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CEO Pay‐For‐Performance Heterogeneity Using Quantile Regression

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  • Kevin F. Hallock
  • Regina Madalozzo
  • Clayton G. Reck

Abstract

We provide some examples of how quantile regression can be used to investigate heterogeneity in pay‐firm size and pay‐performance relationships for U.S. CEOs. For example, do conditionally (predicted) high‐wage managers have a stronger relationship between pay and performance than conditionally low‐wage managers? Our results using data over a decade show, for some standard specifications, there is considerable heterogeneity in the returns‐to‐firm performance across the conditional distribution of wages. Quantile regression adds substantially to our understanding of the pay‐performance relationship. This heterogeneity is masked when using more standard empirical techniques.

Suggested Citation

  • Kevin F. Hallock & Regina Madalozzo & Clayton G. Reck, 2010. "CEO Pay‐For‐Performance Heterogeneity Using Quantile Regression," The Financial Review, Eastern Finance Association, vol. 45(1), pages 1-19, February.
    • Handle: RePEc:bla:finrev:v:45:y:2010:i:1:p:1-19
    DOI: 10.1111/j.1540-6288.2009.00235.x
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    Cited by:

    1. Geiler, P.H.M. & Renneboog, L.D.R., 2014. "Executive Remuneration and the Payout Decision," Discussion Paper 2014-032, Tilburg University, Center for Economic Research.
    2. Cheng, Chia-Yi, 2014. "A longitudinal study of newcomer job embeddedness and sales outcomes for life insurance salespersons," Journal of Business Research, Elsevier, vol. 67(7), pages 1430-1438.
    3. K. Sommerfeld, 2013. "Higher and higher? Performance pay and wage inequality in Germany," Applied Economics, Taylor & Francis Journals, vol. 45(30), pages 4236-4247, October.
    4. Guilherme Resende Oliveira & Benjamin Miranda Tabak & José Guilherme de Lara Resende & Daniel Oliveira Cajueiro, 2012. "Determinantes da Estrutura de Capital das Empresas Brasileiras: uma abordagem em regressão quantílica," Working Papers Series 272, Central Bank of Brazil, Research Department.
    5. Riachi, Ilham & Schwienbacher, Armin, 2013. "Securitization of corporate assets and executive compensation," Journal of Corporate Finance, Elsevier, vol. 21(C), pages 235-251.
    6. Livingston, Miles & Yao, Ping & Zhou, Lei, 2019. "The volatility of mutual fund performance," Journal of Economics and Business, Elsevier, vol. 104(C), pages 1-1.
    7. Conyon, Martin J. & He, Lerong, 2017. "Firm performance and boardroom gender diversity: A quantile regression approach," Journal of Business Research, Elsevier, vol. 79(C), pages 198-211.
    8. Owen P. Hall Jr. & Darrol J. Stanley, 2012. "A comparative modelling analysis of firm performance," International Journal of Data Analysis Techniques and Strategies, Inderscience Enterprises Ltd, vol. 4(1), pages 43-56.
    9. Haylock, Michael, 2020. "Executives' short-term and long-term incentives - a distributional analysis," University of Tübingen Working Papers in Business and Economics 131, University of Tuebingen, Faculty of Economics and Social Sciences, School of Business and Economics.
    10. Seth Armitage & Dionysia Dionysiou & Angelica Gonzalez, 2014. "Are the Discounts in Seasoned Equity Offers Due to Inelastic Demand?," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 41(5-6), pages 743-772, June.
    11. Harris, Oneil & Glegg, Charmaine & Buckley, Winston, 2019. "Do co-opted boards enhance or reduce R&D productivity?," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
    12. Owen P. Hall Jr. & Kenneth Ko, 2014. "Determinates of Executive Compensation: A Hierarchical Linear Modeling Approach," International Journal of Knowledge-Based Organizations (IJKBO), IGI Global, vol. 4(2), pages 53-63, April.
    13. Mohamed S. Ahmed & John A. Doukas, 2021. "Revisiting disposition effect and momentum: a quantile regression perspective," Review of Quantitative Finance and Accounting, Springer, vol. 56(3), pages 1087-1128, April.
    14. Zeinedini, Sh & Karimi, M. Sh & Khanzadi, A., 2022. "Impact of global oil and gold prices on the Iran stock market returns during the Covid-19 pandemic using the quantile regression approach," Resources Policy, Elsevier, vol. 76(C).

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