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The Effect of the Fair Value Reporting Model on Analyst Forecast Properties: Evidence from Real Estate
Firms

Table 4 (continued) Additional Analysis: The Effect of Fair Value Model Versus
Historical Cost Model on Forecast Revision Response Time

Panel B: Significance Tests of Sum of Coefficients
Coef. t-stat p-value Coef. t-stat p-value
UK + UK×POST 8.574 3.64 0.000
UK + UK×YEAR_0506 12.048 2.65 0.009
UK + UK×YEAR_0708 14.671 4.63 0.000
UK + UK×YEAR_0910 10.939 3.25 0.001
UK + UK×YEAR_1112 6.203 1.99 0.048
UK + UK×YEAR_1314 4.138 1.21 0.226
Notes: This table presents the results of the multivariate analysis of the determinants of analyst
forecast response time using UK and US firm-year observations from 2002 to 2014. Panel
A presents the regression results, and Panel B details whether the sums of the coefficients
of interest are significant. DURATION is the average analyst forecast revision response
time, measured as the average length of time between the annual report date and the first
report for each analyst. POST equals one after 2005 and zero otherwise. In Column (2), we
replace POST with a vector of time-period indicator variables: YEAR_0506, YEAR_0708,
YEAR_0910, YEAR_1112, and YEAR_1314. YEAR_0506 equals one for the period 2005-
2006 and zero otherwise; all other time-period indicator variables are defined accordingly.
The t-statistics are calculated using robust standard errors clustered at the firm level.

analysis are presented in Column (2). Interestingly, we find that forecast error for UK
firms reporting under IFRS increases only early on in the post-adoption period (2005-2006),
13
exhibiting no change later on in the post-adoption period (2007-2014). These results
are consistent with our argument that IFRS adoption has a time-varying effect on analyst

forecast properties. In other words, while Liang and Riedl (2014) find that introducing
IFRS reduces forecast accuracy, this effect is not permanent; in fact, it is most pronounced
immediately after the adoption of IFRS, disappearing two years later.

Overall, our findings extend those of Liang and Riedl (2014). Moreover, we observe
that, as UK firms’ net income includes non-serially correlated and transient items—
complicating earnings prediction—forecast error increases in the post-IFRS period.
However, this pattern appears to be a short-term phenomenon, as there is no significant
reduction in later years.

13 We extend the sample used in Liang and Riedl (2014) and include firm-year observations after 2010.

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