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| Registros recuperados: 20 | |
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| Bokusheva, Raushan; Hockmann, Heinrich. |
| This paper aims to contribute to a better understanding of possible causes of considerable production variability that characterised Russian agriculture during the last decade. The study investigates production risk and technical inefficiency as two sources that influence production variability. Using panel data from 1996 to 2001, an empirical analysis of 443 large agricultural enterprises from three regions in central, southern and Volga Russia is conducted. A production function specification accounting for the effect of inputs on both risk and technical inefficiency is found to describe production technologies of Russian farms more appropriately than the traditional stochastic frontier formulation. |
| Tipo: Conference Paper or Presentation |
Palavras-chave: Production risk; Technical efficiency; Panel data; Russian agriculture; Production Economics; D81; Q12. |
| Ano: 2005 |
URL: http://purl.umn.edu/24610 |
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| Kobus, Pawel. |
| The paper deals with the problem of modelling yield risk measures for major crop plants in Poland. Hence, in some cases the gamma distribution offers a better fit to the data than normal distribution, and in addition to linear models, generalized linear models were also used. The research was based on data from Polish FADN, with sample sizes ranging from 416 up to 2300, depending on the crop plant. It was found that models based on the farm level data, can explain on average 20% of variation coefficient unevenness. The most important variables were average yield, type of farming, arable area and land quality. The elimination of the average yield from the models reduced the average determination coefficient to about 9%. |
| Tipo: Presentation |
Palavras-chave: Production risk; Risk measures; Yield distribution; Risk and Uncertainty; Q10; C46. |
| Ano: 2012 |
URL: http://purl.umn.edu/122535 |
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| Carew, Richard; Smith, Elwin G.; Grant, Cynthia. |
| Production functions to explain regional wheat yields have not been studied extensively in the Canadian prairies. The objective of this study is to employ a Just-Pope production function to examine the relationship between fertilizer inputs, soil quality, biodiversity indicators, cultivars qualifying for Plant Breeders’ Rights (PBR), and climatic conditions on the mean and variance of spring wheat yields. Using regional-level wheat data from Manitoba, Canada, model results show nitrogen fertilizer, temporal diversity, and PBR wheat cultivars are associated with increased yield variance. Mean wheat yield is reduced by the proportion of land in wheat, the interaction of growing temperature and precipitation, and spatial diversity. By contrast, higher soil... |
| Tipo: Journal Article |
Palavras-chave: Climate; Fertilizer; Manitoba; Plant Breeders’ Rights; Production risk; Wheat; Yield; Agribusiness; Crop Production/Industries; Farm Management; Land Economics/Use; Productivity Analysis; Risk and Uncertainty; O18; Q16. |
| Ano: 2009 |
URL: http://purl.umn.edu/56649 |
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| Bakhshoodeh, Mohamad; Shajari, S.. |
| This paper focuses on linkage between new rice seed varieties and production risk and also factors affecting adoption of these varieties in Iran. Farm-level data were collected from a sample of 154 rice farms located in two major districts of Fars province in Southern Iran for 2001-02. The risk-premium associated with the use of seed is estimated following by analyzing a moment-based production risk approach. The results show that the risk premium increases with new seed varieties in the lack of appropriate production conditions implying that new seed varieties is a riskincreasing input and involves a higher cost of risk. However, under suitable production conditions, the cultivation of new rice varieties on average ensures greater yield and at the same... |
| Tipo: Conference Paper or Presentation |
Palavras-chave: Production risk; Moments-based estimation; New seed varieties; Rice; Crop Production/Industries; D8; Q12; Q16. |
| Ano: 2006 |
URL: http://purl.umn.edu/25578 |
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| Musshoff, Oliver; Hirschauer, Norbert. |
| Agricultural production relies to a great extent on biological processes in natural environments. In addition to volatile prices, it is thus heavily exposed to risks caused by the variability of natural conditions such as rainfall, temperature and pests. With a view to the apparently lacking support of risky farm production program decisions through formal planning models, the objective of this paper is to examine whether, and eventually by how much, farmers’ “intuitive” program decisions can be improved through formal statistical analyses and stochastic optimization models. In this performance comparison, we use the results of the formal planning approach that are generated in a quasi ex-ante analysis as a normative benchmark for the empirically observed... |
| Tipo: Conference Paper or Presentation |
Palavras-chave: Stochastic optimization; Stochastic processes; Production risk; Program planning; Time series analysis; C1; C61; M11; Q12. |
| Ano: 2008 |
URL: http://purl.umn.edu/36865 |
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| Koundouri, Phoebe; Nauges, Celine. |
| In the estimation of production functions, ignoring risk considerations can cause inefficient estimates, while biased parameter estimates arise in the presence of sample selection. In the presence of uncertainty and selection bias, the latter introduced by the endogeneity of qualitative characteristics of inputs in crop choice, we show that correcting for risk considerations (a la Just and Pope, 1978, 1979) but not selection bias, can produce incorrect inferences in terms of risk behavior. The arguments raised in this study have estimation and policy implications for stochastic production analysis applied to all goods whose qualitative characteristics can affect sample selection. |
| Tipo: Journal Article |
Palavras-chave: Crop choice; Production risk; Sample selection; Production Economics. |
| Ano: 2005 |
URL: http://purl.umn.edu/30977 |
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| Chang, Hung-Hao; Wen, Fang-I. |
| The objective of this paper is to investigate the differences in yield production, production efficiency, and yield risk for farmers with and without off-farm work. Using a nationwide survey of Taiwanese rice farmers, we estimate a stochastic production frontier model accommodating the technical inefficiency and the production risk simultaneously. Applying the stochastic dominance criterion to rank the estimated technical efficiency and yield risk between professional farmers and farmers with off-farm jobs, our empirical analysis shows that off-farm work is significantly associated with lower technical efficiency. Additionally, farmers with off-farm work face higher production risks. Comparing the marginal effects of input uses on technical inefficiency... |
| Tipo: Conference Paper or Presentation |
Palavras-chave: Off-farm work; Technical efficiency; Production risk; Taiwan; Crop Production/Industries; Farm Management. |
| Ano: 2008 |
URL: http://purl.umn.edu/6164 |
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| Belasco, Eric J.; Taylor, Mykel R.; Goodwin, Barry K.; Schroeder, Ted C.. |
| Cattle feeding enterprises operate amid variability originating in prices and production. This research explicitly models yield risks related to cattle feeding by relating the mean and variance of yield performance factors to observable conditioning variables. The results demonstrate that pen characteristics, such as entry weight, gender, placement season, and location influence the mean and variability of yield factors, defined as dry matter feed conversion, average daily gain, mortality, and animal health costs. Ex ante profit distributions, conditional on cattle placement characteristics, are derived through simulation methods to evaluate the effects of price or yield shocks on the distributional characteristics of expected profits. |
| Tipo: Journal Article |
Palavras-chave: Conditional variance; Production risk; Cattle feeding; Yields; Agribusiness; Livestock Production/Industries; Production Economics; Productivity Analysis; Risk and Uncertainty; D24; D81; Q12. |
| Ano: 2009 |
URL: http://purl.umn.edu/48761 |
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| Tarasov, Arthur. |
| Modern methods of quantitative risk analysis, specifically value-at-risk and expected shortfall approach, provide comprehensive and coherent risk evaluation throughout entire distribution of outcomes and can take agricultural business from the realm of uncertainty to specific, quantified risks. Monte Carlo simulation with autocorrelation of standard deviation shows the best results in risk modeling and is used for this research. The analysis showed that production risk is systemic within climatic regions of Ukraine with coefficients of correlation ranging from 0.25 to 0.85. Yield correlation among crops in several oblasts is low to negative, creating opportunities for diversification. However, positive price-yield correlation is dominant for agricultural... |
| Tipo: Article |
Palavras-chave: Production risk; Price risk; Value-at-risk in agriculture; Expected shortfall; Production Economics; Risk and Uncertainty; GA; IN. |
| Ano: 2011 |
URL: http://purl.umn.edu/120240 |
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| Registros recuperados: 20 | |
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