Recolección de datos

Methodology of Variability of Earnings

We have considered variety of accounting characteristics in quality of earnings, which have been examined in prior studies. The ratio of cash flows relative to earnings ratio has been determined as the measure of accounting quality in previous chapter. The simple cash flow from operation over earnings (CFO/E) ratio captures the fundamental financial reporting behavior across different sizes of firms. Given the reported earnings is made of cash flows and accruals, that accruals are used to solve to the timing and matching problems of cash flows. Hence, CFO/E ratio is able to present the level of accruals.

However, the CFO/E ratio only measures one aspect of accounting quality, and quality of accruals is sensitive to a variety of other factors. Prior tests might be an initial indication of firms’ financial reporting behavior in a general view. Therefore, in order to further examine how reported earnings are related to operating cash flows, following Barth et al (2008), we estimate each reported earnings and cash flows with controls of factors that related to accounting quality.

As discussed earlier, accruals and earnings are influenced by both economic effects and accounting effects. Thus, in order to compare the quality of earnings between each group of companies (large, medium and small companies), firstly we need to adjust economic factors for earnings and then compare their earnings based

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on accounting effects. These factors should be at least partially mitigated by our inclusion of control variables. To incorporate our controls we first estimate a regression of the change in annual net income scaled by total assets (Lang et al, 2006). We then use the residuals from underlying regression to compute our measure of earnings variability. Accordingly, variability of is the variance of the residuals from the regression of the change in earnings scaled by total assets [ ]. Hence, following Lang et al (2006) and Barth et al (2008), our regression model on earnings variability is as follows:

₀ 𝐺 𝐿 ₆

Where, i = 1, …, ;

g = L (Large), M (Medium), S (Small); k = Industry 1, 2, … 10;

changes in net income scaled by total asset;

the natural logarithm of end of year value of equity;

𝐺 percentage change in sales;

𝐿 end of year total liabilities divided by end of year equity book value;

percentage change in total liabilities;

sales divided by end of year total assets;

annual net cash flow from operating activities divided by end of year total assets.

Basic intuition is that accruals that lead to smoothness can hide or delay the measurement of changes in fundamental performance, which presumably would be decision useful, thus, smoothness may not be an indication of greater decision usefulness or higher earnings quality (Dechow et al, 2010 pg.361). Hence, we adjust economic factors according to prior studies (e.g. Lang et al 2003; Lang et al 2006; Barth et al 2008) and use the measure of volatility of change in earnings deflated by total assets as the measure of earnings quality. If firms smooth their earnings, the volatility of change in earnings is expected to be small.

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In order to compare the differences in accounting quality between each group of companies, following Barth et al (2008), we test for the significant differences between each group of firms based on the empirical distribution of R-squares from the regression. We obtain the empirical distribution of differences for each group of companies (i.e. large companies, medium companies and small companies) by estimating the above regression using the method of bootstrapping.

Specifically,

 We firstly estimate the above equation by splitting observations into three groups of companies to fit into the equation.

 We randomly select (5% of number of each group of companies), with replacement, firm-observations from each group of companies and then run the value relevance regressions for each group 1,000 times.

 We will then obtain 1,000 R-squared for each group of firms for particular test. In testing the significant difference between each group, we take the differences between 1,000 R-squared from each group of companies and then use the variance of 1,000 differences to compute the z-stat to see whether the difference is greater than zero.

Results of Variability of Earnings

[Table 4.1 Here]

Descriptive Statistics for all variables

Table 4.1 presents the descriptive statistics relating to each variable used in the measure of earnings smoothing. Values below 5th level and above 95th level are different from values at other percentiles for all variables. Therefore, we winsorized each variable at 95% level in testing the variability of earnings and ratio of variability of earnings to variability of cash flows.

In terms of test variables, large companies and small companies have less variance in changes in earnings than medium companies. Especially large companies, they have the lowest variances in changes in earnings and changes in cash flows. Medium companies are more likely to manage earnings downwards compared with previous years.

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Large and medium companies tend to have more growth than small companies. Large companies are more highly levered than medium and small companies. Medium and small companies are more likely to issue debts and have higher sales turnover than large companies. Cash flows of each group companies are varied.

[Table 4.2 Here]

Variability of Earnings

Table 4.2 presents results of the variability of change in earnings across large (public companies), medium and small companies in the observation year. Medium companies exhibit the lowest variability of changes in earnings (0.0056) and small companies have the highest variability of changes in earnings (0.021). The variability of changes in earnings for large companies (0.0073) is in between of medium and small companies. Based on the assumption of Barth et al (2008), lower variability of changes in earnings is the evidence of earnings smoothing. This suggests that medium companies are more likely to smooth their earnings than large and small companies.

[Figure 4.1 Here]

Empirical Distribution of R-squares

In order to compare the differences in accounting quality between each group of companies, we test for the significant differences between each group of firms based on the empirical distribution of R-squares from regression. That means, we firstly randomly select firm observations for each group of companies, and then fit these observations into the variability of changes in earnings model. We then obtain the empirical distribution of R-squared by repeating above procedures by 1,000 times. The distributions of 1,000 R-squared for each group of companies are presented in Figure 3. The distribution of medium companies is significantly different from large and small companies.

Key Findings from Table 4.2:

1. Medium companies have lower variability of change in earnings than large and small companies.

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2. The variability of changes in earnings for medium companies is significantly different from large and small companies, given the distribution of R-squares of medium companies is different from large and small companies

3. These suggest that accounting quality for large and small companies is quite similar, whereas medium companies have different reporting behaviour from large and small companies.

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TABLE 4.1: Summary Statistics Relating to Variables used in Earnings Quality Model Analysis

₀ 𝐺 𝐿 ₆ 0 𝐺 𝐿 6 𝜈

Large Companies

Number Mean Std Deviation Min 1st Percentile 5th Percentile 25th Percentile Median 75th Percentile 95th Percentile 99th Percentile Max

Test Variables 2,253 0.09* 1.47 -2.75 -0.57 -0.19 -0.02 0.01 0.05 0.25 1.03 42.19 2,253 0.09* 3.37 -6.94 -0.68 -0.27 -0.05 0.00 0.06 0.31 0.93 158.00 Control Variables 2,128 9.03* 2.27 1.39 3.99 5.82 7.53 8.72 10.27 13.27 15.20 18.29 𝐺 1,987 2.45* 76.01 -1.27 -0.78 -0.36 -0.06 0.05 0.18 0.76 3.44 3,143.00 𝐿 2,253 128.10* 2,635.00 -11,358.00 -17.72 -1.49 0.34 1.04 2.60 14.00 306.10 103,022.00 2,248 0.53* 7.91 -1.16 -0.88 -0.49 -0.11 0.01 0.20 1.14 4.13 304.70 2,039 1.39* 1.44 0.00 0.00 0.02 0.35 1.09 1.93 3.89 6.15 22.33 2,253 0.13* 3.02 -2.14 -0.55 -0.20 -0.01 0.05 0.13 0.32 0.73 143.00 Medium Companies

Number Mean Std Deviation Min 1st Percentile 5th Percentile 25th Percentile Median 75th Percentile 95th Percentile 99th Percentile Max

Test Variables 35,560 -3.21* 612.00 -114,506.00 -0.71 -0.18 -0.02 0.00 0.04 0.24 0.99 5,778.00 35,560 -3.42* 622.80 -116,338.00 -1.03 -0.40 -0.08 0.00 0.07 0.37 1.29 5,894.00 Control Variables 32,123 8.47* 1.75 0.00 4.23 5.95 7.47 8.28 9.34 11.65 13.57 18.84 𝐺 30,482 2.33* 197.00 -1,258.00 -0.80 -0.39 -0.06 0.04 0.18 0.69 3.29 31,117.00 𝐿 35,560 7.29* 5,958.00 -942,675.00 -40.58 -4.84 0.32 1.16 3.06 17.28 118.20 595,936.00 35,274 1.72* 99.83 -17.57 -0.97 -0.53 -0.11 0.01 0.20 0.94 4.41 16,632.00 31,270 2.66* 51.99 -0.27 0.01 0.05 0.57 1.36 2.26 4.54 8.97 5,479.00 35,560 -2.92* 674.10 -126,806.00 -0.64 -0.19 0.00 0.06 0.14 0.38 1.05 3,500.00

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Small Companies

Number Mean Std Deviation Min 1st Percentile 5th Percentile 25th Percentile Median 75th Percentile 95th Percentile 99th Percentile Max

Test Variables 8,205 0.05* 66.53 -5,809.00 -1.10 -0.29 -0.03 0.01 0.11 0.65 4.21 818.50 8,205 -0.06* 66.11 -5,809.00 -1.54 -0.57 -0.11 0.01 0.18 0.87 4.00 765.50 Control Variables 7,124 6.07* 1.48 0.00 1.10 3.30 5.30 6.28 7.16 7.87 8.61 10.73 𝐺 7,561 1.36* 46.45 -9.32 -0.76 -0.36 -0.06 0.06 0.26 1.34 7.78 3,546.00 𝐿 8,205 4.68* 74.51 -3,084.00 -33.41 -3.87 0.15 0.70 2.28 15.08 103.80 2,781.00 8,122 1.068* 38.57 -19.26 -0.96 -0.60 -0.15 0.03 0.31 1.62 7.22 3,251.00 7,691 3.70* 30.15 -0.41 0.02 0.07 1.05 2.01 3.13 6.80 19.01 1,746.00 8,205 2.21* 105.30 -198.50 -0.94 -0.31 0.00 0.11 0.29 1.05 4.85 9,232.00

This table presents the descriptive statistics for variables used in models of testing earnings quality. Sample of firms are selected in the observation years of 2009 and 2010 from FAME database.

Variable Definition: Test Variables: is the change in earnings, where earnings is scaled by end-of-year total assets; is the change in cash flow from operations, where cash flow is scaled by end-of-year total assets, cash flow from operation is defined as Net income after interest, tax and extraordinary items in the observation year + Depreciation – Changes in Working Capital;

Control Variables: is the natural logarithm of value of equity in millions of dollars as of the end of the year; 𝐺 is the percentage change in sales; 𝐿 is end-of- year total liabilities divided by end-of-year book value of equity; is the percentage change in total liabilities; is sales divided by end-of-year total assets; is the cash flow from operating activities, scaled by end-of-year total assets

Large companies are companies that are public quoted companies following with International Financial Reporting Standards (IFRS). Medium companies are those have turnover of not more than £25.9 million, a balance sheet total of not more than £12.9 million and not more than 250 employees, following with UK GAAP. Small companies are those have turnover of not more than £6.5 million, a balance sheet total of not more than £3.26 million and not more than 50 employees, following with FRESSE.

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TABLE 4.2: Result of Volatility of Earnings for Large, Medium and Small Companies

₀ 𝐺 𝐿 ₆

Large Companies (N=2253) Medium Companies (N=35596) Small Companies (N=8297)

Variability of 0.0073 0.0056* 0.021

R-square 0.072 0.116 0.286

This table presents results of regression from on various control variables. We based the analysis on control variables as defined in Table 4.1. We define variability of

as the variance of residuals from a regression of the on the control variables. We compute the residuals from the regression of each variable on the control variables.

is defined in Table 4.1.

Variable Definition: Test Variables: is the change in earnings, where earnings are scaled by end-of-year total assets;

Control Variables: is the natural logarithm of market value of equity in millions of dollars as of the end of the year; 𝐺 is the percentage change in sales; 𝐿 is end-of-year total liabilities divided by end-of-year book value of equity; is the percentage change in total liabilities; is sales divided by end-of-year total assets;

is the cash flow from operating activities, scaled by end-of-year total assets

Large companies are companies that are public quoted companies following with International Financial Reporting Standards (IFRS). Medium companies are those have turnover of not more than £25.9 million, a balance sheet total of not more than £12.9 million and not more than 250 employees, following with UK GAAP. Small companies are those have turnover of not more than £6.5 million, a balance sheet total of not more than £3.26 million and not more than 50 employees, following with FRESSE.

Each sample of companies is winsorized at the 5th and 95th percentile in order to control the influence of outliers. * indicates significantly different from other types of companies at 5% level (one-tailed).

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Figure 4.1: The empirical distribution of 1,000 R-squares for each group of companies

This figure presents the empirical distribution of R-square from bootstrapping regression model of changes in earnings.

The model of variability of changes in earnings is:

₀ 𝐺 𝐿 ₆

 Dependent Variable: is the change in earnings, where earnings is scaled by end-of-year total assets;

 Control Variables: is the natural logarithm of market value of equity in millions of dollars as of the end of the year; 𝐺 is the percentage change in sales; 𝐿 is end-of-year total liabilities divided by end-of-year book value of equity; is the percentage change in total liabilities; is sales divided by end-of-year total assets; is the cash flow from operating activities, scaled by end- of-year total assets

The bootstrap procedures are as follows: we firstly randomly select firm observations from each group of companies to fit into the model of variability of changes in earnings; the sample size is 5% of number of firms from each group of companies. Secondly, we repeat above procedure by 1000 times. We then obtain 1000 R-squares for each group of companies. The frequency distribution is plotted based on 1000 R-squares.

Large companies are companies that are public quoted companies following with International Financial Reporting Standards (IFRS). Medium companies are those have turnover of not more than £25.9 million, a balance sheet total of not more than £12.9 million and not more than 250 employees, following with UK GAAP. Small companies are those have turnover of not more than £6.5 million, a balance sheet total of not more than £3.26 million and not more than 50 employees, following with FRESSE.

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