On Empirically Capturing 'Other Information'

43 Pages Posted: 12 Mar 2013

See all articles by Thanamas Kungwal

Thanamas Kungwal

Keele University - Keele Management School

Yun Shen

University of Nottingham, Ningbo

Andrew W. Stark

Alliance Manchester Business School, University of Manchester

Date Written: March 12, 2013


In this study, we examine the performance of two different measures of 'other information' found in the accounting literature. One is based upon last year’s valuation error, once the impact of accounting variables on value is controlled for. The other is based upon using one-year-ahead consensus analyst forecasts. We consider both measures from a theoretical perspective and find that they suffer from different problems which make it difficult to rank them in the absence of empirical evidence. We adopt the criterion of addition to explanatory power to evaluate the measures empirically. The two measures are also likely to impose (possibly different) sample selection biases, as well, in terms of both the numbers of firm-years lost and the characteristics of the observations data, because of their different requirements for additional data.

In terms of observations lost and contribution to explanatory power, the use of last year’s valuation error is far superior to the use of the one-year-ahead valuation error. Further, our results suggest that the two measures impose sample selection and the selection biases are different between the two measures. Nonetheless, the measures do appear to contain complementary information such that they can both contribute to the explanation of market value in tandem. To do so, however, requires losing a majority of the available observations. Whether the loss of observations is compensated for by the additional statistical power provided by incorporating more significant explanatory variables, combined with any attendant sample selection bias, can only be decided in a particular context.

Keywords: Accounting-based corporate valuation model, Ohlson model, other information

JEL Classification: G12, M41

Suggested Citation

Kungwal, Thanamas and Shen, Yun and Stark, Andrew W., On Empirically Capturing 'Other Information' (March 12, 2013). Available at SSRN: https://ssrn.com/abstract=2231852 or http://dx.doi.org/10.2139/ssrn.2231852

Thanamas Kungwal

Keele University - Keele Management School ( email )

Darwin Building
Staffordshire, ST5 5BG
United Kingdom

Yun Shen (Contact Author)

University of Nottingham, Ningbo ( email )

199 Taikang East Road
Ningbo, Zhejiang 315100

HOME PAGE: http://www.nottingham.edu.cn

Andrew W. Stark

Alliance Manchester Business School, University of Manchester ( email )

Booth Street West
Manchester, M15 6PB
United Kingdom

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