##plugins.themes.bootstrap3.article.main##

The structure of the European Union producer price indices, nominal total agricultural production varies from one country to another. The EU agricultural price indices involve the index of producer prices of agricultural products and the index of purchase prices of the means of agricultural production. The purpose of agricultural price indices is to unveil trends in the prices of individual agricultural products and purchase prices of the means of agricultural production. Moreover, the objective of the applying statistics on agricultural prices is to make comparisons between member states and also for economic analyses. Absolute agricultural prices are needed for many model calculations and for the ascertainment of price elasticity. The means through which these objectives could be achieved are believed to be when the absolute prices are compared between the member states, and also, when the products for which the prices from the respective member state are to be recorded for economic relevance. These objectives are not always compatible and sometimes require some compromise. In this study, we evaluate the price indices of domestic agricultural production as a whole in the EU24, using the most accurate association model of the Categorical Data Analysis. Figures from the Eurostat office calculated on annual base year from 2005-2017 were used to analyse this study. Since the main focus is to have a better understanding of producer price indices, nominal total domestic agricultural production, the analysis of association table (ANOAS) is given in order to ascertain the percentage of the data which is covered by each model. We find and estimate the association model with the best fit and in conclusion we find out that the Row-Effects Association Model (R) has the best fit because it covers 93% of the data, thereby giving the best fit among all.

Downloads

Download data is not yet available.

References

  1. Handbook for EU Agricultural Price Statistics, Version 2.1., November 2015.
     Google Scholar
  2. European Commission - Agriculture and Rural Development (2006), Rural Development 2007-2013; Handbook on common monitoring and evaluation framework – Guidance document. Brussels: European Commission.
     Google Scholar
  3. Eliason Ρ. Scott-Clifford Clogg (1990), Categorical Data Analysis (CDAS).
     Google Scholar
  4. Diewert, W. Erwin, (1995). Axiomatic and Economic Approaches to Elementary Price indexes. NBER working paper 5104.
     Google Scholar
  5. Goodman, L.A., (1979a). Multiple Models for the Analysis of Occupational Mobility Tables &Other Kinds of Cross-Classification Tables, “American Journal of Sociology”, 84:804-819.
     Google Scholar
  6. Goodman, L.A., (1979b). Multiple Models for the Analysis of Occupational Mobility Tables and Other Kinds of Cross-Classification Tables. “American Journal of Sociology”.
     Google Scholar
  7. Clogg, C.C. (1990), Analysis of Association (ANOAS) Program.
     Google Scholar
  8. Schwarz, Gideon E. (1978). Annals of Statistics, Estimating the Dimension of a Model; Volume 6, Number 2, pp. 461-464.
     Google Scholar
  9. Goodman, L.A., (1981b). Association Models and Canonical Correlation in the Analysis of Cross-Classifications Having Ordered Categories. “Journal of American Statistical Association”, 76:3, 20-34.
     Google Scholar
  10. Tullock, G. (1967), "The Welfare Costs of Tariffs, Monopolies and Theft", Western Economic Journal, vol. 5, pp. 224-32.
     Google Scholar
  11. Fairbanks, Michael. (2005). Changing the Mind of a Nation: Elements in a Process for Creating Prosperity, “in Culture Matters”, Huntington, editors, “New York: Basic Books”, pp.270-281.
     Google Scholar
  12. Mueller, D.C. (2003), Public Choice III, Cambridge: Cambridge University Press.
     Google Scholar
  13. Olson, M. (1965), The Logic of Collective Action, Cambridge, MA: Harvard University Press.
     Google Scholar
  14. Hotlling, H. (1929), "Stability in Competition", Economic Journal, vol. 39, pp. 41-57.
     Google Scholar
  15. Buchanan, J.M. (1980), "Rent Seeking and Profit Seeking", in J.M. Buchanan, R.D.
     Google Scholar
  16. Monroe, K.R. (1991), "The Theory of Rational Action: What is it? How Useful is it for Political Science", in W. Crotty (ed.)
     Google Scholar
  17. Bhagwati, J. (1982), "Directly Unproductive Profit Seeking Activities", Journal of Political Economy, vol. 90, pp. 988-1002.
     Google Scholar
  18. Diewert, W. Erwin, (1976). Exact and Superlative Index Numbers,’’ Journal of econometrics May 1976, 4: 115–45.
     Google Scholar
  19. Goodman, L.A., (1981a). Association models and the Bivariate Normal for Contingency Tables with Ordered Categories. Biometrica, 68:347-55.
     Google Scholar
  20. Eurostat /JP (2010): European Data Agency, “Eurostat-Online data code (t2020_20), OECD statistics at regional level”.
     Google Scholar
  21. Haritou A., Nwaubani J C. (2008). “Categorical Data Analysis - Working paper” (University Press).
     Google Scholar
  22. Haritou A., Nwaubani J C. (2010). “Categorical Data Analysis - Working paper” (University Press).
     Google Scholar
  23. UN – Eurostat Population "European Commission, Department of Economic and Social Affairs.” 27 January 2017.
     Google Scholar