IDEAS home Printed from https://ideas.repec.org/a/gam/jagris/v14y2024i1p119-d1318382.html
   My bibliography  Save this article

Determinants of Financial Security of European Union Farms—A Factor Analysis Model Approach

Author

Listed:
  • Ewa Szafraniec-Siluta

    (Faculty of Economics, Department of Finance, Koszalin University of Technology, Kwiatkowskiego 6e, 75-343 Koszalin, Poland)

  • Agnieszka Strzelecka

    (Faculty of Economics, Department of Finance, Koszalin University of Technology, Kwiatkowskiego 6e, 75-343 Koszalin, Poland)

  • Roman Ardan

    (Faculty of Economics, Department of Economics, Koszalin University of Technology, Kwiatkowskiego 6e, 75-343 Koszalin, Poland)

  • Danuta Zawadzka

    (Faculty of Economics, Department of Finance, Koszalin University of Technology, Kwiatkowskiego 6e, 75-343 Koszalin, Poland)

Abstract

The objective of this study was to assess the level of financial security of farms and identify its determinants based on factor analysis. The data used in this research were obtained from the European FADN (Farm Accountancy Data Network). Factor analysis (FA) was employed to reduce the number of variables that potentially determine the financial security of farms. The results indicate that the surveyed entities maintained financial security between 2014 and 2021. This study suggests that it is necessary to examine these factors separately for farms engaged in crop farming and animal production. The results obtained for all farms were less satisfactory than those that took into account the specifics of agricultural production. This study addresses a gap in the literature by including highly correlated variables in the analysis of the determinants of financial security. Factor analysis is used to reduce the number of variables without losing important information. Firstly, seventeen variables related to the financial security of all farms were assigned to six factors. These were income and self-financing of operations ; area and subsidies ; long-term investments and financial decisions consequences ; economic size, taxes, and non-breeding livestocks ; investment activity; and inputs, stock, short-term loans, and labor . Then, the determinants of the financial security of farms were examined, taking into account the specialization of activities. For crop-producing farms, six factors were identified, including three that were identical to those for all farms: income and self-financing of operations ; long-term investment and financial decisions consequences; and investment activity . In addition, the following items were specified: area, subsidies, non-breeding livestocks, and taxes ; economic size, inputs, and labor; and stock and short-term loans . The correlated variables in the case of livestock production combined into factors in a different way. In this case, four factors were distinguished: economic size, non-breeding livestocks, income, and self-financing of operations ; operational activities of animal production ; long-term investment and financial decisions consequences; and investment activity . Financial security is a complex matter that can be affected by a range of factors related to agricultural activities.

Suggested Citation

  • Ewa Szafraniec-Siluta & Agnieszka Strzelecka & Roman Ardan & Danuta Zawadzka, 2024. "Determinants of Financial Security of European Union Farms—A Factor Analysis Model Approach," Agriculture, MDPI, vol. 14(1), pages 1-18, January.
    • Handle: RePEc:gam:jagris:v:14:y:2024:i:1:p:119-:d:1318382
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2077-0472/14/1/119/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2077-0472/14/1/119/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Agnieszka Kurdyś-Kujawska & Agnieszka Strzelecka & Danuta Zawadzka, 2021. "The Impact of Crop Diversification on the Economic Efficiency of Small Farms in Poland," Agriculture, MDPI, vol. 11(3), pages 1-21, March.
    2. Cristina Echevarria, 1998. "A Three-Factor Agricultural Production Function: The Case of Canada," International Economic Journal, Taylor & Francis Journals, vol. 12(3), pages 63-75.
    3. Edward I. Altman, 1968. "Financial Ratios, Discriminant Analysis And The Prediction Of Corporate Bankruptcy," Journal of Finance, American Finance Association, vol. 23(4), pages 589-609, September.
    4. Peter J. Barry, 1998. "Credit Constraints, Farm Characteristics, and the Farm Economy: Differential Impacts on Feeder Cattle and Beef Cow Inventories," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 80(4), pages 708-723.
    5. Yang, Dan & Liu, Zimin, 2012. "Does farmer economic organization and agricultural specialization improve rural income? Evidence from China," Economic Modelling, Elsevier, vol. 29(3), pages 990-993.
    6. Chen, Siyan & Desiderio, Saul, 2018. "Factor analysis with a single common factor," MPRA Paper 90426, University Library of Munich, Germany.
    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. Danuta Zawadzka & Agnieszka Strzelecka & Ewa Szafraniec-Siluta, 2021. "Debt as a Source of Financial Energy of the Farm—What Causes the Use of External Capital in Financing Agricultural Activity? A Model Approach," Energies, MDPI, vol. 14(14), pages 1-17, July.
    2. Shaikh, Ibrahim A. & O'Brien, Jonathan Paul & Peters, Lois, 2018. "Inside directors and the underinvestment of financial slack towards R&D-intensity in high-technology firms," Journal of Business Research, Elsevier, vol. 82(C), pages 192-201.
    3. Mikel Bedayo & Gabriel Jiménez & José-Luis Peydró & Raquel Vegas, 2020. "Screening and Loan Origination Time: Lending Standards, Loan Defaults and Bank Failures," Working Papers 1215, Barcelona School of Economics.
    4. Ruey-Ching Hwang, 2013. "Forecasting credit ratings with the varying-coefficient model," Quantitative Finance, Taylor & Francis Journals, vol. 13(12), pages 1947-1965, December.
    5. Giordani, Paolo & Jacobson, Tor & Schedvin, Erik von & Villani, Mattias, 2014. "Taking the Twists into Account: Predicting Firm Bankruptcy Risk with Splines of Financial Ratios," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 49(4), pages 1071-1099, August.
    6. Li, Chunyu & Lou, Chenxin & Luo, Dan & Xing, Kai, 2021. "Chinese corporate distress prediction using LASSO: The role of earnings management," International Review of Financial Analysis, Elsevier, vol. 76(C).
    7. Suzan Hol, 2006. "The influence of the business cycle on bankruptcy probability," Discussion Papers 466, Statistics Norway, Research Department.
    8. Pavol Durana & Lucia Michalkova & Andrej Privara & Josef Marousek & Milos Tumpach, 2021. "Does the life cycle affect earnings management and bankruptcy?," Oeconomia Copernicana, Institute of Economic Research, vol. 12(2), pages 425-461, June.
    9. Dinh, K. & Kleimeier, S., 2006. "Credit scoring for Vietnam's retail banking market : implementation and implications for transactional versus relationship lending," Research Memorandum 012, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).
    10. Elizaveta Danilova & Evgeny Rumyantsev & Ivan Shevchuk, 2018. "Review of the Bank of Russia – IMF Workshop 'Recent Developments in Macroprudential Stress Testing'," Russian Journal of Money and Finance, Bank of Russia, vol. 77(4), pages 60-83, December.
    11. Alderson, Michael J. & Betker, Brian L. & Halford, Joseph T., 2021. "Fictitious dividend cuts in the CRSP data," Journal of Corporate Finance, Elsevier, vol. 71(C).
    12. Pesaran, M. Hashem & Schuermann, Til & Treutler, Bjorn-Jakob & Weiner, Scott M., 2006. "Macroeconomic Dynamics and Credit Risk: A Global Perspective," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 38(5), pages 1211-1261, August.
    13. Nabeel Al-Milli & Amjad Hudaib & Nadim Obeid, 2021. "Population Diversity Control of Genetic Algorithm Using a Novel Injection Method for Bankruptcy Prediction Problem," Mathematics, MDPI, vol. 9(8), pages 1-18, April.
    14. Sandrine Lardic & Claire Gauthier, 2003. "Un modèle multifactoriel des spreads de crédit : estimation sur panels complets et incomplets," Économie et Prévision, Programme National Persée, vol. 159(3), pages 53-69.
    15. Hu, Xiaolu & Shi, Jing & Wang, Lafang & Yu, Jing, 2020. "Foreign ownership in Chinese credit ratings industry: Information revelation or certification?," Journal of Banking & Finance, Elsevier, vol. 118(C).
    16. Modina, Michele & Pietrovito, Filomena & Gallucci, Carmen & Formisano, Vincenzo, 2023. "Predicting SMEs’ default risk: Evidence from bank-firm relationship data," The Quarterly Review of Economics and Finance, Elsevier, vol. 89(C), pages 254-268.
    17. Lauren Stagnol, 2015. "Designing a corporate bond index on solvency criteria," EconomiX Working Papers 2015-39, University of Paris Nanterre, EconomiX.
    18. Nadiah Amirah Nor Azhari & Suhaily Hasnan & Zuraidah Mohd Sanusi, 2020. "The Relationships Between Managerial Overconfidence, Audit Committee, CEO Duality and Audit Quality and Accounting Misstatements," International Journal of Financial Research, International Journal of Financial Research, Sciedu Press, vol. 11(3), pages 18-30, June.
    19. Nagar, Neerav & Sen, Kaustav, 2016. "Earnings management in India: Managers’ fixation on operating profits," Journal of International Accounting, Auditing and Taxation, Elsevier, vol. 26(C), pages 1-12.
    20. Lin, Hsiou-Wei William & Lo, Huai-Chun & Wu, Ruei-Shian, 2016. "Modeling default prediction with earnings management," Pacific-Basin Finance Journal, Elsevier, vol. 40(PB), pages 306-322.

    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:gam:jagris:v:14:y:2024:i:1:p:119-:d:1318382. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.