IDEAS home Printed from https://ideas.repec.org/p/ags/eaae14/186381.html
   My bibliography  Save this paper

Simulation model for income risk analyses at the sector level, case of Slovenia

Author

Listed:
  • Zgajnar, Jaka

Abstract

This paper presents possible approach how different sources of data at farm level, national statistics and analytical models could be merged in simulation process to analyse income risk at the sector level. Baseline is production structure resumed out of annual subsidy applications as key information per each agricultural holding within the sector. Presented approach 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 sector level is analysed. The developed approach is tested on the 21 farm types further divided into 13 economic classes. Obtained preliminary results suggest that this could be useful approach for rough estimation of income risk and points on some limitations and drawbacks that should be further improved.

Suggested Citation

  • Zgajnar, Jaka, 2014. "Simulation model for income risk analyses at the sector level, case of Slovenia," 2014 International Congress, August 26-29, 2014, Ljubljana, Slovenia 186381, European Association of Agricultural Economists.
    • Handle: RePEc:ags:eaae14:186381
    DOI: 10.22004/ag.econ.186381
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/186381/files/14th%20EAAE_Zgajnar_J.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.22004/ag.econ.186381?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Severini, Simone & Cortignani, Raffaele, 2011. "Modeling farmer participation to a revenue insurance scheme by means of Positive Mathematical Programming," 2011 International Congress, August 30-September 2, 2011, Zurich, Switzerland 116001, European Association of Agricultural Economists.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Britz, Wolfgang & Linda, Arata, "undated". "How Important Are Crop Shares In Managing Risk For Specialized Arable Farms? A Panel Estimation Of A Programming Model For Three European Regions," 56th Annual Conference, Bonn, Germany, September 28-30, 2016 244801, German Association of Agricultural Economists (GEWISOLA).
    2. Liu, Xuan & van Kooten, Gerrit Cornelis & Duan, Jun, 2020. "Calibration of agricultural risk programming models using positive mathematical programming," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 64(3), July.
    3. Jansson, Torbjörn & Heckelei, Thomas & Gocht, Alexander & Basnet, Shyam Kumar & Zhang, Yinan & Neuenfeldt, Sebastian, 2014. "Analysing impacts of changing price variability with estimated farm risk-programming models," 2014 International Congress, August 26-29, 2014, Ljubljana, Slovenia 182665, European Association of Agricultural Economists.
    4. Basnet, Shyam Kumar & Jansson , Torbjorn & Heckelei, Thomas, 2021. "A Bayesian econometrics and risk programming approach for analysing the impact of decoupled payments in the European Union," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 65(03), January.
    5. Wolfgang Britz & Linda Arata, 2019. "Econometric mathematical programming: an application to the estimation of costs and risk preferences at farm level," Agricultural Economics, International Association of Agricultural Economists, vol. 50(2), pages 191-206, March.
    6. Arfini, Filippo & Donati, Michele & Marongiu, Sonia & Cesaro, Luca, 2012. "Farm production costs estimation trough PMP Models: an application in three Italian Regions," 2012 First Congress, June 4-5, 2012, Trento, Italy 124117, Italian Association of Agricultural and Applied Economics (AIEAA).
    7. Kamel Elouhichi & Maria Espinosa Goded & Pavel Ciaian & Angel Perni Llorente & Bouda Vosough Ahmadi & Liesbeth Colen & Sergio Gomez Y Paloma, 2018. "The EU-Wide Individual Farm Model for Common Agricultural Policy Analysis (IFM-CAP v.1): Economic Impacts of CAP Greening," JRC Research Reports JRC108693, Joint Research Centre.
    8. Heckelei, Thomas & Britz, Wolfgang & Zhang, Yinan, 2012. "Positive Mathematical Programming Approaches – Recent Developments in Literature and Applied Modelling," Bio-based and Applied Economics Journal, Italian Association of Agricultural and Applied Economics (AIEAA), vol. 1(1), pages 1-16, April.

    More about this item

    Keywords

    Production Economics; Risk and Uncertainty;

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ags:eaae14:186381. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: AgEcon Search (email available below). General contact details of provider: https://edirc.repec.org/data/eaaeeea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.