The Experts below are selected from a list of 360 Experts worldwide ranked by ideXlab platform
Donald F Larson - One of the best experts on this subject based on the ideXlab platform.
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heterogeneous technology and panel data the case of the Agricultural Production function
Journal of Development Economics, 2008Co-Authors: Yair Mundlak, Rita Butzer, Donald F LarsonAbstract:The paper presents empirical analysis of a panel of countries to estimate an Agricultural Production function using a measure of capital in agriculture absent from most studies. The authors employ a heterogeneous technology framework where implemented technology is chosen jointly with inputs to interpret information obtained in the empirical analysis of panel data. The paper discusses the scope for replacing country and time effects by observed variables and the limitations of instrumental variables. The empirical results differ from those reported in the literature for cross-country studies, largely in augmenting the role of capital, in combination with productivity gains, as a driver of Agricultural growth. The results indicate that total factor productivity increased at an average rate of 3.2 percent, accounting for 59 percent of overall growth. Most of the remaining gains stem from large inflows of fixed capital into agriculture. The results also suggest possible constraints to fertilizer use.
Fredrick Ikpesu - One of the best experts on this subject based on the ideXlab platform.
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credit supply and Agricultural Production in nigeria a vector autoregressive var approach
2016Co-Authors: Friday Osemenshan Anetor, Chris Ogbechie, Ikechukwu Kelikume, Fredrick IkpesuAbstract:Agriculture used to be the mainstay of the Nigerian economy contributing over 70 percent to the country’s total output and accounts for over 90 percent of total food consumption. However, the performance of the sector has drastically deteriorated since the discovery of crude oil in 1956. The strategic roles of the Agricultural sector in national development led the Federal Government to establish Agricultural sector credit schemes and various other institutions to boost the level of productivity in the sector. Notwithstanding, the intensification of government and private sector support to the sector, the contribution of Agricultural to GDP has fallen significantly creating a fundamental gap in resource allocation to the Agricultural sector. The basic question raised in this research, is, does increased credit supply through the Agricultural Credit Guarantee Scheme Fund (ACGSF) and commercial loans to the sector boost Agricultural sector productivity? This study examines the impact of the credit supply, and various commercial bank loan schemes on Agricultural sector Production using vector autoregressive (VAR) approach. Using time series data sourced from Central Bank of Nigeria Statistical Bulletin over the sample period of 1981-2013, the study found ACGSF to have performed poorly in explaining Agricultural sector performance while commercial loans to Agricultural sector had a significant impact on Agricultural Production. The policy implication of this study is that government should encourage the commercial bank to finance investment in the Agricultural sector by granting credit facilities at below market interest rates.
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credit supply and Agricultural Production in nigeria a vector autoregressive var approach
Journal of economics and sustainable development, 2016Co-Authors: Friday Osemenshan Anetor, Chris Ogbechie, Ikechukwu Kelikume, Fredrick IkpesuAbstract:Agriculture used to be the mainstay of the Nigerian economy contributing over 70 percent to the country’s total output and accounts for over 90 percent of total food consumption. However, the performance of the sector has drastically deteriorated since the discovery of crude oil in 1956. The strategic roles of the Agricultural sector in national development led the Federal Government to establish Agricultural sector credit schemes and various other institutions to boost the level of productivity in the sector. Notwithstanding, the intensification of government and private sector support to the sector, the contribution of Agricultural to GDP has fallen significantly creating a fundamental gap in resource allocation to the Agricultural sector. The basic question raised in this research, is, does increased credit supply through the Agricultural Credit Guarantee Scheme Fund (ACGSF) and commercial loans to the sector boost Agricultural sector productivity? This study examines the impact of the credit supply, and various commercial bank loan schemes on Agricultural sector Production using vector autoregressive (VAR) approach. Using time series data sourced from Central Bank of Nigeria Statistical Bulletin over the sample period of 1981-2013, the study found ACGSF to have performed poorly in explaining Agricultural sector performance while commercial loans to Agricultural sector had a significant impact on Agricultural Production. The policy implication of this study is that government should encourage the commercial bank to finance investment in the Agricultural sector by granting credit facilities at below market interest rates. Keywords : ACGSF; Agricultural Production; Credit Supply; Nigeria; Vector Autoregressive Model
Yair Mundlak - One of the best experts on this subject based on the ideXlab platform.
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heterogeneous technology and panel data the case of the Agricultural Production function
Journal of Development Economics, 2008Co-Authors: Yair Mundlak, Rita Butzer, Donald F LarsonAbstract:The paper presents empirical analysis of a panel of countries to estimate an Agricultural Production function using a measure of capital in agriculture absent from most studies. The authors employ a heterogeneous technology framework where implemented technology is chosen jointly with inputs to interpret information obtained in the empirical analysis of panel data. The paper discusses the scope for replacing country and time effects by observed variables and the limitations of instrumental variables. The empirical results differ from those reported in the literature for cross-country studies, largely in augmenting the role of capital, in combination with productivity gains, as a driver of Agricultural growth. The results indicate that total factor productivity increased at an average rate of 3.2 percent, accounting for 59 percent of overall growth. Most of the remaining gains stem from large inflows of fixed capital into agriculture. The results also suggest possible constraints to fertilizer use.
Sufen Wang - One of the best experts on this subject based on the ideXlab platform.
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Agricultural Production planning approach based on interval fuzzy credibility constrained bi level programming and nerlove supply response theory
Journal of Cleaner Production, 2019Co-Authors: Fan Zhang, Bernard A Engel, Chenglong Zhang, Shanshan Guo, Ping Guo, Sufen WangAbstract:Abstract: When planning Agricultural Production, planting area and water allocation are two major subjects faced by decision makers. In this study, a framework integrated Nerlove supply response model (Nerlove model) and interval fuzzy credibility-constraint bi-level programming (IFCBP) model is developed for planning the Agricultural Production in arid and semi-arid regions. Through Nerlove model, the planning process of crop planting area was described as an economic problem for forecasting farmers' behavior rather than an optimization problem for allocating farmland resources, and the relationship between crop planting area and market price can be obtained and further provide credible future crop planting area information. The IFCBP model can not only deal with uncertainties presented as interval and fuzzy numbers but also examine the credibility of the constraints and handle tradeoffs between two-level decision makers. To solve the IFCBP model, a solution method based on the interval interactive algorithm and credibility-cut method is proposed. Then, to verify the validity of the developed framework and solving method for Agricultural Production planning, they were applied to a real-case in the middle reaches of the Heihe River basin, northwest China. The forecasting results obtained from Nerlove model have better performance in predicting the future planting area of corn and vegetable than wheat, indicating that wheat plays a more vulnerable role in the decision-making process of planting area owing to its higher substitutability. The results show that the proposed framework can tackle two-level decision makers’ concerns under uncertainties featured as inexact and fuzzy numbers, which can help regional managers plan future resources effectively. Furthermore, a comparison was made between IFCBP and two corresponding single-level models in this study. The comparison indicates that the developed model provides an effective tradeoff between two decision makers from different decision-making levels in IFCBP. The developed framework provides managers an effective way to plan Agricultural Production in arid and semi-arid regions, and the developed model and related thinking may help solve similar problems.
Molly Jahn - One of the best experts on this subject based on the ideXlab platform.
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vulnerabilities to Agricultural Production shocks an extreme plausible scenario for assessment of risk for the insurance sector
Climate Risk Management, 2016Co-Authors: Tobias Lunt, Aled Jones, William S Mulhern, David Lezaks, Molly JahnAbstract:Climate risks pose a threat to the function of the global food system and therefore also a hazard to the global financial sector, the stability of governments, and the food security and health of the world’s population. This paper presents a method to assess plausible impacts of an Agricultural Production shock and potential materiality for global insurers. A hypothetical, near-term, plausible, extreme scenario was developed based upon modules of historical Agricultural Production shocks, linked under a warm phase El Nino-Southern Oscillation (ENSO) meteorological framework. The scenario included teleconnected floods and droughts in disparate Agricultural Production regions around the world, as well as plausible, extreme biotic shocks. In this scenario, global crop yield declines of 10% for maize, 11% for soy, 7% for wheat and 7% for rice result in quadrupled commodity prices and commodity stock fluctuations, civil unrest, significant negative humanitarian consequences and major financial losses worldwide. This work illustrates a need for the scientific community to partner across sectors and industries towards better-integrated global data, modeling and analytical capacities, to better respond to and prepare for concurrent Agricultural failure. Governments, humanitarian organizations and the private sector collectively may recognize significant benefits from more systematic assessment of exposure to Agricultural climate risk.