Using partial least squares in archival accounting research: an application to earnings quality measuring

• Ana Licerán-Gutiérrez ^[1] ; Manuel Cano-Rodríguez ^[1]
  1. [1] Universidad de Jaén

     Universidad de Jaén

     Jaén, España

     
• Localización: Revista española de financiación y contabilidad, ISSN 0210-2412, Vol. 49, Nº 2, 2020, págs. 143-170
• Idioma: inglés
• DOI: 10.1080/02102412.2019.1608705
• Títulos paralelos:
  • Utilización de mínimos cuadrados parciales en la investigación contable de archivo: aplicación a la medición de la calidad del resultado.
• Texto completo no disponible (Saber más ...)
• Resumen
  • español

    A pesar de las ventajas de los Modelos de Ecuaciones Estructurales (SEM) respecto a los modelos de regresión que han contribuido a su popularización en diversos campos de invenstigación en Ciencias Sociales, no ha sido ampliamente aplicada en la investigación contable de archivo. En este estudio, presentamos una guía para la aplicación del SEM - y, en particular, el método de Mínimos Cuadrados Parciales (PLS) - al tema (posiblemente) más recurrente en investigación empírica contable de archivo: la calidad del resultado. Destacamos diversos problemas que surgen en la medición de la calidad del resultado, indicando cómo PLS puede ayudar a solventarlos. Asimismo desarrollamos un proceso de simulación cuyos resultados muestran cómo el método PLS supera a otros métodos incluso en situaciones de información limitada.

  • English

    Despite the advantages of Structural Equation Modelling (SEM) over regression models that have contributed to its popularisation in several fields of research in social sciences, it has not been broadly applied in archival accounting research. In this paper, we present a guidance for the application of SEM – and, particularly, the Partial Least Squares (PLS) method – to the (arguably) most recurrent topic on empirical archival accounting research: earnings quality. We highlight several problems that arise in earnings quality measuring, indicating how PLS can help to overcome them. We also run a simulation process whose results show that PLS method outperforms the other approaches even in situations of limited information.

• Referencias bibliográficas
  • Aguirre-Urreta, M. I, Marakas, G. M. (2012). Revisiting bias due to construct misspecification: different results from considering coefficients...
  • Babbie, E. (2017). The basics of social research (7th ed.). Boston, United States, Boston: Wadsworth Publishing. (Cengage, Ed.)
  • Ball, R., Shivakumar, L. (2005). Earnings quality in UK private firms: Comparative loss recognition timeliness. Journal of Accounting &...
  • Barclay, D. W., Higgins, C. A., Thompson, R. (1995). The partial least squares approach to causal modeling: Personal computer adoption and...
  • Barth, M. E., Landsman, W. R., Lang, M. H. (2008). International accounting standards and accounting quality. Journal of Accounting Research,...
  • Becker, J. M., Rai, A., Rigdon, E. E. (2013). Predictive validity and formative measurement in structural equation modeling: Embracing practical...
  • Bhattacharya, N., Ecker, F., Olsson, P., Schipper, K. (2012). Direct and mediated associations among earnings quality, information asymmetry,...
  • Bhattacharya, U., Daouk, H., Welker, M. (2003). The world price of earnings opacity. The Accounting Review, 78(3), 641–678.
  • Biddle, G. C., Hilary, G. (2006). Accounting quality and firm-level capital investment. The Accounting Review, 81(5), 963–982.
  • Bisbe, J., Batista-Foguet, J.-M., Chenhall, R. (2007). Defining management accounting constructs: A methodological note on the risks of conceptual...
  • Blanthorne, C., Jones-Farmer, L. A., Almer, E. D. (2006). Why you should consider SEM: A guide to getting started. In V. Arnold, B. D. Clinton,...
  • Bollen, K. A. (2002). Latent variables in psychology and the social sciences. Annual Review of Psychology, 53, 605–634.
  • Bollen, K. A., Bauldry, S. (2011). Three Cs in measurement models: Causal indicators, composite indicators, and covariates. Psychological...
  • Boulton, T. J., Smart, S. B., Zutter, C. J. (2011). Earnings quality and international IPO underpricing. The Accounting Review, 86(2), 483–505.
  • Burgstahler, D., Hail, L., Leuz, C. (2006). The importance of reporting incentives: Earnings management in European private and public firms....
  • Carmines, E. G., Zeller, R. A. (1979). Reliability and validity assessment. SAGE University papers on quantitative applications in the social...
  • Chaney, P. K., Cooil, B., Jeter, D. (2008). A latent class model of earnings attributes.(June 12, 2008). Available at SSRN: https://ssrn.com/abstract=916605
  • Chang, W., Franke, G. R., Lee, N. (2016). Comparing reflective and formative measures: New insights from relevant simulations. Journal of...
  • Chin, W. (1998). The partial least squares approach for estructural equation modeling. Modern methods for business researchs (pp. 295–336)....
  • Chin, W. W. (2010). How to write up and report PLS analyses. In V. Esposito Vinzi, W. W. Chin, J. Henseler, & H. Wang (Eds.), Handbook...
  • Christodoulou, D., Ma, L., Vasnev, A. (2018). Inference-in-residuals as an estimation method for earnings management. Abacus, 54(2), 154–180.
  • Davick, N. S. (2014). The use and misuse of structural equation modeling in management research: A review and critique. Journal of Advances...
  • Dechow, P., Dichev, I. (2002). The quality of accruals and earnings: The role of accrual estimation errors. The Accounting Review, 77(Supplement),...
  • Dechow, P., Ge, W., Schrand, C. (2010). Understanding earnings quality: A review of the proxies, their determinants and their consequences....
  • Dechow, P., Schrand, C. (2004). Earnings quality. The research foundation of CFA institute. Charlottesville,VA., United States.
  • Dechow, P., Sloan, R. G., Sweeney, A. P. (1995). Detecting earnings management. The Accounting Review, 70(2), 193–225.
  • DeFond, M. L. (2010). Earnings quality research: Advances, challenges and future research. Journal of Accounting and Economics, 50(2–3), 402–409.
  • Demerjian, P., Lewis, M., Lev, B., McVay, S. (2013). Managerial ability and earnings quality. The Accounting Review, 88(2), 463–498.
  • Dichev, I., Tang, V. W. (2009). Earnings volatility and earnings predictability. Journal of Accounting and Economics, 47(1–2), 160–181.
  • Dijkstra, T. K. (2015). Consistent partial least squares path modeling. MIS Quarterly, 39(2), 297–316.
  • Dijkstra, T. K., Henseler, J. (2015). Consistent and asymptotically normal PLS estimators for linear structural equations. Computational Statistics...
  • Doupnik, T. S. (2008). Influence of culture on earnings management: A note. Abacus, 44(3), 317–340.
  • Edwards, J. R. (2001). Multidimensional constructs in organizational behavior research: An integrative analytical framework. Organizational...
  • Edwards, J. R., Bagozzi, R. P. (2000). On the nature and direction of relationships between constructs and measures. Psychological Methods,...
  • Ewert, R., Wagenhofer, A. (2011). Earnings quality metrics and what they measure (Working Paper). University of Graz.
  • Ferrer, C., Lainez, J. (2013). Detecting differences on the earnings quality measurement: Empirical evidence on Spanish firms. Revista de...
  • Fornell, C., Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing...
  • Francis, J., LaFond, R., Olsson, P., Schipper, K. (2004). Costs of equity and earnings attributes. The Accounting Review, 79(4), 967–1010....
  • Francis, J., Nanda, D., Olsson, P. (2008). Voluntary disclosure, earnings quality and cost of capital. Journal of Accounting Research, 46(1),...
  • Gaio, C., Raposo, C. (2011). Earnings quality and firm valuation: International evidence. Accounting and Finance, 51(2), 467–499.
  • Gefen, D., Rigdon, E. E., Straub, D. W. (2011). An update and extension to SEM guidelines for administrative and social science research....
  • Gefen, D., Straub, D. W., Boudreau, M.-C. (2000). Structural equation modeling and regression: Guidelines for research practice. Communications...
  • Givoly, D., Hayn, C. (2000). The changing time-series properties of earnings, cash flows and accruals: Has financial reporting become more...
  • Goodhue, D., Lewis, W., Thompson, R. (2012). Does PLS have advantages for small sample size or non-normal data? MIS Quarterly, 36(3), 981–1001.
  • Gow, I. D., Larcker, D. F., Reiss, P. C. (2016). Causal inference in accounting research. Journal of Accounting Research, 54(2), 477–523.
  • Hair, J. F., Ringle, C. M., Sarstedt, M. (2011). PLS-SEM: Indeed a silver bullet. The Journal of Marketing Theory and Practice, 19(2), 139–152.
  • Hair, J. F., Ringle, C. M., Sarstedt, M. (2013). Partial least squares structural equation modeling: Rigorous applications, better results...
  • Hair, J. F., Sarstedt, M., Pieper, T. M., Ringle, C. M. (2012). The use of partial least squares structural equation modeling in strategic...
  • Hair, J. F., Sarstedt, M., Ringle, C. M., Gudergan, S. P. (2017). Advanced issues in partial least squares structural equation modeling (2nd...
  • Hair, J. F., Tomas, G., Hult, M., Ringle, C. M., Sarstedt, M. (2016). A primer on partial least squares structural equation modeling (PLS-SEM)...
  • Hampton, C. (2015). Estimating and reporting structural equation models with behavioral accounting data. Behavioral Research in Accounting,...
  • Henri, J.-F. (2007). A quantitative assessment of the reporting of structural equation modeling information. The case of management accounting...
  • Henseler, J., Ringle, C. M., Sarstedt, M. (2012). Using partial least squares path modeling in advertising research: Basic concepts and recent...
  • Henseler, J., Dijkstra, T. K., Sarstedt, M., Ringle, C. M., Diamantopoulos, A., Straub, D. W., Calantone, R. (2014). Common beliefs and reality...
  • Henseler, J., Ringle, C. M., Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation...
  • Henseler, J., Ringle, C. M., Sinkovics, R. R. (2009). The use of partial least squares structural equation modeling in marketing research....
  • Henseler, J., Sarstedt, M. (2013). Goodness-of-fit indices for partial least squares path modeling. Computational Statistics, 28(2), 565–580.
  • Hermanns, S. (2006). Financial information and earnings quality: A literature review. (April 2006). Available at SSRN: https://ssrn.com/abstract=897722
  • Hinson, L. A., Utke, S. (2018). Structural equation modeling in archival capital markets research. (July 2, 2018). Available at SSRN: https://ssrn.com/abstract=2614085
  • IASB. (2010). The conceptual framework for financial reporting. International Accounting Standards Board, London.
  • Jackson, A. B. (2018). Discretionary accruals: Earnings management . . . or Not? Abacus, 54(2), 136–153.
  • Jarvis, C. B., MacKenzie, S. B., Podsakoff, P. M. (2003). A critical review of construct indicators and measurement model misspecification...
  • Jones, K. L., Krishnan, G. V., Melendrez, K. D. (2008). Do models of discretionary accruals detect actual cases of fraudulent and restated...
  • Laksmana, I., Yang, Y. (2009). Corporate citizenship and earnings attributes. Advances in Accounting, 25(1), 40–48.
  • Larcker, D. F., Rusticus, T. O. (2010). On the use of instrumental variables in accounting research. Journal of Accounting and Economics,...
  • Lee, L., Petter, S., Fayard, D., Robinson, S. (2011). On the use of partial least squares path modeling in accounting research. International...
  • Leuz, C., Nanda, D., Wysocki, P. D. (2003). Earnings management and investor protection: An international comparison. Journal of Financial...
  • Leuz, C., Wysocki, P. D. (2016). The economics of disclosure and financial reporting regulation: Evidence and suggestions for future research....
  • Libby, R., Bloomfield, R., Nelson, M. W. (2002). Experimental research in financial accounting. Accounting, Organizations and Society, 27(8),...
  • Licerán-Gutiérrez, A., Cano-Rodríguez, M. (2019). A review on the multidimensional analysis of earnings qualilty. Revista de Contabilidad,...
  • MacKenzie, S. B., Podsakoff, P. M., Jarvis, C. B. (2005). The problem of measurement model misspecification in behavioral and organizational...
  • Mackenzie, S. B., Podsakoff, P. M., Podakoff, N. P. (2011). Construct measurement and validation procedures in mis and behavioral research:...
  • Mateos-Aparicio, G. (2011). Partial least squares (PLS) methods: Origins, evolution, and application to social sciences. Communications in...
  • McNichols, M. F., Stubben, S. R. (2018). Research design issues in studies using discretionary accruals. Abacus, 54(2), 227–246.
  • Nitzl, C. (2016). The use of partial least squares structural equation modelling (PLS-SEM) in management accounting research: Directions for...
  • Numally, J. C., Bernstein, I. H. (1994). Psychometric theory (3rd ed.). New York, NY: Mc Graw Hill.
  • Penman, S. H., Zhang, X.-J. (2002). Accounting conservatism, the quality of earnings, and stock returns. The Accounting Review, 77(2), 237–264....
  • Perotti, P., Wagenhofer, A. (2014). Earnings quality measures and excess returns. Journal of Business Finance & Accounting, 41(5–6), 545–571.
  • Reinartz, W., Haenlein, M., Henseler, J. (2009). An empirical comparison of the efficacy of covariance-based and variance-based SEM. International...
  • Rigdon, E. E. (2012). Rethinking partial least squares path modeling: In praise of simple methods. Long Range Planning, 45(5–6), 341–358.
  • Rigdon, E. E. (2014). Rethinking partial least squares path modeling: Breaking chains and forging ahead. Long Range Planning, 47(3), 161–167.
  • Rigdon, E. E. (2016). Choosing PLS path modeling as analytical method in European management research: A realist perspective. European Management...
  • Ringle, C. M., Sarstedt, M., Schlittgen, R. (2014). Genetic algorithm segmentation in partial least squares structural equation modeling....
  • Ringle, C. M., Sarstedt, M., Straub, D. W. (2012). A critical look at the use of PLS-SEM in MIS Quarterly. MIS Quarterly, 36(1), 3–14.
  • Rodgers, W., Guiral, A. (2011). Potential model misspecification bias: Formative indicators enhancing theory for accounting researchers. The...
  • Roldán, J. L., Sánchez-Franco, M. J. (2012). Variance-based structural equation modeling: Guideliness for using partial least squares in information...
  • Ronkko, M., Evermann, J. (2013). A critical examination of common beliefs about partial least squares path modeling. Organizational Research...
  • Sarstedt, M., Hair, J. F., Ringle, C. M., Thiele, K. O., Gudergan, S. P. (2016). Estimation issues with PLS and CBSEM: Where the bias lies!...
  • Sarstedt, M., Ringle, C. M., Hair, J. F. (2014). PLS-SEM: Looking back and moving forward. Long Range Planning, 47(3), 132–137.
  • Schipper, K., Vincent, L. (2003). Earnings quality. Accounting Horizons, 17, 97–110.
  • Tenenhaus, M., Vinzi, V. E., Chatelin, Y. M., Lauro, C. (2005). PLS path modeling. Computational Statistics and Data Analysis, 48(1), 159–205.
  • Ullman, J. B. (2006). Structural equation modeling : Reviewing the basics and moving forward. Journal of Personality Assessment, 87(1), 35–50.
  • VanTendeloo, B., Vanstraelen, A. (2008). Earnings management and audit quality in Europe: Evidence from the private client segment market....
  • Wold, H. (1980). Model construction and evaluation when theoretical knowledge is scarce (pp. 47–74). Bureau of Economic Research. Cambridge,...
  • Wold, H. (1985, September). Systems analysis by partial least squares. Measuring the unmeasurable, Llumina Press. NYC, United States.