1. Voluntary Disclosure of Firms as a Function of Industry Correlation: An Experimental Study Gabriel D. Rosenberg

2. Motivation U.S. securities markets are based mainly on mandatory disclosure. Mandatory disclosure is expensive – will voluntary disclosure work just as well? – Are there different circumstances under which we need mandatory vs. voluntary disclosure?

3. Different Industries Firms are not all the same. Firms in the same industry may have a common component to their value – correlation between firms in an industry. – “Disclosures by one firm in an industry may alter investors’ beliefs about the profitability of other firms in the same industry, and thereby change their market value.” (Dye, citing Foster)

4. Question Do firms’ voluntary disclosure choices change as the correlation between firm values change?

5. Hypotheses Public goods hypothesis: – “Voluntary disclosure will necessarily be incomplete, will not be as informative as it potentially could be, and might be very wasteful. Disclosure involves information, which is a free good and is difficult for those who produce it to capture the full gain from the cost of disclosure (public good). Thus, there is underproduction of information. There is a free-rider effect for similar companies.” [paraphrasing Judge Ralph Winter, Yale Law School class on Securities Regulation] Alternatively, disclosure decision might just be based on value.

6. Experimental Method Common Weighting % randomly chosen Value = (Common Weighting %)*(Common Component) + (100–Common Weighting %)*(Individual Component) Firms decide whether to disclose (cost of 10) Investors bid on firms

7. Total Disclosures Common Weighting % Total Number of Disclosures Round 1161 Round 2121 Round 3741 Round 4273 Round 5472 Round 6220 Round 7162 Round 8622 Round 9322 Round 10121

8. Total Disclosures Common Weighting % Total Number of Disclosures 121 1 161 2 220 273 322 472 622 741

9. Total Disclosures

10. Disclosure as a Function of Value

11. Disclosure as a Function of CommonValue

12. Disclosure as a Function of Independent Value

13. Logit Model Used to predict a binary event Pr(DisclosureChoice = 1|Var1, Var2, Var3 …) = f(β 0 + β 1 Var1 + β 2 Var2 + β 3 Var3 …)

14. Logit Model: Disclosure Choice as a Function of Value DisChoiceCoef.Std. Err.ZP>z [95% Conf. Interval] Value.0876932.02830263.100.002.0322211.1431652 _cons-5.8072281.849376-3.140.002-9.431939-2.182517

15. Logit Model: Disclosure Choice as a Function of Value DisChoiceCoef.Std. Err.ZP>z [95% Conf. Interval] Value.0876932.02830263.100.002.0322211.1431652 _cons-5.8072281.849376-3.140.002-9.431939-2.182517

16. Logit Model: Disclosure Choice as a Function of Correlation, CommonValue, and IndependentValue DisChoiceCoef.Std. Err.zP>z[95% Conf.Interval] Correlation-.0147318.0276366-0.530.594-.0688985.0394349 Common Value 1.5164592.457820.620.537-3.3007786.333697 Independent Value 8.5191572.4977793.410.0013.623613.41471 _cons-5.9654542.1691-2.750.006-10.21681-1.714097

17. Logit Model: Disclosure Choice as a Function of Correlation, CommonValue, and IndependentValue DisChoiceCoef.Std. Err.zP>z[95% Conf.Interval] Correlation-.0147318.0276366-0.530.594-.0688985.0394349 Common Value 1.5164592.457820.620.537-3.3007786.333697 Independent Value 8.5191572.4977793.410.0013.623613.41471 _cons-5.9654542.1691-2.750.006-10.21681-1.714097

18. DisChoiceCoef.Std. Err.zP>z[95% Conf.Interval] Correlation-.0147318.0276366-0.530.594-.0688985.0394349 Common Value 1.5164592.457820.620.537-3.3007786.333697 Independent Value 8.5191572.4977793.410.0013.623613.41471 _cons-5.9654542.1691-2.750.006-10.21681-1.714097 Logit Model: Disclosure Choice as a Function of Correlation, CommonValue, and IndependentValue

19. DisChoiceCoef.Std. Err.zP>z[95% Conf.Interval] Correlation-.0147318.0276366-0.530.594-.0688985.0394349 Common Value 1.5164592.457820.620.537-3.3007786.333697 Independent Value 8.5191572.4977793.410.0013.623613.41471 _cons-5.9654542.1691-2.750.006-10.21681-1.714097 Logit Model: Disclosure Choice as a Function of Correlation, CommonValue, and IndependentValue

20. Logit Model: Disclosure Choice as a Function of the Components Value Disclosure Choice Coef.Std. Err.zP>z[95% Conf.Interval] Common TimesCorr.0687366.03092822.220.026.0081184.1293548 IndTimes Weighting.1231108.03806773.230.001.0484994.1977221 _cons-6.7090122.110985-3.180.001-10.84647-2.571558

21. Logit Model: Disclosure Choice as a Function of the Components Value Disclosure Choice Coef.Std. Err.zP>z[95% Conf.Interval] Correlation-.0125845.0269673-0.470.641-.0654395.0402706 Common Value 1.4637472.5044740.580.559-3.4449326.372426 Independent Value 8.3005792.6161793.170.0023.17296313.42819 Previous Profit -.0192508.0335655-0.570.566-.085038.0465364 _cons-5.9256562.289073-2.590.010-10.41216-1.439156

22. Logit Model: Disclosure Choice as a Function of the Components Value Disclosure Choice Coef.Std. Err.zP>z[95% Conf.Interval] Correlation-.0125845.0269673-0.470.641-.0654395.0402706 Common Value 1.4637472.5044740.580.559-3.4449326.372426 Independent Value 8.3005792.6161793.170.0023.17296313.42819 Previous Profit -.0192508.0335655-0.570.566-.085038.0465364 _cons-5.9256562.289073-2.590.010-10.41216-1.439156

23. Conclusion Firms seem to make decision based on value (mainly independent value) rather than correlation – No visible public goods problem In the future, would be better to pick certain correlation levels and randomize within those rather than completely random