IDEAS home Printed from https://ideas.repec.org/a/gam/jjrfmx/v14y2021i12p579-d693491.html
   My bibliography  Save this article

Efficiency and Determinants of Capital Structure in the Greek Pharmaceutical, Cosmetic and Detergent Industries

Author

Listed:
  • Ioannis E. Tsolas

    (School of Applied Mathematical and Physical Sciences, National Technical University of Athens, 15780 Athens, Greece)

Abstract

The purpose of this paper is to investigate the relationship between a firm’s capital structure (i.e., leverage) and its operating environment, taking into account firm (i.e., efficiency, asset structure, profitability, size, age and risk) and industry effects. For a sample of Greek pharmaceutical, cosmetic and detergent (PCD) enterprises, firm efficiency was estimated using bootstrapped data envelopment analysis (DEA), and a leverage model was produced using ordinary least squares (OLS) regression. The findings confirm the significance of firm efficiency (i.e., the franchise-value hypothesis over the efficiency-risk hypothesis) and asset structure on leverage. Efficiency and overall and short-term leverage have a significant negative relationship, indicating that more efficient firms tend to choose a relatively low debt ratio. Pharma firms are more affected since they are less efficient than cosmetics and detergents firms. Furthermore, asset structure and short- and long- term leverage have a significant negative and positive relationship, respectively, indicating that the firms with more tangible assets have less short-term debt and more long-term debt in their capital structure. Cosmetic and detergent firms, which have slightly more tangible assets than pharma firms, appear to be able to substitute high-cost, short-term debt with the low-cost, long-term debt by using such assets as collateral.

Suggested Citation

  • Ioannis E. Tsolas, 2021. "Efficiency and Determinants of Capital Structure in the Greek Pharmaceutical, Cosmetic and Detergent Industries," JRFM, MDPI, vol. 14(12), pages 1-13, December.
    • Handle: RePEc:gam:jjrfmx:v:14:y:2021:i:12:p:579-:d:693491
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1911-8074/14/12/579/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1911-8074/14/12/579/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. William W. Cooper & Lawrence M. Seiford & Joe Zhu (ed.), 2011. "Handbook on Data Envelopment Analysis," International Series in Operations Research and Management Science, Springer, number 978-1-4419-6151-8, September.
    2. Leopold Simar & Paul Wilson, 2000. "A general methodology for bootstrapping in non-parametric frontier models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 27(6), pages 779-802.
    3. Cinzia Daraio & Léopold Simar & Paul W. Wilson, 2018. "Central limit theorems for conditional efficiency measures and tests of the ‘separability’ condition in non‐parametric, two‐stage models of production," Econometrics Journal, Royal Economic Society, vol. 21(2), pages 170-191, June.
    4. Daraio, Cinzia & Simar, Leopold & Wilson, Paul, 2018. "Central limit theorems for conditional efficiency measures and tests of the ‘separability’ condition in non-parametric, two-stage models of production," LIDAM Reprints ISBA 2018023, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    5. Haifeng Guo & Tenkir Seifu Legesse & Jiqiang Tang & Zhen Wu, 2021. "Financial leverage and firm efficiency: the mediating role of cash holding," Applied Economics, Taylor & Francis Journals, vol. 53(18), pages 2108-2124, April.
    6. Léopold Simar & Paul W. Wilson, 1998. "Sensitivity Analysis of Efficiency Scores: How to Bootstrap in Nonparametric Frontier Models," Management Science, INFORMS, vol. 44(1), pages 49-61, January.
    7. Laurent Weill, 2008. "Leverage and Corporate Performance: Does Institutional Environment Matter?," Small Business Economics, Springer, vol. 30(3), pages 251-265, March.
    8. Julie Harrison & Paul Rouse, 2016. "DEA and Accounting Performance Measurement," International Series in Operations Research & Management Science, in: Shiuh-Nan Hwang & Hsuan-Shih Lee & Joe Zhu (ed.), Handbook of Operations Analytics Using Data Envelopment Analysis, chapter 0, pages 385-412, Springer.
    9. Sarada Dakua, 2019. "Effect of determinants on financial leverage in Indian steel industry: A study on capital structure," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 24(1), pages 427-436, January.
    10. Simar, Leopold & Wilson, Paul W., 2007. "Estimation and inference in two-stage, semi-parametric models of production processes," Journal of Econometrics, Elsevier, vol. 136(1), pages 31-64, January.
    11. Veronique Vermoesen & Marc Deloof & Eddy Laveren, 2013. "Long-term debt maturity and financing constraints of SMEs during the Global Financial Crisis," Small Business Economics, Springer, vol. 41(2), pages 433-448, August.
    12. William W. Cooper & José L. Ruiz & Inmaculada Sirvent, 2011. "Choices and Uses of DEA Weights," International Series in Operations Research & Management Science, in: William W. Cooper & Lawrence M. Seiford & Joe Zhu (ed.), Handbook on Data Envelopment Analysis, chapter 0, pages 93-126, Springer.
    13. Shaik, Saleem, 2015. "Impact of liquidity risk on variations in efficiency and productivity: A panel gamma simulated maximum likelihood estimation," European Journal of Operational Research, Elsevier, vol. 245(2), pages 463-469.
    14. William W. Cooper & Lawrence M. Seiford & Kaoru Tone, 2007. "Data Envelopment Analysis," Springer Books, Springer, edition 0, number 978-0-387-45283-8, September.
    15. Wafaa M. Sbeti & Imad Moosa, 2012. "Firm-specific factors as determinants of capital structure in the absence of taxes," Applied Financial Economics, Taylor & Francis Journals, vol. 22(3), pages 209-213, February.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Dominika Gajdosikova & Katarina Valaskova & Tomas Kliestik & Maria Kovacova, 2023. "Research on Corporate Indebtedness Determinants: A Case Study of Visegrad Group Countries," Mathematics, MDPI, vol. 11(2), pages 1-30, January.
    2. Ștefan Cristian Gherghina, 2023. "Corporate Finance, Governance, and Social Responsibility," JRFM, MDPI, vol. 16(6), pages 1-5, June.

    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. Mohamed Mehdi Jelassi & Ezzeddine Delhoumi, 2021. "What explains the technical efficiency of banks in Tunisia? Evidence from a two-stage data envelopment analysis," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-26, December.
    2. Falavigna, G. & Ippoliti, R., 2020. "The socio-economic planning of a community nurses programme in mountain areas: A Directional Distance Function approach," Socio-Economic Planning Sciences, Elsevier, vol. 71(C).
    3. Amir Moradi-Motlagh & Ali Emrouznejad, 2022. "The origins and development of statistical approaches in non-parametric frontier models: a survey of the first two decades of scholarly literature (1998–2020)," Annals of Operations Research, Springer, vol. 318(1), pages 713-741, November.
    4. Matthews, Kent & Xiao, Zhiguo, 2020. "Rational cost inefficiency and convergence in Chinese banks," Economic Modelling, Elsevier, vol. 91(C), pages 696-704.
    5. Valentin Zelenyuk, 2019. "Data Envelopment Analysis and Business Analytics: The Big Data Challenges and Some Solutions," CEPA Working Papers Series WP072019, School of Economics, University of Queensland, Australia.
    6. Valiyattoor, Vipin & Bhandari, Anup Kumar, 2020. "Outsourcing and firm performance nexus: An analysis using the conventional and panel double-bootstrap procedure," Research in International Business and Finance, Elsevier, vol. 54(C).
    7. Ioannis E. Tsolas, 2022. "Assessing Regional Entrepreneurship: A Bootstrapping Approach in Data Envelopment Analysis," Stats, MDPI, vol. 5(4), pages 1-10, November.
    8. Kohl, Sebastian & Brunner, Jens O., 2020. "Benchmarking the benchmarks – Comparing the accuracy of Data Envelopment Analysis models in constant returns to scale settings," European Journal of Operational Research, Elsevier, vol. 285(3), pages 1042-1057.
    9. Franz R. Hahn, 2007. "Determinants of Bank Efficiency in Europe. Assessing Bank Performance Across Markets," WIFO Studies, WIFO, number 31499, April.
    10. Ioannis E. Tsolas, 2020. "Financial Performance Assessment of Construction Firms by Means of RAM-Based Composite Indicators," Mathematics, MDPI, vol. 8(8), pages 1-16, August.
    11. Iparraguirre, José Luis & Ma, Ruosi, 2015. "Efficiency in the provision of social care for older people. A three-stage Data Envelopment Analysis using self-reported quality of life," Socio-Economic Planning Sciences, Elsevier, vol. 49(C), pages 33-46.
    12. Kim, Man-Keun & Harris, Thomas R., 2008. "An Efficiency Analysis of Nevada and Utah Counties: Region Size Leads Regional Efficiency," 2008 Annual Meeting, July 27-29, 2008, Orlando, Florida 6338, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    13. Calogero Guccio & Marco Ferdinando Martorana & Isidoro Mazza & Giacomo Pignataro & Ilde Rizzo, 2022. "Is innovation in ICT valuable for the efficiency of Italian museums?," European Planning Studies, Taylor & Francis Journals, vol. 30(9), pages 1695-1716, September.
    14. Łukasz Brzezicki, 2020. "The Efficiency of Public and Private Higher Education Institutions in Poland," Gospodarka Narodowa. The Polish Journal of Economics, Warsaw School of Economics, issue 4, pages 33-51.
    15. Moran, Valerie & Jacobs, Rowena, 2013. "An international comparison of efficiency of inpatient mental health care systems," Health Policy, Elsevier, vol. 112(1), pages 88-99.
    16. Ioannis E. Tsolas, 2023. "Efficiency Measurement of Lignite-Fired Power Plants in Greece Using a DEA-Bootstrap Approach," Sustainability, MDPI, vol. 15(4), pages 1-10, February.
    17. Sebastian Kohl & Jan Schoenfelder & Andreas Fügener & Jens O. Brunner, 2019. "The use of Data Envelopment Analysis (DEA) in healthcare with a focus on hospitals," Health Care Management Science, Springer, vol. 22(2), pages 245-286, June.
    18. Cifuentes-Faura, Javier & Faura-Martínez, Ursula, 2023. "Measuring Spanish airport performance: A bootstrap data envelopment analysis of efficiency," Utilities Policy, Elsevier, vol. 80(C).
    19. Dana PANCUROVA & Stefan LYOCSA, 2013. "Determinants of Commercial Banks’ Efficiency: Evidence from 11 CEE Countries," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 63(2), pages 152-179, May.
    20. Manuel Salas-Velasco, 2020. "Measuring and explaining the production efficiency of Spanish universities using a non-parametric approach and a bootstrapped-truncated regression," Scientometrics, Springer;Akadémiai Kiadó, vol. 122(2), pages 825-846, February.

    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:jjrfmx:v:14:y:2021:i:12:p:579-:d:693491. 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.