Combining sample and non-sample information in a mixed generalized maximum entropy approach: Modeling the primary dairy sectors of Hungary and Poland

A. Tonini, R.A. Jongeneel

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademic

Abstract

The EU dairy sector has undergone and is still facing important changes. The April 2004 accession of the new member states led to an increase in production and demand for dairy products in the EU. Therefore quantitative information concerning the likely response of dairy supply to changes in output prices for the new member states is an urgent need for reliable policy analysis. Our model, based on a microeconomic dual approach, is dynamic in its specification allowing gradual adjustments in stock variables. Cow milk and beef and veal productions are directly integrated in the model since in the new member states there is almost no specialized beef production. A mixed generalized maximum entropy estimator is developed coping with limited data by exploiting nonsample information. Non-sample information comes both from economic theory and agro-economic plausibility. Our estimates suggest overall an inelastic dairy supply response for Hungary and Poland. In addition we find medium-run complementarity between the production of cow milk and beef and veal
LanguageEnglish
Title of host publication2005 Proceedings of the American Statistical Association, Statistical Computing Section, Alexandria, USA
Place of PublicationAlexandria, USA
PublisherAmerican Statistical Association
Pages4110-4117
Number of pages18
Publication statusPublished - 2005

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veal
entropy
Hungary
Poland
dairies
beef
microeconomics
economic theory
policy analysis
beef cows
sampling
milk
economics

Cite this

Tonini, A., & Jongeneel, R. A. (2005). Combining sample and non-sample information in a mixed generalized maximum entropy approach: Modeling the primary dairy sectors of Hungary and Poland. In 2005 Proceedings of the American Statistical Association, Statistical Computing Section, Alexandria, USA (pp. 4110-4117). Alexandria, USA: American Statistical Association.
Tonini, A. ; Jongeneel, R.A. / Combining sample and non-sample information in a mixed generalized maximum entropy approach: Modeling the primary dairy sectors of Hungary and Poland. 2005 Proceedings of the American Statistical Association, Statistical Computing Section, Alexandria, USA. Alexandria, USA : American Statistical Association, 2005. pp. 4110-4117
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Tonini, A & Jongeneel, RA 2005, Combining sample and non-sample information in a mixed generalized maximum entropy approach: Modeling the primary dairy sectors of Hungary and Poland. in 2005 Proceedings of the American Statistical Association, Statistical Computing Section, Alexandria, USA. American Statistical Association, Alexandria, USA, pp. 4110-4117.

Combining sample and non-sample information in a mixed generalized maximum entropy approach: Modeling the primary dairy sectors of Hungary and Poland. / Tonini, A.; Jongeneel, R.A.

2005 Proceedings of the American Statistical Association, Statistical Computing Section, Alexandria, USA. Alexandria, USA : American Statistical Association, 2005. p. 4110-4117.

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademic

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Tonini A, Jongeneel RA. Combining sample and non-sample information in a mixed generalized maximum entropy approach: Modeling the primary dairy sectors of Hungary and Poland. In 2005 Proceedings of the American Statistical Association, Statistical Computing Section, Alexandria, USA. Alexandria, USA: American Statistical Association. 2005. p. 4110-4117