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Alternative Errors-in-Variables Models and Their Applications in Finance Research

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Encyclopedia of Finance

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Abstract

Specification error and measurement error are two major issues in finance research. The main purpose of this entry is (i) to review and extend existing errors-in-variables (EIV) estimation methods, including classical method, grouping method, instrumental variable method, mathematical programming method, maximum likelihood method, LISREL method, and the Bayesian approach; (ii) to investigate how EIV estimation methods have been used to finance related studies, such as cost of capital, capital structure, investment equation, and test capital asset pricing models; and (iii) to give a more detailed explanation of the methods used by Almeida et al. (Review of Financial Studies, 23, 3279–3328, 2010).

This entry is the revised and updated version of our entry entitled “Alternative Errors-in-Variables Models and their applications in Finance Research” which was published in The Quarterly Review of Economics and Finance in 2015.

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Notes

  1. 1.

    For the measurement problems related to the determinants of the capital structure, please see Titman and Wessels (1988), Chang et al. (2009), and Yang et al. (2009). For the measurement problems related to the investment function, please see Erickson and Whited (2000, 2002) and Almeida et al. (2010).

  2. 2.

    Please see Lee (1973) and Chen (2011) for detail.

  3. 3.

    Please see Lee (1973) for the solution of Eq. (33).

  4. 4.

    Stapleton (1978) further develops MIMIC with more latent variables.

  5. 5.

    Roll (1969, 1977), and Lee and Jen (1978) show that the observed market rate returns in terms of stock market index are measured with errors since the stock market index does not include all assets which investors can invest. Lee and Jen (1978) have theoretically shown how beta estimate and Jensen performance measures can be affected by both constant and random measurement errors of Rm and Rf.

    Diacogiannis and Feldman (2011), Green (1986), Roll and Ross (1994), and Gibbons and Ferson (1985) have argued that market portfolio measure with errors is an inefficient portfolio and show how the inefficient benchmark can affect theoretical CAPM derivation. Diacogiannis and Feldman (2011) provide a pricing model that uses inefficient benchmarks, a two beta model, one induced by the benchmark, and one adjusting for its inefficiency.

  6. 6.

    Please check Chap. 8 of Lee et al. (2019) entitled “Three alternative methods in testing capital asset pricing model.”

  7. 7.

    Empirical work in testing association between the investment decision and cash flow shows that cash flow has poor explanation in determining investment decision. In addition to cash flow, output, sales, and internal funds have significant explanation in determining investment decision.

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Authors and Affiliations

  1. Department of Finance, National Chengchi University, Taipei, Taiwan

    Hong-Yi Chen

  2. Center for PBBEF Research, Phoenix, AZ, USA

    Alice C. Lee

  3. Department of Finance and Economics, Rutgers University, Rutgers Business School, Rutgers, The State University of New Jersey, Piscataway, NJ, USA

    Cheng-Few Lee

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  1. Hong-Yi Chen
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  2. Alice C. Lee
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  1. Rutgers School of Business, Rutgers, The State University of New Jer, Piscataway, NJ, USA

    Cheng-Few Lee

  2. Phoenix, AZ, USA

    Alice C. Lee

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Chen, HY., Lee, A.C., Lee, CF. (2021). Alternative Errors-in-Variables Models and Their Applications in Finance Research. In: Lee, CF., Lee, A.C. (eds) Encyclopedia of Finance. Springer, Cham. https://doi.org/10.1007/978-3-030-73443-5_103-1

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