Voluntary Disclosure of Firms as a Function of Industry Correlation: An

Experimental StudyGabriel D. Rosenberg

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?

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)

Question

• Do firms’ voluntary disclosure choices change as the correlation between firm values change?

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.

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

Total DisclosuresCommon

Weighting %Total Number of

Disclosures

Round 1 16 1

Round 2 12 1

Round 3 74 1

Round 4 27 3

Round 5 47 2

Round 6 22 0

Round 7 16 2

Round 8 62 2

Round 9 32 2

Round 10 12 1

Total DisclosuresCommon

Weighting %Total Number of

Disclosures

12 1

12 1

16 1

16 2

22 0

27 3

32 2

47 2

62 2

74 1

Total Disclosures

Disclosure as a Function of Value

Disclosure as a Function of CommonValue

Disclosure as a Function of Independent Value

Logit Model

• Used to predict a binary event

Pr(DisclosureChoice = 1|Var1, Var2, Var3 …)

= f(β0 + β1Var1 + β2Var2 + β3Var3 …)

Logit Model: Disclosure Choice as a Function of Value

DisChoice Coef. Std. Err. Z P>z[95% Conf.

Interval]

Value .0876932 .0283026 3.10 0.002 .0322211 .1431652

_cons -5.807228 1.849376 -3.14 0.002 -9.431939 -2.182517

Logit Model: Disclosure Choice as a Function of Value

DisChoice Coef. Std. Err. Z P>z[95% Conf.

Interval]

Value .0876932 .0283026 3.10 0.002 .0322211 .1431652

_cons -5.807228 1.849376 -3.14 0.002 -9.431939 -2.182517

Logit Model: Disclosure Choice as a Function of Correlation,

CommonValue, and IndependentValue

DisChoice Coef. Std. Err. z P>z [95% Conf. Interval]

Correlation -.0147318 .0276366 -0.53 0.594 -.0688985 .0394349

Common Value

1.516459 2.45782 0.62 0.537 -3.300778 6.333697

Independent Value

8.519157 2.497779 3.41 0.001 3.6236 13.41471

_cons -5.965454 2.1691 -2.75 0.006 -10.21681 -1.714097

Logit Model: Disclosure Choice as a Function of Correlation,

CommonValue, and IndependentValue

DisChoice Coef. Std. Err. z P>z [95% Conf. Interval]

Correlation -.0147318 .0276366 -0.53 0.594 -.0688985 .0394349

Common Value

1.516459 2.45782 0.62 0.537 -3.300778 6.333697

Independent Value

8.519157 2.497779 3.41 0.001 3.6236 13.41471

_cons -5.965454 2.1691 -2.75 0.006 -10.21681 -1.714097

DisChoice Coef. Std. Err. z P>z [95% Conf. Interval]

Correlation -.0147318 .0276366 -0.53 0.594 -.0688985 .0394349

Common Value

1.516459 2.45782 0.62 0.537 -3.300778 6.333697

Independent Value

8.519157 2.497779 3.41 0.001 3.6236 13.41471

_cons -5.965454 2.1691 -2.75 0.006 -10.21681 -1.714097

Logit Model: Disclosure Choice as a Function of Correlation,

CommonValue, and IndependentValue

DisChoice Coef. Std. Err. z P>z [95% Conf. Interval]

Correlation -.0147318 .0276366 -0.53 0.594 -.0688985 .0394349

Common Value

1.516459 2.45782 0.62 0.537 -3.300778 6.333697

Independent Value

8.519157 2.497779 3.41 0.001 3.6236 13.41471

_cons -5.965454 2.1691 -2.75 0.006 -10.21681 -1.714097

Logit Model: Disclosure Choice as a Function of Correlation,

CommonValue, and IndependentValue

Logit Model: Disclosure Choice as a Function of the Components Value

DisclosureChoice

Coef. Std. Err. z P>z [95% Conf. Interval]

CommonTimesCorr

.0687366 .0309282 2.22 0.026 .0081184 .1293548

IndTimesWeighting

.1231108 .0380677 3.23 0.001 .0484994 .1977221

_cons -6.709012 2.110985 -3.18 0.001 -10.84647 -2.571558

Logit Model: Disclosure Choice as a Function of the Components Value

Disclosure Choice

Coef. Std. Err. z P>z [95% Conf. Interval]

Correlation -.0125845 .0269673 -0.47 0.641 -.0654395 .0402706Common

Value1.463747 2.504474 0.58 0.559 -3.444932 6.372426

IndependentValue

8.300579 2.616179 3.17 0.002 3.172963 13.42819

Previous Profit

-.0192508 .0335655 -0.57 0.566 -.085038 .0465364

_cons -5.925656 2.289073 -2.59 0.010 -10.41216 -1.439156

Logit Model: Disclosure Choice as a Function of the Components Value

Disclosure Choice

Coef. Std. Err. z P>z [95% Conf. Interval]

Correlation -.0125845 .0269673 -0.47 0.641 -.0654395 .0402706Common

Value1.463747 2.504474 0.58 0.559 -3.444932 6.372426

IndependentValue

8.300579 2.616179 3.17 0.002 3.172963 13.42819

Previous Profit

-.0192508 .0335655 -0.57 0.566 -.085038 .0465364

_cons -5.925656 2.289073 -2.59 0.010 -10.41216 -1.439156

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