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Angelova, D. (2014). The state-contingent approach to production and choice under uncertainty: usefulness as a basis for economic modeling. FACCE MACSUR Mid-term Scientific Conference, 3(S) Sassari, Italy.
Abstract: The state-contingent approach developed by Chambers and Quiggin (2000) constitutes an attractive blend of a theory of production analysis under uncertainty and a theory of decision-making under uncertainty. One of the goals of this contribution is to introduce the reader to the approach by outlining its contents while comparing and contrasting it to related theories. With respect to production analysis: an emphasis is made on the ability of the approach to deliver well defined cost functions corresponding to stochastic production technologies. With respect to decision-making under uncertainty: the comparison with other theories consistent with a rational agent emphasizes the production theoretical basis of the state-contingent approach. It is the author’s belief that appropriately categorizing the state-contingent approach serves the primary goal of this work: to explore its usefulness as a basis for economic modeling. Some challenges regarding an empirical implementation are discussed: challenges in estimating the parameters of a state-contingent technology representation in general, as well as challenges arising from the fact that the approach is constructed around the argument pioneered by Leonard J Savage: that probabilities underlying economic decision-making are inherently subjective.(The financial support of ScienceCampus Halle is gratefully acknowledged.)
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Angelova, D. (2014). The state-contingent approach to production and choice under uncertainty: usefulness as a basis for economic modeling (Vol. 3). FACCE MACSUR Reports, 3.
Abstract: The state-contingent approach developed by Chambers and Quiggin (2000) constitutes an attractive blend of a theory of production analysis under uncertainty and a theory of decision-making under uncertainty.One of the goals of this contribution is to introduce the reader to the approach by outlining its contents while comparing and contrasting it to related theories. With respect to production analysis: an emphasis is made on the ability of the approach to deliver well defined cost functions corresponding to stochastic production technologies. With respect to decision-making under uncertainty: the comparison with other theories consistent with a rational agent emphasizes the production theoretical basis of the state-contingent approach.It is the author’s belief that appropriately categorizing the state-contingent approach serves the primary goal of this work: to explore its usefulness as a basis for economic modeling. Some challenges regarding an empirical implementation are discussed: challenges in estimating the parameters of a state-contingent technology representation in general, as well as challenges arising from the fact that the approach is constructed around the argument pioneered by Leonard J Savage: that probabilities underlying economic decision-making are inherently subjective.(The financial support of ScienceCampus Halle is gratefully acknowledged.) No Label
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Kersebaum, K., & C,. (2014). Results of uncalibrated model runs available (ROTATIONEFFECTS) (Vol. 3).
Abstract: The study ROTATIONEFFECT aims to compare the output of different models simulating field data sets with multi-year crop rotations including different treatments. Data sets for 5 locations in Europe were distributed to 19 interested modeller groups comprising a total of 201 crop growth seasons. In a first step only minimal information for calibration were provided to the modellers. In total 14 modelling teams sent their “uncalibrated” results as single-year calculations and/or calculations of rotation depending on the capability of the model. 7-10 models were capable to run the rotations as continuous runs. Up to 12 models provided single year simulations of at least one crop. Comparing results of models which provided both single year and continuous runs, show a little lower root mean square error for the continuous rotations runs. Cereal crop yields were generally better simulated than tuber/beet yields. Additionally, the models’ response to various treatments (irrigation/rainfed, nitrogen level, CO2 level, residue management/ tillage, catch crops) were compared to observed differences. First indicators of model performance have been developed and presented at international conferences. No Label
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Vitali, A., Lana, E., Amadori, M., Bernabucci, U., Nardone, A., & Lacetera, N. (2014). Analysis of factors associated with mortality of heavy slaughter pigs during transport and lairage. J. Anim. Sci., 92(11), 5134–5141.
Abstract: The study was based on data collected during 5 yr (2003-2007) and was aimed at assessing the effects of the month, slaughter house of destination (differing for stocking density, openings, brightness, and cooling device types), length of the journey, and temperature-humidity index (THI) on mortality of heavy slaughter pigs (approximately 160 kg live weight) during transport and lairage. Data were obtained from 24,098 journeys and 3,676,153 pigs transported from 1,618 farms to 3 slaughter houses. Individual shipments were the unit of observation. The terms dead on arrival (DOA) and dead in pen (DIP) refer to pigs that died during transport and in lairage at the abattoir before slaughtering, respectively. These 2 variables were assessed as the dependent counts in separate univariate Poisson regressions. The independent variables assessed univariately in each set of regressions were month of shipment, slaughter house of destination, time traveled, and each combination of the month with the time traveled. Two separate piecewise regressions were done. One used DOA counts within THI levels over pigs transported as a dependent ratio and the second used DIP counts within THI levels over pigs from a transport kept in lairage as a dependent ratio. The THI was the sole independent variable in each case. The month with the greatest frequency of deaths was July with a risk ratio of 1.22 (confidence interval: 1.06-1.36; P < 0.05) and 1.27 (confidence interval: 1.06-1.51; P < 0.05) for DOA and DIP, respectively. The lower mortality risk ratios for DOA and DIP were recorded for January and March (P < 0.05). The aggregated data of the summer (June, July, and August) versus non-summer (January, March, September, and November) months showed a greater risk of pigs dying during the hot season when considering both transport and lairage (P < 0.05). The mortality risk ratio of DIP was lower at the slaughter house with the lowest stocking density (0.64 m(2)/100 kg live weight), large open windows on the roof and sidewalls, low brightness (40 lx) lights, and high-pressure sprinklers as cooling devices. The mortality risk ratio of DOA increased significantly for journeys longer than 2 h, whereas no relationship was found between length of transport and DIP. The piecewise analysis pointed out that 78.5 and 73.6 THI were the thresholds above which the mortality rate increased significantly for DOA and DIP, respectively. These results may help the pig industry to improve the welfare of heavy slaughter pigs during transport and lairage.
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Rusu, T. (2014). Impact of Climate Change on Crop Land and Technological Recommendations for the Main Crops in Transylvanian Plain, Romania (Vol. 3).
Abstract: The Transylvanian Plain (TP) is an important agricultural production area of Romania that is included among the areas with the lowest potential of adapting to climate changes in Europe. Thermal and hydric regime monitoring is necessary to identify and implement measures of adaptation to the impacts of climate change. Soil moisture and temperature regimes were evaluated using a set of 20 data logging stations positioned throughout the plain. Each station stores electronic data regarding ground temperature at 3 depths (10, 30, 50 cm), humidity at a depth of 10 cm, air temperature (at 1 m) and precipitation. For agricultural crops, the periods of drought and extreme temperatures require specific measures of adaptation to climate changes. During the growing season of crops in the spring (April – October) in the southeastern, southern, and eastern escarpments, precipitation decreased by 43.8 mm, the air temperature increased by 0.37°C, and the ground temperature increased by 1.91°C at a depth of 10 cm, 2.22°C at a depth of 20 cm and 2.43°C at a depth of 30 cm compared with values recorded for the northern, northwestern or western escarpments. Water requirements were ensured within an optimal time frame for 58.8-62.1% of the spring row crop growth period, with irrigation being necessary to guarantee the optimum production potential. The biologically active temperature recorded in the TP demonstrates the need to renew the division of the crop areas reported in the literature. No Label
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