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

that cognitive biases diminish as they become increasingly familiar with the reporting
environment. Moreover, the implementation of new standards may impose “one-time”
adjustment costs that temporarily raise the difficulty of generating accurate forecasts.
Thus, in our analysis, we examine the potential time-varying effects of IFRS adoption on

forecast dispersion, recognizing that analysts may need time to adjust to new standards
and that the impact may evolve as these analysts gain experience and overcome initial
adjustment costs.

In our sample period, US firms report properties, plants, and equipment at historical
cost subject to impairment without any change in the reporting model. In contrast, the
UK’s 2005 adoption of IFRS marks a shift from a partial fair value model to a full fair
value model. This transition allows for a meaningful comparison to the valuation model
used by US real estate investment firms across the same period, both pre- and post-

transition. As there are two possible outcomes regarding how forecast dispersion changes
following the adoption of IFRS, we do not predict a priori the direction of the effect of the
full fair value model versus that of the partial fair value model on forecast dispersion. The

discussion above leads to the following hypothesis:
H1: The dispersion of analysts’ EPS forecasts is not different between the pre-IFRS and
post-IFRS periods.

3. Research Design

To examine the effect of the fair value model versus that of the historical cost model
on analysts’ forecast dispersion, we follow the approach lied out by prior works (Chen,

Cheng, and Lo, 2014; Lang and Lundholm, 1996; Lee, Pandit, and Willis, 2013; Lehavy,
Li, and Merkley, 2011; Liang and Riedl, 2014; Weiss, 2010) and estimate the following
regression, where subscript i denotes the company and subscript t denotes the year:

DISPERSION = β + β UK + β POST + β UK ×POST + β ROA + β SIZE + β LEV +
3
it
it
2
it
it
it
it
6
4
it
5
0
1
it
β BM + β OTHER_A + β OTHER_L + β EPS_CHANGE +
9
it
10
it
it
7
it
8
β GROWTH + β REIT + β DIVERSIFIED + β STD_RET +
12
it
it
14
it
it
11
13
β PINT + β FOLLOW + β HORIZON + YEAR + ε (1)
it
it
it
16
17
15
it
t
The dependent variable DISPERSION is the dispersion of analyst forecasts, measured as
it.
the average of individual analysts’ forecasts scaled by the absolute value of the mean EPS
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