期刊
REVIEW OF ACCOUNTING STUDIES
卷 20, 期 1, 页码 395-435出版社
SPRINGER
DOI: 10.1007/s11142-014-9300-0
关键词
Linear valuation; Estimation methods; Theil-Sen estimator; OLS
资金
- Samsung Scholarship
OLS-based archival accounting research encounters two well-known problems. First, outliers tend to influence results excessively. Second, heteroscedastic error terms raise the specter of inefficient estimation and the need to scale variables. This paper applies a robust estimation approach due to Theil (Nederlandse Akademie Wetenchappen Ser A 53:386-392, 1950) and Sen (J Am Stat Assoc 63(324):1379-1389, 1968) (TS henceforth). The TS method is easily understood, and it circumvents the two problems in an elegant, direct way. Because TS and OLS are roughly equally efficient under OLS-ideal conditions (Wilcox, Fundamentals of modern statistical methods: substantially improving power and accuracy, 2nd edn. Springer, New York 2010), one naturally hypothesizes that TS should be more efficient than OLS under non-ideal conditions. This research compares the relative efficiency of OLS versus TS in cross-sectional valuation settings. There are two dependent variables, market value and subsequent year earnings; basic accounting variables appear on the equations' right-hand side. Two criteria are used to compare the estimation methods' performance: (i) the inter-temporal stability of estimated coefficients and (ii) the goodness-of-fit as measured by the fitted values' ability to explain actual values. TS dominates OLS on both criteria, and often materially so. Differences in inter-temporal stability of estimated coefficients are particularly apparent, partially due to OLS estimates occasionally resulting in incorrect signs. Conclusions remain even if winsorization and the scaling of variables modify OLS.
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