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REPORTING OF CASH FLOWS UNDER INTERNATIONAL FINANCIAL REPORTING STANDARDS VERSUS GENERALLY ACCEPTED ACCOUNTING PRINCIPLES AND THE EFFECT ON SECURITY PRICES.

Keywords: Statements of cash flow, International Financial Reporting Standards (IFRS), Generally Accepted Accounting Principles (GAAP), security prices

INTRODUCTION

This study examines the consequences of comparative flexibility in classification choices within the statement of cash flows. International Financial Reporting Standards (IFRS) are perceived to allow managers more flexibility than Generally Accepted Accounting Principles (GAAP). This increased flexibility is evident with regard to the classification of certain items within the statement of cash flows. U.S. GAAP requires that firms classify interest paid, interest received, and dividends received as operating cash flows. In contrast, IFRS allows firms the flexibility to report these items within operating cash flow or, alternatively, to classify them as investing or financing.

Cash flow, and particularly Operating Cash Flow, is well documented as a basis for business valuation (Damodaran, 2006, Imam et al., 2008) and financial analysis (Estridge & Lougee 2007). Although extensive literature examines the importance of Operating Cash Flows and its relation to security returns (Livnat & Zarowin 1990; Sloan 1996, Stunda, 1996; Dechow, 1998) less attention has been given to the impact that this relationship has when comparing GAAP methodology to that of IFRS.

The effect of flexibility on cash flow classification and its consequences are important because both the International Accounting Standards Board (IASB) and Financial Accounting Standards Board (FASB) share the objective that financial information should enable financial statement users to better predict future cash flows. It is also important because cash flows have been widely found to be a determinant of stock prices.

This study examines differences associated with the flexibility in reporting cash flows under respective IFRS and GAAP bases and the corollary effect each has on associated security prices.

LITERATURE REVIEW

Cash flows have been used in many studies to achieve several objectives. Perhaps the most notable cash flow studies are those of Wilson (1986, 1987). In both studies, findings suggest that the cash and total accruals component of earnings have incremental information content beyond earnings themselves. These studies compelled other researchers to evaluate the information content of cash flow components.

Livnat and Zarowin (1990) disaggregated cash flow into its operating, financing and investing components. They concluded that the disaggregation of cash flows into operating cash flows and accruals does not improve the relationship between cash flows and security returns beyond the contribution of net income. Further, they find that there is an improved degree of association between financing and operating cash flows and security returns.

Sloan (1996) found that stock prices fail to fully reflect information contained in the accrual and cash flow components of current earnings until that information impacts future earnings. Cash flow is defined in this study as the income from continuing operations less accruals. Again the uncertainty of the accrual calculations limits the accuracy of this proxy for cash flows.

Stunda (1996) found that reported cash flows, when disaggregated by operating, financing and investing components, have a greater relationship with security returns than with disaggregated estimates reported by Livnat and Zarowin (1990).

Dechow (1998) disaggregates the accrual components of cash flows and found that some have greater predictive value on security returns than others. Barth, Cram, and Nelson (2002) pick up on the Dechow study and circle back to the findings of the studies from the 1980's and re-assert that accruals have a greater predictive ability of security returns than do actual cash flows, thereby contradicting the finding of Stunda (1996).

These studies are extended by later studies that emphasize the need for stable cash flows. Graham, Campbell, and Rajgopal (2005) finds 97% of corporate executives favor stable, nonvolatile cash flows as being a positive influence on earnings and security prices. Brown and Kapadia (2007) show the rise in cash flow volatility, especially among new public offerings. Bennett and Sias (2007) relate a good deal of the cash flow volatility to small stocks, although Irvine and Pontiff (2008) attribute only 1/3 of the total cash flow volatility to small stocks, and further find that such volatility has increased since 1997. Morck, Yung, and Yu (2009) posit that because of increased volatility in cash flows, perhaps cash flows do not have the predictive ability they were found to have in prior research.

The issuance of operating cash flow forecasts by analysts is a relatively recent phenomenon. As documented by DeFond and Hung (2003), analysts' cash flow forecasts first appear in the IBES database in 1993. The percentage of US firms in the IBES database with at least one cash flow forecast issued by analysts increased from 4% in 1993 to 65% in 2015. This growth trend in cash flow forecast issuance is also observed at the analyst level. Specifically, the percentage of analysts' earnings forecasts that are accompanied by cash flow forecasts has increased from 1% in 1993 to 77% in 2015.

With regard to cash flow forecasts, DeFond and Hung (2003) report that firms which have cash flow forecasts tend to have greater capital intensity and risk relative to industry peers. Ertimur and Stubben (2005) examine whether analyst characteristics play a role in the supply of cash flow forecasts. They find analysts from bigger brokerage houses, who forecast earnings more frequently and who have more accurate prior earnings forecasts, are more likely to issue cash flow forecasts.

In addition, DeFond and Hung (2003), McInnis and Collins (2008), and Call (2008) examine whether investors respond differently to the cash flow and management's accrual components of earnings when setting stock prices for firms. These studies provide evidence indicating that investors place relatively more weight on the cash flows, as opposed to the accruals emanating from management. DeFond and Hung (2003) examine the two-day abnormal returns surrounding firms' announcement of earnings. The authors find no significant relation between unexpected earnings and security prices but a strong positive relation between unexpected cash flows and security prices.

This above result contrasts with prior studies that show a strong positive relation between unexpected earnings and security prices without cash flow forecasts (i.e., Ball & Brown 1968, Beaver, Clarke, & Wright 1979, Baginski & Hassell 1990, etc). In examining managerial response to cash flow forecasts, McInnis and Collins (2008) predict that cash flow forecasts increase the transparency of accrual manipulations because cash flow forecasts enable market participants to decompose earnings surprises into their cash flow and accrual components. They find firms with cash flow forecasts are less likely to manipulate reported earnings relative to firms without cash flow forecasts, resulting in better accruals quality and a decreased likelihood of meeting earnings targets. In addition, Call (2008) finds that cash flow forecasts discipline managers to report more informative operating earnings. Thus, existing research indicates that analysts' cash flow forecasts have important implications for both investors and managers.

All prior studies have evaluated Cash Flows, and specifically Operating Cash Flows from the perspective of an historical GAAP basis and exclusive of IFRS and firms currently utilizing IFRS. As convergence continues to be a high priority on the agendas of both FASB and the IASB, it is appropriate to evaluate any significant differences that accounting for cash flows may have under these two scenarios. Any differences may have the consequence of impacting security prices and subsequent investor behavior, and therefore, must be evaluated.

METHODOLOGY

Sample and Data Collection

IASB Regulation Number 1606 (2002) requires companies listed on European securities markets to begin using IFRS in their consolidated financial statements starting in 2005. This includes accounting for the statement of cash flows. As a result, the sample used in this study will include the years 2006-2016 (first full year subsequent to the adoption of IFRS in the European markets to most current year available). Securities traded on the European Stock Exchange (ESE), the London Stock Exchange (LSE) and the Frankfurt Stock Exchange (FSE) and their associated prices are identified from the AMADEUS database. Earnings and other corporate data related to these firms/securities is found on Compustat Global. U.S. firm data is obtained from Compustat for earnings information, and the Center for Research on Security Prices (CRSP) for security price information.

Also, Analysts' forecast of cash flow is obtained from the Investment Brokers Estimate Service (IBES), and consists of quarterly point forecasts of cash flows for a given period. In addition, the Electronic Data Gathering and Retrieval System (EDGAR), the Wall Street Journal, and the European Business Register are used to analyze financial notes and other associated firm information in order to control for such things as change of corporate form, change in ownership, or change in management. If any of these could be documented during the test period, the firm is subsequently eliminated from the study. Table 1 summarizes firms included in the sample.

HYPOTHESES DEVELOPMENT

Forecast Accuracy

In their analysis of forecast accuracy of corporate earnings, Sinha, Brown, and Das (1997) utilize a matched-pair design in which the forecast accuracy of the same analyst is measured over time. Stunda (2016) uses the same methodology to determine forecast accuracy of groups of analysts over a longer time period. Both studies evaluate U.S. firms exclusively.

Although these prior studies assessed the analysts' forecast accuracy of earnings, this study will attempt to do the same with respect to cash flow forecasts, and in comparison between U.S. and European firms. This is an attempt to first assess the accuracy of cash flow forecasts in relation to actual cash flow for the different venues, something that has not been measured in previous studies. The comparison gives rise to the first hypothesis, stated in null form:
Hypothesis 1: There is no significant difference in forecast accuracy
              of cash flow when assessed between European firms
              utilizing an IFRS basis and U.S. firms using a GAAP basis
              of accounting.


Information Content of Accounting Earnings

Ball and Brown 1968, Beaver, Clarke and Wright 1979, Baginski and Hassell 1990, and a host of other researchers over the past five decades have found an association between accounting earnings and security returns of the firm. The strength of this association has commonly been described as an "earnings response coefficient" or ERC. To assess the ERC of firms in the selected study sample, the model first employed by Ball and Brown in 1968 is used in order to establish that there is a correlation between earnings and security prices. This analysis will also be used to form a baseline comparison against which the information content of cash flow will be measured. The Dow Jones News Retrieval Service (DJNRS) along with Worldscope is used to identify the date that each firm released quarterly financial data for the study periods. This date of data release is known as the event date. This leads to the second hypothesis, stated in the null form:
Hypothesis 2: There is no significant difference in the information
              content of accounting earnings between European firms
              utilizing an IFRS basis and U.S. firms using a GAAP basis
              of accounting.


Information Content of Cash Flow

As previously noted, the DeFond and Hung (2003) study finds a strong positive relation between cash flows and security prices. Their study is comprised entirely of U.S. firms in various industries. An analysis along the same lines between European and U.S. firms would provide a basis of comparison between the two. This extension leads to the third hypothesis, stated in the null form:
Hypothesis 3: There is no significant difference in the information
              content of cash flows between European firms utilizing an
              IFRS basis and U.S. firms using a GAAP basis of
              accounting.


TEST OF HYPOTHESES AND RESULTS

Test of Hypotheses

Hypothesis 1 proposed that "There is no significant difference in forecast accuracy of cash flow when assessed between European firms utilizing an IFRS basis and U.S. firms using a GAAP basis of accounting". Consistent with the methodology of Sinha, Brown, and Das (1997), the following model is used to assess forecast accuracy among analysts:

([rapfe.sub.ijt] = |[R.sub.jt] - [F.sub.mjt])/[R.sub.jt]|*100 - |[R.sub.jt] - [F.sub.ijt])/[R.sub.jt]|*100 (1)
Where:  subscripts i, j, t denote analyst, firm and year, respectively
        [R.sub.jt] is the j firm's cash flows in year t
        [F.sub.ijt] is the forecast of cash flow by analyst i for firm
        j in year t
        [F.sub.mjt] is the forecast of the average analyst for the firm
        in question
        [rapfe.sub.ijt] is each analyst's relative absolute percentage
        forecast error, which is calculated as the absolute percentage
        forecast error of the average analyst minus that of the above
        average analyst. For below average analysts, the order of the
        two terms on the right hand side are reversed (i.e. in the
        latter case the individual analyst's projection is below the
        average analyst's projection).


A pooled, cross-sectional analysis is performed over the study period 2016-2016 and incorporating all analyst forecasts. Data analysis in Table 2 indicates the results of the analysis. Results indicate that U.S. analysts have a larger average forecast error (2.85) which is significant at the 0.05 level. European analysts have a smaller average forecast error (1.02) which is significant at the 0.01 level.

Because the variances of the groups are not equal, there exists violation of the assumption of homogeneity across the sample. In order to account for this, the Welch's test was performed. This test assesses the significance between groups when variances do not equal. Based on the Welch's test, and as indicated in Table 2, a t-statistic of 1.609 was computed with a p-value of less than .020. This indicates that the means of the sample groups are significantly different, and thus the null of similarity between the groups is rejected.

Muller and Verschoor (2005) find that European firms have a history of placing importance on cash flows along with their associated forecast. Obrien (1990) surmises that the relatively more experienced analysts have greater forecast accuracy. The above results could be a combination of European firms placing greater emphasis on cash flow forecasts, while possessing analysts who are more experienced in these forecasts.

Hypothesis 2 proposed that "There is no significant difference in the information content of accounting earnings between European firms utilizing an IFRS basis and U.S. firms using a GAAP basis of accounting". Using the Ball and Brown (1968) model to determine the ERC, the following model is established for determining information content:

CARit = a + b1UEUSit + b2UEEit + b3MBit + b4Bit + b5MVit + eit (2)
Where:  CARit   = Cumulative abnormal return firm i, time t
        a       = Intercept term
        UEUSit  = Unexpected earnings for U.S. firms in the sample
        UEEit   = Unexpected earnings for European firms in the sample
        MBit    = Market to book value of equity as proxy for growth
                  and persistence
        Bit     = Market model slope coefficient as proxy for
                  systematic risk
        MVit    = Market value of equity as proxy for firm size
        eit     = Error term for firm i, time t


The coefficient "a" measures the intercept. The coefficient b1 represents U.S. firms and is the traditional earnings response coefficient (ERC), found to have correlation with security prices in market based studies (Ball and Brown, 1968). The coefficient b2 is the ERC associated with European firms. Unexpected earnings (UEi) is measured as the difference between the management earnings forecast (MFi) and security market participants' expectations for earnings as a proxy for consensus analyst following as per Investment Brokers Estimate Service (IBES) (EXi). The unexpected earnings are scaled by the firm's stock price (Pi) 180 days prior to the forecast:

UEi = [(MFi) - (EXi)]/Pi (3)

Unexpected earnings are measured for each of the sample firms during the test period. The coefficients b3, b4, and b5, are contributions to the ERC for all firms in the sample. To investigate the effects of the information content of earnings on security returns, there must be some control for variables shown by prior studies to be determinants of ERC. For this reason, the variables represented by coefficients b3 through b5 are included in the study.

For each firm sample, an abnormal return (ARit) is generated around the event dates of -1, 0, +1 (day 0 representing the day that the firm's financials were available per DJNRS or Worldscope). The market model is utilized along with the CRSP equally-weighted market index and regression parameters are established between -290 and -91. Abnormal returns are then summed to calculate a cross-sectional cumulative abnormal return (CARit).

Results of correlating the ERC to security returns are presented in Table 3. Results show that coefficient b1, representing the ERC of U.S. firms, is 1.98 and significant at the .01 level. These results provide a fairly strong relationship between accounting earnings and security prices, indicating that investors perceive that accounting earnings possess information content and therefore have predictive value when correlated with security returns. Coefficient b2, representing the ERC of European firms, is 0.12 and significant at the .10 level.

Performing the Welch's test, and as indicated in Table 3, a t-statistic of 1.718 was computed with a p-value of less than .010. This indicates that the means of the sample groups are significantly different, and thus the null of similarity between the groups is rejected.

Although the relationship between accounting earnings and security prices is positive, it is not very strong. This indicates that accounting earnings carry a lesser extent of information content among European investors, and therefore they are perceived to have less predictive value. Ali and Hwang (2000) find that the European model emphasizes tax rules and accounting standards and as such, more emphasis is spent adhering to rules and standards and less emphasis to earnings disclosures. This could account for some of the difference seen in this test.

In addition, whenever regression variables are employed, there is a probability of the presence of multicollinearity within the set of independent variables which may be problematic from an interpretive perspective. To assess the presence of multicollinearity, the Variance Inflation Factor (VIF) was utilized. Values of VIF exceeding 10 are often regarded as indicating multicollinearity. In the test of hypothesis 2, a VIF of 2.5 was observed, thus indicating a non-presence of significant multicollinearity

Hypothesis 3 proposed that "There is no significant difference in the information content of cash flows between European firms utilizing an IFRS basis and U.S. firms using a GAAP basis of accounting". Using a similar approach as hypothesis two, a regression model is constructed to assess the information content of cash flows. This model is consistent with that used by Clement 1999, Jacob et al. 1999, Chen and Matsumoto 2006, and Call, Chen and Tong 2009. The model is:

CARit = a + b1UEUSit + h2UEEit + b3MBit + h4Bit + h5MVit + eit (4)
Where:  CARit   = Cumulative abnormal return firm i, time t
        a       = Intercept term
        UEUSit  = Cash for U.S. firms in the sample
        UEEit   = Cash for European firms in the sample
        MBit    = Market to book value of equity as proxy for growth
                  and persistence
        Bit     = Market model slope coefficient as proxy for
                  systematic risk
        MVit    = Market value of equity as proxy for firm size
        eit     = Error term for firm i, time t


The coefficient "a" measures the intercept. The coefficient b1 represents U.S. firms and is the response coefficient correlating cash flows with security prices. The coefficient b2 is the similar response coefficient associated with European firms. Once again, variables b3, b4, and b5 are inserted for assessment of other determinants which may influence results.

Similarly, for each firm sample, an abnormal return (ARit) is generated around the event dates of -1, 0, +1 (day 0 representing the day that the firm's financials were available per DJNRS or Worldscope). The market model is utilized along with the CRSP equally-weighted market index and regression parameters are established between -290 and -91. Abnormal returns are then summed to calculate a cross-sectional cumulative abnormal return (CARit).

Results of the test for hypothesis 3 are found in Table 4. Results show that coefficient b1, representing the response coefficient of U.S. firms, is 0.58 and significant at the .10 level. These results indicate that a positive relationship exists between cash flows and security prices for U.S. firms. Coefficient b2, representing the response coefficient of European firms, is 3.04 and significant at the .01 level. This indicates a strong relationship between the information content contained in reported cash flows and security prices.

Performing the Welch's test, and as indicated in Table 4, a t-statistic of 1.693 was computed with a p-value of less than .010. This shows that the means of the sample groups are significantly different, and thus the null of similarity between the groups is rejected. This reinforces the finding of Marshall (2000) which indicates that European Union firms tends to place significant reliance on cash flows.

Again, regression variables are assessed for multicollinearity using the Variance Inflation Factor (VIF). Values of VIF exceeding 10 are often regarded as indicating multicollinearity. In the test of hypothesis 2, a VIF of 2.1 was observed, thus indicating a non-presence of significant multicollinearity

CONCLUSION

Convergence of IFRS and GAAP continues to be a high priority on the agendas of both FASB and the IASB. It is, therefore, appropriate to evaluate any significant differences that accounting for cash flows may have under these two scenarios. This paper examines the differences that exist between IFRS-based and GAAP-based statement of cash flow presentation and recognition along with subsequent stock price effect.

First, in assessing forecast accuracy of cash flows in European firms utilizing IFRS accounting versus U.S. firms using GAAP accounting, findings indicate that there is a higher degree of forecast accuracy of cash flows among European firms. This may be due to findings of prior studies that show European firms have a history of placing importance on cash flows along with their associated forecast.

Next, the information content of accounting earnings is assessed under the two different scenarios in order to form a baseline comparison against which the information content of cash flow will be measured. This analysis finds that a higher degree of correlation between accounting earnings and stock price exists for GAAP-based U.S. firms than for IFRS-based European firms. This may be due in part to prior studies which show that the European model emphasizes tax rules and accounting standards and as such, more emphasis is spent adhering to rules and standards and less emphasis to earnings disclosures.

Finally, the information content of cash flows is assessed under the two differing bases. Findings show that a higher degree of correlation between cash flow and security returns exists for IFRS-based European firms than for GAAP-based U.S. firms. This may be related to prior studies which indicate that European Union firms tends to place significant reliance on cash flows.

Overall results indicate that, with respect to security prices, IFRS-based firms appear to be more cash flow sensitive while GAAP-based firms appear to be more accounting earnings sensitive. These findings may be the result of institutional and structural differences among nations. On the other hand, it is noteworthy to understand that differences in cash flow presentation and recognition exist between the nations and their standard-setters. These differences have the potential of contributing to how investors make stock purchase decisions and therefore must be considered as the transitional phase between IFRS and GAAP continues.

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Ronald A. Stunda

Valdosta State University

About the Author:

Ronald A. Stunda is Professor of Accounting at Valdosta State University. His area of specialization is market-based Accounting research. He has published in numerous accounting and finance journals and is on the editorial board and assists as reviewer for multiple journals.
Table 1
Summary of the Firms, 2006-2016

Item                          U.S. Firms  European Firms

Firms initially identified    387         279
Firms eliminated due to lack   18          21
of CRSP/AMADEUS data
Firms eliminated due to lack   10          13
of Compustat Global/
Compustat data
Firms eliminated due to         7           9
EDGAR/European Business
Register information
Total firms in study sample   352         236

Table 2
Analysis Accuracy 2006-2016

                U.S. Firms versus European Firms
                Model: [rapfe.sub.ijt]= |[R.sub.jt] - [F.sub.mjt]/
                [R.sub.jt]|*100-|[R.sub.jt] - [F.sub.mjt]/
                [R.sub.jt]|*100

Entity          Number             Average Mean  t-test  Probability

U.S. Firms      352                2.85          1.98    0.05
European Firms  236                1.02          1.66    0.01
                t-stat     df       p-value
Welch's t-test    1.609     1      <.020

Table 3
Information Content of Accounting Earnings 2006-2016

                   U.S. Firms versus European Firms
Model: CARit = a + b1UBUSit + b2UEEit + b3M Bit + b4Bit + b5MVit + eit

a                b1          b2        b3    b4    b5    Adj. [R.sup.2]

0.20             1.98        0.12      0.59  0.22  0.18  0.223
(.87)            1.60 (a)    2.27 (b)  0.23  0.45  0.76
a = significant at the .01 level       b = significant at the .10 level
                    t-stat  df  p-value
Welch's t-test      1.718   1   <.010

Table 4
Information Content of Cash Flow 2006-2016

                U.S. Firms versus European Firms
Model: CARit = a +b1UEUSit + b2UEEit + b3MBit + b4Bit + b5MVit + eit

a      b1        b2                b3    b4    b5    Adj. [R.sup.2]

0.39   0.58      3.04              0.65  0.38  0.27  0.245
(.47)  2.19 (b)  1.54 (a)          0.78  0.33  0.41
a = significant at the .01 level   b = significantat the .10 level
                t-stat   df   p-value
Welch's t-test  1.693    1    <.010
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Author:Stunda, Ronald A.
Publication:International Journal of Business, Accounting and Finance (IJBAF)
Article Type:Report
Date:Sep 22, 2017
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