Estimating input allocation for farm supply models

When building an economic model for supply analysis the aim is to model a decision making process of one or more agents which fits the observed practice as good as possible. Hereby the modeller is often confronted with incomplete information about the production process; particular crop specific input data are rarely available. The problem of defining activity related technology inputs coefficients is not new. A good deal of literature comes from the mathematical programming perspective, where input coefficients were estimated using a standard linear regression function to fully represent the mathematical program. However this approach is a pure technical device and may result in an inconsistent model. The author of the paper wants to investigate whether it is possible, employing proper estimation techniques, to simultaneously estimate all unknown coefficients of a mathematical farm supply model. This includes the estimation of parameters of the non linear cost function, used to calibrate and catch the simulation behaviour and the crop specific input coefficients. It is shown that a simultaneous estimation of all parameters improves the goodness of fit of the estimated parameters and that such an approach is technically feasible.farm supply model, input allocation, entropy, HDP, Research Methods/ Statistical Methods,

EU-WIDE FARM TYPES SUPPLY IN CAPRI - HOW TO CONSISTENTLY DISAGGREGATE SECTOR MODELS INTO FARM TYPE MODEL

EU-wide farm supply analysis, highest posterior density estimator, CAPRI, Research Methods/ Statistical Methods,

RECOVERING LOCALIZED INFORMATION ON AGRICULTURAL STRUCTURE UNDERLYING DATA CONFIDENTIALITY REGULATIONS - POTENTIALS OF DIFFERENT DATA AGGREGATION AND SEGREGATION TECHNIQUES

The modelling and information system RAUMIS is used for policy impact assessment to measure the impact of agriculture on the environment. The county level resolution often limits the analysis and a further disaggregation at the municipality level would reduce aggregation bias and improve the assessment. Although the necessary data exists in Germany, data protection rules (DPR) prohibit their direct use. With methods such as the Locally Weighted Averages (LWA), and with aggregation singling production activities into larger groups of activities, the data at the municipality level can be made publicly available. However, this reduces the information content and introduces an additional error. This paper’s aim is to investigate how much information is necessary to satisfactorily estimate Germany-wide production activity levels at the municipality level and whether the data requirements are still in compliance with the DPR. We apply Highest Posterior Density (HPD) estimation, which is easily able to include sample information as prior. We tested different prior information content at the municipality level. However, the goodness of the developed estimation approach can only be evaluated having knowledge about the population. Because the real population is not known to us, we took advantage of the special situation in Bavaria and derived a pseudo population for that region. This is used to draw information conforming to DPR for our estimation and to evaluate the resulting estimates. We found that the proposed approach is capable of adequately estimating most activities without violating the DPR. These findings allow us to extend the approach towards the Germany-wide municipality coverage in RAUMIS.Highest Posterior Density estimator (HPD), RAUMIS, locally weighted average (LWA), Research Methods/ Statistical Methods,

Salvage the treasure of geographic information in Farm census data

In Germany, since several decades the RAUMIS modelling system is applied for policy impact assessments to measure the impact of agriculture on the environment. A disaggregation at the municipality level with more than 9.600 administrative units, instead of currently used 316 counties, would tremendously improve the environmental impact analysis. Two sets of data are used for this purpose. The first are geo-referenced data, that are, however, incomplete with respect its coverage of production activities in agriculture. The second set is the micro census statistic itself, that has a full coverage, but data protection rules (DPR) prohibit its straightforward use. The paper show how this bottleneck can be passed to obtain a reliable modelling data set at municipality level with a complete coverage of the agricultural sector in Germany. We successfully applied a Bayesian estimator, that uses prior information derived a cluster analysis based on the micro census and GIS information. Our test statistics of the estimation, calculated by the statistical office, comparing our estimates and the real protected data, reveals that the proposed approach adequately estimates most activities and can be used to fed the municipality layer in the RAUMIS modelling system for an extended policy analysis.Highest Posterior Density estimator (HPD), RAUMIS, Down scaling, Research Methods/ Statistical Methods, C11, C61, C81, Q15,

MUNICIPALITY DISAGGREGATION OF GERMAN'S AGRICULTURAL SECTOR MODEL RAUMIS

Since several decades the RAUMIS modelling system is applied for policy impact assessments to measure the impact of agriculture on the environment. A disaggregation at the municipality level with more than 9.000 administrative units, instead of currently used 316 counties, would tremendously improve the environmental impact analysis. Two sets of data are used for this purpose. The first are geo-referenced data, that are, however, incomplete with respect its coverage of production activities in agriculture. The second set is the micro census statistic itself, that has a full coverage, but data protection rules (DPR) prohibit its straightforward use. The paper show how this bottleneck can be passed to obtain a reliable modelling data set at municipality level with a complete coverage of the agricultural sector in Germany. We successfully applied a Bayesian estimator, that uses prior information derived a cluster analysis based on the micro census and GIS information. Our test statistics of the estimation, calculated by the statistical office, comparing our estimates and the real protected data, reveals that the proposed approach adequately estimates most activities and can be used to fed the municipality layer in the RAUMIS modelling system for an extended policy analysis.Highest Posterior Density estimator (HPD), RAUMIS, Down scaling, Agricultural and Food Policy, C11, C61, C81, Q15,

A handbook on the use of FADN database in programming models

The main objective of the current report is to provide a guideline on how the farm accountancy data network (FADN) can be employed in mathematical programming models. The reader of this report is introduced to the FADN database to become familiar with the underlying rules and specific issues

On the reliability of multistate systems with imprecise probabilities

Розглядається обчислення надійності в складних системах за наявності випадкового набору оцінок працездатності елементів. Виявлено, що підхід Демпстер-Шефера є відповідним математичним інструментом, який відповідає поставленим задачам. Для випадку, коли взаємозалежності елементів невідомі, наведено також оцінки ефективності системи переконань і правдоподібність функції.Рассматривается вычисления надежности в сложных системах при наличии случайного набора оце- нок работоспособности элементов. Выявлено, что подход Демпстер-Шефера является соответствующим математическим инструментом, который соответствует поставленным задачам. Для случая, когда взаимозависимости элементов неизвестны, приведены также оценки эффективности системы убеждений и правдоподобность функции.We consider the computation of multistate systems reliabilities in the presence of random set estimations for the elements' working abilities. It turns out that the Dempster-Shafer approach is a suitable mathematical tool. For the case that the interdependence of the elements is unknown, bounds for the system's performance belief and plausibility functions are given as well

EU-wide Distributional Effects of EU Direct Payments Harmonization analyzed with CAPRI

We argue in this paper that available econometric estimates of farmers’ risk aversion do not measure true farmers’ preferences towards risky outcomes. Available analyses are mostly of static nature and indeed measure the parameters of the synthetic optimal value function rather than the deep parameters of the utility functions. We derive analytical and empirical results in a simple dynamic and stochastic framework showing that that there is not a simple relationship between utility functions and value functions when agents have many decision variables. In particular we find that the value function does not necessarily exhibit DARA when the instantaneous utility function satisfies DARA and conversely. We recommend performing dynamic econometric estimation with at least farm production and consumption data.distributional effects, SPS, flat-rate payment, CAP reform, farm level model, CAPRI farm type layer, International Relations/Trade, Q11, Q12, Q18,

FarmBoss – Software zur strategischen Beratung von Umstellungs- und Öko– Betrieben

To supervise and advise the process of conversion into organic farming is a challenge caused by the complexity which has to taken into account. Decisions about investments, crop rotation, marketing and much more were to set up. The demand for a software system which supports and give help to administrate and to calculate different options or scenarios for a particular farm increased and now after a test phase it is available in form of a software package called FARMBOSS

Impact of Agricultural and Trade Policy Reform on land-use within the EU

Land Economics/Use,