IDEAS home Printed from https://ideas.repec.org/p/pra/mprapa/24336.html
   My bibliography  Save this paper

The Determinants of Corporate Growth

Author

Listed:
  • Rosique, Francisco

Abstract

Corporate Growth is a concept that has been widely treated in a specific way or as part of strategy theories, in definition and in econometric models and has also been studied in many different aspects and approaches. The author describes in depth the main variables affecting corporate growth and the underlying business processes. This empirical research has focused on Sales, Profit-Cash Flow, Risk, Created Shareholder Value, Market Value and Overall Performance econometric models. These panel data models are based on the 500 Companies of the Standard & Poor’s 500. The methodology used has been very strict in identifying exogenous variables, walking through the different alternative econometric models, discussing results, and, in the end, describing the practical implications in today’s business corporate management. We basically assume that the Functions/Departments act independently in the same company, many times with different objectives, and in this situation clear processes are key to clarify the situations, roles and responsibilities. We also assume that growth implies interactions among the different functions in a company and the CEO acts to lead and coach his immediate Directors as a referee of the key conflicts through his Operating Mechanism. The objective of this PhD Dissertation is to clarify the business priorities and identify the most relevant variables in every process leading to the highest efficiency in reaching a sustainable and profitable growth. It covers the lack of academic studies on the nature and specific driving factors of corporate growth and provides a working framework for Entrepreneurs and Management leading to the Company’s success.

Suggested Citation

  • Rosique, Francisco, 2010. "The Determinants of Corporate Growth," MPRA Paper 24336, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:24336
    as

    Download full text from publisher

    File URL: https://mpra.ub.uni-muenchen.de/24336/1/MPRA_paper_24336.pdf
    File Function: original version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Andrew Ang & Geert Bekaert, 2007. "Stock Return Predictability: Is it There?," The Review of Financial Studies, Society for Financial Studies, vol. 20(3), pages 651-707.
    2. Barnhill Jr., Theodore M. & Maxwell, William F., 2002. "Modeling correlated market and credit risk in fixed income portfolios," Journal of Banking & Finance, Elsevier, vol. 26(2-3), pages 347-374, March.
    3. Abel, Andrew B, 1985. "A Stochastic Model of Investment, Marginal q and the Market Value of the Firm," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 26(2), pages 305-322, June.
    4. Arellano, Manuel, 2003. "Panel Data Econometrics," OUP Catalogue, Oxford University Press, number 9780199245291.
    5. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
    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. Paul Hewson & Keming Yu, 2008. "Quantile regression for binary performance indicators," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 24(5), pages 401-418, September.
    2. Hasan, Iftekhar & Lozano-Vivas, Ana, 2002. "Organizational Form and Expense Preference: Spanish Experience," Bulletin of Economic Research, Wiley Blackwell, vol. 54(2), pages 135-150, April.
    3. repec:hal:spmain:info:hdl:2441/dambferfb7dfprc9m052g20qh is not listed on IDEAS
    4. Lundgren, Tommy & Marklund, Per-Olov & Zhang, Shanshan, 2016. "Industrial energy demand and energy efficiency – Evidence from Sweden," Resource and Energy Economics, Elsevier, vol. 43(C), pages 130-152.
    5. Subhash C. Ray, 2004. "A Simple Statistical Test of Violation of the Weak Axiom of Cost Minimization," Indian Economic Review, Department of Economics, Delhi School of Economics, vol. 39(1), pages 111-121, January.
    6. Raushan Bokusheva & Lukáš Čechura & Subal C. Kumbhakar, 2023. "Estimating persistent and transient technical efficiency and their determinants in the presence of heterogeneity and endogeneity," Journal of Agricultural Economics, Wiley Blackwell, vol. 74(2), pages 450-472, June.
    7. Giacomo De Giorgi & Michele Pellizzari & William Gui Woolston, 2012. "Class Size And Class Heterogeneity," Journal of the European Economic Association, European Economic Association, vol. 10(4), pages 795-830, August.
    8. Barros, Carlos Pestana & Williams, Jonathan, 2013. "The random parameters stochastic frontier cost function and the effectiveness of public policy: Evidence from bank restructuring in Mexico," International Review of Financial Analysis, Elsevier, vol. 30(C), pages 98-108.
    9. Khanal, Aditya & Koirala, Krishna & Regmi, Madhav, 2016. "Do Financial Constraints Affect Production Efficiency in Drought Prone Areas? A Case from Indonesian Rice Growers," 2016 Annual Meeting, February 6-9, 2016, San Antonio, Texas 230087, Southern Agricultural Economics Association.
    10. Wu, Yanrui, 1995. "The productive efficiency of Chinese iron and steel firms A stochastic frontier analysis," Resources Policy, Elsevier, vol. 21(3), pages 215-222, September.
    11. Iván Fernández-Val & Martin Weidner, 2018. "Fixed Effects Estimation of Large-TPanel Data Models," Annual Review of Economics, Annual Reviews, vol. 10(1), pages 109-138, August.
    12. Valeriy Makarov & Albert Bakhtizin, 2014. "The Estimation Of The Regions’ Efficiency Of The Russian Federation Including The Intellectual Capital, The Characteristics Of Readiness For Innovation, Level Of Well-Being, And Quality Of Life," Economy of region, Centre for Economic Security, Institute of Economics of Ural Branch of Russian Academy of Sciences, vol. 1(4), pages 9-30.
    13. Kui-Wai Li & Tung Liu & Lihong Yun, 2007. "Technology Progress, Efficiency, and Scale of Economy in Post-reform China," Working Papers 200701, Ball State University, Department of Economics, revised Apr 2007.
    14. Firna Varina & Sri Hartoyo & Nunung Kusnadi & Amzul Rifin, 2020. "The Determinants of Technical Efficiency of Oil Palm Smallholders in Indonesia," International Journal of Economics and Financial Issues, Econjournals, vol. 10(6), pages 89-93.
    15. Johannes Blum & Klaus Gründler, 2020. "Political Stability and Economic Prosperity: Are Coups Bad for Growth?," CESifo Working Paper Series 8317, CESifo.
    16. Marktanner Marcus & Makdisi Samir, 2008. "Development against All Odds? The Case of Lebanon," Review of Middle East Economics and Finance, De Gruyter, vol. 4(3), pages 101-133, September.
    17. Rossi, Martín, 2000. "Análisis de eficiencia aplicado a la regulación ¿Es importante la Distribución Elegida para el Término de Ineficiencia?," UADE Textos de Discusión 22_2000, Instituto de Economía, Universidad Argentina de la Empresa.
    18. Gabriel Burdí­n & Andrés Dean, 2009. "Las decisiones de empleo y salarios de cooperativas de trabajo y empresas capitalistas : evidencia para Uruguay en base a datos de panel," Documentos de Trabajo (working papers) 09-02, Instituto de Economía - IECON.
    19. Chen, Yufeng & Ni, Liangfu & Liu, Kelong, 2021. "Does China's new energy vehicle industry innovate efficiently? A three-stage dynamic network slacks-based measure approach," Technological Forecasting and Social Change, Elsevier, vol. 173(C).
    20. Hertrich Markus, 2019. "A Novel Housing Price Misalignment Indicator for Germany," German Economic Review, De Gruyter, vol. 20(4), pages 759-794, December.
    21. Mochebelele, Motsamai T. & Winter-Nelson, Alex, 2000. "Migrant Labor and Farm Technical Efficiency in Lesotho," World Development, Elsevier, vol. 28(1), pages 143-153, January.

    More about this item

    Keywords

    Models with Panel Data; Capital; Produtivity; Firm choice; Growth; Investment; Corporate Finance; Firm objectives; Firm performance; Industry studies; Manufacturing; Primary products and construction; Services; Transportation and utilities; Business economics; Research and development;
    All these keywords.

    JEL classification:

    • L25 - Industrial Organization - - Firm Objectives, Organization, and Behavior - - - Firm Performance
    • L90 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - General
    • O32 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Management of Technological Innovation and R&D
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • G30 - Financial Economics - - Corporate Finance and Governance - - - General
    • L80 - Industrial Organization - - Industry Studies: Services - - - General
    • L60 - Industrial Organization - - Industry Studies: Manufacturing - - - General
    • L21 - Industrial Organization - - Firm Objectives, Organization, and Behavior - - - Business Objectives of the Firm
    • D92 - Microeconomics - - Micro-Based Behavioral Economics - - - Intertemporal Firm Choice, Investment, Capacity, and Financing
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • M21 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Economics - - - Business Economics
    • L70 - Industrial Organization - - Industry Studies: Primary Products and Construction - - - 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:pra:mprapa:24336. 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: Joachim Winter (email available below). General contact details of provider: https://edirc.repec.org/data/vfmunde.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.