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The accuracy of Canadian and New Zealand earnings forecasts: A comparison of voluntary versus compulsory disclosures
The Accuracy of Canadian and New Zealand Earnings Forecasts: A Comparison of Voluntary Versus Compulsory Disclosures
Kathryn Pedwell Hussein Warsame Dean Neu
Zhis study compares the accuracy of earnings forecasts provided in voluntary (Canada) and mandatory (New Zealand) disclosure environments. Previous research indicates that voluntary disclosure is usually undertaken by higher-quality firms who wish to communicate favorable signals to the market, whereas lower-quality firms are unable to mimic these signals, and that by these means the capital markets are capable of making appropriate valuations of the firms. Social regulation which mandates earnings forecast disclosures assumes that the market is imperfect and regulation is required to level thefield for the public good. These two environments are compared to draw some conclusions regarding the benefits of regulating forecast disclosure. The results of the comparison suggest that mandatory forecast regulation may force firms to forecast that have neither the ability nor incentives to do so. Instead, the results imply that regulations prohibiting suchjirms from forecasting may be a more appropriate regulatory strategy.
INTRODUCTION For firms applying for a new stock exchange listing, earnings forecasts represent a substantial proportion of the information available about the organization to the public. However, provision of such earnings forecasts varies, with inclusion being rare in the United States and virtually universal in the United Kingdom and New Zealand. In Canada, the inclusion of earnings forecasts is strictly voluntary. This study compares the predictive accuracy of voluntary (earnings forecasts made in Canadian prospectuses against the
Journal of International Accounting Auditing & Taxation, 3(2):221-236 Copyright @ 1994 by JAI Press, Inc. All rights of reproduction
ISSN: 1061-9518 in any form reserved.
Kathryn Pedwell, Hussein Warsame, and Dean Neu l Faculty of Management, Calgary, 2500 University Drive NW, Calgary, Alberta T2N 1N4, Canada.
University
of
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accuracy of compulsory forecasts provided in New Zealand prospectuses (Firth and Smith, 1992). Economic models indicate that voluntary disclosure is one means by which managers can communicate firm value. Firms which anticipate earnings that exceed current market expectations will voluntarily provide forecasts whenever the expected benefit (in terms of higher market value for the shares) exceeds the costs of disclosure (Verrecchia, 1983; Dye, 1986). In addition, the signaling literature postulates that high-quality firms are capable of communicating information that signals favorable firm value in a manner which is too costly for lower-quality firms to mimic (Lev and Penman 1990; Clarkson et al., 1992). Therefore, firms that do not anticipate such favorable prospects do not include earnings forecasts and their IPOs will be valued accordingly. In the regulated environment of New Zealand, where all firms are mandated to provide earnings forecasts, these market forces are circumvented. Social regulation, based on the “public-interest” theory of legislation developed in the economics literature by Pigou (1950) and Baumol (1965), argues that regulation is designed to correct imperfections or failures in the functioning of the market economy and thereby increase social welfare. However, Posner (1977) argues that regulation should be a supplement, not a replacement for market forces. It is appropriate to regulate when the damages to an individual in society are so small that litigation is not a paying proposition or when the damage judgement is so large that the firm is unwilling to comply and simply declares bankruptcy. Posner (1977) also indicates that direct regulation can be problematic; it is more politicized than the market mechanism, less flexible, and more costly, both in terms of compliance costs to firms and monitoring and enforcement costs for regulatory agencies. These costs are passed onto consumers in the form of higher product prices and increased taxes. Yet, the benefits of regulation remain a controversial topic and the subject of considerable research. Most socially regulated activities lack information about their effects and this deficiency contributes to the demand for the regulation. The objective of this study is to compare earnings forecasts provided in voluntary and mandatory disclosure environments. Do mandated forecasts provide the market with more reliable information than is provided within an do the results from New Zealand and unregulated market? Furthermore, Canada indicate that certain types of firms are better able to provide reliable earnings forecasts? To address these two issues, the accuracy of earnings forecasts included in New Zealand prospectus offerings (Firth and Smith, 1992) is compared to a similar sample of earnings forecasts found in Canadian initial prospectus offerings. In some sense, such a direct comparison can be problematic, particularly when noting that the comparison involves a self-selected sample of Canadian firms to a total population of New Zealand firms within different economic environments. Yet with regard to the aforementioned research
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questions, the comparison is a logical one. The issue is whether mandating all firms to forecast, whether or not they are capable, provides the market with more useful information than allowing firms to self-select. Therefore, the comparison logically uses such samples. In the initial direct comparison, the approach assumes that the firms in both countries faced a similar level of difficulty in forecasting. In Canada, the economy during 1983-1987 was emerging from a recession. Inflation declined and growth was erratic during this period. In New Zealand, the economy was facing higher levels of inflation and nominal growth. Additionally, firms in both countries experienced the stock market crash of 1987. This comparison provides preliminary evidence on the efficacy of mandating earnings forecasts for firms going public for the first time. The subsequent analysis argues that the Firth and Smith model is underspecified. The results provide evidence on the association between forecasting accuracy and firm characteristics. It is expected that the results of this comparison will be of interest to both regulators and investors. For regulators, the comparison of forecasting accuracy under two different regulatory regimes yields additional information for use in policy deliberations. And for investors, the finding that firm characteristics are associated with forecast accuracy supplies useful information for future investment decision-making.
BACKGROUND
In Canada, the Ontario Securities Commission (OSC) has permitted the inclusion of earnings forecasts in prospectuses since December 1982. The regulations state that “a forecast must be made in good faith and prepared in accordance with the CICA Accounting Guidelines and reviewed in accordance with CICA Auditing Guidelines” (OSC, 1983). However, the accounting and auditing guidelines issued by the Canadian Institute of Chartered Accountants in 1983 concerning the presentation, disclosure, and review of financial forecasts are very general in nature. The Guidelines specify that the purpose of the review is to assess the reasonableness of the forecast assumptions rather than attest to the degree to which the forecast will approximate actual results. Therefore, public accountants are required only to undertake review procedures such as general enquiry, comparison to historical financial statements, tests of computation and compilation, and consideration of the significant forecast assumptions (CICA 1990, Sections 4250 and 7100). In New Zealand, the Securities Act 1978 and Securities Regulations 1983 require that a prospectus contain statements in qualitative and quantitative terms regarding the prospects of the firm in terms of both trading and profits. In the legislation, Clause 42(2) of the First Schedule Securities Regulations 1983 specifies that the auditor give an opinion on the compilation of the specific
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forecast and on the accounting policies used (Firth and Smith, 1992, p. 240). The extent of the auditor’s undertaking is similar to that performed by Canadian auditors in this regard. In recent years, the accuracy of earnings forecasts in IPO prospectuses has taken on new significance. Litigation based on misrepresentation in a prospectus has been increasing as institutional investors have become more “activist” in protecting their positions (Clarkson et al., 1992). Clarkson et al. (1992) observe that there are institutional constraints to prevent misrepresentation and ensure accurate predictions. OSC policy 5.8 requires that forecasts be reviewed by the issuer and revised if necessary or withdrawn in extreme cases, and that significant errors be discussed in subsequent financial statements. Also, Section 126(l) of the Ontario Securities Act holds the issuer and its directors, the underwriters, and the auditors liable for damages resulting from misrepresentation. The penalties for significant forecast inaccuracies can be as high as the total issue proceeds. Forecasting error has also been of major concern in New Zealand, where the Securities Commission in 1991 issued a discussion paper to review forecasting in prospectuses (Firth and Smith 1992, p. 239). Similarly, in the United States, Leese (1978) indicates that during the 197Os, the Securities and Exchange Commission (SEC) was also considering mandating the publication of forecasts. This activity was accompanied by considerable literature warning about the perils of publishing forecasts, particularly the related legal liability. DATAANDMETHOD The Canadian sample consists of 112 firms that applied for an initial Toronto Stock Exchange (TSE) listing between 1983 and 1987 and met the criteria of issuing nonpreferred equity shares via a prospectus and including in their prospectus an earnings forecast for the following year. This sample was identified from the Toronto Stock Exchange Review (1983-1987) which is published monthly. The sample used by Firth and Smith (1992) consists of 89 firms which came to the stock market between 1983 and 1986 and met the same criteria as the Canadian firms. The accuracy of earnings forecasts was calculated by comparing the forecast to the actual audited earnings. Forecast errors were measured three ways. The relative or mean forecast error (RFE) measures the bias in forecasting, that is, whether forecasted earnings are systematically over- or underestimating actual performance. This measure is consistent with previous studies examining forecast accuracy (McDonald, 1973; Imhoff, 1978). The mean absolute forecast error (AFE) provides a measure of the magnitude of the forecast error and the mean squared forecast error (SFE) gives greater weight to large errors, a method which may better model the loss to investors due to erroneous forecasts (Brandon and Jarrett, 1976; Firth and Smith, 1992). Table 1 summarizes these methods.
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TABLE 1 RFE
= Relative Forecast
AFE
= Absolute
Error (%) =
Forecast
Error (%) =
Actual Income
-
Forecast
Income
x
100
1Forecast Income 1 1Actual Income
-
Forecast
Income1
x
loo
Income)’
x
loo
)Forecast Income) SFE
Note:
= Squared
Forecast
Error (%) =
(Actual Income
-
Forecast
(Forecast
Income)’
where Income is measured as Net Income before taxes and extraordinary items.
RESULTS
Comparative Study The descriptive results from the forecast error analyses are shown in Table 2. The relative forecast errors in both the current study and the Firth and Smith (1992) study were large and negative, indicating that, on average, both groups of firms tend to overestimate forecast earnings. However, when firms with forecast errors greater than l,OOO% are removed from both samples, RFE decreases to -29% for the Canadian sample and -5% for the New Zealand sample. These results are comparable to those reported by U.S. studies using voluntary forecasts provided by New York Stock Exchange firms and reported in the WaN Street Journal. For example, studies examining this group of firms find a RFE of -13.6% (McDonald, 1973), -4.7% (Leese, 1978), and -1.1% (Imhoff, 1978), depending on the time period examined. On the surface, when both studies exclude extreme outliers, it appears as though the New Zealand firms are more accurate owing to the fact that the mean is closer to the true value and the results are less biased with an almost equal distribution of firms under- and over-reporting. The results from the Canadian sample, on the other hand, show a strong bias with fully 76% of the firms issuing an over-optimistic forecast. While an argument can be made that the New Zealand sample provides an unbiased result, it is not necessarily a more “accurate” result. With a more in-depth analysis, it becomes evident that Canadian forecasts are in fact more accurate. Judge et al. (1988, pp. 70-72) argue that when determining accuracy, mean squared error and variance are the definitive parameters. When the absolute measure of forecast error is considered, Table 2 indicates that, after deleting the aforementioned outliers, the AFE for the Canadian sample was 39% versus 141% for the New Zealand sample. A comparison of mean squared forecast errors, both with and excluding outliers, indicates that the Canadian sample is more accurate than the New Zealand sample.
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Descriptive
AUDITING & TAXATION,
TABLE 2 Statistics of Forecast
Mean
Highest
Highest
Positive
Negative
Deviation
Error
Error
Squared forecast error (%) Squared forecast error after deleting two outliers(%)
Study)
-71.7
403.9
101.3
-3958.5
-28.8
10.1
101.3
-501.3
88.0
401.8
39.3
65.4
1677.5
14966.5
57.8
263.1
Absolute forecast error (To) Absolute forecast error after deleting two outliers(%)
Compulsory
Disclosure
(Firth
& Smith,
Forecast error (%) Forecast error after deleting three outliers (%)
-92
1387
-5
232
Absolute forecast error (%) Absolute forecast error after deleting three outliers (%)
328
1350
141
183
Squared forecast error (%) Squared forecast error after deleting three outliers (%)
19100
162900
532
1421
1994
Error
Standard
Voluntary Disclosure (Current Forecast error (%) Forecast error after deleting two outliers (%)
3(2)
1992)
3041
-12393
Further, as Table 3 suggests, 55% of the Canadian forecasts were clustered within + 20% of actual earnings compared to 19% of the New Zealand forecasts. The broader dispersion of the New Zealand forecasts are evidenced by the fact that 57% of the forecasts lie within + 100% of the actual results; as mentioned previously for the Canadian sample, a comparable 55% fall within +20% of the actual results. The results presented in Tables 2 and 3 raise questions regarding the efficacy of a mandatory forecast disclosure policy for firms going public for the first time. For example, the wider dispersion and the fairly uniform distribution between over- and underestimated forecast earnings for the New Zealand sample of firms raises the question of the extent to which mandated forecasting provides useful information to the market. Given the broad and symmetric distribution evident in the New Zealand study, it can be argued that such mandated disclosure is little more than a random process which provides little useful information (Judge et al., 1988, pp. 79438).
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TABLE 3 Distribution of Errors Number of Companies in Error Category % Forecast Error
> 501
Firth & Smith (1992)
Current Study 0
401 to 500 301 to 400 201 to 300 101 to 200 81 to 100 61 to 80 41 to 60 21 to 40 0 to 20 -20 to -1 -40 to -21 -60 to -41 -80 to -61 -100 to -81 -200 to -101 -300 to -201 -400 to -301 -500 to -401
4 1 0 2 15 4 4 6 3 11 6 5 5 4 3 4 3 4 1
< -500
_!I
3
Total firms
89
112
Actual earnings below forecast Actual earnings exceedforecast
50 (56%) 39 (44%)
0 0
0 1 2 1 0 3 20 42 9 15 5 4 6 I 0 0
85 (76%) 27 (24%~
Stated differently, mandatory disclosure of earnings forecasts may be forcing firms to forecast that have neither the ability nor incentives to provide accurate earnings forecasts. As previous studies have suggested, firms with stable earnings processes and larger firms are better able to provide accurate forecasts (Imhoff, 1978; Jaggi and Grier, 1980). As a consequence, these same firms have greater incentives to voluntarily disclose such forecasts, especially if they reflect favorably on firm value (Waymire, 1984; McNichols, 1989; Lev and Penman, 1990; Clarkson et al., 1992). Thus, from this perspective, mandatory disclosure may actually minimize the usefulness of earnings forecasts as a signaling mechanism by forcing firms that would not otherwise forecast to do so. The preceding conclusion, however, must be tempered by two caveats. First, the comparison provided in Tables 2 and 3 is based on univariate statistics-in other words, differences in firm characteristics may, in part, explain some of the differences between the observed degrees of forecast
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accuracy. Thus, the New Zealand results may not necessarily be representative of the results that would be obtained under a mandatory disclosure regime with a different group of firms (i.e., firms going public in Canada and the United States tend to be much larger than those in the New Zealand sample; cf. Simunic and Stein, 1987). Second, while the Canadian results were more narrowly dispersed, they also tended to be much more optimistic (76% of the Canadian firms overestimated forecasted income compared to 56% of the New Zealand firms). However, Clarkson et al. (1992) demonstrate that the market is able to at least partially correct for this optimistic bias of management. Factors Influencing Forecast Accuracy The preceding section suggested that firms included in the New Zealand sample tended to provide less accurate forecasts than those in the Canadian sample. But are these differences a consequence of the two samples containing different “types” of firms? In this section, we start by examining the association between forecast accuracy and firm characteristics using the characteristics examined by Firth and Smith (1992). This analysis is then supplemented by using the Canadian data to reconsider the influence of firm characteristics on forecast accuracy. Table 4 provides a description of the firm characteristic variables identified by Firth and Smith (1992). Cox (1985) and Gaber (1985) suggest that larger companies have both the resources to prepare higher-quality forecasts and more predictable earnings which enables more accurate forecasting. This predictability is predicated on the contention that larger companies enjoy economies of scale and greater
TABLE
4
Description of Independent Variables Used In Predicting Forecast Accuracy Expected Sign
Variable
Description
SIZE ($ thousands)
-
Gross assets in millions. The Canadian study uses gross assets prior to the IPO, whereas the New Zealand study uses gross assets which include the proceeds from the IPO.
PERIOD
+
Length of the forecast period measured as the number of months between the prospectus date and the year end to which the forecast pertains.
-
The number existence.
AGE
AUDITOR
(months)
of years the company
has been in
The dummy variable takes a value of one if the auditor is a member of the Big Eight; 0 otherwise.
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229
control of their markets and, therefore, are less susceptible to economic fluctuations. These studies imply a negative relationship between firm size and forecast error. However, it is important to realize that companies newly listing on a stock exchange tend to be smaller in comparison to existing listed firms. It is anticipated that forecasting accuracy will improve as the size of the forecasting firm increases. Several studies, including Brown, Foster, and Noreen (1985) and Brown, Richardson, and Schwager (1987), show that the shorter the time interval in months between the prospectus date and the year end to which the forecast pertains, the more accurate the forecast becomes. Therefore, it is anticipated that forecast accuracy improves with a shorter interval. Previous studies postulate that the longer a firm has been in existence, the greater the forecasting accuracy, predominantly because the predictions of earnings for completely new firms are extremely difficult compared to a firm with a solid earnings history (cf. Davidson and Neu, 1993). It is anticipated that the age of the company, in years, will be negatively correlated with the forecast error. Finally, previous studies have suggested that the reputation of the firm’s public accountant influences forecast accuracy, however there is disagreement as to the direction of this influence. Firth and Smith (1992) argue that the expertise which Big Eight accounting firms bring to the forecasting process will lead to more accurate forecasts, that is, they hypothesize a negative relationship between forecast errors and public accountant quality. In contrast, Davidson and Neu (I 993) argue that management’s ability to manipulate actual income in the direction of forecasted income is decreased when a high quality auditor is present, resulting in a negative relationship between forecast errors and public accountant quality.’ This disagreement aside, both of these studies suggest that absolute forecast errors and public accountant quality are related. For the Canadian sample of firms, public accounting firms are divided into Big Eight and non-Big Eight firms based on the firm’s ranking by revenue in the 1986 Bottom Line. The indicator variable is coded 1 if the auditor is a member of a Big Eight firm and 0 otherwise. Table 5 presents the descriptive statistics for the sample firms. It is interesting to note that while the Canadian firms issuing IPOs are almost three times the size of their New Zealand counterparts, these Canadian firms are only 20% of the size in terms of gross assets of the average firm listed on the Toronto Stock Exchange during the same period, whereas the New Zealand IPOs are 40% of the size of the average firm listed on the New Zealand Stock Exchange. Therefore, although the Canadian IPO firms are comparatively larger than their New Zealand counterparts, they are much smaller firms on their own stock exchange than are the New Zealand companies. This raises the question of whether size becomes significant at a threshold level or whether the relationship is nonlinear. The methodology used by Firth and Smith (1992) was duplicated
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TABLE 5 Descriptive Statistics for Sample Firms Canadian Firms
New Zealand Firms
Variable
Mean
Standard Deviation
Mean
Standard Deviation
Size ($ millions) Period (months) Age Auditor
88.37 8.05 3.90
0.19 3.13 1.64
25.62 7.23 4.32
76.82 2.15 3.14
N/A
N/A
N/A
N/A
for the current study so that direct comparisons could be made. To test the explanatory power of the hypothesized determinants, the following regression was constructed: AFE = Bo + BlPERIOD
+ BzSIZE + BsAGE + BdAUDITOR
In the New Zealand study, the three outliers with forecast errors exceeding 1,OOO%were eliminated from the regression, as were the two outliers exceeding 1,OOO%in the Canadian sample. Therefore, the New Zealand study uses a sample of 86 firms and the Canadian study uses 110 firms. Table 6 provides the results of the regression. The R2 statistic in the Firth and Smith (1992) study indicates a moderate fit, with both PERIOD and SIZE being statistically significant at conventional levels (although the estimated coefficient for SIZE is in the direction contrary to expectations). The R2 statistic for the Canadian sample indicates that the model explains little of the variance in forecast accuracy results. In spite of this, PERIOD, AGE and A UDITOR are significant at conventional levels. The results presented in Table 6 suggest that forecast accuracy is influenced by firm characteristics. In particular, the studies agree that: (1) the length of the forecast period (PERIOD), (2) the age of the firm going public (AGE), and (3) the reputation of the firm’s auditor are associated with the relative accuracy of the forecast. Whereas AGE and AUDITOR did not attain significance in the New Zealand sample, the coefficients are in the same direction as those found in the Canadian sample (where the results were significant at conventional levels). The only troubling findings are the insignificance of SIZE in the Canadian sample and the significant but contrary result for SIZE in the New Zealand sample. However, as the next section implies, it is possible that a failure to adjust for nonlinearities in the data may account for both the less than significant findings in the New Zealand results and the troubling results regarding SIZE in both samples.
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TABLE 6 Regression of Absolute Forecast Errors Variable
Coefficient
Standard Error
-28.740 7.995 ,319 -1.638 32.261
101.425 5.660 0.081 1.806 43.568
T-statistic
Firth & Smith (1992) Intercept Period Size Age Auditor
-0.283 1.413* 3.960*** -0.907 0.742
R2 = 0.219 Current Study Intercept Period Size Age Auditor
26.230 3.285 -0.0001 -6.337 18.723
24.456 1.981 0.000 I 3.737 14.153
1.073 1.658* -0.908 -1.696** 1.323*
R’ = 0.0817 Adjusted R’ == 0.0467 Notes:
Remlts of a one-tailed test: * Significant at the 10% level. ** Significant at the 5% level. *** Significant at the 1% level.
Expanding the Model The preceding section duplicated the methodology employed by Firth and Smith (1992) for comparative purposes; however, diagnostic tests indicated that the relationship between forecast error and the explanatory variables may not be linear. The current section provides the results for the Canadian sample after adjusting for these nonlinearities.* In addition, three additional possible influences on forecast accuracy are considered. Based on the studies by Simunic and Stein (1987) and Booth and Smith (1986) that the reputation of the underwriter influences the perceived “success” of the issue in much the same manner as the reputation of the auditor, UNDER WRITER was included in the expanded regression. UNDER WRZTER, an indicator variable, measures the reputation of the firm’s underwriter. It is coded one (zero otherwise) if the firm’s underwriter is one of the major Canadian underwriters (cf. Balvers et al., 1988, p. 615; Beatty, 1989, p. 701). Who’s Who in Canadian Finance (1987) was used to identify the 15 largest Canadian underwriters by capital employed. It is assumed that larger underwriters have higher reputations than the other underwriters and thus are more likely to be associated with an accurate earnings forecast.
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TABLE 7 Regression Results Variable
Coefficient I.285 1.030 -0.114 ,683 -0.113 -0.188 3.914 0.020
Constant LNPERIOD LNSIZE AUDITOR AGE UNDERWRlTER INDUSTRY RISK
Standard
Deviation
1.073 0.305 0.090 0.305 0.087 0.285 1.379 0.028
T-statistic 1.198 3.375*** -1.267 2.242*** -1.291* -0.662 2.882*** 0.702
R= = .3085 Adjusted R2 = .26102 Notes:
Results of * Significant ** Significant *** Significant
a one-tailed test: at the 10% level. at the 5% level. at the 1% level.
Previous studies have suggested that the ability to forecast accurately is influenced by the variability of the economic conditions in effect from the beginning to the end of the forecast period (Leese, 1978; Davidson and Neu, 1993). The variable ZND USTR Y measures the absolute change in the specific Toronto Stock Exchange (TSE) industry index over the forecast interval. It is anticipated that the forecast error and ZND USTR Y will be positively related, given that the more variable are economic conditions, the more difficult it is to forecast accurately. RISK measures the ex-post variability of the firm’s reported earnings over the first 12 quarters subsequent to the forecast. The greater the variability of the firm’s earnings, the more difficult it is to forecast future earnings (Davidson and Neu, 1993); therefore, it is expected that RISK will be positively related to forecast error. In keeping with the assumption that the relationships within the model may not be linear, diagnostic tests were undertaken to determine the best fit. The selected variables are LNAFE, LNPERIOD and LNSIZE, which are logarithmic transformations of the variables absolute forecast error (AFE), the forecasting interval (PERIOD) and the size of the firm. The following regression was constructed: LNAFE
= Bo + BlLNPERIOD + BzLNSIZE + B3AGE + BdAUDITOR + Bs UNDER WRITER + BsINDUSTR Y + B,RISK
The results, which are presented model does a better job of explaining
in Table 7, indicate that the expanded the variation in forecast accuracy than
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does the model reported in Table 6. As in Table 6, the length of the forecast period (LNPERIOD), the age of the firm (AG@, and the firm’s public accountant (AUDITOR) are associated with the accuracy of the earnings forecast. In addition, variability in the economy as measured by fluctuations in the stock market index (INDUSTRY) is important in explaining forecast accuracy. However, firm size once again just misses being significant whereas underwriter reputation (UNDER WRITER) and firm risk (RISK) are in the direction expected but clearly insignificant. CONCLUSION
The first part of the study set out to compare the accuracy of earnings forecasts in voluntary versus mandatory forecast disclosure environments. Initial public offerings (IPO) of firms in Canada were selected as examples of a voluntary disclosure policy and were compared to the New Zealand IPO firms studied by Firth and Smith (1992), which operate in a mandated disclosure environment. Both studies used data from approximately the same time period: 1983- 1987 for Canadian firms and 1983-l 986 for New Zealand firms. Forecast error, absolute forecast error, and squared forecast error were calculated. The re,sults of this comparison raise questions regarding the efficacy of mandatory disclosure. Specifically, the dispersion of forecast errors for the New Zealand sarnple of firms implies that mandatory disclosure forces firms that have neither the ability nor incentives to forecast to do so, thus impairing the ability of other firms to use earnings forecasts as a signaling device. However, as mentioned previously, this conclusion must be tempered by the recognition that: (1) the New Zealand results may not be representative of those that would be obtained elsewhere under a mandatory forecast regime, and (2) voluntary forecasts may only work as a signaling device if potential investors are able to discount biased forecasts. Also, further consideration must be given to the loss which could result to investors in the regulated markets should audited forecast information be discontinued. The provision of this information, with identified assumptions, currently provides investors with additional information on which they can form their own estimations of accuracy, and these forecasts may reasonably provide managers with incentive to at least attempt to achieve them. Arguably, there are both costs and benefits to both mandatory and voluntary disclosures. Whereas the univariate statistics regarding forecasting accuracy provide “preliminary” evidence on the benefits and costs of mandatory forecast disclosure, multivariate results regarding the association between firm characteristics and forecasting accuracy bring other aspects of this issue to the fore. In particular, the results indicate that, regardless of the forecasting environment (voluntary versus mandatory), some firms are more likely to
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provide relatively accurate earnings forecasts. That is, firms with a previous “track record,” firms forecasting for shorter periods into the future, and those employing a smaller public accounting firm are more likely to provide accurate forecasts. In addition, the results for the Canadian sample noted that industry variability influenced the likely accuracy of the earnings forecast. Returning to the question of mandatory versus voluntary disclosure, the regression results suggest that a mandatory disclosure policy may be inappropriate for certain firms, especially those firms (1) in a start-up position, (2) operating in a highly variable environment, and (3) attempting to forecast 12 months into the future. Stated differently, these types of firms are unlikely to have the experience and resources necessary to produce a “quality” forecast. Instead, the results suggest that there may be benefits to having regulations that prohibit such firms from providing an earnings forecast as opposed to regulations that require such firms to forecast! Presently, in Canada, informal regulations to this effect exist. While the provision of earnings forecasts in prospectuses remains voluntary, preapproval of the Director of the Ontario Securities Commission is required (OSC, 1990). As a consequence, “high risk” firms such as junior mining companies tend not to include forecasts in their prospectuses (Neu, 1992) in part because there is a perception that the market will not believe the provided forecast and also because of the aforementioned regulation. In sum, the current study has compared the forecasting accuracy and the influence of firm characteristics on accuracy for Canadian and New Zealand samples of firms. The results suggest that regulations requiring all firms to forecast may be inappropriate and that the market may be better served by regulations that prohibit certain firms from forecasting. While the provided interpretation must be regarded as “tentative,” it is hoped that regulators and investors will find the provided analyses useful. NOTES 1. 2.
In essence, these studies disagree over whether the firm’s public accountant exerts more influence over the forecast process or the calculation of actual results. Unfortunately, it was not possible to reanalyze the Smith and Firth (1992) data to determine whether such nonlinearities were present.
REFERENCES Baumol, W. 1965. Welfare Economics and the Theory of the State. 2nd edition. London: G. Bell and Sons. Balvers, R., B. McDonald, and R. Miller, 1988. Underpricing of new issues and the choice of auditor as a signal of investment banker reputation. The Accounting Review 63(4): 605 622.
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Beatty, R.P. 1989. Auditor reputation and the pricing of initial public offerings. The Accounting Review (October): 693-709. Booth, J., and R. Smith. 1986. Capital raising, underwriting and the certification hypothesis. Journal of Financial Economics (January/ February): 26 1-28 1 Brandon, C.-H., and J.E. Jarrett. 1976. Evaluating accounting forecasts. Journal of Business Finance and Accounting (Autumn): 67-77 Brown, L., GI. Richardson, and S. Schwager. 1987. An information interpretation of financial analyst superiority in forecasting earnings. Journal of Accounting Research (Spring):. 4961 Brown, P., G;. Foster, and E. Noreen. 1985. Security Analyst Multi-Year Earnings Forecasts and the Capital Market (Studies in Accounting Research No. 21). Saasota, FL: American Accounting Association. Canadian Institute of Chartered Accountants (CICA). 1990. Handbook. Toronto: CICA. Clarkson, P., A, Dontoh, G. Richardson, and S. Sefcik. 1992. The voluntary inclusion of earnings forecasts in IPO prospectuses. Contemporary Accounting Research (Spring): 601-626. Cox, C. 1985. Further evidence on the representativeness of management earnings forecasts. The Accounting Review (October): 692-701. Davidson, R..4., and D. Neu. 1993. A note on the association between audit firm size and audit quality. Contemporary Accounting Research 9(2, Spring): 479-488. Dye, R. 1986. Proprietary and nonproprietary disclosures. The Journal of Business 59(2, Part I): 331-366. Firth, M., and A. Smith. 1992. The accuracy of profits forecasts in initial public offering prospectuses. Accounting and Business Research 22(87): 239-247. Gaber, M. 1985. Management incentives to report forecasts of corporate earnings. Ph.D. dissertation, City University of New York. Imhoff, E. 1978. The representativeness of management earnings forecasts. 77re Accounting Review (October): 836-850. Jaggi, B., and P. Grier. 1980. A comparative analysis of forecast disclosing and non-disclosing firms. Financial Management (Summer): 38-43. Judge, G.G., R.C. Hill, W.E. Griffiths, H. Lutkepohl, and T. Lee. 1988. Introduction to the Theory and Practice of Econometrics. 2nd edition. New York: John Wiley & Sons. Leese, W.R. 1978. Management’s published financial forecasts: an evaluation of accuracy and small investor reaction. Ph.D. dissertation, Arizona State University. Lev, B., and S. Penman. 1990. Voluntary forecast disclosure, nondisclosure, and stock prices. Journal of Accounting Research (Spring): 49-76. McDonald, C. 1973. An empirical examination of the reliability of published predictions of future earnings. The Accounting Review (January): l-27. McNichols, M. 1989. Evidence of informational asymmetries from manager earnings forecasts and stock returns. The Accounting Review 64(l): l-72. Neu, D. 1992. The social construction of positive choices. Accounting, Organizations and Society 17(3/4): 223-237. Ontario Securities Commission (OSC). 1983, 1990. Ontario Securities Act and Regulation with Policy Statements. Don Mills, Ontario: Richard De Boo. Ontario Securities Commission. 1988. Policy 5.8-Future oriented iinancial informationRequest for comments. (September). Pigou. A. 1950. 7’he Economics of Welfare. 4th edition. London: MacMillan. Posner, R.A. 1977. Economic analysis of law. 3rd edition. Toronto: Little, Brown. and Company Simunic, D., and M. Stein. 1987. Product Differentiation in Auditing: A Study of Auditor Choice in the Market for Unseasoned New Issues. Vancouver: Canadian Certified General Accountants’ Research Foundation.
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Toronto Stock Exchange Review. 1983-1987. Toronto Stock Exchange. Verrecchia, R. 1983. Discretionary disclosure. Journal of Accounting and Economics (December): 173-194. Waymire, G. 1984. Additional evidence on the information content of earnings forecasts. Journal of Accounting Research (Autumn): 703-718. Who S Who in Canadian Finance. 1987. Toronto: Trans-Canada Press.
Kathryn Pedwell Hussein Warsame Dean Neu
Zhis study compares the accuracy of earnings forecasts provided in voluntary (Canada) and mandatory (New Zealand) disclosure environments. Previous research indicates that voluntary disclosure is usually undertaken by higher-quality firms who wish to communicate favorable signals to the market, whereas lower-quality firms are unable to mimic these signals, and that by these means the capital markets are capable of making appropriate valuations of the firms. Social regulation which mandates earnings forecast disclosures assumes that the market is imperfect and regulation is required to level thefield for the public good. These two environments are compared to draw some conclusions regarding the benefits of regulating forecast disclosure. The results of the comparison suggest that mandatory forecast regulation may force firms to forecast that have neither the ability nor incentives to do so. Instead, the results imply that regulations prohibiting suchjirms from forecasting may be a more appropriate regulatory strategy.
INTRODUCTION For firms applying for a new stock exchange listing, earnings forecasts represent a substantial proportion of the information available about the organization to the public. However, provision of such earnings forecasts varies, with inclusion being rare in the United States and virtually universal in the United Kingdom and New Zealand. In Canada, the inclusion of earnings forecasts is strictly voluntary. This study compares the predictive accuracy of voluntary (earnings forecasts made in Canadian prospectuses against the
Journal of International Accounting Auditing & Taxation, 3(2):221-236 Copyright @ 1994 by JAI Press, Inc. All rights of reproduction
ISSN: 1061-9518 in any form reserved.
Kathryn Pedwell, Hussein Warsame, and Dean Neu l Faculty of Management, Calgary, 2500 University Drive NW, Calgary, Alberta T2N 1N4, Canada.
University
of
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accuracy of compulsory forecasts provided in New Zealand prospectuses (Firth and Smith, 1992). Economic models indicate that voluntary disclosure is one means by which managers can communicate firm value. Firms which anticipate earnings that exceed current market expectations will voluntarily provide forecasts whenever the expected benefit (in terms of higher market value for the shares) exceeds the costs of disclosure (Verrecchia, 1983; Dye, 1986). In addition, the signaling literature postulates that high-quality firms are capable of communicating information that signals favorable firm value in a manner which is too costly for lower-quality firms to mimic (Lev and Penman 1990; Clarkson et al., 1992). Therefore, firms that do not anticipate such favorable prospects do not include earnings forecasts and their IPOs will be valued accordingly. In the regulated environment of New Zealand, where all firms are mandated to provide earnings forecasts, these market forces are circumvented. Social regulation, based on the “public-interest” theory of legislation developed in the economics literature by Pigou (1950) and Baumol (1965), argues that regulation is designed to correct imperfections or failures in the functioning of the market economy and thereby increase social welfare. However, Posner (1977) argues that regulation should be a supplement, not a replacement for market forces. It is appropriate to regulate when the damages to an individual in society are so small that litigation is not a paying proposition or when the damage judgement is so large that the firm is unwilling to comply and simply declares bankruptcy. Posner (1977) also indicates that direct regulation can be problematic; it is more politicized than the market mechanism, less flexible, and more costly, both in terms of compliance costs to firms and monitoring and enforcement costs for regulatory agencies. These costs are passed onto consumers in the form of higher product prices and increased taxes. Yet, the benefits of regulation remain a controversial topic and the subject of considerable research. Most socially regulated activities lack information about their effects and this deficiency contributes to the demand for the regulation. The objective of this study is to compare earnings forecasts provided in voluntary and mandatory disclosure environments. Do mandated forecasts provide the market with more reliable information than is provided within an do the results from New Zealand and unregulated market? Furthermore, Canada indicate that certain types of firms are better able to provide reliable earnings forecasts? To address these two issues, the accuracy of earnings forecasts included in New Zealand prospectus offerings (Firth and Smith, 1992) is compared to a similar sample of earnings forecasts found in Canadian initial prospectus offerings. In some sense, such a direct comparison can be problematic, particularly when noting that the comparison involves a self-selected sample of Canadian firms to a total population of New Zealand firms within different economic environments. Yet with regard to the aforementioned research
The Accuracy of Canadian and New Zealand Earnings Forecasts
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questions, the comparison is a logical one. The issue is whether mandating all firms to forecast, whether or not they are capable, provides the market with more useful information than allowing firms to self-select. Therefore, the comparison logically uses such samples. In the initial direct comparison, the approach assumes that the firms in both countries faced a similar level of difficulty in forecasting. In Canada, the economy during 1983-1987 was emerging from a recession. Inflation declined and growth was erratic during this period. In New Zealand, the economy was facing higher levels of inflation and nominal growth. Additionally, firms in both countries experienced the stock market crash of 1987. This comparison provides preliminary evidence on the efficacy of mandating earnings forecasts for firms going public for the first time. The subsequent analysis argues that the Firth and Smith model is underspecified. The results provide evidence on the association between forecasting accuracy and firm characteristics. It is expected that the results of this comparison will be of interest to both regulators and investors. For regulators, the comparison of forecasting accuracy under two different regulatory regimes yields additional information for use in policy deliberations. And for investors, the finding that firm characteristics are associated with forecast accuracy supplies useful information for future investment decision-making.
BACKGROUND
In Canada, the Ontario Securities Commission (OSC) has permitted the inclusion of earnings forecasts in prospectuses since December 1982. The regulations state that “a forecast must be made in good faith and prepared in accordance with the CICA Accounting Guidelines and reviewed in accordance with CICA Auditing Guidelines” (OSC, 1983). However, the accounting and auditing guidelines issued by the Canadian Institute of Chartered Accountants in 1983 concerning the presentation, disclosure, and review of financial forecasts are very general in nature. The Guidelines specify that the purpose of the review is to assess the reasonableness of the forecast assumptions rather than attest to the degree to which the forecast will approximate actual results. Therefore, public accountants are required only to undertake review procedures such as general enquiry, comparison to historical financial statements, tests of computation and compilation, and consideration of the significant forecast assumptions (CICA 1990, Sections 4250 and 7100). In New Zealand, the Securities Act 1978 and Securities Regulations 1983 require that a prospectus contain statements in qualitative and quantitative terms regarding the prospects of the firm in terms of both trading and profits. In the legislation, Clause 42(2) of the First Schedule Securities Regulations 1983 specifies that the auditor give an opinion on the compilation of the specific
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forecast and on the accounting policies used (Firth and Smith, 1992, p. 240). The extent of the auditor’s undertaking is similar to that performed by Canadian auditors in this regard. In recent years, the accuracy of earnings forecasts in IPO prospectuses has taken on new significance. Litigation based on misrepresentation in a prospectus has been increasing as institutional investors have become more “activist” in protecting their positions (Clarkson et al., 1992). Clarkson et al. (1992) observe that there are institutional constraints to prevent misrepresentation and ensure accurate predictions. OSC policy 5.8 requires that forecasts be reviewed by the issuer and revised if necessary or withdrawn in extreme cases, and that significant errors be discussed in subsequent financial statements. Also, Section 126(l) of the Ontario Securities Act holds the issuer and its directors, the underwriters, and the auditors liable for damages resulting from misrepresentation. The penalties for significant forecast inaccuracies can be as high as the total issue proceeds. Forecasting error has also been of major concern in New Zealand, where the Securities Commission in 1991 issued a discussion paper to review forecasting in prospectuses (Firth and Smith 1992, p. 239). Similarly, in the United States, Leese (1978) indicates that during the 197Os, the Securities and Exchange Commission (SEC) was also considering mandating the publication of forecasts. This activity was accompanied by considerable literature warning about the perils of publishing forecasts, particularly the related legal liability. DATAANDMETHOD The Canadian sample consists of 112 firms that applied for an initial Toronto Stock Exchange (TSE) listing between 1983 and 1987 and met the criteria of issuing nonpreferred equity shares via a prospectus and including in their prospectus an earnings forecast for the following year. This sample was identified from the Toronto Stock Exchange Review (1983-1987) which is published monthly. The sample used by Firth and Smith (1992) consists of 89 firms which came to the stock market between 1983 and 1986 and met the same criteria as the Canadian firms. The accuracy of earnings forecasts was calculated by comparing the forecast to the actual audited earnings. Forecast errors were measured three ways. The relative or mean forecast error (RFE) measures the bias in forecasting, that is, whether forecasted earnings are systematically over- or underestimating actual performance. This measure is consistent with previous studies examining forecast accuracy (McDonald, 1973; Imhoff, 1978). The mean absolute forecast error (AFE) provides a measure of the magnitude of the forecast error and the mean squared forecast error (SFE) gives greater weight to large errors, a method which may better model the loss to investors due to erroneous forecasts (Brandon and Jarrett, 1976; Firth and Smith, 1992). Table 1 summarizes these methods.
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TABLE 1 RFE
= Relative Forecast
AFE
= Absolute
Error (%) =
Forecast
Error (%) =
Actual Income
-
Forecast
Income
x
100
1Forecast Income 1 1Actual Income
-
Forecast
Income1
x
loo
Income)’
x
loo
)Forecast Income) SFE
Note:
= Squared
Forecast
Error (%) =
(Actual Income
-
Forecast
(Forecast
Income)’
where Income is measured as Net Income before taxes and extraordinary items.
RESULTS
Comparative Study The descriptive results from the forecast error analyses are shown in Table 2. The relative forecast errors in both the current study and the Firth and Smith (1992) study were large and negative, indicating that, on average, both groups of firms tend to overestimate forecast earnings. However, when firms with forecast errors greater than l,OOO% are removed from both samples, RFE decreases to -29% for the Canadian sample and -5% for the New Zealand sample. These results are comparable to those reported by U.S. studies using voluntary forecasts provided by New York Stock Exchange firms and reported in the WaN Street Journal. For example, studies examining this group of firms find a RFE of -13.6% (McDonald, 1973), -4.7% (Leese, 1978), and -1.1% (Imhoff, 1978), depending on the time period examined. On the surface, when both studies exclude extreme outliers, it appears as though the New Zealand firms are more accurate owing to the fact that the mean is closer to the true value and the results are less biased with an almost equal distribution of firms under- and over-reporting. The results from the Canadian sample, on the other hand, show a strong bias with fully 76% of the firms issuing an over-optimistic forecast. While an argument can be made that the New Zealand sample provides an unbiased result, it is not necessarily a more “accurate” result. With a more in-depth analysis, it becomes evident that Canadian forecasts are in fact more accurate. Judge et al. (1988, pp. 70-72) argue that when determining accuracy, mean squared error and variance are the definitive parameters. When the absolute measure of forecast error is considered, Table 2 indicates that, after deleting the aforementioned outliers, the AFE for the Canadian sample was 39% versus 141% for the New Zealand sample. A comparison of mean squared forecast errors, both with and excluding outliers, indicates that the Canadian sample is more accurate than the New Zealand sample.
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Descriptive
AUDITING & TAXATION,
TABLE 2 Statistics of Forecast
Mean
Highest
Highest
Positive
Negative
Deviation
Error
Error
Squared forecast error (%) Squared forecast error after deleting two outliers(%)
Study)
-71.7
403.9
101.3
-3958.5
-28.8
10.1
101.3
-501.3
88.0
401.8
39.3
65.4
1677.5
14966.5
57.8
263.1
Absolute forecast error (To) Absolute forecast error after deleting two outliers(%)
Compulsory
Disclosure
(Firth
& Smith,
Forecast error (%) Forecast error after deleting three outliers (%)
-92
1387
-5
232
Absolute forecast error (%) Absolute forecast error after deleting three outliers (%)
328
1350
141
183
Squared forecast error (%) Squared forecast error after deleting three outliers (%)
19100
162900
532
1421
1994
Error
Standard
Voluntary Disclosure (Current Forecast error (%) Forecast error after deleting two outliers (%)
3(2)
1992)
3041
-12393
Further, as Table 3 suggests, 55% of the Canadian forecasts were clustered within + 20% of actual earnings compared to 19% of the New Zealand forecasts. The broader dispersion of the New Zealand forecasts are evidenced by the fact that 57% of the forecasts lie within + 100% of the actual results; as mentioned previously for the Canadian sample, a comparable 55% fall within +20% of the actual results. The results presented in Tables 2 and 3 raise questions regarding the efficacy of a mandatory forecast disclosure policy for firms going public for the first time. For example, the wider dispersion and the fairly uniform distribution between over- and underestimated forecast earnings for the New Zealand sample of firms raises the question of the extent to which mandated forecasting provides useful information to the market. Given the broad and symmetric distribution evident in the New Zealand study, it can be argued that such mandated disclosure is little more than a random process which provides little useful information (Judge et al., 1988, pp. 79438).
The Accuray
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227
TABLE 3 Distribution of Errors Number of Companies in Error Category % Forecast Error
> 501
Firth & Smith (1992)
Current Study 0
401 to 500 301 to 400 201 to 300 101 to 200 81 to 100 61 to 80 41 to 60 21 to 40 0 to 20 -20 to -1 -40 to -21 -60 to -41 -80 to -61 -100 to -81 -200 to -101 -300 to -201 -400 to -301 -500 to -401
4 1 0 2 15 4 4 6 3 11 6 5 5 4 3 4 3 4 1
< -500
_!I
3
Total firms
89
112
Actual earnings below forecast Actual earnings exceedforecast
50 (56%) 39 (44%)
0 0
0 1 2 1 0 3 20 42 9 15 5 4 6 I 0 0
85 (76%) 27 (24%~
Stated differently, mandatory disclosure of earnings forecasts may be forcing firms to forecast that have neither the ability nor incentives to provide accurate earnings forecasts. As previous studies have suggested, firms with stable earnings processes and larger firms are better able to provide accurate forecasts (Imhoff, 1978; Jaggi and Grier, 1980). As a consequence, these same firms have greater incentives to voluntarily disclose such forecasts, especially if they reflect favorably on firm value (Waymire, 1984; McNichols, 1989; Lev and Penman, 1990; Clarkson et al., 1992). Thus, from this perspective, mandatory disclosure may actually minimize the usefulness of earnings forecasts as a signaling mechanism by forcing firms that would not otherwise forecast to do so. The preceding conclusion, however, must be tempered by two caveats. First, the comparison provided in Tables 2 and 3 is based on univariate statistics-in other words, differences in firm characteristics may, in part, explain some of the differences between the observed degrees of forecast
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accuracy. Thus, the New Zealand results may not necessarily be representative of the results that would be obtained under a mandatory disclosure regime with a different group of firms (i.e., firms going public in Canada and the United States tend to be much larger than those in the New Zealand sample; cf. Simunic and Stein, 1987). Second, while the Canadian results were more narrowly dispersed, they also tended to be much more optimistic (76% of the Canadian firms overestimated forecasted income compared to 56% of the New Zealand firms). However, Clarkson et al. (1992) demonstrate that the market is able to at least partially correct for this optimistic bias of management. Factors Influencing Forecast Accuracy The preceding section suggested that firms included in the New Zealand sample tended to provide less accurate forecasts than those in the Canadian sample. But are these differences a consequence of the two samples containing different “types” of firms? In this section, we start by examining the association between forecast accuracy and firm characteristics using the characteristics examined by Firth and Smith (1992). This analysis is then supplemented by using the Canadian data to reconsider the influence of firm characteristics on forecast accuracy. Table 4 provides a description of the firm characteristic variables identified by Firth and Smith (1992). Cox (1985) and Gaber (1985) suggest that larger companies have both the resources to prepare higher-quality forecasts and more predictable earnings which enables more accurate forecasting. This predictability is predicated on the contention that larger companies enjoy economies of scale and greater
TABLE
4
Description of Independent Variables Used In Predicting Forecast Accuracy Expected Sign
Variable
Description
SIZE ($ thousands)
-
Gross assets in millions. The Canadian study uses gross assets prior to the IPO, whereas the New Zealand study uses gross assets which include the proceeds from the IPO.
PERIOD
+
Length of the forecast period measured as the number of months between the prospectus date and the year end to which the forecast pertains.
-
The number existence.
AGE
AUDITOR
(months)
of years the company
has been in
The dummy variable takes a value of one if the auditor is a member of the Big Eight; 0 otherwise.
The Accuracy of Canadian and New Zealand Earnings Forecasts
229
control of their markets and, therefore, are less susceptible to economic fluctuations. These studies imply a negative relationship between firm size and forecast error. However, it is important to realize that companies newly listing on a stock exchange tend to be smaller in comparison to existing listed firms. It is anticipated that forecasting accuracy will improve as the size of the forecasting firm increases. Several studies, including Brown, Foster, and Noreen (1985) and Brown, Richardson, and Schwager (1987), show that the shorter the time interval in months between the prospectus date and the year end to which the forecast pertains, the more accurate the forecast becomes. Therefore, it is anticipated that forecast accuracy improves with a shorter interval. Previous studies postulate that the longer a firm has been in existence, the greater the forecasting accuracy, predominantly because the predictions of earnings for completely new firms are extremely difficult compared to a firm with a solid earnings history (cf. Davidson and Neu, 1993). It is anticipated that the age of the company, in years, will be negatively correlated with the forecast error. Finally, previous studies have suggested that the reputation of the firm’s public accountant influences forecast accuracy, however there is disagreement as to the direction of this influence. Firth and Smith (1992) argue that the expertise which Big Eight accounting firms bring to the forecasting process will lead to more accurate forecasts, that is, they hypothesize a negative relationship between forecast errors and public accountant quality. In contrast, Davidson and Neu (I 993) argue that management’s ability to manipulate actual income in the direction of forecasted income is decreased when a high quality auditor is present, resulting in a negative relationship between forecast errors and public accountant quality.’ This disagreement aside, both of these studies suggest that absolute forecast errors and public accountant quality are related. For the Canadian sample of firms, public accounting firms are divided into Big Eight and non-Big Eight firms based on the firm’s ranking by revenue in the 1986 Bottom Line. The indicator variable is coded 1 if the auditor is a member of a Big Eight firm and 0 otherwise. Table 5 presents the descriptive statistics for the sample firms. It is interesting to note that while the Canadian firms issuing IPOs are almost three times the size of their New Zealand counterparts, these Canadian firms are only 20% of the size in terms of gross assets of the average firm listed on the Toronto Stock Exchange during the same period, whereas the New Zealand IPOs are 40% of the size of the average firm listed on the New Zealand Stock Exchange. Therefore, although the Canadian IPO firms are comparatively larger than their New Zealand counterparts, they are much smaller firms on their own stock exchange than are the New Zealand companies. This raises the question of whether size becomes significant at a threshold level or whether the relationship is nonlinear. The methodology used by Firth and Smith (1992) was duplicated
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TABLE 5 Descriptive Statistics for Sample Firms Canadian Firms
New Zealand Firms
Variable
Mean
Standard Deviation
Mean
Standard Deviation
Size ($ millions) Period (months) Age Auditor
88.37 8.05 3.90
0.19 3.13 1.64
25.62 7.23 4.32
76.82 2.15 3.14
N/A
N/A
N/A
N/A
for the current study so that direct comparisons could be made. To test the explanatory power of the hypothesized determinants, the following regression was constructed: AFE = Bo + BlPERIOD
+ BzSIZE + BsAGE + BdAUDITOR
In the New Zealand study, the three outliers with forecast errors exceeding 1,OOO%were eliminated from the regression, as were the two outliers exceeding 1,OOO%in the Canadian sample. Therefore, the New Zealand study uses a sample of 86 firms and the Canadian study uses 110 firms. Table 6 provides the results of the regression. The R2 statistic in the Firth and Smith (1992) study indicates a moderate fit, with both PERIOD and SIZE being statistically significant at conventional levels (although the estimated coefficient for SIZE is in the direction contrary to expectations). The R2 statistic for the Canadian sample indicates that the model explains little of the variance in forecast accuracy results. In spite of this, PERIOD, AGE and A UDITOR are significant at conventional levels. The results presented in Table 6 suggest that forecast accuracy is influenced by firm characteristics. In particular, the studies agree that: (1) the length of the forecast period (PERIOD), (2) the age of the firm going public (AGE), and (3) the reputation of the firm’s auditor are associated with the relative accuracy of the forecast. Whereas AGE and AUDITOR did not attain significance in the New Zealand sample, the coefficients are in the same direction as those found in the Canadian sample (where the results were significant at conventional levels). The only troubling findings are the insignificance of SIZE in the Canadian sample and the significant but contrary result for SIZE in the New Zealand sample. However, as the next section implies, it is possible that a failure to adjust for nonlinearities in the data may account for both the less than significant findings in the New Zealand results and the troubling results regarding SIZE in both samples.
The Accuracy of Canadian and New Zealand Earnbtgs Forecasts
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TABLE 6 Regression of Absolute Forecast Errors Variable
Coefficient
Standard Error
-28.740 7.995 ,319 -1.638 32.261
101.425 5.660 0.081 1.806 43.568
T-statistic
Firth & Smith (1992) Intercept Period Size Age Auditor
-0.283 1.413* 3.960*** -0.907 0.742
R2 = 0.219 Current Study Intercept Period Size Age Auditor
26.230 3.285 -0.0001 -6.337 18.723
24.456 1.981 0.000 I 3.737 14.153
1.073 1.658* -0.908 -1.696** 1.323*
R’ = 0.0817 Adjusted R’ == 0.0467 Notes:
Remlts of a one-tailed test: * Significant at the 10% level. ** Significant at the 5% level. *** Significant at the 1% level.
Expanding the Model The preceding section duplicated the methodology employed by Firth and Smith (1992) for comparative purposes; however, diagnostic tests indicated that the relationship between forecast error and the explanatory variables may not be linear. The current section provides the results for the Canadian sample after adjusting for these nonlinearities.* In addition, three additional possible influences on forecast accuracy are considered. Based on the studies by Simunic and Stein (1987) and Booth and Smith (1986) that the reputation of the underwriter influences the perceived “success” of the issue in much the same manner as the reputation of the auditor, UNDER WRITER was included in the expanded regression. UNDER WRZTER, an indicator variable, measures the reputation of the firm’s underwriter. It is coded one (zero otherwise) if the firm’s underwriter is one of the major Canadian underwriters (cf. Balvers et al., 1988, p. 615; Beatty, 1989, p. 701). Who’s Who in Canadian Finance (1987) was used to identify the 15 largest Canadian underwriters by capital employed. It is assumed that larger underwriters have higher reputations than the other underwriters and thus are more likely to be associated with an accurate earnings forecast.
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TABLE 7 Regression Results Variable
Coefficient I.285 1.030 -0.114 ,683 -0.113 -0.188 3.914 0.020
Constant LNPERIOD LNSIZE AUDITOR AGE UNDERWRlTER INDUSTRY RISK
Standard
Deviation
1.073 0.305 0.090 0.305 0.087 0.285 1.379 0.028
T-statistic 1.198 3.375*** -1.267 2.242*** -1.291* -0.662 2.882*** 0.702
R= = .3085 Adjusted R2 = .26102 Notes:
Results of * Significant ** Significant *** Significant
a one-tailed test: at the 10% level. at the 5% level. at the 1% level.
Previous studies have suggested that the ability to forecast accurately is influenced by the variability of the economic conditions in effect from the beginning to the end of the forecast period (Leese, 1978; Davidson and Neu, 1993). The variable ZND USTR Y measures the absolute change in the specific Toronto Stock Exchange (TSE) industry index over the forecast interval. It is anticipated that the forecast error and ZND USTR Y will be positively related, given that the more variable are economic conditions, the more difficult it is to forecast accurately. RISK measures the ex-post variability of the firm’s reported earnings over the first 12 quarters subsequent to the forecast. The greater the variability of the firm’s earnings, the more difficult it is to forecast future earnings (Davidson and Neu, 1993); therefore, it is expected that RISK will be positively related to forecast error. In keeping with the assumption that the relationships within the model may not be linear, diagnostic tests were undertaken to determine the best fit. The selected variables are LNAFE, LNPERIOD and LNSIZE, which are logarithmic transformations of the variables absolute forecast error (AFE), the forecasting interval (PERIOD) and the size of the firm. The following regression was constructed: LNAFE
= Bo + BlLNPERIOD + BzLNSIZE + B3AGE + BdAUDITOR + Bs UNDER WRITER + BsINDUSTR Y + B,RISK
The results, which are presented model does a better job of explaining
in Table 7, indicate that the expanded the variation in forecast accuracy than
The A ccuraq of Canadk
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233
does the model reported in Table 6. As in Table 6, the length of the forecast period (LNPERIOD), the age of the firm (AG@, and the firm’s public accountant (AUDITOR) are associated with the accuracy of the earnings forecast. In addition, variability in the economy as measured by fluctuations in the stock market index (INDUSTRY) is important in explaining forecast accuracy. However, firm size once again just misses being significant whereas underwriter reputation (UNDER WRITER) and firm risk (RISK) are in the direction expected but clearly insignificant. CONCLUSION
The first part of the study set out to compare the accuracy of earnings forecasts in voluntary versus mandatory forecast disclosure environments. Initial public offerings (IPO) of firms in Canada were selected as examples of a voluntary disclosure policy and were compared to the New Zealand IPO firms studied by Firth and Smith (1992), which operate in a mandated disclosure environment. Both studies used data from approximately the same time period: 1983- 1987 for Canadian firms and 1983-l 986 for New Zealand firms. Forecast error, absolute forecast error, and squared forecast error were calculated. The re,sults of this comparison raise questions regarding the efficacy of mandatory disclosure. Specifically, the dispersion of forecast errors for the New Zealand sarnple of firms implies that mandatory disclosure forces firms that have neither the ability nor incentives to forecast to do so, thus impairing the ability of other firms to use earnings forecasts as a signaling device. However, as mentioned previously, this conclusion must be tempered by the recognition that: (1) the New Zealand results may not be representative of those that would be obtained elsewhere under a mandatory forecast regime, and (2) voluntary forecasts may only work as a signaling device if potential investors are able to discount biased forecasts. Also, further consideration must be given to the loss which could result to investors in the regulated markets should audited forecast information be discontinued. The provision of this information, with identified assumptions, currently provides investors with additional information on which they can form their own estimations of accuracy, and these forecasts may reasonably provide managers with incentive to at least attempt to achieve them. Arguably, there are both costs and benefits to both mandatory and voluntary disclosures. Whereas the univariate statistics regarding forecasting accuracy provide “preliminary” evidence on the benefits and costs of mandatory forecast disclosure, multivariate results regarding the association between firm characteristics and forecasting accuracy bring other aspects of this issue to the fore. In particular, the results indicate that, regardless of the forecasting environment (voluntary versus mandatory), some firms are more likely to
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provide relatively accurate earnings forecasts. That is, firms with a previous “track record,” firms forecasting for shorter periods into the future, and those employing a smaller public accounting firm are more likely to provide accurate forecasts. In addition, the results for the Canadian sample noted that industry variability influenced the likely accuracy of the earnings forecast. Returning to the question of mandatory versus voluntary disclosure, the regression results suggest that a mandatory disclosure policy may be inappropriate for certain firms, especially those firms (1) in a start-up position, (2) operating in a highly variable environment, and (3) attempting to forecast 12 months into the future. Stated differently, these types of firms are unlikely to have the experience and resources necessary to produce a “quality” forecast. Instead, the results suggest that there may be benefits to having regulations that prohibit such firms from providing an earnings forecast as opposed to regulations that require such firms to forecast! Presently, in Canada, informal regulations to this effect exist. While the provision of earnings forecasts in prospectuses remains voluntary, preapproval of the Director of the Ontario Securities Commission is required (OSC, 1990). As a consequence, “high risk” firms such as junior mining companies tend not to include forecasts in their prospectuses (Neu, 1992) in part because there is a perception that the market will not believe the provided forecast and also because of the aforementioned regulation. In sum, the current study has compared the forecasting accuracy and the influence of firm characteristics on accuracy for Canadian and New Zealand samples of firms. The results suggest that regulations requiring all firms to forecast may be inappropriate and that the market may be better served by regulations that prohibit certain firms from forecasting. While the provided interpretation must be regarded as “tentative,” it is hoped that regulators and investors will find the provided analyses useful. NOTES 1. 2.
In essence, these studies disagree over whether the firm’s public accountant exerts more influence over the forecast process or the calculation of actual results. Unfortunately, it was not possible to reanalyze the Smith and Firth (1992) data to determine whether such nonlinearities were present.
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