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PR - Farm Income Risk Analysis At The Sector Level

Author

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  • Zgajnar, Jaka
  • Kavcic, Stane

Abstract

Macroeconomic developments on international agricultural commodities’ markets have in recent years considerably amplified interest of income risk management in agriculture. In EU countries this is also new prospective of further agricultural policy development. Therefore, there is a need for empirical analysis and tools aimed at providing in depth insight into the topic. For preliminary decisions and for efficient and effective agricultural policy planning, magnitude and characteristics of income risk that agricultural holdings face, have to be analysed from different viewpoints. Indirect income risk analyses demands high quality microeconomic data at farm level, which are in most cases not available. This paper presents possible theoretical approach how different sources of data at farm level, national statistics and analytical models could be merged and utilised in simulation process to analyse income losses at the sector level. It is grounded on production structure resumed out of annual subsidy applications as key information per each agricultural holding. Presented approach’s utilises potential of random number generator and random distributions of Monte Carlo to roughly reconstruct different sources of risks in different states of nature that may occur with diverse probabilities at the particular farm. In such a manner income situation at the farm level is analysed. The developed approach is tested on dairy farms in Slovenia. Obtained results suggest that this could be useful approach for rough estimation of income risk and points on some limitations and drawbacks that could be further improved.

Suggested Citation

  • Zgajnar, Jaka & Kavcic, Stane, 2013. "PR - Farm Income Risk Analysis At The Sector Level," 19th Congress, Warsaw, Poland, 2013 345707, International Farm Management Association.
  • Handle: RePEc:ags:ifma13:345707
    DOI: 10.22004/ag.econ.345707
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    Keywords

    Risk and Uncertainty;

    Statistics

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