DISCUSSION AND CONCLUDING REMARKS

977 variance, under good-news and bad-news environments have incremental predictive power for predicting earnings levels. Our evidence is also consistent with the idea that the distributions of analysts earnings forecasts are significantly different in good news or a bad news environment. This finding has some implication for any study that assumes analysts‘ forecast variances represent random variables from a single population. Our evidence indicates a need to consider forecast variances conditioned on good news and bad news. The existence of arbitrage return for portfolios constructed with analyst forecast variance is consistent with the predictive power of forecast variances of annual earnings. We refrain from making any conclusions regarding market efficiency because these returns do not consider factors such as transaction costs. Future research is needed in these areas. 978 REFERENCES Abdel-khalik, A. R. and J. Espejo, 1978. 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The Accounting Review 65 2: 477-488. 982 Table 1 Industry affiliation and descriptive statistics on the firms included in the sample 1 Panel A: Industry Distribution Two -Digit SIC Code Industry Description Number of Firms 10 Gold and Silver 11 13 Crude Petroleum and Natural Gas 28 28 Pharmaceutical Preparations 37 36 Telephone and Telegraph Apparatus 26 37 Rail Road Equipment 15 63 Hospital and Medical Plans 18 Other 199 Total Firms 334 Panel B: Descriptive statistics computed over firm-years included in the sample Mean Standard Deviation Median Minimum Maximum Total Assets 30,016 108,122 4,765 136 527,715 Total Equity 4.803 10,783 1,640 127 63,706 Market Value 15,731 35,509 4,473 177 192,472 Income before extra ordinary items 708.82 2,246 184 -1,536 10,270 Earnings Per Share 1.46 2.42 1.29 -4.00 35.00 Return on Assets 3.30 15.49 4.02 -42.00 24.10 Return on Equity 13.13 19.30 13.01 -25.80 39.50 1 For inclusion in the sample, the firm must have analysts‘ forecast variance data for all four PEAPs of the year over a minimum of seven years during the period, 1996-2006. Analysts forecast variance is computed for firms with a minimum of four distinct analysts‘ forecasts in any pre-earnings announcement period PEAP. 983 Table 2 Analyst forecast variance for the two ex post and two ex ante definitions of good-news and bad-news, by year and PEAP. Ex post good news is defined as meeting or exceeding previous years‘ earnings A, or as reporting profits B. Ex ante good news is when the mean of analyst earnings forecasts exceeds previous years ‘ earnings C or the mean of analysts‘ earnings forecasts exceeds zero D. Bad news is defined as the absence of good news. Good-News Definitions ex post Good-News Definitions ex ante Year Exceeding Previous Years’ Earning A Reporting Profits B Expected to Exceed Previous Years ’ Earning C Expected to Report Profits D Bad- News Good- News Bad News- Good News Bad- News Good- News Bad News- Good News Bad- News Good- News Bad News- Good News Bad- News Good- News Bad News- Good News 1996 0.09 0.06 0.03 0.17 0.09 0.08 0.1 0.06 0.04 0.16 0.09 0.08 1997 0.1 0.07 0.03 0.14 0.07 0.06 0.11 0.07 0.04 0.12 0.08 0.04 1998 0.13 0.06 0.07 0.21 0.07 0.14 0.14 0.07 0.07 0.13 0.08 0.05 1999 0.12 0.06 0.07 0.15 0.07 0.08 0.14 0.06 0.08 0.14 0.07 0.07 2000 0.19 0.08 0.11 0.11 0.09 0.02 0.18 0.09 0.09 0.12 0.10 0.02 2001 0.20 0.07 0.13 0.38 0.09 0.28 0.2 0.08 0.12 0.37 0.11 0.26 2002 0.13 0.08 0.05 0.28 0.07 0.20 0.11 0.09 0.02 0.30 0.07 0.22 2003 0.13 0.1 0.02 0.31 0.08 0.22 0.15 0.1 0.04 0.33 0.09 0.23 2004 0.15 0.01 0.05 0.25 0.09 0.15 0.15 0.1 0.05 0.28 0.09 0.17 2005 0.22 0.13 0.09 0.35 0.14 0.21 0.2 0.14 0.06 0.35 0.14 0.21 2006 0.23 0.14 0.09 0.34 0.17 0.17 0.21 0.16 0.05 0.47 0.16 0.30 Positive Differences 100 100 100 100 PEAP 1 0.21 0.12 0.08 0.34 0.13 0.20 0.21 0.14 0.07 0.35 0.13 0.21 PEAP 2 0.18 0.11 0.07 0.31 0.11 0.20 0.18 0.11 0.07 0.34 0.11 0.23 PEAP 3 0.17 0.08 0.08 0.28 0.09 0.16 0.17 0.09 0.07 0.3 0.10 0.23 PEAP 4 0.11 0.06 0.05 0.16 0.06 0.09 0.11 0.07 0.05 0.17 0.07 0.10 Positive Differences 100 100 100 100 984 Table 3 Results from the regression of analyst forecast variance on dummy variables corresponding to firm, year, PEAP, good news and bad news, by news type. Good news is defined as meeting previous years ‘ earnings A or reporting profits B, when the mean of analyst earnings forecasts exceeds previous years ‘ earnings C or the mean of analysts‘ earnings forecasts exceeds zero D. The coefficients for dummy variables corresponding to firm, year, and PEAP are not reported. All three effects are significant in each estimation. I 1 T 1 itp i i t t g itp 1 it b itp 1 it itp i 1 t 1 V F Y V GN V BN                  1 PEAP Exceeding Previous Years ’ Earning A Reporting Profits B Expected to Exceed Previous Years ’ Earnings C Expected to Report Profits D ALL Good-News Dummy 0.02 0.03 0.02 0.02 Bad-News Dummy 0.06 0.14 0.05 0.14 Firm-Years 12,269 12,369 10,744 12,076 Adjusted R 2 55.96 56.65 56.93 56.13 Goodness Of Fit 42.52 43.1 41.21 44.98 1 = 2 116.68 256.23 29.26 209.81 1 Good-News Dummy 0.03

0.03 0.04

0.02 Bad-News Dummy 0.06 0.15 0.06 0.17 Firm-Years 3,068 3,093 2,686 3,019 Adjusted R 2 70.74 71.58 72.72 71.17 Goodness Of Fit 18.42 18.85 18.77 19.84 1 = 2 26.6 84.71 5.38 82.59 2 Good-News Dummy 0.02 0.03 0.02 0.03 Bad-News Dummy 0.05 0.16 0.05 0.2 Firm-Years 3,067 3,092 2,686 3,019 Adjusted R 2 67.57 68.72 68.68 68.77 Goodness Of Fit 15.91 16.51 15.44 17.17 1 = 2 25.19 109 11.08 140.27 3 Good-News Dummy 0.007 0.02 0.01 0.02 Bad-News Dummy 0.07 0.16 0.06 0.18 Firm-Years 3,067 3,092 2,686 3,019 Adjusted R 2 50.21 50.72 51.24 50.54 Goodness Of Fit 7.7 7.73 7.4 8.21 1 = 2 43.93 61.42 17.73 70.68 4 Good-News Dummy 0.01 0.02 0.02 0.02 Bad-News Dummy 0.04 0.08 0.04 0.09 Firm-Years 3,067 3,092 2,686 3,019 Adjusted R 2 48.84 49.23 49.57 48.62 Goodness Of Fit 7.29 7.29 6.92 7.61 1 = 2 24.12 26.81 16.69 31.35  985 TABLE 4 Results from the regression of analyst forecast variance on its PEAP lagged values interacted with dummy variables for good news and bad news, after controlling for firm and year effects. Good news is defined as meeting previous years‘ earnings A or reporting profits B, when the mean of analyst earnings forecasts exceeds previous years‘ earnings C or the mean of analysts‘ earnings forecasts exceeds zero D. The coefficients for dummy variables corresponding to firm, year, and PEAP are not reported. Tests of the significance of firm, year and PEAP effects were all significant. I 1 T 1 itp i i t t g itp 1 it b itp 1 it itp i 1 t 1 V F Y V GN V BN                  2 PEAP Model Details Exceeding Previous years ’ earnings A Reporting Profits B Expected to Exceed Previous Years ’ Earnings C Expected to Report Profits D 2 ρ g 0.74 0.61 0.74 0.59 ρ b 0.67 0.77 0.78 0.77 Observations 3,093 3,093 2,686 3,019 Adjusted R 2 83.83 84.27 83.75 84.3 Model F statistics 48.48 50.46 42.33 49.38 Test of Hypothesis ρ g =1 334.26 621.37 282.6 563.88 ρ b =1 526.86 276.77 354.49 297.89 ρ b = ρ g 24.64 97.87 8.06 101.23 3 ρg 0.41 0.59 0.43 0.48 ρb 1.04 0.71 1.04 0.75 Observations 3,093 3,093 2,686 3,019 Adjusted R2 65.09 57.04 63.57 57.59 Model F statistics 18.07 13.25 14.99 13.24 Test of Hypothesis ρ g =1 675.26 168.89 517.7 268.96 ρ b =1 2.99 136.03 2.52 99.32 ρ b = ρ g 653.99 11.69 478.31 65.77 4 ρg 0.44 0.48 0.37 0.45 ρb 0.27 0.23 0.26 0.24 Observations 3,093 3,093 2,686 3,019 Adjusted R2 53.56 54.94 52.63 54.3 Model F statistics 11.56 12.25 9.91 11.71 Test of Hypothesis ρ g =1 609.78 707.73 637.03 698.11 ρ b =1 4101.68 4095.66 3546.64 4058.6 ρ b = ρ g 60.17 143.17 19.24 96.38 986 Table 5 Results from the regression of annual earnings on dummy variables corresponding to firm and year, and mean and variance of analysts ‘ forecasts for firms with expected good news and expected bad news, by PEAP. Good news is defined as mean analyst earnings expectation exceeding previous years ‘ earnings C or mean analyst earnings expectation exceeding zero D. Bad news definition is complementary to the good news definition. The coefficients for dummy variables corresponding to firm, year, and PEAP are not reported. Tests of the significance of firm, year and PEAP effects were all significant. I 1 T 1 it i i t t gp itp it bp itp it gp itp it bp itp it it i 1 t 1 E F Y M GN M BN V GN V BN                   3 PEAP Variables Expected to Exceed Previous Years Earnings C Expected to Report Profits D 1 ρ gp 0.93 1.02 ρ bp 0.89 0.76 τ gp -0.05 -0.08 τ bp -0.09 -0.17 Observations 2,686 3,019 H : τ gp =τ bp 1.03 1.37 2 ρ gp 1.02 1.02 ρ bp 0.97 1.03 τ gp -0.01 -0.07 τ bp -0.11 -0.13 Observations 2,686 3,019 H : τ gp =τ bp 11.69 1.05 3 ρ gp 1.03 1 ρ bp 1.04 1.03 τ gp -0.04 -0.07 τ bp -0.14 -0.38 Observations 2,686 3,019 H : τ gp =τ bp 25.11 83.22 4 ρ gp 0.97 1.01 ρ bp 0.96 0.91 τ gp 0.005 -0.001 τ bp -0.17 -0.12 Observations 2,686 3,019 H : τ gp =τ bp 1.93 21.4 987 Table 6 Buy and hold returns on portfolios of stocks constructed at the end of each PEAP on basis of standard deviation of analysts‘ forecasts of earnings during that PEAP. Firms are classified into low and high standard deviation on the basis of their variance quartile. Reported are the raw returns computed by holding the stocks over the remaining fiscal year. Analysis is performed for the two ex ante definitions – Mean Analyst Earnings Expectation Exceeding Previous Years Earnings Panel A and Mean Analyst Earnings Expectation Exceeding Zero Panel B. Bad News definition is complementary to the Good News definition. PANEL A: Earnings Expected to Exceed Previous Yea rs’ Earnings C Portfolio Holding Period PORTFOLIO-1 PORTFOLIO-2 PORTFOLIO-3 Good News Low Variance Good News High Variance Difference Bad News Low Variance Bad News High Variance Difference Good News Low Variance Bad News High Variance Difference PEAP1- Year End 0.1574 0.0991 0.0583 0.0880 0.0948 -0.0068 0.1574 0.0948 0.0626 PEAP2-Year End 0.1119 0.0847 0.0272 0.0600 0.0650 -0.0050 0.1190 0.0650 0.0540 PEAP3-Year End 0.0882 0.0819 0.0063 0.1334 0.0800 0.0534 0.0882 0.0800 0.0082 PEAP4-Year End t+1 0.1707 0.119 0.0517 0.2100 0.0700 0.1400 0.1707 0.0725 0.0982 PANEL B: Expected to Report Profits D Portfolio Holding Period Good News Low Variance Good News High Variance Difference Bad News Low Variance Bad News High Variance Difference Good News Low Variance Bad News High Variance Difference PEAP1- Year End 0.1481 0.0931 0.0550 0.2396 0.1006 0.1390 0.1481 0.1006 0.0475 PEAP2-Year End 0.1048 0.0798 0.0250 0.0663 0.1100 -0.0437 0.1048 0.1100 -0.0052 PEAP3-Year End 0.0913 0.0780 0.0133 0.1509 0.0915 0.0594 0.0913 0.0915 -0.0002 PEAP4-Year End t+1 0.1887 0.1201 0.0686 0.2169 0.0869 0.1300 0.1887 0.0869 0.1018 988 PUBLIC DISCLOSURE, PRIVATE INFORMATION, AND INVESTMENT EFFICIENCY Yoshikazu Ishinagi, Nagoya University of Commerce and Business Atsushi Shiiba, Osaka University, Hiroji Takao, Osaka University Abstract This paper investigates how and when the quality of accounting information improves firm investment efficiency. In particular, we focus on the role of public disclosure in forming more efficient security prices and thereby improving firm investment. Using a stock market model that incorporates managerial investment decisions, we show in general that higher quality accounting information generally improves investment efficiency by reducing information asymmetries, and this is consistent with recent empirical findings. Key Words: public disclosure, private information, investment efficiency, information asymmetry, market liquidity

1. Introduction

This paper investigates how and when the quality of accounting information improves firm investment efficiency using a stock market model that incorporates managerial investment decisions. In particular, we focus on the role of public disclosure in forming more efficient security prices and thereby improving firm investment. Recent empirical research suggests that higher quality financial reporting improves capital investment efficiency by reducing information asymmetries. For example, Biddle and Hilary 2006 examine how accounting quality relates to capital investment efficiency, and empirically find that higher quality accounting enhances investment efficiency by reducing information asymmetry between managers and outside suppliers of capital. Similarly, Biddle et al. 2008 find that higher quality financial reporting enhances investment efficiency. In particular, they find a negative 989 association between financial reporting quality and investment in firms operating in settings prone to overinvestment. However, financial reporting quality and investment are positively associated for firms operating in settings prone to underinvestment. These findings suggest that accounting information quality improves the economic performance of firms. 140 However, high-quality public disclosure may not improve investment efficiency. For example, stock prices may not be an adequate indicator upon which we could base compensation to reward managerial effort. Recent corporate crises indicate that stock- based compensation distorts manager‘s effort toward short-term outcomes. See, for instance, Bolton et al. 2006 for a recent analytical model based on stock price efficiency. 141 In sum, we cannot claim that public disclosure always improves stock price efficiency and thereby firm investment efficiency. In this paper, we attempt to identify the conditions where the quality of accounting information improves managerial investment decision making. Our model extends the single-signal framework in Kyle 1985 by introducing a second public signal that the firm must disclose. In this capital market setting, we examine firm investment efficiency as a key determinant of economic productivity. The work most related to the present analysis is Fishman and Hagerty 1989, as they also model managerial decision making on investments using an extension of the model in Kyle 1985. However, unlike Fishman and Hagerty 1989, we explicitly model public information along with private information, and examine a setting in which both a market maker and informed traders know this information. We also 140 Several recent empirical studies concern the relation between investment efficiency and earnings management. See, for instance, McNichols and Stubben 2008, Kedia and Philippon 2009 and Durnev and Mangen 2009. However, we do not consider earnings management here. 141 There may be another reason why high-quality public disclosure may not improve the economic performance of firms. Public information sometimes communicates a firm‘s proprietary information to competitors. In fact, some studies suggest an association between competition and voluntary disclosure. See, for example, Guo et al. 2004 and Jin 2005. In considering this effect, we could argue that managers change the level of investment when the precision of public information changes, and this could decrease firm profits.