IDEAS home Printed from https://ideas.repec.org/p/upf/upfgen/612.html
   My bibliography  Save this paper

Importancia de la información contable para el análisis y predicción de la viabilidad de las explotaciones agrícolas

Author

Listed:
  • Josep M. Argilés

Abstract

Spanish and Western agriculture show a continuous decrease in the number of farms. One of the main factors for this trend is the economic non-viability of many of the existing farms. In addition, interrelationship of agriculture with other industries is growing. Thus, policymakers, banks, creditors and other stakeholders are interested in predicting farm viability. The aim of this paper is to provide empirical evidence that the use of accounting-based information could significantly improve understanding and prediction of various degrees of farm viability. Two multinomial logit models were applied to a sample of farms of Catalonia, Spain. One model included non-accounting-based variables, while the other also considered accounting-based variables. It was found that accounting added significant information to predict various degrees of farm viability. This finding reveals, both the need of encouraging the little existing use of accounting by farms and to develop appropriate accounting standards for agriculture.

Suggested Citation

  • Josep M. Argilés, 2002. "Importancia de la información contable para el análisis y predicción de la viabilidad de las explotaciones agrícolas," Economics Working Papers 612, Department of Economics and Business, Universitat Pompeu Fabra.
    • Handle: RePEc:upf:upfgen:612
    as

    Download full text from publisher

    File URL: https://econ-papers.upf.edu/papers/612.pdf
    File Function: Whole Paper
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. J.-C. Kroll, 1987. "Le Nouveau Plan Comptable : les occasions perdues," Économie rurale, Programme National Persée, vol. 180(1), pages 20-25.
    2. Kenneth R. Krause & Paul L. Williams, 1971. "Personality Characteristics and Successful Use of Credit by Farm Families," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 53(4), pages 619-624.
    3. James C. Cox, 1998. "Quantifying the Effects of Sow-Herd Management Information Systems on Farmers' Decision Making Using Experimental Economics," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 80(4), pages 821-829.
    4. Martin, Daniel, 1977. "Early warning of bank failure : A logit regression approach," Journal of Banking & Finance, Elsevier, vol. 1(3), pages 249-276, November.
    5. Ohlson, Ja, 1980. "Financial Ratios And The Probabilistic Prediction Of Bankruptcy," Journal of Accounting Research, Wiley Blackwell, vol. 18(1), pages 109-131.
    6. Edward Knopf & Richard Schoney, 1993. "An Evaluation of Farm Financial Benchmarks and Loan Success/Failure: The Case of the Agricultural Credit Corporation of Saskatchewan," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 41(1), pages 61-69, March.
    7. Jos A.A.M. Verstegen & Ruud B.M. Huirne & Aalt A. Dijkhuizen & Robert P. King, 1995. "Quantifying Economic Benefits of Sow-Herd Management Information Systems Using Panel Data," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 77(2), pages 387-396.
    8. James J. Wadsworth & Boris E. Bravo-Ureta, 1992. "Financial performance of New England dairy farms," Agribusiness, John Wiley & Sons, Ltd., vol. 8(1), pages 47-56.
    9. Palepu, Krishna G., 1986. "Predicting takeover targets : A methodological and empirical analysis," Journal of Accounting and Economics, Elsevier, vol. 8(1), pages 3-35, March.
    10. Lo, Andrew W., 1986. "Logit versus discriminant analysis : A specification test and application to corporate bankruptcies," Journal of Econometrics, Elsevier, vol. 31(2), pages 151-178, March.
    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. Josep M. Argilés, 1998. "Accounting information and the prediction of farm viability," Economics Working Papers 277, Department of Economics and Business, Universitat Pompeu Fabra.
    2. Le, Hong Hanh & Viviani, Jean-Laurent, 2018. "Predicting bank failure: An improvement by implementing a machine-learning approach to classical financial ratios," Research in International Business and Finance, Elsevier, vol. 44(C), pages 16-25.
    3. repec:hum:wpaper:sfb649dp2013-037 is not listed on IDEAS
    4. Alexander Hölzl & Sebastian Lobe, 2016. "Predicting above-median and below-median growth rates," Review of Managerial Science, Springer, vol. 10(1), pages 105-133, January.
    5. Mohammad Mahdi Mousavi & Jamal Ouenniche & Kaoru Tone, 2023. "A dynamic performance evaluation of distress prediction models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(4), pages 756-784, July.
    6. John W. Pacey & Toan M. Pham, 1990. "The Predictiveness of Bankruptcy Models: Methodological Problems and Evidence," Australian Journal of Management, Australian School of Business, vol. 15(2), pages 315-337, December.
    7. Härdle, Wolfgang Karl & Prastyo, Dedy Dwi & Hafner, Christian, 2012. "Support vector machines with evolutionary feature selection for default prediction," SFB 649 Discussion Papers 2012-030, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    8. fernández, María t. Tascón & gutiérrez, Francisco J. Castaño, 2012. "Variables y Modelos Para La Identificación y Predicción Del Fracaso Empresarial: Revisión de La Investigación Empírica Reciente," Revista de Contabilidad - Spanish Accounting Review, Elsevier, vol. 15(1), pages 7-58.
    9. Fernando Zambrano Farias & María del Carmen Valls Martínez & Pedro Antonio Martín-Cervantes, 2021. "Explanatory Factors of Business Failure: Literature Review and Global Trends," Sustainability, MDPI, vol. 13(18), pages 1-26, September.
    10. Barniv, Ran & Mehrez, Abraham & Kline, Douglas M., 2000. "Confidence intervals for controlling the probability of bankruptcy," Omega, Elsevier, vol. 28(5), pages 555-565, October.
    11. Fourgeaud Claude & Gourieroux Christian & Pradel Jacqueline, 1990. "Sélection de clientèle et tarification de prêt bancaire," CEPREMAP Working Papers (Couverture Orange) 9004, CEPREMAP.
    12. repec:hum:wpaper:sfb649dp2012-030 is not listed on IDEAS
    13. Mohammad Mahdi Mousavi & Jamal Ouenniche, 2018. "Multi-criteria ranking of corporate distress prediction models: empirical evaluation and methodological contributions," Annals of Operations Research, Springer, vol. 271(2), pages 853-886, December.
    14. Härdle, Wolfgang Karl & Prastyo, Dedy Dwi, 2013. "Default risk calculation based on predictor selection for the Southeast Asian industry," SFB 649 Discussion Papers 2013-037, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    15. Hossein Nouri & Robert Parker & Subarna Sumanta, 2005. "Students' perceptions of work in public accounting and employment preferences," Accounting Education, Taylor & Francis Journals, vol. 14(3), pages 293-311.
    16. Harlan Platt & Marjorie Platt, 2002. "Predicting corporate financial distress: Reflections on choice-based sample bias," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 26(2), pages 184-199, June.
    17. Zhou, Fanyin & Fu, Lijun & Li, Zhiyong & Xu, Jiawei, 2022. "The recurrence of financial distress: A survival analysis," International Journal of Forecasting, Elsevier, vol. 38(3), pages 1100-1115.
    18. Zeineb Affes & Rania Hentati-Kaffel, 2016. "Forecast bankruptcy using a blend of clustering and MARS model - Case of US banks," Post-Print halshs-01314553, HAL.
    19. Pablo de Llano Monelos & Manuel Rodríguez López & Carlos Piñeiro Sánchez, 2013. "Bankruptcy Prediction Models in Galician companies. Application of Parametric Methodologies and Artificial Intelligence," International Journal of Economics & Business Administration (IJEBA), International Journal of Economics & Business Administration (IJEBA), vol. 0(1), pages 117-136.
    20. Nijskens, Rob & Mokas, Dimitris, 2019. "Credit Risk in Commercial Real Estate Bank Loans : The Role of Idiosyncratic versus Macro-Economic Factors," Other publications TiSEM ea4f2f0e-dc50-4987-91d3-6, Tilburg University, School of Economics and Management.
    21. Paramonovs Sergejs & Ijevleva Ksenija, 2015. "The Role of Marketing Tools in the Improvement of Consumers Financial Literacy," Acta Universitatis Sapientiae, Economics and Business, Sciendo, vol. 27(1), pages 40-45, December.
    22. Balios, Dimitris & Thomadakis, Stavros & Tsipouri, Lena, 2016. "Credit rating model development: An ordered analysis based on accounting data," Research in International Business and Finance, Elsevier, vol. 38(C), pages 122-136.

    More about this item

    Keywords

    Accounting; agriculture; farm; non-viability; failure prediction models;
    All these keywords.

    JEL classification:

    • M40 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Accounting - - - General

    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:upf:upfgen:612. 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: the person in charge (email available below). General contact details of provider: http://www.econ.upf.edu/ .

    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.