Michael Lenox

1. Sustaining Industry Self-Regulation in the Face of Free-Riding Michael Lenox Andy King Associate Professor Fuqua School of Business Duke University Associate Professor Tuck School of Business Dartmouth University March 27th, 2004

2. Industry Self-Regulation Collective attempts by firms to regulate their own behavior • Some examples: • Movie ratings by the MPAA • Accounting standards by FASB • Environmental standards by trade associations • When is industry self-regulation (ISR) feasible? • What are the major impediments to self-regulation? • What institutional structures are needed to make viable?

3. Responsible Care • Established in October 1989 • Sponsored by the American Chemistry Council (formerly CMA) • Members pledge to adopt 10 principles, 6 codes, >100 practices • Participation required for ACC membership • A leading example of environmental self-regulation • Widely cited program • ACC is a strong association with many leading firms • Chemical industry accounts for majority of toxic emissions in U.S.

4. TUESDAY, NOVEMBER 9, 1999 Bush Approach to Pollution: Preference for Self-Policing By JIM YARDLEY Early this summer, with political pressure mounting to address his state's severe air pollution problems, Gov. George W. Bush signed a law he regards as the gold star of his green resume: A program to regulate outdated industrial plants that are among the heaviest polluters in Texas. For Mr. Bush, who began his career in the oil fields of West Texas, the program meant confronting the oil, gas and chemical industries that are among his most generous contributors. With the law, Mr. Bush now boasts that he is the first Texas governor ''to ever have brought industry together and said, 'Get into compliance.' '' What he actually did was a little different, and it offers insight into Mr. Bush's operating style on environmental issues, a style widely praised by business but heavily criticized by environmental groups.

5. Why self-regulate? • Tangible benefits to self-regulation • Avoid or preempt costly government regulation • Limit cross-industry substitution (e.g. boycotts) • Minimize stakeholder ire (e.g. NIMBY problems) • Poor behavior often impacts others within industry • Exxon Valdez spill impacted entire oil shipping industry • UC Bhopal accident had negative impact on all chemical stocks • Rampant information asymmetries with stakeholders

6. The Reputation Commons Differentiated High Ability of Stakeholders to Differentiate Between Firms Common Reputation Problem Mollified Stakeholders Low Low High Threat of Sanctions by Stakeholders Against Firms

7. Challenges to ISR • Adverse Selection & Moral Hazard • Do worse performing firms choose to participate? • Do participating firms perform worse? (King & Lenox. 2000. Industry Self-Regulation Without Sanctions. AMJ.) (Lenox & Nash. 2002. Industry Self-Regulation and Adverse Selection.) • Spillovers & Free Riding • Do spillovers and free-riding occur? • Why do firms participate? (King & Lenox. 2003. Sustaining ISR in the Face of Free-Riding.)

8. Spillovers and Free-riding • Reputation may suffer from the tragedy of the commons • Benefits of improving ‘reputation’ may spillover to others • Commons will be subject to free-riding by firms in industry • Solutions involve structures to sanction non-compliance • Participation is typically voluntary • Anti-trust laws limit sanctions firms may use against competitors • Any fines or similar punishments must be accepted voluntarily • Expulsion from association is only true sanction Can ISR be sustained in the face of spillovers and free-riding?

9. Some Possibilities • Participation in self-regulatory efforts provides an excludable private good • Practices embodied in the standard create value for the firm, i.e., the win-win hypothesis (why collective?) • Membership allows firms to credibly communicate that they are of a superior type, i.e., differentiate • Participants in self-regulatory efforts internalize more of the public (collective) good created

10. Some Possibilities • Unilateral benefits exceed private costs of self-regulation (Olson) • Greater cost borne if program collapses (Segerson & Dawson) • Firms benefit from the presence of self-regulation • Firms would be better off free-riding (if the program continues) • A critical number of firms may band together to prevent the program from collapsing • A knife’s edge equilibrium exists where if one exits, all exit

11. Our Approach • Empirically examine the U.S. chemical industry and the Responsible Care Program • Analyze Tobin’s Q pre and post the advent of Responsible Care across all chemical firms • Consider and empirically address the fact that firms self-select into the Responsible Care program

12. Our Data • Sample • Public U.S. chemical manufacturing firms • Unbalanced panel from 1987-1996 • 198 firms constituting 1473 firm-year observations • 48 participants in Responsible Care (in 1990) • Sources • American Chemistry Council membership lists • Financial data from Standard & Poor’s Compustat Dataset • Environmental data from U.S. EPA’s Toxic Release Inventory (aggregated from facility level)

13. Our Measures

14. Estimates of Q (1987-1996)

15. Our Findings I • Pre-post test of Responsible Care impact on firm performance • Advent of RC corresponded with a simultaneous rise in Tobin’s q (10%) • Impact on non-RC firms was greater than for members (14% vs. 5%) • Member firms benefited from ACC but less so after RC (16% vs. 7.5%) • Thus, the benefits of RC appear to spillover to non-participants at an expense to participants

16. Additional Measures

17. Estimates of RC Membership

19. Our Findings II • Selection model with participation decision • On average, non-RC firms would have been worse off participating • On average, RC firms would have been better off not participating! • 23 out of 48 RC firms were better off by participating • Tended to be the dirty firms in dirty segments • Likely seeking the insurance benefit • 25 out of 48 RC firms would have been better off by not participating • Tended to be the large, visible firms (e.g. Dupont, Dow) • Taking one for the team, a la Segerson & Dawson model?

20. A Speculative Typology Loners (visible, diversified) Leaders (large, visible) Self-regulate Leeches (dirty, low cost) Laggards (small, niche) Do not self-regulate Do not participate Participate in program

21. Leeches? • Participation may serve as a “smoke screen” • Membership may reduce insurance premiums and liability by demonstrating due diligence • Poor performing forms join to gain insurance benefits • Compliance is weakly enforced • Compliance is self-reported, sanctioning is informal • Members are rarely kicked out • Velvet glove (vs. iron fist) approach

22. Previous Findings • Probit model of RC participation decision • Larger, focused, visible firms tended to join RC • Dirty firms in dirty segments tended to join RC • FE model of changes in relative factory emissions • In general, chemical firms reduced emissions since 1990 • On average, RC firms improved their environmental performance less quickly than non-members • Poor performers tended to be the dirty firms in dirty segments

23. Previous Findings • Comparative analysis across four environmental codes • Responsible Care (Chemical Manufacturers) • Sustainable Forestry Initiative (Pulp & Paper) • Encouraging Environmental Excellence (Textiles) • Responsible Distribution (Chemical Distributors) • Probit model of ISR participation decision • Those with third-party verification and who kicked out non-complying members did not suffer from adverse selection.

24. Summary • Benefits of self-regulation spillover to the industry as a whole • Small firms free-ride off the efforts of participants • Large, visible firms tend to join the self-regulatory program and comply to prevent its collapse • Poor performing firms tend to join the self-regulatory program to gain insurance but fail to comply • Monitoring and sanctioning appear to solve the adverse selection and moral hazard problems • Speculation -- solving the above problems may address the free-riding problem by differentiating firms

25. Policy Implications • Suggests both opportunities & limits to industry self-regulation • Public policy may facilitate self-regulation by … • Raising the costs of failure to self-regulate (though is this really self-regulation?) • Rewarding self-regulatory participants (when they get the governance structures right) • Reducing stakeholder information asymmetries (providing unilateral incentives to differentiate) • Perhaps easier to implement the latter in a global context than traditional regulation