Using Environmental Using Environmental Emissions Permit Prices to Emissions Permit Prices to

Raise ElectricityRaise ElectricityPrices: Evidence from the Prices: Evidence from the

California Electricity MarketCalifornia Electricity MarketJonathan T. Kolstad and Frank A. Wolak Jonathan T. Kolstad and Frank A. Wolak

Department of Economics Department of Economics Stanford UniversityStanford University

Stanford, CA 94305-6072Stanford, CA 94305-6072wolak@zia.stanford.eduwolak@zia.stanford.edu

http://www.stanford.edu/~wolakhttp://www.stanford.edu/~wolak

Outline of TalkOutline of Talk South Coast Air Quality Management District South Coast Air Quality Management District

(SCAQMD) (SCAQMD) Regional Clear Air Incentive Market (RECLAIM) for NOx Regional Clear Air Incentive Market (RECLAIM) for NOx

emissions permitsemissions permits Compare market Performance before and after electricity Compare market Performance before and after electricity

industry restructuringindustry restructuring How to Use NOx Emissions Permit Prices to Raise How to Use NOx Emissions Permit Prices to Raise

Electricity Prices in California MarketElectricity Prices in California Market Three lines of empirical evidence in favor of this viewThree lines of empirical evidence in favor of this view

Prices paid for NOx permits as function of type of market Prices paid for NOx permits as function of type of market participant in SCAQMD marketparticipant in SCAQMD market

Operating behavior of instate fossil fuel generation units as Operating behavior of instate fossil fuel generation units as a function of plant location, ownership and NOx emissions a function of plant location, ownership and NOx emissions raterate

Relationship between implied marginal cost from profit-Relationship between implied marginal cost from profit-maximizing bidding behavior and actual fuel costs and NOx maximizing bidding behavior and actual fuel costs and NOx emissions costsemissions costs

NOx market reforms to enhance competitiveness of NOx market reforms to enhance competitiveness of electricity marketelectricity market

South Coast Air Quality South Coast Air Quality Management District Management District

(SCAQMD)(SCAQMD)

RECLAIM MarketRECLAIM Market Began operation in 1994Began operation in 1994

Started with 390 market participantsStarted with 390 market participants Currently 364 market participantsCurrently 364 market participants

Each actor receives an allocation of RECLAIM Trading Credits (RTCs) Each actor receives an allocation of RECLAIM Trading Credits (RTCs) each yeareach year

One RTC allows owner to emit one pound of NOx emissions during that yearOne RTC allows owner to emit one pound of NOx emissions during that year RTC allocations initially set very conservativelyRTC allocations initially set very conservatively

Above emissions levels that existed at the timeAbove emissions levels that existed at the time Each year, two vintages of permits are issued Each year, two vintages of permits are issued

Cycle 1– January 1 to December 31 of vintage yearCycle 1– January 1 to December 31 of vintage year Cycle 2—July 1 of vintage year to June 30 of following yearCycle 2—July 1 of vintage year to June 30 of following year Either vintage can be used to rationalize NOx emissions during period permit Either vintage can be used to rationalize NOx emissions during period permit

is validis valid Firms are randomly assigned to the two emissions cyclesFirms are randomly assigned to the two emissions cycles

Firm must rationalize its emissions with qualifying RTCs that it holds within Firm must rationalize its emissions with qualifying RTCs that it holds within three months of the end of its permit cyclethree months of the end of its permit cycle

Aggregate RECLAIM RTC allocations were to be reduced at 8.3% relative Aggregate RECLAIM RTC allocations were to be reduced at 8.3% relative initial allocations until 2003initial allocations until 2003

Larger emissions reductions were demanded from electricity generating Larger emissions reductions were demanded from electricity generating facilities and oil refineriesfacilities and oil refineries

Firms can purchase RTCs through bilateral negotiations from other Firms can purchase RTCs through bilateral negotiations from other RECLAIM market participants to rationalize their actual emissionsRECLAIM market participants to rationalize their actual emissions

While maintaining market-wide compliance with SCAQMD NOx emissions While maintaining market-wide compliance with SCAQMD NOx emissions limitslimits

RTC Allocations and NOx RTC Allocations and NOx EmissionsEmissions

0

5,000

10,000

15,000

20,000

25,000

30,000

35,000

40,000

45,000

1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010

Compliance Year

NO

x E

mis

sio

ns

(to

ns/

yr)

Total RTC Supply

Reported Emissions

Source: Coy et al. “SCAQMD White Paper on Stabilization of NOx RTC Prices,” 2001.

Mean RTC Prices Over TimeMean RTC Prices Over Time

Mean RTC Price by Vintage

0

5

10

15

20

25

30

35

1994 1995 1996 1997 1998 1999 2000 2001 2002

Transactions Year

Me

an

Pri

ce

($

/lb.)

2000

2001

Standard Deviation of RTC Standard Deviation of RTC Prices Over TimePrices Over Time

Standard Deviation of RTC Price by Vintage

0

2

4

6

8

10

12

14

16

18

20

1994 1995 1996 1997 1998 1999 2000 2001 2002

Transactions Year

Std

. Dev

.

2000

2001

Average Transactions Average Transactions Volume Volume

Average Transaction Voume by Vintage

0

20000

40000

60000

80000

100000

120000

140000

160000

1994 1995 1996 1997 1998 1999 2000 2001 2002

Transaction Year

RT

Cs

Per

Tra

nsa

ctio

n (

lbs

of

No

x)

2001

2000

Number of Transactions Number of Transactions Number of Transactions by Vintage

0

50

100

150

200

250

300

350

1994 1995 1996 1997 1998 1999 2000 2001 2002

Transaction Year

Tota

l Num

ber

of T

rans

actio

ns

2001

2000

Summary of FiguresSummary of Figures For 2000 and 2001 vintage RTCsFor 2000 and 2001 vintage RTCs

Dramatic increase in average transactions prices in Dramatic increase in average transactions prices in 2000 and 20012000 and 2001

Enormous increase in standard deviation of Enormous increase in standard deviation of transactions prices in 2000 and 2001transactions prices in 2000 and 2001

Reduction in average transactions volume in 2000 and Reduction in average transactions volume in 2000 and 2001 2001

Substantial increase in number of transactions in 2000 Substantial increase in number of transactions in 2000 and 2001and 2001

Many small RTC purchases at very high prices Many small RTC purchases at very high prices (and low prices) in 2000 and 2001(and low prices) in 2000 and 2001 Figures are consistent with use of RTCs permits prices Figures are consistent with use of RTCs permits prices

to raise electricity pricesto raise electricity prices

Additional Profits to Units Without NOx

Costs

PricePAct

PNo NOx

QuantityQd

Supply without NOx

Costs

Supply with NOx Costs

Additional Profits to Unit with lower NOx emissions rate

Using NOx Permits To Raise Electricity Using NOx Permits To Raise Electricity PricesPrices

Two Benefits from Raising NOx Two Benefits from Raising NOx Emissions Permit PricesEmissions Permit Prices

Generation units that do not require NOx Generation units that do not require NOx emissions permits will earn higher profits emissions permits will earn higher profits If market price set by bid from a unit If market price set by bid from a unit

requiring NOx permitsrequiring NOx permits Generation units that require NOx Generation units that require NOx

emissions permits will earn higher profitsemissions permits will earn higher profits If market price set by bid from a unit If market price set by bid from a unit

requiring NOx permits with a higher NOx requiring NOx permits with a higher NOx emission rateemission rate

Did Generation Unit Owners Did Generation Unit Owners Requiring NOx Permit Pay More For Requiring NOx Permit Pay More For

Permits?Permits? All RTC transactions of vintages 1997 to All RTC transactions of vintages 1997 to

2000 that occurred before June 1, 20012000 that occurred before June 1, 2001 ln(P) = transaction price in $/lb of NOxln(P) = transaction price in $/lb of NOx Wholesale = 1 if parent company is wholesalerWholesale = 1 if parent company is wholesaler Utility = 1 if parent company is utilityUtility = 1 if parent company is utility AQMD = 1 if parent company owns units only in AQMD = 1 if parent company owns units only in

SCAQMDSCAQMD InOut = 1 if parent owns units in and out of InOut = 1 if parent owns units in and out of

SCAQMDSCAQMD Out = 1 if parent company owns units only Out = 1 if parent company owns units only

outside of SCAQMDoutside of SCAQMD Vintage indicator variables and transaction year Vintage indicator variables and transaction year

indicator variablesindicator variables

Owners With Units in SCAQMD Paid Owners With Units in SCAQMD Paid MoreMore

Results in Tables 1 and 2 show thatResults in Tables 1 and 2 show that InOut wholesale suppliers paid approximatelyInOut wholesale suppliers paid approximately

20%-30% more for vintage 2000 RTCs20%-30% more for vintage 2000 RTCs 25%-30% more for vintage 2001 RTCs25%-30% more for vintage 2001 RTCs Estimates for 2000 and 2001 vintages very precise in Estimates for 2000 and 2001 vintages very precise in

both Tables 1 and 2both Tables 1 and 2 AMQD wholesale suppliers paid approximatelyAMQD wholesale suppliers paid approximately

11%-17% more for vintage 2000 RTCs11%-17% more for vintage 2000 RTCs 12%-30% more for vintage 2001 RTC12%-30% more for vintage 2001 RTC Estimate for vintage 2000 results in Table 1 preciseEstimate for vintage 2000 results in Table 1 precise

Table 1 controls for vintage fixed-effects Table 1 controls for vintage fixed-effects Table 2 adds transaction year fixed-effectsTable 2 adds transaction year fixed-effects

Were Plants Operated in Manner Were Plants Operated in Manner Consistent with NOx Permit Costs?Consistent with NOx Permit Costs?

For period June 1, 1998 to December 1, 2000, For period June 1, 1998 to December 1, 2000, compare actual operation to least-cost compare actual operation to least-cost operationoperation

OUT_ACTOUT_ACThjhj = hourly output of unit j in hour h = hourly output of unit j in hour h OUT_BBWOUT_BBWhjhj = predicted hourly output of unit = predicted hourly output of unit

j in hour h from Borenstein, Bushnell and j in hour h from Borenstein, Bushnell and Wolak (BBW) competitive benchmark pricingWolak (BBW) competitive benchmark pricing Computes generation unit-level marginal cost as Computes generation unit-level marginal cost as

sum of fuel costs, variable operating and sum of fuel costs, variable operating and maintenance costs and NOx emissions costsmaintenance costs and NOx emissions costs

yyhjhj = OUT_ACT = OUT_ACThj hj - OUT_BBW- OUT_BBWhjhj Dependent variable in regressionDependent variable in regression

Were Plants Operated in Manner Were Plants Operated in Manner Consistent with NOx Permit Costs?Consistent with NOx Permit Costs? InGenInGenhjhj = 1 if unit owned by supplier with = 1 if unit owned by supplier with

units in SCAQMD onlyunits in SCAQMD only InOutGenInOutGenhjhj = 1 if unit owned by supplier = 1 if unit owned by supplier

with units in and out of SCAQMD and unit is with units in and out of SCAQMD and unit is located in SCAQMDlocated in SCAQMD

OutGenOutGenhjhj = 1 if unit owned by supplier with = 1 if unit owned by supplier with units in and out of SCAQMD and unit is units in and out of SCAQMD and unit is located out of SCAQMDlocated out of SCAQMD

NOxPriceNOxPricehh = NOx emissions price for hour h = NOx emissions price for hour h NOxRateNOxRatejj = NOx emission rate for unit j = NOx emission rate for unit j Year and Month indicator variablesYear and Month indicator variables

Plants in SCAQMD with Higher NOx Plants in SCAQMD with Higher NOx Permit Costs Operated More Permit Costs Operated More

IntensivelyIntensively Table 3 shows InGenTable 3 shows InGenhj, hj, InOutGenInOutGenhjhj and OutGen and OutGenhjhj units units

operated more intensively relative to output of BBW operated more intensively relative to output of BBW benchmark pricing in 2000benchmark pricing in 2000

Table 4 shows that higher Table 4 shows that higher InGen*NOxRate*NOxPrice and InGen*NOxRate*NOxPrice and InOutGen*NOxRate*NOxPrice predicts more InOutGen*NOxRate*NOxPrice predicts more intensive operation of unit relative to BBW intensive operation of unit relative to BBW benchmark pricing level in 2000benchmark pricing level in 2000

Even though BBW benchmark pricing algorithm Even though BBW benchmark pricing algorithm accounts for NOxRate*NOxPrice in unit-level accounts for NOxRate*NOxPrice in unit-level marginal cost, these units were operated more marginal cost, these units were operated more intensivelyintensively Consistent with logic that unit owners did not perceive NOx Consistent with logic that unit owners did not perceive NOx

costs in same manner as fuel costscosts in same manner as fuel costs

Did Suppliers Bid as if NOx Emissions Did Suppliers Bid as if NOx Emissions Costs Were Part of Marginal Costs?Costs Were Part of Marginal Costs?

Wolak (2003) “Measuring Unilateral Market Power Wolak (2003) “Measuring Unilateral Market Power in Wholesale Electricity Markets: The California in Wholesale Electricity Markets: The California Market 1998 to 2000,” (on web-site) shows Market 1998 to 2000,” (on web-site) shows expected that profit-maximizing bidding into expected that profit-maximizing bidding into CAISO real-time market should cause following CAISO real-time market should cause following equation to hold each hour h for each supplier k:equation to hold each hour h for each supplier k:

(Ph – MChk)/Ph = -1/εhk

PPhh= real-time price for hour h= real-time price for hour h

MCMChkhk = marginal cost of higher cost unit = marginal cost of higher cost unit operating in hour h owned by supplier koperating in hour h owned by supplier k

εhk = elasticity of residual demand curve facing supplier k during hour h

p2

MR 2

MR 1

S(p)

MC(q) DR 2(p)

DR 1(p)

q2 q1

p1

Price

Quantity

Bidding to Maximize Expected Bidding to Maximize Expected ProfitsProfits

Recovering Implied MCRecovering Implied MC Compute hourly value implied marginal cost asCompute hourly value implied marginal cost as

IMChk = Ph(1 + 1/εhk)

Wolak (2003) discusses computation of Wolak (2003) discusses computation of εhk from from

bids into CAISO’s real-time marketbids into CAISO’s real-time market IMCIMChkhk =marginal cost implied by expected =marginal cost implied by expected

profit-maximizing bidding behaviorprofit-maximizing bidding behavior MCMChkhk based on input costs = based on input costs =

Gas_PriceGas_Pricehh*Heat_Rate*Heat_Ratekk + NOxRate + NOxRatekk*NOxPrice*NOxPricehh + + Variable Operating and Maintence CostsVariable Operating and Maintence Costskk

Inferring Costs from Inferring Costs from BehaviorBehavior

For five large fossil fuel suppliers in California For five large fossil fuel suppliers in California AES/Williams, Duke, Dynegy, Reliant and MirantAES/Williams, Duke, Dynegy, Reliant and Mirant Only three of these suppliers have units in SCAQMDOnly three of these suppliers have units in SCAQMD

For period June 1 to September 30 for 1998, 1999 For period June 1 to September 30 for 1998, 1999 and 2000 (same as Wolak (2003)) regress IMCand 2000 (same as Wolak (2003)) regress IMChkhk on on Fuel costs of highest cost unit operating in hour h owned Fuel costs of highest cost unit operating in hour h owned

by firm kby firm k NOx emissions costs of highest cost unit operating in hour NOx emissions costs of highest cost unit operating in hour

h owned by supplier kh owned by supplier k Supplier fixed-effectsSupplier fixed-effects Daily natural gas prices and heat rates from BBW (2002)Daily natural gas prices and heat rates from BBW (2002) NOx emissions rates and NOx prices from BBW (2002)NOx emissions rates and NOx prices from BBW (2002) BBW marginal cost estimates and actual unit-level output BBW marginal cost estimates and actual unit-level output

during hour used to determine highest cost unit operatingduring hour used to determine highest cost unit operating Under null hypothesis that suppliers behave as if fuel Under null hypothesis that suppliers behave as if fuel

costs and NOx emission costs enter marginal cost costs and NOx emission costs enter marginal cost Coefficients on both of these variables for all firms should Coefficients on both of these variables for all firms should

equal to oneequal to one

Suppliers Do Not Behave as if NOx Suppliers Do Not Behave as if NOx Costs Enter Coefficient of 1 in MCCosts Enter Coefficient of 1 in MChkhk

Tables 6 and 7 shows that Tables 6 and 7 shows that Coefficients on fuel costs are not jointly Coefficients on fuel costs are not jointly

statistically significantly different from one statistically significantly different from one for all suppliersfor all suppliers

Coefficients on NOx emissions costs are Coefficients on NOx emissions costs are jointly statistically significantly less than one jointly statistically significantly less than one for all suppliersfor all suppliers

Estimates that assume same coefficients Estimates that assume same coefficients for each variable for all firms findsfor each variable for all firms finds Coefficient on fuel cost has point estimate of Coefficient on fuel cost has point estimate of

0.95, and is not statistically significantly 0.95, and is not statistically significantly different from 1different from 1

Coefficient on NOx emissions cost has point Coefficient on NOx emissions cost has point estimate of 0.45, and is statistically estimate of 0.45, and is statistically significantly less than 1significantly less than 1

Conclusions from Empirical Conclusions from Empirical AnalysisAnalysis

Suppliers with units located in SCAQMD Suppliers with units located in SCAQMD paid substantially more for same permits paid substantially more for same permits than other RECLAIM market participantsthan other RECLAIM market participants

Suppliers with units located in SCAQMD Suppliers with units located in SCAQMD operated units with high emissions rates operated units with high emissions rates more intensively than would be the case more intensively than would be the case under competitive benchmark pricing under competitive benchmark pricing dispatchdispatch

Suppliers with units located in SCAQMD Suppliers with units located in SCAQMD did not behave as if NOx emission costs did not behave as if NOx emission costs entered marginal costs in same manner as entered marginal costs in same manner as fuel costsfuel costs Marginal cost implied by expected profit-Marginal cost implied by expected profit-

maximizing behavior was much less sensitive maximizing behavior was much less sensitive to NOx emissions costs than fuel coststo NOx emissions costs than fuel costs

Conclusions from Empirical Conclusions from Empirical AnalysisAnalysis

Design of emissions market must be consistent Design of emissions market must be consistent with design of energy market or emissions market with design of energy market or emissions market can be used to enhance market power in can be used to enhance market power in electricity marketelectricity market

Decision of Federal Energy Regulatory Commission Decision of Federal Energy Regulatory Commission (FERC) to allow suppliers to pass-through prices of (FERC) to allow suppliers to pass-through prices of RTC permits (purchased in bilateral market) in bid RTC permits (purchased in bilateral market) in bid prices in CAISO real-time market appears to have prices in CAISO real-time market appears to have allowed suppliers with units located in SQAQMD allowed suppliers with units located in SQAQMD appear to raise wholesale electricity pricesappear to raise wholesale electricity prices

Events of 2000 and 2001 in RECLAIM market argue Events of 2000 and 2001 in RECLAIM market argue in favor of periodic trading of emissions permits in favor of periodic trading of emissions permits through anonymous multi-unit auction mechanism through anonymous multi-unit auction mechanism rather than through bilateral negotiationrather than through bilateral negotiation