CH-FARMIS - An agricultural sector model for Swiss agriculture

This working paper gives an overview of the farm group model CH-FARMIS - a comparative static, process analytical, non-linear programming model that allows a separate assessment of the impacts of policies on organic and non-organic farming in Switzerland. In CH-FARMIS, the agricultural sector is represented by thirty farm groups, which can be char-acterised by their farming system, farm type and geographic location. Book keeping data from the Swiss FADN was used as a primary source for the model. By applying farm-specific weight-ing factors, farm data were aggregated to sector accounts. The technical coefficients of the farm model were either taken directly from farm accounts or calculated on the basis of normative data. Agricultural production is represented by 29 crop activities and 15 livestock activities. The factor allocation and production of each farm group is optimised by maximising farm income under policy and management restrictions. The restrictions cover the area of land and labour use, livestock feeding, fertiliser balance, rearing of young stock, allocation of direct payments and requirements with respect to the organic production system. A positive mathematical pro-gramming approach (PMP) was used to calibrate the production activities in the base year to observed activity levels

Reconciling household surveys and national accounts data using a cross entropy estimation method:

This paper presents an approach to reconciling household surveys and national accounts data that starts from the assumption that the macro data represent control totals to which the household data must be reconciled. The economic data gathered in the survey are also assumed to be accurate, or have been adjusted to be accurate. Given these assumptions, the problem is how to use the additional information provided by the national accounts data to re-estimate the household weights used in the survey so that the survey results are consistent with the aggregate data. The estimation approach represents an efficient “information processing rule” using an estimation criterion based on an entropy measure of information. The survey household weights are treated as a prior. New weights are estimated that are close to the prior using a cross-entropy metric and that are also consistent with the additional information. This approach is implemented to reconcile LSMS survey data and macro data for Madagascar. The results indicate that the approach is powerful and flexible, supporting the efficient use of information from a variety of sources to reconcile data at different levels of aggregation in a consistent framework.National income Accounting., Household surveys., Madagascar.,

Documentation of model components EXPAMOD and CAPRI

ISBN no.: 978-90-8585-129-

PACIOLI 17; Innovation in the management and use of Micro Economic Databases in Agriculture

The PACIOLI network explores the need for and feasibility of innovation in farm accounting and its consequences for data gathering for policy analysis in Farm Accountancy Data Networks (FADNs). PACIOLI 17 took place in Ettenhausen, Switzerland, in June 2009. The theme of the workshop was 'Innovation in the management and use of Micro Economic Databases in Agriculture'

Evaluation of a firm model in estimating aggregate supply response

The North Central Regional Research Project NC- 54, “Supply Response and Adjustments for Hog and Beef Cattle Production,” was started in 1961. The project statement lists these objectives: (1) To estimate farm resource use and supply response of hogs and beef cattle in representative farm situations. (2) To estimate total production of hogs and beef cattle and patterns of resource use for states in the North Central Region and for the nation. (3) To determine the production situations and the areas in which a specified output of hogs and beef cattle would or could be produced most efficiently under various projected levels of demand and prices and at a given level of technology representing that now known but not yet generally adopted. Linear-programming, time-series analysis, production function analysis and “outlook” research were used in the study. The linear-programming research was divided into two phases. Phase I involved (a) estimating the optimum organization and production for representative farms at various prices for hogs, cattle and feed grains and (b) aggregating these results to give estimates of regional production. The purpose of Phase II was to examine the effects of permitting acquisition and disposal of factors of production assumed fixed in the Phase I model. This was accomplished by including purchase and sale activities for fixed assets at predetermined prices. Insofar as the purchases and sales were not conducted within a framework of regional constraints and because an appropriate weighting scheme was not readily available, no aggregation of the Phase II results was made. Time-series analysis, production function analysis and “outlook” analysis were used to complement the programming analysis

Technical efficiency of olive oil manufacturing and efficacy of modernization programme in Tunisia

This study investigates firm level technical efficiency of production and its determinants in a sample of 137 olive oil manufacturing firms in Tunisia using a stochastic frontier production model applied to cross-section data. Results indicate that technical efficiency of production in the sample of olive oil manufacturing firms investigated ranges from a minimum of 47.1% to a maximum 99.5% with an average technical efficiency estimate of 86.5%. This implies olive oil manufacturing firms in Tunisia can increase their production on average by 13.5% through more efficient use of technology and production inputs. The fact that 93 firms represented more than 64.4% of the sample hit more than 80% of technical efficiency score implies the efficacy of modernization programme implemented in Tunisia. The estimated coefficients in the technical inefficiency effects model indicate that level of technology, frequent use of computer and internet, the owner’s age, the share of skilled labour, the employment of management staff, and the input sourcing by the own production have a significant and positive effect on technical efficiency. On the other hand, negative relationships are found between technical efficiency and entrepreneur dummy variable, continuous relationship with the suppliers in the same district, and with the private sector and trader as customers. These results imply that the adoption of new technology, accumulation of skill and knowledge as well as stable input sourcing contribute to improve the technical efficiency of olive oil manufacturing.olive oil manufacturing, stochastic frontier production function, technical efficiency, modernization programme, Tunisia, Crop Production/Industries,

Analysis of aggregation error in supply functions based on farm-programming models

The over-all purpose of this study is to investigate problems of aggregation error in supply estimates. Specific elements of the analysis include an exploration of the theoretical aspects of developing error-free or minimum-error aggregates, the development of empirical supply estimates for Iowa pork and beef (based on different stratifications of representative farms), determination of the relative magnitude of the aggregation error and possible factors contributing to it, and recommending practical research procedures for controlling aggregation error. The grouping implied by Theorem I developed in the study extends beyond the practice of grouping farms by restrictive resources. Although grouping by restrictive resources is important, it does not reflect differences in the response patterns of individual farms. The requirements of Theorem I provide a basic principle to follow in controlling aggregation error