Dr. Daniel Matisoff Georgia Institute of Technology Alliance for Research on Corporate Sustainability May 10, 2011

Rational model for voluntary policy Deter mandatory policy / enforcement of mandatory policy (Lyon &

Maxwell, 2003)

Reputational benefits

Market benefits

Gain experience

Mixed evidence for effectiveness (Lyon & Maxwell, 2007; King and Lenox 2000; Khanna 2001; Khanna and Damon 1999)

Boundedly rational model for voluntary policy Firms are boundedly rational (Simon, 1955)

Opportunities for low / no-cost environmental improvements (Porter et al, 1995)

Wide variety in strategies across firms, particularly in power industry (Hoffman 2007; Kolk & Pinske 2005; Matisoff 2010; Welch & Barnum 2009)

Firms implementing voluntary EMS improve environmental outcomes (Potoski & Prakash, 2005; )

Failure to find benefits of voluntary policy - analysis mis-specified? (Lyon & Maxwell, 2007)

Distinguish between different types of voluntary policy

Carbon has different incentives than toxics

Regulated industry is complex

An analysis of private voluntary initiatives – most efforts have focused on public voluntary environmental policy Club good, rather than public good

Compare two very different private policy instruments Cap-and-trade

▪ Set a cap, firms can trade “property rights” to emit CO2 ▪ Case study = Chicago Climate Exchange

▪ Firms voluntarily commit to reducing 1% per year of CO2 collectively ▪ About 90 firms, 1/3 utilities ▪ Firms can trade, buy offsets, etc ▪ Enforced via contract law

Information disclosure ▪ Sunlight is the best disinfectant ▪ What gets measured gets managed ▪ Case study = Carbon Disclosure Project

▪ Firms pressured to disclose carbon emissions; carbon strategy by financial firms ▪ Targets thousands of the world’s largest publicly traded firms ▪ Encourages firms to adopt standardized accounting methodology ▪ Rates firms on transparency of responses

Measures the change in trajectory of treatment group, compared with control group

First difference: Measures difference (CO2 emissions) between treated plants and control group plants

Second difference: Measures difference between time period t, and t-1 (first differences)

Controls for all unobserved static heterogeneity across plants

Converted fuel use (publicly available, at prime mover level) to CO2

DOE 1605b regulations

Eliminated nuclear (renewables & hydro not in dataset either)

1994 – 2007

Matched participants in Chicago Climate Exchange & participants in Carbon Disclosure Project against control group Propensity score matching

▪ Publicly traded; ▪ firm parent size; ▪ age of plant; ▪ plant capacity; ▪ whether restructuring was active in a state; ▪ Green Group membership rates, ▪ firm growth rate, ▪ ECHO data for air violations ▪ % of generation from coal

Controls for observable differences between each group & control

Tested for balancing using Hotelling T2 test (F test that compares the joint means of the matched & unmatched samples)

Regression of first differences (difference-in-difference) Controls for any unobserved differences between

treatment & control

Regression of the changes within each plant

Is there a difference in the trajectory of plant emissions?

Alternative matching techniques

Fixed Effects vs. Difference-in-differences

Full sample vs. matched sample

Model CCX1 CCX2 CDP1 CDP2

Observations 2470 2470 10998 10998

F Statistic 2.65** 84.73 6.16*** 284.84***

R-Squared .004 .5864 .0016 .6629

Program

Participation

- 42,857**

(21,207)

- 11,786

(13,772)

- 8,376

(12,362)

- 1,151

(6,692)

Publicly traded -24,887*

(13,357)

10,261

(9,863)

Active State

Restructuring

48,907**

(21,056)

7,684

(10,745)

-8,859

(8,648)

7,657

(4,941)

∆Firm Revenue

(ln $000,000)

- 8,131

(14,876)

-9,921

(7,662)

1,659

(14,220)

- 4,087

(6,309)

∆State Programs - 8,083**

(3,996)

- 3,275

(2311)

- 11,423***

(2,711)

- 4,148***

(1,539)

∆MWh .672***

(.030)

.756***

(.0205)

Constant 7,968

(14,468)

-8,905

(10,839)

31,689***

(5,313)

- 242

(3193)

1.5

1.6

1.7

1.8

1.9

2

2.1

2.2

2.3

2.4

1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007

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Predicted Plant Emissions From Difference in Differences Model (Matched Samples, demonstrating program intervention)

All Observations

CCX Control

CDP Control

CCX Treatment

CDP Treatment

1.5

1.6

1.7

1.8

1.9

2

2.1

2.2

2.3

2.4

2.5

1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007

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Predicted Emissions, Controlling for MWH, Matched Samples, Demonstrating Program Intervention

All Observations

CCX Control

CDP Control

CCX Treatment

CDP Treatment

0

0.5

1

1.5

2

2.5

3

1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007

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Predicted CO2 emissions by sample, matched samples

All Observations

CCX Control

CDP Control

CCX Treatment

CDP Treatment

0

0.5

1

1.5

2

2.5

3

1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007

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Predicted CO2 emissions (intensity) by matched subsample

All Observations

CCX Control

CDP Control

CCX Treatment

CDP Treatment

CCX

-43,000 metric tons of carbon (2%)

10,000 tons per year, per plant

.5% decrease * 4 years

Reduction in Carbon intensity?

CDP

-8,000 Metric Tons (.8% decrease)

3,000 tons per year, per plant

(0.3% decrease, per year, for 2.7 years)

4x as many plants are involved in CDP

Broader, shallower reductions

Results are unbiased and consistent

CCX has more of an impact, per plant

More statistically significant results, despite nature of trading

Large standard errors

▪ Nature of trading in CCX

▪ Voluntary nature

CCX has been in effect longer

CDP is broader program

Decision to participate indicates change in management decision CDP participation requires that firms have started to pay attention CCX participation signals that attention is being paid to carbon Difficulty of evaluating policy with binary variable

Voluntary program participation correlated with changes

Voluntary programs can reward firms that are proactive Achieve low-cost carbon reductions

Still, problems with transparency of process

CDP works to force transparency CCX very opaque

Voluntary policy may help achieve low-cost environmental improvements

Still a bit of a black box

Source of reductions

Need to learn what’s going on inside firms

Improve upon binary measurement

NSF Dissertation improvement grant (SBE) #0819244

Indianapolis Power & Light

Program CCX CDP

Number of initial plants 966 966

Initial plant-year

observations

13,558 13,558

Matched pairs 95 423

Total plant-year

observations after first

differencing

2,548 10,988

Probit Model CCX CDP

Number of Observations 884 884

LR Chi2 110.63*** 516.17

Pseudo R2 .1833 .4218

Publicly Traded Firm (1=yes) 1.35 (.269)*** †

Firm Level Revenue

(ln$000,000)

-.351 (.067)*** .784 (.051)***

Plant Capacity (MW) .000026 (.0001)** .00005 (.00009)

Year of Construction -.001 (.0032) -.011 (.0028)***

Active State Restructuring

(1=yes)

.559 (.141)*** -.1922 (.1262)

Firm Growth Rate .261 (.063)*** -.598 (.084)***

Green Group Membership

(1990)

.065 (.023)*** .063 (.0207)***

Regulatory Penalties .036 (.017)** -.006 (.019)

Coal % of electricity generation -.280 (.147)* .1297 (.128)

Constant 1.19 (6.24) 14.71 (5.54)***

Variable Full Sample

Mean

Full Sample

Standard

Deviation

Control

Mean

Control

Standard

Deviation

Treatment

Mean

Treatment

Standard

Deviation

Publicly

Traded Firm

(1=yes)

.72 .45 .810 .394 .873 .333

Firm Level

Revenue

(ln$000,000)

8.83 1.19 7.71 1.93 7.98 1.20

Plant

Capacity

(MW)

642 679 543 648 686 686

Year of

Construction

1968 22.00 1963 20.50 1963 20.50

Active State

Restructuring

(1=yes)

.413 .493 .76 .432 .72 .453

% of Coal .432 .484 .303 .445 .347 .469

Avg Growth

Rate

9% 9.4% 9.3% 9.8% 13.7% 20.1%

Average

Penalties

$000

3.55 3.35 6.28 5.22 5.51 3.45

Green Group

membership

7.79 3.02 9.53 2.50 9.53 3.03

Variable Full Sample

Mean

Full Sample

Standard

Deviation

Control

Mean

Control

Standard

Deviation

Treatment

Mean

Treatment

Standard

Deviation

Firm Level

Revenue

(ln$000,000)

8.83 1.19 6.58 1.89 8.81 .808

Plant

Capacity

(MW)

642 679 543 648 686 686

Year of

Construction

1968 22.00 1970 21.74 1964 18.24

Active State

Restructuring

(1=yes)

.413 .493 .385 .487 .501 .500

% of Coal .432 .484 .396 .481 .469 .484

Avg Growth

Rate

9% 9.4% 9% 11.3% 9.2% 7.6%

Average

Penalties

$000

3.55 3.35 3.35 3.28 3.86 3.58

Green Group

membership

7.79 3.02 7.64 3.01 8.03 2.97

1.5

1.7

1.9

2.1

2.3

2.5

2.7

1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007

Predicted Emissions of Sub-Samples (Unmatched, Appendix A, model 1)

Emissions - Non-participants (Tons)

Emissions - CCX

Emissions - CDP

Emissions - CDP & CCX

1.5

1.7

1.9

2.1

2.3

2.5

2.7

2.9

1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007

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Predicted Emissions, Conditional On MWH, Unmatched Subsamples - Appendix A, Model 2

Emissions - Non-participants (Tons)

Emissions - CCX

Emissions - CDP

Emissions - CDP & CCX