e-journal
Coincident and forecast relevance of accounting numbers
Purpose – Value relevance studies, in particular international comparative studies, use market
values sampled at different dates relative to the fiscal year-end. This paper aims to contribute a
theoretical and empirical analysis of the relationship between value relevance and the month of market
value sampling.
Design/methodology/approach – The paper examines two components of value relevance,
coincident relevance and forecast relevance, which the paper develops on the basis of the Ohlson
model. The paper measures value relevance by estimating separate panel-data regressions for each of
the 12 months around fiscal year-end. The sample consists of companies listed in two continental
European countries, France and Germany, over the 1989-2008 period.
Findings – In both country panels, the paper finds that overall value relevance is higher when market
value is sampled before or close to fiscal year-end, but incremental value relevance varies
between domestic and International Financial Reporting (IFRS) accounting standards. Regression
results reveal significant variations in coefficients over the following months of market value in
French panel and its IFRS sub-sample only.
Research limitations/implications – The scope of the study is limited to the average value
relevance parameters of companies listed on stock exchanges in France and Germany. Future research
may be devoted to other countries and study additional determinants of value relevance.
Practical implications – The study shows that the selection of the month of market value sampling
can have significant impact on value relevance regression results. Therefore, sensitivity analysis
needs to be included in research studies which rely on the value relevance approach.
Originality/value – The paper contributes the first systematic analysis of the variation in value
relevance parameters in response to the selection of the month in which market value is sampled.
Keywords Value relevance, Accounting-based valuation, Panel regression, Residual income model
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