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Measuring firm performance by using linear and non-parametric quantile regressions


  • Manuel Landajo
  • Javier de Andrés
  • Pedro Lorca


Quantile regression models are examined from the standpoint of their suitability to analyse company profitability. Some linear and non-linear ("B"-spline) structures are proposed. Linear conditional quantile models provide an intuitive framework which permits conventional statistical inference tools to be applied. Non-parametric spline-based quantile regression is a flexible approach, allowing a different grade of curvature for each conditional quantile, thus providing the possibility of capturing certain non-linear effects that are predicted by economic theory. The behaviour of these variants of the quantile framework is tested on a representative database, which was obtained from the Spanish book publishing industry. Our results confirm the usefulness of the quantile regression approach. Linear models seem to provide suitable descriptions for the behaviour of average performing firms, whereas non-parametric estimates provide the best fit for the extreme conditional quantiles (i.e. companies which exhibit the highest and the lowest performance in terms of profitability). Copyright (c) 2008 Royal Statistical Society.

Suggested Citation

  • Manuel Landajo & Javier de Andrés & Pedro Lorca, 2008. "Measuring firm performance by using linear and non-parametric quantile regressions," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 57(2), pages 227-250.
  • Handle: RePEc:bla:jorssc:v:57:y:2008:i:2:p:227-250

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    References listed on IDEAS

    1. Raffaella Giacomini & Halbert White, 2006. "Tests of Conditional Predictive Ability," Econometrica, Econometric Society, vol. 74(6), pages 1545-1578, November.
    2. Zimmerman, Jerold L., 1983. "Taxes and firm size," Journal of Accounting and Economics, Elsevier, vol. 5(1), pages 119-149, April.
    3. S. Illeris & G. Akehurst, 2001. "Introduction," The Service Industries Journal, Taylor & Francis Journals, vol. 21(1), pages 1-4, January.
    4. Mata, Jose & Machado, Jose A. F., 1996. "Firm start-up size: A conditional quantile approach," European Economic Review, Elsevier, vol. 40(6), pages 1305-1323, June.
    5. Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
    6. Fattouh, Bassam & Scaramozzino, Pasquale & Harris, Laurence, 2005. "Capital structure in South Korea: a quantile regression approach," Journal of Development Economics, Elsevier, vol. 76(1), pages 231-250, February.
    7. Dowen, Richard J & Bauman, W Scott, 1997. "The Relationship between Market Efficiency and Insider Ownership in Large and Small Firms," The Financial Review, Eastern Finance Association, vol. 32(1), pages 185-203, February.
    8. Melly, Blaise, 2005. "Decomposition of differences in distribution using quantile regression," Labour Economics, Elsevier, vol. 12(4), pages 577-590, August.
    9. Bougheas, Spiros & Mizen, Paul & Yalcin, Cihan, 2006. "Access to external finance: Theory and evidence on the impact of monetary policy and firm-specific characteristics," Journal of Banking & Finance, Elsevier, vol. 30(1), pages 199-227, January.
    10. Moshe Buchinsky, 1998. "Recent Advances in Quantile Regression Models: A Practical Guideline for Empirical Research," Journal of Human Resources, University of Wisconsin Press, vol. 33(1), pages 88-126.
    11. Sudarsanam, P. S. & Taffler, R. J., 1995. "Financial ratio proportionality and inter-temporal stability: An empirical analysis," Journal of Banking & Finance, Elsevier, vol. 19(1), pages 45-60, April.
    12. Josep-Maria Arauzo-Carod & Agustí Segarra-Blasco, 2005. "The Determinants of Entry are not Independent of Start-up Size: Some Evidence from Spanish Manufacturing," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 27(2), pages 147-165, September.
    13. Basu, Sudipta, 1997. "The conservatism principle and the asymmetric timeliness of earnings," Journal of Accounting and Economics, Elsevier, vol. 24(1), pages 3-37, December.
    14. Racine, Jeff, 1997. "Consistent Significance Testing for Nonparametric Regression," Journal of Business & Economic Statistics, American Statistical Association, vol. 15(3), pages 369-378, July.
    15. Joe Whittaker & Chris Whitehead & Mark Somers, 2005. "The neglog transformation and quantile regression for the analysis of a large credit scoring database," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 54(5), pages 863-878.
    16. Hudson, Carl D & Jahera, John S, Jr & Lloyd, William P, 1992. "Further Evidence on the Relationship between Ownership and Performance," The Financial Review, Eastern Finance Association, vol. 27(2), pages 227-239, May.
    17. Joshua Angrist & Victor Chernozhukov & Iván Fernández-Val, 2006. "Quantile Regression under Misspecification, with an Application to the U.S. Wage Structure," Econometrica, Econometric Society, vol. 74(2), pages 539-563, March.
    18. Mulherin, J. Harold & Boone, Audra L., 2000. "Comparing acquisitions and divestitures," Journal of Corporate Finance, Elsevier, vol. 6(2), pages 117-139, July.
    19. Koenker, Roger, 2000. "Galton, Edgeworth, Frisch, and prospects for quantile regression in econometrics," Journal of Econometrics, Elsevier, vol. 95(2), pages 347-374, April.
    20. Natália Barbosa & Helen Louri, 2005. "Corporate Performance: Does Ownership Matter? A Comparison of Foreign- and Domestic-Owned Firms in Greece and Portugal," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 27(1), pages 73-102, August.
    21. Lev, Baruch & Sunder, Shyam, 1979. "Methodological issues in the use of financial ratios," Journal of Accounting and Economics, Elsevier, vol. 1(3), pages 187-210, December.
    22. Thorburn, Karin S., 2000. "Bankruptcy auctions: costs, debt recovery, and firm survival," Journal of Financial Economics, Elsevier, vol. 58(3), pages 337-368, December.
    23. Sophia Dimelis & Helen Louri, 2002. "Foreign ownership and production efficiency: a quantile regression analysis," Oxford Economic Papers, Oxford University Press, vol. 54(3), pages 449-469, July.
    24. Hong, Yongmiao & White, Halbert, 1995. "Consistent Specification Testing via Nonparametric Series Regression," Econometrica, Econometric Society, vol. 63(5), pages 1133-1159, September.
    25. Timotheos Angelidis & Stavros Degiannakis, 2005. "Modeling risk for long and short trading positions," Journal of Risk Finance, Emerald Group Publishing, vol. 6(3), pages 226-238, May.
    26. Kothari, S.P. & Leone, Andrew J. & Wasley, Charles E., 2005. "Performance matched discretionary accrual measures," Journal of Accounting and Economics, Elsevier, vol. 39(1), pages 163-197, February.
    27. Landajo, Manuel & de Andres, Javier & Lorca, Pedro, 2007. "Robust neural modeling for the cross-sectional analysis of accounting information," European Journal of Operational Research, Elsevier, vol. 177(2), pages 1232-1252, March.
    28. Angelidis, Timotheos & Degiannakis, Stavros, 2005. "Modeling Risk for Long and Short Trading Positions," MPRA Paper 80467, University Library of Munich, Germany.
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    2. Gregg, Daniel & Rolfe, John, 2016. "The value of environment across efficiency quantiles: A conditional regression quantiles analysis of rangelands beef production in north Eastern Australia," Ecological Economics, Elsevier, vol. 128(C), pages 44-54.
    3. Timo Schmid & Ralf Münnich, 2014. "Spatial robust small area estimation," Statistical Papers, Springer, vol. 55(3), pages 653-670, August.
    4. Abdelaati Daouia & Léopold Simar & Paul W. Wilson, 2017. "Measuring firm performance using nonparametric quantile-type distances," Econometric Reviews, Taylor & Francis Journals, vol. 36(1-3), pages 156-181, March.
    5. Yan Alperovych & Georges Hübner, 2013. "Incremental impact of venture capital financing," Small Business Economics, Springer, vol. 41(3), pages 651-666, October.
    6. Alperovych, Yan & Hübner, Georges, 2011. "Explaining returns on venture capital backed companies: Evidence from Belgium," Research in International Business and Finance, Elsevier, vol. 25(3), pages 277-295, September.
    7. Philippe Van Kerm & Seunghee Yu & Chung Choe, 2016. "Decomposing quantile wage gaps: a conditional likelihood approach," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 65(4), pages 507-527, August.
    8. VAN KERM Philippe & YU Seunghee & CHOE Chung, 2014. "Wage differentials between native, immigrant and cross-border workers: Evidence and model comparisons," LISER Working Paper Series 2014-05, LISER.

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