being whether farmers kept digital records. The results showed that higher education levels, younger age, membership in a technology transfer group or management center, leasing land, and higher personal risk tolerance were statistically significant predictors of adopting digital record-keeping. The model had good predictive power for different farmer groups.
11.productivity and resource use efficiency in tomato and watermelon farmsAlexander Decker
This study examines productivity and resource use efficiency in tomato and watermelon farms in Ghana. The value of output for watermelon farms was higher than for tomato farms, due to differences in output prices and input costs. It cost more to produce a hectare of tomato (GH¢704.59) than watermelon (GH¢509.03), but tomato yields per hectare were lower (GH¢480.37 vs GH¢1738.68 for watermelon). Factors like land, labor, and experience influenced tomato output value, while land, non-farm activity, and training impacted watermelon output. Marginal values for land and labor exceeded market prices, indicating inefficient resource use for both crops
Productivity and resource use efficiency in tomato and watermelon farmsAlexander Decker
This document summarizes a study that examined productivity and resource use efficiency in tomato and watermelon farms in Ghana. The study found that the value of output for watermelon was higher than for tomato, due to differences in output prices and input costs. Analysis of factors affecting output value found that for tomato, land, labor and experience were significant, while for watermelon, land, non-agricultural activity and training were significant. Marginal values for land and labor were higher than market prices, indicating inefficient use of those resources for both crops. Fertilizer use for tomato and capital use for watermelon did not significantly impact output values, showing underutilization of those inputs. The results have implications for
Determinants of seed cotton output evidence from the northern region of ghanaAlexander Decker
This document summarizes a study that analyzed the factors influencing seed cotton output in Ghana's Northern Region. 200 cotton farmers were surveyed using multi-stage random sampling. An augmented Cobb-Douglas production model was used for analysis. The results showed farmer's education, experience, farm size, fertilizer use, labor, location, extension contact and farmer group size were significant determinants of output. The estimation also showed decreasing returns to scale of 0.824. The relevance of input factors calls for policies focusing on timely provision of quality inputs.
Agriculture Public Expenditure Workshop organized by the Strengthening National Comprehensive Agricultural Public Expenditure in Sub-Saharan Africa Program
Dar es Salaam, June 2013
Accra, Ghana, April 13-14, 2011
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This document summarizes a study that assessed the budgetary allocation to agriculture in Rivers State, Nigeria from 1999-2010 and its effect on agricultural output. The study found:
1) Agricultural output of crops like cassava, yam, oil palm and plantain showed little to no growth over the 12-year period despite over 21 billion naira being allocated to agriculture.
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3) There was a very poor relationship between budgetary allocations and agricultural output, as the allocations did
Analysis of the effects of monetary and fiscal policy indicators on agricult...researchagriculture
This document analyzes the effects of monetary and fiscal policy indicators on agricultural output in Nigeria from 1990-2000. It specifically examines the relationship between money supply, interest rates, inflation, savings, budgetary allocation and the output of cereals like maize, millet, rice and wheat. The results of a regression analysis showed that money supply, budgetary allocation and interest rates had a significant relationship with agricultural output, while inflation and savings were not significant. The analysis also revealed that while budgetary allocations to agriculture increased dramatically over the period, agricultural output levels remained largely the same, indicating a weak relationship between fiscal policy and output.
Analysis of the effects of monetary and fiscal policy indicators on agricultu...researchagriculture
The research was conducted to determine the effect of monetary and fiscal policy indicators on Nigeria’s agricultural output. The output considered were mainly cereals such as maize, sorghum, rice, millet and wheat while the monetary policy indicators studied were inflation, money supply, interest rate and savings. Budgetary allocation represents the fiscal component while inflation, savings, interest rate, money supply represented monetary policy indicators. One of the fundamental objectives was to examine the relationship between monetary and fiscal policy indicators on agricultural output. Multiple regression was used as the main analytical tool, and the result showed that money supply, budgetary allocation, interest rate were 94%, 54% and 82% significant in the order above i.e. they had significant relationship with output, while inflation and savings were not significant. The result also revealed that within the period of study, agriculture contributed 28% to 35% of the gross domestic product. Forestry and fisheries contributed the least, while crop and animal sub sectors contributed the highest.
Article Citation:
Okidim IA and Albert CO.
Analysis of the Effects of Monetary and Fiscal Policy Indicators on Agricultural
Output (Cereal) (1990-2000).
Journal of Research in Agriculture (2012) 1(1): 058-064.
Full Text:
http://www.jagri.info/documents/AG0021.pdf
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This document summarizes a study that assessed resource use efficiency for maize production in soils in
northcentral Nigeria. Soil and socioeconomic data were collected from 90 farmers in 3 communities. Soil
properties varied within locations but soil types were similar. Regression analysis found a quadratic model best fit
the data, with yield increasing based on optimal levels of inputs. Returns to scale were decreasing for all inputs
except fertilizer. The study concluded more efficient use of inputs could increase production profits and
recommended educating farmers on innovative technologies for sustainable land management and crop
production.
Technical Efficiency of Smallholder Sorghum Producers in West Hararghe Zone, ...Premier Publishers
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Energy consumption pattern in wheat production in sindhsanaullah noonari
Wheat (Triticum aestivium L.) is the main staple food for most of the population and largest grain source o the
country. It occupies the central position in formulating agricultural policies. It contributes 13.1 percent to the
value added in agriculture and 2.7 percent to GDP. Area and production target of wheat for the year 2012-13 had
been set at 9045 thousand hectares and 25 million tons, respectively. Wheat was cultivated on an area of 8805
thousands hectares, showing a decrease of 3.6 percent over last year’s area of 9132 thousand hectares. However,
a bumper wheat crop of 24.2 million tons has been estimated with 3.9 percent increase over the last year’s crop
of 23.3 million tons. The prospects for wheat harvest improved with healthy fertilizer off-take and reasonable
rainfall during pre-harvesting period. Energy is a necessary of life for human beings all over the world due to its
function in strengthening the security and contentment of the people. Energy demand is growing with the
passage of time due to infrastructural and industrial development. Energy is required to perform all the human
activities. It is need for food preparation, water heating and cooling, for lighting, for production of goods etc.
The study was focused on all types of energy (fossil fuels, chemicals, animals dung, animate etc). A sample of
60 farmers was selected from study area. A pre tested questioner was used to collect data from selected
respondents through personal interviews. Descriptive statistics and Cobb-Douglas production function was
applied to analyze the data. Result shows that wheat farmer achieved highest amount of net energy which was
calculated as small, medium and large farmers is 1368336.88, 1698003.79 and1702527.75 MJ/acre respectively.
In production of wheat large, medium and small farmers achieve amount of net energy which was calculated
41525.06, 38590.99, 39095.33 MJ/acre. The impact of various energy inputs on yield was studied. The share of
various energy types in total cost of production was estimated. Commercial energy (diesel and electricity)
consumed highest amount of energy in production of wheat.
1. The document discusses annual post-harvest losses of grains in Ganye, Southern Adamawa State, Nigeria. It finds that over 50% of annual losses are due to a lack of viable storage and processing facilities.
2. Major losses occur during harvesting, storage, transportation and processing. Up to 30% of crops like groundnuts are lost during post-harvest operations due to traditional techniques and inadequate infrastructure.
3. The study estimates that 15-20% of grains are lost or wasted annually across the entire supply chain from production to consumption. Improving storage technologies and establishing agro-processing facilities could significantly reduce losses.
Effects Of Khat Production On Rural Household’s Income In.pdfNadhi2
This document summarizes a study on the effects of khat production on rural household incomes in Kenya. Khat is a cash crop grown and exported from parts of Kenya. The study used surveys of 125 households, both khat producers and non-producers, to analyze factors influencing participation in khat through logistic regression and to assess the contribution of khat to incomes through propensity score matching. The analysis found that access to extension services, land size, income, and occupation of household head promoted participation, while age, distance to market, and credit access hindered it. The study also found that khat production positively contributed to rural household incomes.
This document discusses a study that used a computable general equilibrium (CGE) model to analyze the potential impacts of adopting hydroponics technology in Pakistan's fruit and vegetable sector and on global trade. The study adapted the GTAP global CGE model with separate sectors for fruits and vegetables among 15 aggregated sectors and 30 aggregated regions including Pakistan. Simulations were run to quantify the effects of increasing hydroponics production of fruits and vegetables in Pakistan and reducing import tariffs on chemicals used as inputs. The results showed overall positive impacts on Pakistan's real GDP, sectoral exports and imports, terms of trade, and domestic prices of fruits and vegetables, indicating that adopting hydroponics technology could benefit Pakistan's macroeconomic indicators and consumer welfare.
Impact of the Adoption of Improved Varieties of Household Income of Farmers i...BRNSS Publication Hub
In Benin, maize occupies a strategic place in the agricultural sector due to its growing importance in national
consumption and trade with neighboring countries. This study aims to analyze the impact of the adoption of
improved maize varieties on the income and expenditure of maize farmers in the South Atlantic Department
of Benin. The data used were collected from 144 maize growers in the Atlantic Department. Maize farmers
with or without improved varieties were selected randomly. The average treatment effect method with
propensity score matching was used to estimate the impact of the adoption of improved maize varieties
on household income and expenditure. Maize growers using four impact indicators: (i) Netincome; (ii)
school expenses; (iii) health expenditure; and (iv) food expenditures. The results showed that the adoption
of improved maize varieties led to an improvement in annual netincome (a relative effect of 8.78%), health
expenditure (a relative effect of 15.88%), and expenditure on education (a relative effect of 16.08%). On
the other hand, the adoption of improved varieties of maize has no significant influence on the expenditure
invested in the dietof household members. It shows that the adoption of improved varieties of maize by
which has a positive impact on the netincome, health expenditure, and household education expenditure.
Impact of the Adoption of Improved Varieties of Household Income of Farmers i...BRNSS Publication Hub
In Benin, maize occupies a strategic place in the agricultural sector due to its growing importance in national consumption and trade with neighboring countries. This study aims to analyze the impact of the adoption of improved maize varieties on the income and expenditure of maize farmers in the South Atlantic Department of Benin. The data used were collected from 144 maize growers in the Atlantic Department. Maize farmers with or without improved varieties were selected randomly. The average treatment effect method with propensity score matching was used to estimate the impact of the adoption of improved maize varieties on household income and expenditure. Maize growers using four impact indicators: (i) Netincome; (ii) school expenses; (iii) health expenditure; and (iv) food expenditures. The results showed that the adoption of improved maize varieties led to an improvement in annual netincome (a relative effect of 8.78%), health expenditure (a relative effect of 15.88%), and expenditure on education (a relative effect of 16.08%). On the other hand, the adoption of improved varieties of maize has no significant influence on the expenditure invested in the dietof household members. It shows that the adoption of improved varieties of maize by which has a positive impact on the netincome, health expenditure, and household education expenditure.
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11.[1 10]technical efficiency in agriculture in ghana analyses of determining factors
1. Journal of Biology, Agriculture and Healthcare www.iiste.org
ISSN 2224-3208 (Paper) ISSN 2225-093X (Online)
Vol 2, No.2, 2012
Technical Efficiency in Agriculture in Ghana-Analyses of
Determining Factors
Justice G. Djokoto
Department of Agribusiness, Central Business School, Central University College, Accra Ghana.
*Email:dgameli2002@gmail.com. Tel:+233285039399
Abstract
The paper sought to estimate technical efficiency in Ghana’s agricultural sector and more importantly,
investigate the factors that influence the estimated technical efficiencies. Using data from 1976-2007,
the results showed a decreasing returns to scale in Ghana’s agriculture. Land is negatively inelastic
showing over use of the factor. Technology variables, fertiliser and tractor and combines are positively
related to output. Whilst fertiliser is elastic, tractor and combines is inelastic. The level of inefficiency
is 21% with decreasing returns to scale. The SFA specification is the appropriate model, indeed,
superior to OLS. None of the hypothesised variables to explain technical efficiency were statistically
distinguishable from zero. The negative sign for land requires decrease in the use of land relative to
other inputs. This calls for increase in the use of other variables. The insignificance of the TE effect
variables suggest that these variables may be inappropriate in explaining TE in the case of Ghana.
Other variables may have to be explored.
Keywords: technical efficiency, agriculture, Ghana, determinants
1. Introduction
1.1 Background
The traditional roles of agriculture include provision of food security, supply of raw materials for
industry, creation of employment and generation of foreign exchange earnings. Additionally,
agriculture is recognised for social stabilisation, buffer during economic shocks, support to
environmental sustainability, and cultural values associated with farming. Furthermore, agriculture is
acknowledged to impact on poverty reduction more than other sectors (MOFA, 2007). In fact, Bogetic
et al (2007) and Coulombe & Wodon (2007) provide evidence that the poverty rate in Ghana fell from
51.7% in 1991-1992 to 39.5% in 1998-1999 and 28.5% in 2005-2006. In the light of the foregoing
agriculture remains strong in Ghana. The sector still employs 54% of Ghana’s population (UNCTAD,
2011) and contributes 10% to non-traditional exports despite a decline in the sector’s contribution to
Ghana’s GDP from 40% in 2000 to 30% in 2010 (MOFA, 2011).
Agricultural production which is largely rainfed (only 0.2% of irrigated land) provides food for the
inhabitants. The 2010/2011 food balance sheet revealed that the country recordered food surpluses;
0.075m metric tonnes (MT) of legumes, 0.69m MT of cereals and 8.29m MT starchy staples (MOFA,
2011). The main legume crops grown are groundnuts, cowpea and soyabean. Cassava, yam, plantain
and cocoyam constitute main starchy staple crops produced in Ghana. In respect of cereal production,
the main crops include maize, sorghum, rice and millet. Aside of food, Ghana produces industrial
crops; mainly cocoa, coffee, rubber, sheanut and oil palm for export. The livestock sub-sector is
dominated by poultry on both small and medium scale. The rest are the production of cattle, pigs, sheep
and goats. The fisheries sub-sector, the smallest in terms of GDP contribution is largely marine. There
is however, a growing attraction of fish culture especially, tilapia within Ghana’s main river, the Volta.
The focus of Ghana’s Agricultural Development Agenda emphasises the sustainable utilisation of all
resources and commercialisation of activities in the sector with market-driven growth in mind and
targets some commodities for food security and income diversification, especially of resource poor
farmers. Additionally, greater engagement of the private sector and collaboration with other partners
are court to facilitate implementation of agricultural policies (MOFA, 2007). Moreover, enhancement
of productivity of the commodity value chain, through the application of science and technology, with
environmental sustainability is emphasised.
The focus on enhancement of productivity brings to the fore the issue of productive efficiency.
Technical efficiency (TE) measures the difference between the ideal production possibility curve (PPC)
(in this case for a country) and the actual level of performance (of the country) relative to the PPC. This
Farrell (1957) described as output-oriented efficiency. From a cross-sectional perspective, the concept
involves assessing each farm’s production performance compared to a best-practice input-output
relationship or frontier. The best-practices production frontier is established by the practices of the
1
2. Journal of Biology, Agriculture and Healthcare www.iiste.org
ISSN 2224-3208 (Paper) ISSN 2225-093X (Online)
Vol 2, No.2, 2012
most efficient farmer(s). Thus, the deviation of the individual farm from the frontier measures technical
efficiency (TE). From time series perspective and of a country, the best-practice frontier is the potential
output for the best practice year. Thus, the TE in that case, is the gap between the actual output for any
particular year and the potential output of the best-practice year.
1.2 Problem Statement
Agriculture is predominantly practised on smallholder, family-operated farms using rudimentary
technology to produce about 80% of Ghana’s total agricultural output. Despite contributing 30% to
GDP, agricultural land-use constitutes 50% of total land use in Ghana (MOFA, 2007) and employs
more than 50% of Ghana’s population (UNCTAD, 2011). Following Ghana’s agricultural development
objective of enhancing productivity, the substantial physical and human resources employed in
agriculture, what is the factor productivity in Ghana’s agricultural sector? How efficient is agricultural
production? What factors explain efficiency in the agricultural sector?
1.3 Objectives
The paper seeks to estimate technical efficiency in the agricultural sector and determine the factors that
influence the estimated technical efficiencies.
1.4 Relevance
Determinants of the estimated technical efficiencies have been investigated in several cross-sectional
studies, however, rarely in the case of time series work (Miljkovic and Shaik, 2010), is TE investigated.
Recently, Djokoto (2012) investigated the technical efficiency of agriculture in Ghana but failed to
identify the factors that explain the estimates of TE. Yet, Clark (1957), in his discussion of Farrell’s
paper in 1957 was unsurprised about the need for economists to look for social and other factors that lie
behind technical efficiency estimates of agriculture.
1.5 Organisation of study
The rest of the paper is composed into four main sections. Section 2 presents review of literature
pertinent to the title of study. Section 3 presents data and methods of analyses. Section 4 contains the
results and accompanying discussions. Reporting the research concludes in section 5 with the
associated recommendations.
2. Literature Review
2.1 Theoretical review
The need to assess efficiency of production has long engaged the attention of economists (Debreu,
1951) and statisticians (Farrell, 1957). M. J. Farrell at a meeting of the Royal Statistical Society of UK
presented his seminal work on efficiency and its measurement in agriculture. From then, there have
been several developments in the field of efficiency and its measurement particularly in agriculture.
There are four major approaches to measure efficiency (Coelli et al., 1998). These are the non-
parametric programming approach (Charnes et al., 1978), the parametric programming approach
(Aigner and Chu, 1968; Ali and Chaudry, 1990), the deterministic statistical approach (Afriat, 1972;
Schippers, 2000; Fleming et al., 2004) and the stochastic frontier approach (Aigner et al, 1977).
Due to the inherent stochasticity involved in SFA (outlined in the methodology section), it is preferred
for assessing efficiency in agriculture (Coelli, 1995; Ezeh, 2004). Aigner et al (1977) and Meeusen &
van den Broeck (1977) independently laid the foundations of stochastic frontier approach (SFA).
Kumbhakar & Lovell (2000) and Greene (2004), acknowledged the surge in efficiency studies with
extensions to estimate technical change, efficiency change, and productivity change measures using
SFA. The distribution of asymmetric component, u (inefficiency) and conditional estimation of
inefficiency are examples of additional dimensions of efficiency that has engaged the attention of
investigators.
2.2 Empirical review
Milner & Weyman–Jones (2003) studied 85 developing countries over 1980-1989 and concluded that
country size was important in explaining aggregate efficiency. A strong positive developmental–
efficiency relationship and evidence of a positive impact of trade policy openness and health (measured
as average life expectancy at birth in years) on aggregate efficiency exists in developing countries. The
conclusions of Iyer et al (2008) after investigating 20 OECD countries over 1982-2000 with a
stochastic frontier estimation, showed that trade and all foreign investment inflows were found to
enhance efficiency. FDI outflows rather exacerbated inefficiency. Productive (economic) efficiency
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and factors affecting it were evaluated in the Caribbean between 1983 and 1992 by Lall et al, (2000).
The results from non-parametric programming indicated that efficiency (i.e. pure technical, allocative
and economic) measures were lower and more variable in Caribbean than in other Western Hemisphere
countries. Using a Tobit regression analysis, they showed that higher levels of private and foreign
investments, productive infrastructure, credit availability, education level, and consumption of
domestically produced goods had positive impacts on the efficiency measures. On the other hand,
higher levels of public expenditure, income tax, and export taxes, and higher inflation rates had
negative effects. The study advocated support for the trend towards more open economies (i.e. letting
the free market work) and encouraging governments to confine their functions to facilitative/regulatory
type roles and to undertaking tasks that are not generally undertaken by the private sector. Following
the differing impacts of these factors between Caribbean and Latin America, Lall et al (2000)
admonished that relatively greater emphasis should be placed on TE factors such as foreign and private
investment and developing infrastructure in the Caribbean than in Latin American countries. In
studying 16 African countries using data envelopment analysis (DEA), Nkamleu (2004) showed that
total factor productivity (TFP) increased. With data covering 1970-2001, the study further showed that
the increases in TFP growth in the agricultural sector were due to good progress in technical efficiency
rather than technical progress. The region suffered a regression in productivity in the 1970s, and made
some progress during the 1980s and 1990s. Another highlight was the fact that technical change had
been the main constraint of achievement of high levels of total factor productivity during the reference
period in sub-Saharan Africa. On the contrary, in Maghreb countries, technological change had been
the main driving force of productivity growth. An institutional factor that explained technical change
and TFP change was illiteracy. This was negatively related to the dependent variables.
In a time varying estimation, Sotnikov (1998) showed that average TE of 0.77-0.92 was obtained for
the period 1991-1993 and 0.78 for 1995 covering 75 Russian regions. The factors that were statistically
significant in explaining TE were road density (particularly in rural areas), number of workers per
manager (representing management), manager education and farm size. With exception of manager
education, all other factors exerted a negative effect on technical efficiency.
In the case of Brazil, empirical results suggest that technical efficiency is influenced by a number of
factors that were not related to the technological choices made by the producers (Igliori, 2005).
Environmental conditions, location, transportation network, farm size distribution, and the size of local
economies were the main elements explaining technical efficiency variation which ranged between
0.01 and 0.92 with a mean of 0.38.
Mathijs et al (2001) used Tobit regressions with farm-specific efficiency scores to show the importance
of human capital variables such as education on efficiency. They explained that tackling the problems
of missing or imperfect markets for inputs and output and thus reducing related transaction costs is
necessary to produce efficiently. They observed that being member of a cooperative or partner of a
company affected the efficiency level of family farms positively in the Czech Republic because certain
production inputs were more easily accessible. For farm enterprises, producing on contract increased
efficiency because such contracts facilitated the adoption of technology and access to credit. In
addition, they noted that economies of scope were important as more specialised farms were more
efficient. Provision of services to individuals lowered the efficiency level of farm enterprises.
3. Data and Methods
3.1 Model1
The model used in the study is specified as:
y = f ( X )e v − u .....................................................................................................................................................1
Following Miljkovic and Shaik (2010) and applying natural logarithm and matrix notation will result in
stochastic production frontier model (2).
ln y = X β + v − u .............................................................................................................................................2
t t t t
where yt denotes the output for the year t (t =1, . . . ,N), Xt is a vector of the production inputs as well
as a column of ones, β is a vector of parameters to be estimated, vt and ut are error terms defined
1
This sub-section draws on earlier work by Djokoto (2012).
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below. The frontier production function is a measure of the maximum potential output obtainable. Both
vt and ut cause actual production to deviate from this frontier. The random variable in the production
that cannot be influenced by producers is represented by vt, is identically and independently distributed
(iid) as N(0, σ2v). The non-negative error term ut represents deviation from the maximum potential
output attributable to technical inefficiency which is independent of vt. It is also assumed to be
identically and independently truncated in t instead of zero (half-normal distribution when µ = 0) as N
(µ, σ2u). The stochastic terms vt and ut are assumed to be uncorrelated.
Modifying Jondrow et al (1982), and following Djokoto (2012) the technical efficiency of agricultural
production is given by the mean of the conditional distribution of ut given Ɛt as defined by:
σ σ f (ε λ / σ ) ε λ
E (u / ε ) = u v t − t ..............................................................................................................3
t t σ 1 − F (ε λ / σ σ
t
where λ
= σ / σ , σ 2 = σ 2 + σ 2 , while f and F represent the standard normal density and
u v u v
cumulative distribution functions respectively evaluated at ε λ / σ .
t
Along with the parameters of the function itself, FRONTIER also estimates the following parameters
of the likelihood function:
σ 2 =σ 2 +σ 2 and
u v
σ2
γ= v .....................................................................................................................4
(σ 2 +σ 2)
u v
Testing the significance of the parameter γ is of interest from the point of view of model specification.
It must be in the range 0-1, and measures the share of total variation that is attributed to technical
inefficiency. If γ = 0, it means that σ v2 = 0, then, the stochastic production frontier is not a good
specification, and the model could alternatively be estimated by ordinary least squares.
The year specific technical efficiency is defined in terms of observed output y to the corresponding
t
y * using the available technology derived from the result of (3) as:
E( y | u X )
t t, t
TE = ........................................................................................................................................5
t E ( y | u = 0, X )
t t t
Or
(X β + v − u )
y t t t −u
T .E. = t =e = e t ................................................................................................................6
y* (X + v )
t e t t
where y is the observed output in year t and y * is the frontier output in year t.
t t
−u y
The solution of equation 5 becomes e t so that 0 ≤ t ≤ 1 . That is, technical efficiency is between 0
y *
t
and 1. The above transformation constrains the technical efficiency of each year to a value between
zero and one, and is inversely related to the inefficiency.
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The measure of technical efficiency is thus based on the conditional expectation of (5), given the value
of (vt – ut) evaluated at the maximum likelihood estimates of the parameters β where the maximum
value of y is conditioned on u = 0 (Battese and Coelli, 1995).
t t
The equation:
u = Zδ ..................................................................................................................................................................7
t
was estimated and Z; is a vector of variables that are assumed to influence technical efficiency and δ
is a vector of parameters to be estimated. Following Desai (1976), Li & Wahl (2004), and Miljkovic
and Shaik (2010), a Cobb-Douglas production function in matrix notation (8) and (7) were estimated
jointly in FRONTIER 4.1c (Coelli, 1995).
6
ln y t = β 0 + ∑ β j X jt + v t + u t .......... .......... .......... .......... .......... .......... .......... .......... .......... .......... .......... ........ 8
j =1
where y represents total output per annum in constant 1999-2000 US dollars. j is the number of
t
explanatory variables, so that j = (1,2…6), such that X 1 is agricultural land in hectares, X 2 is labour
in number of persons, X 3 is fertiliser consumption in tonnes, X 4 is tractor and combines in numbers,
X 5 is other agrochemicals in US dollars. X 6 is seeds measured in tonnes. v and u t are as defined
t
earlier.
3.2 Estimation Procedure
Essentially, a two stage procedure is employed. The first involves estimation of TE and the explanatory
variables of the estimated TE determined. This may involve estimating a production function to collect
TEs which are then regressed on explanatory variables. Lall et al, (2000) used this procedure. Fried et
al., (1993) provides some reasons for estimating all parameters of the model in one stage. First, this
procedure provides more efficient estimates than the two-stage procedure, whereby efficiency scores
are obtained and then regressed on explanatory variables. Second, in general, it is hard to distinguish
between a variable that belongs to the first stage (production function) and the second stage
(explanatory variables of efficiency). Third, in a one-stage model, explanatory variables directly
influence the transformation of inputs and efficiency is estimated, controlling for the influence of
explanatory variables (z's). The parameter estimates generated from the stochastic production function
estimation are themselves important statistics for policy analysis, as they are the basis for estimates of
the marginal products and production elasticities of individual inputs (Sotnikov, 1998).
3.3 Data
Below are the details of the variables used for the analysis.
3.1.1 Output
Agricultural production
- Output in 1991-2000 prices of Standard Local Currency (Ghana Cedis) was used. The data was
converted to US dollar by multiplying the inverse of the exchange rate (GHC/US$) data obtained from
International Financial Statistics (IFS) of the International Monetary Fund (IMF). This resulted in US
dollar value of Agricultural production.
3.1.2 Input
- Agricultural land
The sum of area under arable land (land under temporary crops, temporary meadows for mowing or
pasture, land under market and kitchen gardens and land temporarily fallow), Permanent crops (land
cultivated with crops that occupy the land for long periods and need not be replanted after each harvest,
such as cocoa, coffee and rubber), and Permanent pastures (land used permanently for herbaceous
forage crops, either cultivated or growing wild).
- Labour
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This refers to economically active population in agriculture for each year in Ghana. Economically
active population in agriculture was defined as all persons engaged or seeking employment in
agriculture, forestry, hunting or fishing sector, whether as employers, own-account workers, salaried
employees or unpaid workers. Estimates and projection of the data was available from 1980 to 2050.
The 3 years missing data was filled by computing the average annual growth rate for the 1980-2050
and using the average annual growth rate to compute the data points for 1976 to 1979. The
economically active population in agriculture is the best proxy of labour input into the agricultural
sector, since data on information on differentials in skill levels and the number of hours worked on the
farm is not available. The population is numbers of persons.
- Fertiliser
Fertiliser consumption is often viewed as a proxy for the whole range of chemical inputs and more
(Mundlak et al., 2003). Fertilisers used in Ghana involve different amounts and different types of
fertilisers. Following other studies (Hayami and Ruttan, 1970; Rao et al., 2003), the sum of nitrogen
(N), potassium (P2O2) and phosphate (K2O) expressed in thousands of tons, that is contained in the
commercial fertilisers consumed should be used as measure of fertiliser input. However, data of this
measure was available only 2002 to 2008. As a result total consumption of all fertilisers was used.
Fertiliser was measured in tonnes.
- Tractors and Combines
This variable excludes hoes, cutlasses and bullock ploughs which are important machinery for farming
in Ghana. However, in the absence of such secondary data number of tractors, which refer to total
wheel, and crawler tractors (excluding garden tractors) used for agricultural production and combine
harvesters are employed to represent machinery capital. Tractors and combines were measured in
numbers.
- Agrochemicals
Despite the assertion of Mundlak et al (2003), availability of data on agrochemicals specifically
pesticides, herbicides and so on used in agricultural production are included as additional inputs. This
computed as import plus production minus exports equals consumption, This computation was
necessitated because query of FAOSTAT for consumption for Ghana yielded null set elements.
Agrochemicals were measured in US dollars.
3.1.3 TE effect variables
The variables explored are land area cultivated per agriculture employee, per capita consumption of
domestic food production, changes in net agricultural capital stock and agricultural merchandise
exports.
-Land area cultivated per agriculture employee
In the absence of data on land holding, this variable is used as a proxy. This will be interpreted as
average land area worked-on per person employed in agriculture. The land area excludes water bodies
(for fishing) but includes pastures. The variable is computed as land area cultivated divided by
economically active agricultural labour force (ha/person).
-Per capita consumption of domestically produced food
This was computed as domestic production less export divided by population and expressed in
kilogramme per person. It is expected that increased consumption of domestically produced food
improves efficient use of productive capacity and stimulates use of improved technology, thus,
improving efficiency.
-Road infrastructure
Data on percentage of roads paved was obtained from WDI. This was augmented with data from
Ministry of Roads and Highways (MR&H) Ghana Road Condition Report. Missing data were filled by
interpolation and extrapolation. The percentage of roads paved signal some semblance of good
condition. It is expected that good roads will promote efficiency as they will facilitate flow of inputs,
produce and persons. The flow of produce to market centres will intend create cash for farmers who
will then invest these in productive resources to increase efficiency.
- Changes in net agricultural investment stock.
FAO recently published data on composition of agricultural capital stock. The changes were computed
as the current year’s net capital stock less previous year’s net capital stock. The changes in stock are
considered as flow. This variable may be construed as investment in infrastructures specific to
agriculture and is expected to improve output given labour and land. Therefore, a positive sign is
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expected with technical efficiency a priori. The data covers 1975 -2007. However, with the
computation of the difference, there a loss of data point of one year. This will thus constrain the time
series for the whole analysis to 32 years; 1976-2007.
- Agricultural exports
Agricultural merchandise exports computed in US dollars was used as proxy for market of locally
produced agricultural produce. It is expect to increase income of farmers. This increased income should
make it possible to procure technology for production to increase efficiency.
Unless otherwise stated all data was obtained from FAOSTAT (http://faostat.fao.org) system of
statistics used for dissemination of statistics compiled by the Food and Agricultural Organisation.
4. Results and Discussions
4.1 Production Function
The statistical significance of gamma shows that SFA estimation is appropriate. The natural logarithm
formulation of the production function implies that the coefficients are elasticities. All production
function inputs are positive except land. And all inputs are statistically significant (at least at 10%
significance level) except other agrochemicals and seeds (Table 1). Land use is negative and
statistically significant at 1%. This indicates that land in Ghana’s agriculture is over used. A decrease
in land of 1% will induce 2.49% increase in output. This result agrees with Djokoto (2012) who
estimated stochastic frontier model for Ghana with data spanning 1961 to 2010. Labour and fertiliser
were both elastic. The positive and significant sign of the labour variable may be explained by the drift
of the population to urban areas in a predominantly traditional agricultural system. Though positive,
tractor and combines were inelastic. Clearly, the inputs that are capable of influencing Ghana’s
agriculture are land, labour and fertiliser. Increase in the use of labour, fertiliser and tractor and
combines will increase the productivity of land. Tractor and combines as well as fertiliser constitute
technology. Hence, enhanced technology holds key to improving agriculture in Ghana.
The return to scale is 0.19811. This is less than 1 hence there is decreasing returns to scale. This is in
sharp contrast to Djokoto (2012) who found increasing returns to scale. The difference may be
attributable to duration of the study. Whilst his data covered 1961-2010, the data for this study covers
1976 to 2007. The mean technical efficiency is 79%, similar to 86% reported by Djokoto (2012) and
higher than 38% for Brazil (Igliori, 2005).
4. 2 Technical efficiency effects
Turning to main focus of the paper, the technical efficiency effects, two characteristics, percentage of
roads paved and proportion of domestically produced food consumed were positively related to
technical efficiency. Whilst, land cultivated per agricultural labour, net investment and agricultural
exports are negatively related to technical inefficiency. Indeed, none of the variables hypothesised to
explain TE in Ghana’s agriculture were statistically significant. The insignificance of the roads paved is
contrary to the findings of Sotnikov (1998) and Lall (2000) but the negative sign conforms. The
insignificance may be attributable to the nature of the roads variable. The variable includes trunk roads
but excludes feeder roads. The data though not the most appropriate was the available data so was used.
Since agriculture in most developing countries (including Ghana) is a rural phenomenon (World Bank,
2008) the coverage and state of feeder roads would have influenced TE better. Suffice it to say that the
sign was positive indicative of seeming increased percentage of roads paved with technical efficiency.
Land worked per agricultural labour is a proxy for farm size. This was negatively related to TE. The
sign conforms to the findings of Sotnikov (1998). The statistical insignificance disagrees with the
findings of Sotnikov (1998) and Igliori (2005). In respect of domestically produced food, the sign
agrees with the findings of Lall (2000) but diverges with the statistical significance. Agricultural
exports are considered as a market avenue such that increased exports will boost incomes that can be
applied to technology. The negative and statistical significance is rather surprising and diverges with
the findings of Iyer (2008). From the foregoing, none of the variables constructed and hypothesised to
influence TE have been effective.
5. Conclusions and Recommendation
5.1 Conclusions
The paper sought to estimate technical efficiency in Ghana’s agricultural sector and more importantly,
investigate the factors that influence the estimated technical efficiencies. Using data from 1976-2010,
the results showed a decreasing returns to scale in Ghana’s agriculture. Land is negatively inelastic
showing over use of the factor. Technology variables, fertiliser and tractor are positively related to
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output. Whilst fertiliser is elastic, tractor and combines is inelastic. The level of inefficiency is 21%
with decreasing returns to scale. The SFA specification is the appropriate model, indeed, superior to
OLS. None of the hypothesised variables were statistically indistinguishable from zero.
5.2. Recommendations
The negative sign for land requires decrease in the use of land relative to other inputs. This calls for
increased use of other variables. There is the need to support technology such as fertilisers and
equipment such as tractors and combines to increase agricultural production. The use of increased use
of these technologies will increase land productivity leading to decreased land use in the presence of
increased output.
The stack contrast in of returns to scale to that of Djokoto (2012) also for Ghana requires further
investigation. This will establish whether change in time span could result in significant switches in
returns to scale measures. The insignificance of the TE effect variables suggest that these variables may
be inappropriate in explaining TE in the case of Ghana. Other variables may have to be explored.
References
Afriat S.N., 1972. Efficiency estimation of the production function. International Economic Review,
13: 568-598. http://dx.doi.org/10.2307/2525845
Aigner D.J., Chu S.F., 1968. Estimating the industry production function. American Economic
Review, 58: 826-839.
Aigner D., Lovell C.A.K., Schmidt P., 1977. Formulation and estimation of stochastic frontier
production function models. Journal of Econometrics, 6: 21–37. http://dx.doi.org/10.1016/0304-4076
(77)90052-5.
Ali, M. & Chaudry, M.A., 1990. Inter-regional farm efficiency in Pakistan’s Punjab: A frontier
production function study. Journal of Agricultural Economics, 41: 62-74.
http://dx.doi.org/10.1111/j.1477-9552.1990.tb00619.x
Battese, G. E. and Coelli, T. J., 1995. A model for technical inefficiency effects in a stochastic frontier
production function for panel data. Empirical Economics, 20 (2): 325-332, DOI:
10.1007/BF01205442
Bogetic, Y., Bussolo, M., Ye, X., Medvedev, D., Wodon, Q. & Boakye, D., 2007. Ghana’s Growth
Story: How
to Accelerate Growth and Achieve MDGs. Background paper for Ghana CEM, April.
Charnes, A., Copper, W. & Rhodes E., 1978. Measuring the efficiency of decision-making units.
European Journal of Operations Research, 2: 429-444. http://dx.doi.org/10.1016/0377-
2217(78)90138-8
Clark, C., 1957. Clark s discussion of Farrell s work is on page 282 of Farrell 1957. The
measurement of productive efficiency. Journal of the Royal Statistical Society Series A, (General )
120 (3: 253-290..
Coelli T.J., 1995. Estimators and Hypothesis Tests for a Stochastic Frontier Function: A Monte Carlo
Analysis. Journal of Productivity Analysis, 6(4), pp. 247–268. http://dx.doi.org/10.1007/BF01076978
Coelli T.J, Prasada R, & Battese G.E., 1998. An Introduction to Efficiency and Productivity Analysis.
Kluwer Academic Publishers. Boston. http://dx.doi.org/10.1007/978-1-4615-5493-6.
Coulombe, H., & Wodon, Q., 2007. Combining census and household survey data for better targeting:
The
west and central Africa poverty mapping initiative. Findings No. 280, Africa, Region, the World
Bank,
Washington, D.C.
Debreu, G., 1951. The coefficient of resource utilisation. Econometrica 19: 273–92. [online]
http://www.jstor.org/stable/pdfplus/1906814.pdf. [Accessed 4 December 2011, 20:00 GMT].
Djokoto, J. G., 2012. Technical efficiency of agriculture in ghana: a time series stochastic frontier
estimation approach. Journal of Agricultural Science. 4 (1): 154-163. [online]
http://www.ccsenet.org/journal/index.php/jas/article/viewFile/11116/9380 [Accessed 2 December
2012, 16:50 GMT].
8
9. Journal of Biology, Agriculture and Healthcare www.iiste.org
ISSN 2224-3208 (Paper) ISSN 2225-093X (Online)
Vol 2, No.2, 2012
Ezeh C.I., 2004. A comparative study of Fadama and Non-Fadama crop farmers in Osisioma-Ngwa
L.G.A, Abia State. Nigeria. Journal of Sustainable Tropical Agricultural Research, 11.
Farrell, M. J., 1957. The measurement of productive efficiency. Journal of the Royal Statistical
Society. Series A (General), 120 (3): 253-290. [Online] from : http://www.jstor.org/stable/2343100
[Accessed 13 October 2011, 14:41 GMT].
Fleming, E., Fleming, P., Rodgers, H., Grifften, G. & Johnston, D., 2004. Animal efficiency in an
intensive beef production. Genetic Breeding Unit, University of New England, Armidale, NSW,
Australia.
Fried, H. O., Lovell, C. A. K. and Schmidt, S. S. (eds.), 1993. The measurement of productive
efficiency. techniques and applications. New York: Oxford University Press.
Greene W.H., 2004. Fixed and random effects in stochastic frontier models. Journal of Productivity
Analysis,23(1: 7-32. http://dx.doi.org/10.1007/s11123-004-8545-1
Hayami, Y. and Ruttan, V.W., 1970. Agricultural productivity differences among countries.
American Economic Review 60: 895-911.
Igliori, D. C., 2005. Determinants of technical efficiency in agriculture and cattle ranching: A spatial
analysis for the Brazilian amazon. Working Paper No. 09. University of Cambridge Land Economy.
[Online] http://ssrn.com/abstract=753499 [Accessed 2 May 2011, 14:30 GMT].
Iyer, K. G., Rambaldi, A. N. and Tang, K. K., 2008. Efficiency externalities of trade and alternative
forms of foreign investment in OECD countries. Journal of Applied Econometrics 23 (6): 749–766.
DOI: 10.1002/jae.1024
Kumbhakar, S. C., and Lovell, C. A. K. 2000. Stochastic Frontier Analysis. New York, NY:
Cambridge University Press.
Lall, P., Featherstone, A. and Norman, D.W., 2000. Productive efficiency and growth policies for the
Caribbean. Applied Economics, 32 (11): 1483-1493.
Mathijs, E, Maertens, A. and Vranken, L., 2001. Technical efficiency and farm organization in Czech
and Slovak agriculture. [Online] http://www.agr.kuleuven.ac.be/aee/clo/ace97/WP3.doc [Accessed 27
April 2011, 19:29 GMT].
Meeusen W., & van den Broeck, J., 1977. Efficiency estimation from Cobb-Douglas production
functions with composed error. International Economic Review, 18: 435–444.
http://dx.doi.org/10.2307/2525757
Milner, C and Weyman–Jones, T., 2003. Relative national efficiency and country size: evidence for
developing countries. Review of Development Economics 7 (1): 1–14.
MOFA. 2007. Food and Agriculture Sector Development Policy (FASDEP II). Ministry of Food &
Agriculture, Ghana.
MOFA. 2011. Agriculture in Ghana-Facts and Figures (2010). Ministry of Food & Agriculture, Ghana.
Mundlak, Y. and Hellinghausen, R., 1982. The inter-county agricultural production function: Another
view. American Journal of Agricultural Economics 64: 664-672.
Nkamleu, G. B., 2004. Productivity growth, technical progress and efficiency change in African
agriculture. Africa Development Bank. pp. 203-222
Rao, D.S.P., O’Donnell, J. and Battese, G.E., 2003. Metafrontier functions for the study of inter-
regional productivity differences. Centre for Efficiency and Productivity Analysis Working Paper 1.
Schippers, R. R. 2000. African indigenous vegetables, an overview of the cultivated species, Chathan
UK: Natural Resources Institute/ACP-EU Technical Centre for Agriculture and Rural Cooperation.
Sotnikov, S., 1998. Evaluating the effects of price and trade liberalisation on the technical efficiency of
agricultural production in a transition economy: The case of Russia. European Review of Agricultural
Economics 25(3): 412-431. Doi: 10.1093/erae/25.3.412.
UNCTAD. 2011. UNCTADSTAT Database. [Online] http://unctadstat.unctad.org [Accessed on 9
December 2011, 16:26 GMT]
World Bank. 2008. Annual Report. Washington D.C. New York.
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Appendix
Table 1. Estimates of Stochastic Production Function and Technical Efficiency Estimates
Dependent Variable: Value Added Agriculture (US) in natural logarithm
Variables (All in natural logs) Parameters Estimates
Constant β 31.4419***
0
Agricultural land in (hectares) ( X 1 ) β -2.4889***
1
Labour in (number of persons) ( X 2 ) β 1.2214**
2
Fertilizer consumption (tonnes) ( X 3 ) β 1.1604*
3
Tractor and combines (numbers) ( X 4 ) β 0.09668**
4
Other agrochemicals (US dollars) ( X 5 ) β 0.10654
5
Seeds (tonnes) ( X 6 ) β 0.10199
6
Returns to Scale 0.19811
Mean Technical Efficiency 0.79
Technical Effects Coefficients
Constant δ0 -0.15234
Land worked per Agric. Labour (Z1) δ1 -0.32397
Net Investment in Agric. (Z2) δ2 -0.042741
Proportion of domestically produced food consumed (Z3) δ3 0.30918
Percentage of roads paved (Z4) δ4 0.12840
Agricultural Exports (Z5) δ5 -0.05740
Variance Parameters
Sigma squared σ 2 0.05673**
2u
Gamma γ = σ 0.9999***
σ 2 s
Log likelihood function 15.6747
LR test on one sided error 8.5934
Mr. Justice G. Djokoto holds a B.Sc. degree in Agriculture with specialisation in Agricultural
Economics and Master of Philosophy degree in Agricultural Administration both from the University
of Ghana, Legon. Prior to enrolling for the Master’s programme, he obtained a Post graduate diploma
in Education. Justice is a member of faculty in the Agribusiness department of Central Business
School, Central University College in Accra, Ghana and a member of Econometric Society. Foreign
direct investment and agribusiness, technical and economic performance of organisations, and
technology and record keeping of agribusiness firms are research areas that engage his attention.
10
11. International Journals Call for Paper
The IISTE, a U.S. publisher, is currently hosting the academic journals listed below. The peer review process of the following journals
usually takes LESS THAN 14 business days and IISTE usually publishes a qualified article within 30 days. Authors should
send their full paper to the following email address. More information can be found in the IISTE website : www.iiste.org
Business, Economics, Finance and Management PAPER SUBMISSION EMAIL
European Journal of Business and Management EJBM@iiste.org
Research Journal of Finance and Accounting RJFA@iiste.org
Journal of Economics and Sustainable Development JESD@iiste.org
Information and Knowledge Management IKM@iiste.org
Developing Country Studies DCS@iiste.org
Industrial Engineering Letters IEL@iiste.org
Physical Sciences, Mathematics and Chemistry PAPER SUBMISSION EMAIL
Journal of Natural Sciences Research JNSR@iiste.org
Chemistry and Materials Research CMR@iiste.org
Mathematical Theory and Modeling MTM@iiste.org
Advances in Physics Theories and Applications APTA@iiste.org
Chemical and Process Engineering Research CPER@iiste.org
Engineering, Technology and Systems PAPER SUBMISSION EMAIL
Computer Engineering and Intelligent Systems CEIS@iiste.org
Innovative Systems Design and Engineering ISDE@iiste.org
Journal of Energy Technologies and Policy JETP@iiste.org
Information and Knowledge Management IKM@iiste.org
Control Theory and Informatics CTI@iiste.org
Journal of Information Engineering and Applications JIEA@iiste.org
Industrial Engineering Letters IEL@iiste.org
Network and Complex Systems NCS@iiste.org
Environment, Civil, Materials Sciences PAPER SUBMISSION EMAIL
Journal of Environment and Earth Science JEES@iiste.org
Civil and Environmental Research CER@iiste.org
Journal of Natural Sciences Research JNSR@iiste.org
Civil and Environmental Research CER@iiste.org
Life Science, Food and Medical Sciences PAPER SUBMISSION EMAIL
Journal of Natural Sciences Research JNSR@iiste.org
Journal of Biology, Agriculture and Healthcare JBAH@iiste.org
Food Science and Quality Management FSQM@iiste.org
Chemistry and Materials Research CMR@iiste.org
Education, and other Social Sciences PAPER SUBMISSION EMAIL
Journal of Education and Practice JEP@iiste.org
Journal of Law, Policy and Globalization JLPG@iiste.org Global knowledge sharing:
New Media and Mass Communication NMMC@iiste.org EBSCO, Index Copernicus, Ulrich's
Journal of Energy Technologies and Policy JETP@iiste.org Periodicals Directory, JournalTOCS, PKP
Historical Research Letter HRL@iiste.org Open Archives Harvester, Bielefeld
Academic Search Engine, Elektronische
Public Policy and Administration Research PPAR@iiste.org Zeitschriftenbibliothek EZB, Open J-Gate,
International Affairs and Global Strategy IAGS@iiste.org OCLC WorldCat, Universe Digtial Library ,
Research on Humanities and Social Sciences RHSS@iiste.org NewJour, Google Scholar.
Developing Country Studies DCS@iiste.org IISTE is member of CrossRef. All journals
Arts and Design Studies ADS@iiste.org have high IC Impact Factor Values (ICV).