The Experts below are selected from a list of 41094 Experts worldwide ranked by ideXlab platform
Charles Towe - One of the best experts on this subject based on the ideXlab platform.
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The implications of the US renewable fuel standard programme for Farm Structure
Applied Economics, 2015Co-Authors: Constant I. Tra, Charles ToweAbstract:ABSTRACTWe investigate the impact of the 2005 Renewable Fuel Standard (RFS) on Farm Structure, particularly Farm size. We rely on the salience of a new ethanol plant in a Farmers’ local neighbourhood to identify the impact of the RFS mandate on these spatially advantaged Farms. To control for the nonrandom selection of ethanol production facilities, we utilize a propensity score matching estimator, and to remove impact of Farm-level or market shifting unobservables resulting from shifts in commodity prices we employ a difference-in-difference (DD) matching approach. We estimate the treatment effect of an ethanol production facility on Farm size prior to the RFS mandate and after the RFS programme. The effect of the RFS policy on Farm size is obtained as the difference between these two DD matching estimators. Overall, our results suggest that the RFS programme raised the probability of Farm size increase by roughly 12–18%, on average, for Farms located within a 30-mile radius of new ethanol plants. In add...
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the implications of the u s renewable fuel standard program for Farm Structure
Social Science Research Network, 2012Co-Authors: Constant I. Tra, Charles ToweAbstract:This study investigates the extent to which the 2005 Renewable Fuel Standard (RFS) has affected Farm Structure, in particular Farm size. Our empirical strategy relies on the opening of an ethanol plant in a Farmer’s local neighborhood. We identify the effect of the RFS on the size of Farms located in the vicinity of new ethanol plants. Using a unique Farm-level panel dataset from the June Agricultural Survey (JAS), the empirical estimation employs two difference-in-difference (DD) propensity score matching models, one prior to the RFS mandate and one incorporating the RFS program, to estimate an average treatment effect on Farm size of an ethanol production facility. We then measure the effect of the RFS program on Farmland Structure as the difference between these two DD matching estimators. Overall, our results suggest that the RFS program raised the probability of Farm size increase by roughly 12 to 18%, on average, for Farms located within a 30-mile radius of new ethanol plants. In addition, the program contributed to a net increase in Farm size of 25 to 32%, on average, for those spatially advantaged Farms.
Constant I. Tra - One of the best experts on this subject based on the ideXlab platform.
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The implications of the US renewable fuel standard programme for Farm Structure
Applied Economics, 2015Co-Authors: Constant I. Tra, Charles ToweAbstract:ABSTRACTWe investigate the impact of the 2005 Renewable Fuel Standard (RFS) on Farm Structure, particularly Farm size. We rely on the salience of a new ethanol plant in a Farmers’ local neighbourhood to identify the impact of the RFS mandate on these spatially advantaged Farms. To control for the nonrandom selection of ethanol production facilities, we utilize a propensity score matching estimator, and to remove impact of Farm-level or market shifting unobservables resulting from shifts in commodity prices we employ a difference-in-difference (DD) matching approach. We estimate the treatment effect of an ethanol production facility on Farm size prior to the RFS mandate and after the RFS programme. The effect of the RFS policy on Farm size is obtained as the difference between these two DD matching estimators. Overall, our results suggest that the RFS programme raised the probability of Farm size increase by roughly 12–18%, on average, for Farms located within a 30-mile radius of new ethanol plants. In add...
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the implications of the u s renewable fuel standard program for Farm Structure
Social Science Research Network, 2012Co-Authors: Constant I. Tra, Charles ToweAbstract:This study investigates the extent to which the 2005 Renewable Fuel Standard (RFS) has affected Farm Structure, in particular Farm size. Our empirical strategy relies on the opening of an ethanol plant in a Farmer’s local neighborhood. We identify the effect of the RFS on the size of Farms located in the vicinity of new ethanol plants. Using a unique Farm-level panel dataset from the June Agricultural Survey (JAS), the empirical estimation employs two difference-in-difference (DD) propensity score matching models, one prior to the RFS mandate and one incorporating the RFS program, to estimate an average treatment effect on Farm size of an ethanol production facility. We then measure the effect of the RFS program on Farmland Structure as the difference between these two DD matching estimators. Overall, our results suggest that the RFS program raised the probability of Farm size increase by roughly 12 to 18%, on average, for Farms located within a 30-mile radius of new ethanol plants. In addition, the program contributed to a net increase in Farm size of 25 to 32%, on average, for those spatially advantaged Farms.
Zvi Lerman - One of the best experts on this subject based on the ideXlab platform.
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land reform Farm Structure and agricultural performance in cis countries
China Economic Review, 2009Co-Authors: Zvi LermanAbstract:Abstract This article examines the impacts of land reform policies in CIS countries on agricultural performance, including growth and productivity. The focal thesis of the study is that agricultural development in CIS is mainly driven by policy factors, and it is changes in policies (whether agricultural or general economic) that cumulatively affect growth, employment, and productivity in the large rural sector in CIS. The data used in our analysis are taken from an authoritative database that utilizes statistics regularly reported to the Interstate Statistical Committee of the CIS in Moscow by the member countries (CIS 2005). The CIS database covers all the years from 1980 to 2004, and thus provides a useful comparative view of the last decade of the Soviet regime and the 15 years of transition. Some inevitable gaps in the CIS database have been filled in from country yearbooks.
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land reform Farm Structure and agricultural performance in cis countries
2007Co-Authors: Zvi LermanAbstract:This article examines the impacts of land reform policies in CIS countries on agricultural performance, including growth and productivity. The focal thesis of the study is that agricultural development in CIS is mainly driven by policy factors, and it is changes in policies (whether agricultural or general economic) that cumulatively affect growth, employment, and productivity in the large rural sector in CIS. The data used in our analysis are taken from an authoritative database that utilizes statistics regularly reported to the Interstate Statistical Committee of the CIS in Moscow by the member countries (CIS 2005). The CIS database covers all the years from 1980 to 2004, and thus provides a useful comparative view of the last decade of the Soviet regime and the 15 years of transition. Some inevitable gaps in the CIS database have been filled in from country yearbooks. (This abstract was borrowed from another version of this item.)
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evolving Farm Structures and land use patterns in former socialist countries
2004Co-Authors: Zvi Lerman, Csaba Csaki, Gershon FederAbstract:The paper reviews the role of land policies in the evolving Farm Structure of transition countries in Central and Eastern Europe (CEE) and the Commonwealth of Independent States (CIS). The discussion shows how different policies for land property rights, degrees of control of land rental and sale markets, and procedures for restructuring former collective or state Farms resulted in significantly different Farm Structures in CEE countries compared with those in the CIS. In particular, secure land rights, greater emphasis on individualization of land, and more liberal land market policies in CEE generated a Farmer sector with a relatively large share of family Farms and viable corporate Farms. On the other hand, limited tenure security, ineffective individualization of land rights, and restrictive land market policies in most of the CIS produced a Farming Structure dominated by large and generally nonviable jointly-owned Farms that function much like the old collective Farms. Family Farms are slow to emerge in transition countries with inadequate land policies. The agricultural sector in countries dominated by inefficient Farm organizations is characterized by low productivity and misallocation
Muhammad Nadeem - One of the best experts on this subject based on the ideXlab platform.
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a comparison review on transmission mode for onshore integration of offshore wind Farms hvdc or hvac
Electronics, 2021Co-Authors: Syed Rahman, Irfan Khan, Hend I Alkhammash, Muhammad NadeemAbstract:The development of offshore wind Farms (WF) is inevitable as they have exceptional resistance against climate change and produce clean energy without hazardous wastes. The offshore WF usually has a bigger generation capacity with less environmental impacts, and it is more reliable too due to stronger and consistent sea winds. The early offshore WF installations are located near the shore, whereas most modern installations are located far away from shore, generating higher power. This paradigm shift has forced the researchers and industry personnel to look deeper into transmission options, namely, high voltage AC transmission (HVAC) and high voltage DC transmission (HVDC). This evaluation can be both in terms of power carrying capability as well as cost comparisons. Additionally, different performance requirements such as power rating, onshore grid requirements, reactive power compensation, etc., must be considered for evaluation. This paper elaborately reviews and explains the offshore wind Farm Structure and performance requirements for bulk offshore power transfer. Based on the Structure and performance requirements, both HVDC and HVAC transmission modes are compared and analyzed critically. Finally, a criterion for selection and increasing popularity of HVDC transmission is established.
Andres M Perez - One of the best experts on this subject based on the ideXlab platform.
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managing complexity simplifying assumptions of foot and mouth disease models for swine
Transboundary and Emerging Diseases, 2018Co-Authors: Amy C Kinsley, Kimberly Vanderwaal, Meggan E Craft, Robert B Morrison, Andres M PerezAbstract:Compartmental models have often been used to test the effectiveness and efficiency of alternative control strategies to mitigate the spread of infectious animal diseases. A fundamental principle of epidemiological modelling is that models should start as simple as possible and become as complex as needed. The simplest version of a compartmental model assumes that the population is closed, void of births and deaths and that this closed population mixes homogeneously, meaning that each infected individual has an equal probability of coming into contact with each susceptible individual in the population. However, this assumption may oversimplify field conditions, leading to conclusions about disease mitigation strategies that are suboptimal. Here, we assessed the impact of the homogeneous mixing/closed population assumption, which is commonly assumed for within-Farm models of highly contagious diseases of swine, such as foot-and-mouth disease (FMD), on predictions about disease spread. Incorporation of Farm Structure (different barns or rooms for breeding and gestation, farrowing, nursery and finishing) and demography (piglet births and deaths, and animal movement within and off of the Farm) resulted in transmission dynamics that differed in the latter portion of an outbreak. Specifically, Farm Structure and demography, which were included in the farrow to finish and farrow to wean Farms, resulted in FMD virus persistence within the population under certain conditions. Results here demonstrate the impact of incorporating Farm Structure and demography into models of FMD spread in swine populations and will ultimately contribute to the design and evaluation of effective disease control strategies to mitigate the impact of potential incursions.
