IDEAS home Printed from https://ideas.repec.org/a/gam/jjrfmx/v15y2022i10p486-d949740.html

Revisiting the Long-Run Dynamic Linkage between Dividends and Share Price with Advanced Panel Econometrics Techniques

Author

Listed:
  • Sudatta Bharati Mohapatra

    (Department of Business Administration, Utkal University, Bhubaneswar 751004, India)

  • Nirmal Chandra Kar

    (Department of Business Administration, Utkal University, Bhubaneswar 751004, India)

Abstract

The log-linearized present value model (PVM) has been widely used in corporate finance to understand the long-run relationship between share price and dividends using panel data. However, the application of recently established panel econometric approaches that account for slope heterogeneity and cross-section dependency in the recent literature regarding the long-run link between share price and dividends in an Indian setting is limited. This paper re-examines the log-linearized PVM in an Indian setting using newly developed panel unit root, cointegration, and long-run dynamic estimation approaches. This study employed a panel dataset of 60 Bombay Stock Exchange (BSE)-listed Indian firms paying regular dividends for 28 years (1990–2017). The study found unit root, cointegration, and a long-run relationship between dividend and share price series for Indian firms during a 28-year sample period. By demonstrating the presence of a long-run link between share price and dividends, this paper contributes to the literature on the PVM, which is crucial in comprehending market rationality and share price behavior in India. This paper also discusses issues related to panel data, such as cross-section dependency and slope heterogeneity, as well as panel econometric approaches that can be applied in the appropriate settings.

Suggested Citation

  • Sudatta Bharati Mohapatra & Nirmal Chandra Kar, 2022. "Revisiting the Long-Run Dynamic Linkage between Dividends and Share Price with Advanced Panel Econometrics Techniques," JRFM, MDPI, vol. 15(10), pages 1-19, October.
    • Handle: RePEc:gam:jjrfmx:v:15:y:2022:i:10:p:486-:d:949740
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1911-8074/15/10/486/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1911-8074/15/10/486/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Breitung, Jörg & Pesaran, Mohammad Hashem, 2005. "Unit roots and cointegration in panels," Discussion Paper Series 1: Economic Studies 2005,42, Deutsche Bundesbank.
    2. Jan Ditzen, 2018. "Estimating dynamic common-correlated effects in Stata," Stata Journal, StataCorp LLC, vol. 18(3), pages 585-617, September.
    3. Jan Ditzen, 2021. "Estimating long-run effects and the exponent of cross-sectional dependence: An update to xtdcce2," Stata Journal, StataCorp LLC, vol. 21(3), pages 687-707, September.
    4. Diba, Behzad T & Grossman, Herschel I, 1988. "Explosive Rational Bubbles in Stock Prices?," American Economic Review, American Economic Association, vol. 78(3), pages 520-530, June.
    5. Damiaan Persyn & Joakim Westerlund, 2008. "Error-correction–based cointegration tests for panel data," Stata Journal, StataCorp LLC, vol. 8(2), pages 232-241, June.
    6. M. Hashem Pesaran, 2021. "General diagnostic tests for cross-sectional dependence in panels," Empirical Economics, Springer, vol. 60(1), pages 13-50, January.
    7. Dierk Herzer & Julian Donaubauer, 2018. "The long-run effect of foreign direct investment on total factor productivity in developing countries: a panel cointegration analysis," Empirical Economics, Springer, vol. 54(2), pages 309-342, March.
    8. Natalia Bailey & Sean Holly & M. Hashem Pesaran, 2016. "A Two‐Stage Approach to Spatio‐Temporal Analysis with Strong and Weak Cross‐Sectional Dependence," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(1), pages 249-280, January.
    9. John Y. Campbell, Robert J. Shiller, 1988. "The Dividend-Price Ratio and Expectations of Future Dividends and Discount Factors," The Review of Financial Studies, Society for Financial Studies, vol. 1(3), pages 195-228.
    10. Sung, Hyun Mo & Urrutia, Jorge L, 1995. "Long-Term and Short-Term Causal Relations between Dividends and Stock Prices: A Test of Lintner's Dividend Model and the Present Value Model of Stock Prices," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 18(2), pages 171-188, Summer.
    11. Im, Kyung So & Pesaran, M. Hashem & Shin, Yongcheol, 2003. "Testing for unit roots in heterogeneous panels," Journal of Econometrics, Elsevier, vol. 115(1), pages 53-74, July.
    12. John Goddard & David Mcmillan & John Wilson, 2008. "Dividends, prices and the present value model: firm-level evidence," The European Journal of Finance, Taylor & Francis Journals, vol. 14(3), pages 195-210.
    13. M. Hashem Pesaran, 2015. "Testing Weak Cross-Sectional Dependence in Large Panels," Econometric Reviews, Taylor & Francis Journals, vol. 34(6-10), pages 1089-1117, December.
    14. Anshu Agrawal, 2021. "Impact of Elimination of Dividend Distribution Tax on Indian Corporate Firms Amid COVID Disruptions," JRFM, MDPI, vol. 14(9), pages 1-38, September.
    15. repec:bla:obuest:v:61:y:1999:i:0:p:631-52 is not listed on IDEAS
    16. M. Hashem Pesaran, 2006. "Estimation and Inference in Large Heterogeneous Panels with a Multifactor Error Structure," Econometrica, Econometric Society, vol. 74(4), pages 967-1012, July.
    17. Kapetanios, George & Shin, Yongcheol & Snell, Andy, 2006. "Testing For Cointegration In Nonlinear Smooth Transition Error Correction Models," Econometric Theory, Cambridge University Press, vol. 22(2), pages 279-303, April.
    18. Marsh, Terry A & Merton, Robert C, 1986. "Dividend Variability and Variance Bounds Tests for the Rationality ofStock Market Prices," American Economic Review, American Economic Association, vol. 76(3), pages 483-498, June.
    19. Peter C. B. Phillips & Donggyu Sul, 2003. "Dynamic panel estimation and homogeneity testing under cross section dependence *," Econometrics Journal, Royal Economic Society, vol. 6(1), pages 217-259, June.
    20. Froot, Kenneth A & Obstfeld, Maurice, 1991. "Intrinsic Bubbles: The Case of Stock Prices," American Economic Review, American Economic Association, vol. 81(5), pages 1189-1214, December.
    21. Phillips, P. C. B. & Ouliaris, S., 1988. "Testing for cointegration using principal components methods," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 205-230.
    22. M. Hashem Pesaran, 2007. "A simple panel unit root test in the presence of cross-section dependence," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(2), pages 265-312.
    23. G. S. Maddala & Shaowen Wu, 1999. "A Comparative Study of Unit Root Tests with Panel Data and a New Simple Test," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 61(S1), pages 631-652, November.
    24. Hyun Mo Sung & Jorge L. Urrutia, 1995. "Long-Term And Short-Term Causal Relations Between Dividends And Stock Prices: A Test Of Lintner'S Dividend Model And The Present Value Model Of Stock Prices," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 18(2), pages 171-188, June.
    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. Sopani Gondwe & Tendai Gwatidzo & Nyasha Mahonye, 2023. "Impact of capital regulation on interest rate pass‐through in Sub‐Saharan Africa," South African Journal of Economics, Economic Society of South Africa, vol. 91(3), pages 351-374, September.

    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. Gianni Carvelli, 2023. "The long-run effects of government expenditure on private investments: a panel CS-ARDL approach," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 47(3), pages 620-645, September.
    2. Chakraborty, Saptorshee Kanto & Mazzanti, Massimiliano, 2020. "Energy intensity and green energy innovation: Checking heterogeneous country effects in the OECD," Structural Change and Economic Dynamics, Elsevier, vol. 52(C), pages 328-343.
    3. Eibinger, Tobias & Deixelberger, Beate & Manner, Hans, 2024. "Panel data in environmental economics: Econometric issues and applications to IPAT models," Journal of Environmental Economics and Management, Elsevier, vol. 125(C).
    4. Mariam Camarero & Sergi Moliner & Cecilio Tamarit, 2025. "Which are the long-run determinants of US outward FDI? Evidence using large long-memory panels," The Journal of International Trade & Economic Development, Taylor & Francis Journals, vol. 34(2), pages 259-290, February.
    5. Markus Eberhardt & Francis Teal, 2008. "Modeling Technology and Technological Change in Manufacturing: How do Countries Differ?," CSAE Working Paper Series 2008-12, Centre for the Study of African Economies, University of Oxford.
    6. Gillman, Max & Csabafi, Tamas Z. & Benk, Szilard & Matyas, Laszlo & Smith, Mitchell P. & Harris, Mark N., 2026. "Revisiting neoclassical growth theory: A primary role for inflation and capacity utilization," Economic Modelling, Elsevier, vol. 154(C).
    7. Le Clech, Néstor A., 2024. "Policy market orientation, property rights, and corruption effects on the rent of non-renewable resources in Latin America and the Caribbean," Resources Policy, Elsevier, vol. 91(C).
    8. Jung, Alexander, 2025. "The quantity theory of money: An empirical analysis for 1870 - 2020," Journal of Macroeconomics, Elsevier, vol. 85(C).
    9. Gangopadhyay, Partha & Jain, Siddharth & Bakry, Walid, 2022. "In search of a rational foundation for the massive IT boom in the Australian banking industry: Can the IT boom really drive relationship banking?," International Review of Financial Analysis, Elsevier, vol. 82(C).
    10. Hamit-Haggar, Mahamat, 2012. "Greenhouse gas emissions, energy consumption and economic growth: A panel cointegration analysis from Canadian industrial sector perspective," Energy Economics, Elsevier, vol. 34(1), pages 358-364.
    11. Chakraborty, Saptorshee Kanto & Mazzanti, Massimiliano, 2021. "Renewable electricity and economic growth relationship in the long run: Panel data econometric evidence from the OECD," Structural Change and Economic Dynamics, Elsevier, vol. 59(C), pages 330-341.
    12. Marcus Box & Karl Gratzer & Xiang Lin, 2023. "Self-employment, corruption, and property rights: a comparative analysis of European and CEE economies," SN Business & Economics, Springer, vol. 3(1), pages 1-29, January.
    13. Elisabet Rodriguez Llorian & Janelle Mann, 2022. "Exploring the technology–healthcare expenditure nexus: a panel error correction approach," Empirical Economics, Springer, vol. 62(6), pages 3061-3086, June.
    14. Trofimov, Ivan D., 2020. "Is There a J-Curve Effect in the Services Trade in Canada? A Panel Data Analysis," MPRA Paper 106704, University Library of Munich, Germany.
    15. Jian Xue & Zeeshan Rasool & Raima Nazar & Ahmad Imran Khan & Shaukat Hussain Bhatti & Sajid Ali, 2021. "Revisiting Natural Resources—Globalization-Environmental Quality Nexus: Fresh Insights from South Asian Countries," Sustainability, MDPI, vol. 13(8), pages 1-19, April.
    16. Skare, Marinko & PORADA-ROCHON, Małgorzata, 2022. "The role of innovation in sustainable growth: A dynamic panel study on micro and macro levels 1990–2019," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
    17. Peñasco, Cristina & del Río, Pablo & Romero-Jordán, Desiderio, 2017. "Gas and electricity demand in Spanish manufacturing industries: An analysis using homogeneous and heterogeneous estimators," Utilities Policy, Elsevier, vol. 45(C), pages 45-60.
    18. Antonio Musolesi & Giada Andrea Prete & Michel Simioni, 2025. "Is infrastructure capital really productive? Nonparametric modeling and data-driven model selection in a cross-sectionally dependent panel framework," Journal of Productivity Analysis, Springer, vol. 64(3), pages 439-455, December.
    19. Skare, Marinko & Ozturk, Ilhan & Porada-Rochoń, Małgorzata & Stjepanovic, Sasa, 2024. "Energy as the new frontier: Dynamic panel data analysis revealing energy's transformative role in economic growth and technological progress," Technological Forecasting and Social Change, Elsevier, vol. 200(C).

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;
    ;

    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:gam:jjrfmx:v:15:y:2022:i:10:p:486-:d:949740. 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 The email address of this maintainer does not seem to be valid anymore. Please ask MDPI Indexing Manager to update the entry or send us the correct address (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.