Assessing the Strength andEffectiveness of Renewable ElectricityFeed-in TariffsJoe Indvik, ICF InternationalSteffen Jenner...
Background Renewable electricity (RES-E) is rapidlyexpanding in magnitude and geographic scope Literature generally clai...
RES-E Policy LeversPrice QuantityInvestmentInvestment subsidiesTax creditsLow interest/ soft loansTendering systems for in...
 Price-based RES-E production incentive Funded by state budget and/or electricity priceincrease Helps renewables achiev...
Years of RES-E policy enactment in Europe:Feed-in tariffQuotaBECZ BGHU EE IEIT DK GR FR LT NL MT RO BGDE IT LU ES AT PT GB...
FIT Policies and RES-E Capacity0200040006000800010000120001400005101520251998 1999 2000 2001 2002 2003 2004 2005 2006 2007...
7Have feed-in tariffs significantlyincreased onshore wind power andsolar PV deployment in Europe?
The Traditional ApproachCapacity Added = β1(Policy Dummy) + β2(Some Controls)Inevitably, β1 is positiveand highly signific...
Problem 1: Omitted Variables Bias9
Establishing CausalityPolicyCapacityGrowthPoliticalEnvironmentNaturalResourcesSocio-EconomicsElectricityPricesOtherPolicie...
Our Modelln(Added Capacityist) = β0 + β1SFITist + β2INCRQMTSHAREst+ βxZist + βyWist + μs + uistIncremental ShareMeasure of...
Problem 2: Policy Heterogeneity12
1/0Binary Variable: The kingof renewable energy policyanalysis thus far.DurationMagnitudeElectricity price Risk anduncerta...
SFIT: A more nuanced approachContract DurationTariff AmountFIT contract length(years)Size of FIT contractestablished in ye...
SFIT: A more nuanced approachExpected profit overthe lifetime of capacityinstalled under a FITcontractExpected generationc...
Results of Cross-Sectional RegressionsDependent Variable: Added RES-E Capacity (ln)Solar Photovoltaic Onshore Wind(1) (2) ...
Results of Fixed-Effects RegressionsDependent Variable: Added RES-E Capacity (ln)Solar Photovoltaic Onshore Wind(1) (2) (3...
Results of Fixed-Effects RegressionsDependent Variable: Added RES-E Capacity (ln)Solar Photovoltaic Onshore Wind(1) (2) (3...
Results of Fixed-Effects RegressionsDependent Variable: Added RES-E Capacity (ln)Solar Photovoltaic Onshore Wind(1) (2) (3...
If you take one thing away from this paper, let it be...FIT VariableFixed Effects?Model 1:Cross-sectional ApproachModel 2:...
Conclusion Feed-in tariffs have driven solar PV and onshorewind power development in Europe since 1998. Controlling for ...
Thank you! Questions?Joe Indvik, ICF Internationaljoe.indvik@gmail.com515-230-4665Steffen Jenner, Harvard Universitysteffe...
Data SourcesCapacity: Eurostat and the UN Energy Statistics DatabasePolicy: GreenX (University of Vienna) and supplemental...
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Assessing the Strength and Effectiveness of Renewable Electricity Feed-In Tariffs

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Presented at U.S. Association for Energy Economics conference in Washington, DC in October 2011.

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  • IntroPublic/Private/Academic collaborationTime zone synergies
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  • - Won’t discuss data in presentation but we are happy to discuss after
  • - Will not discuss the other variables but have some interesting things to say
  • “Goldilocks” diagram Professor Carley and Professor Shrimali
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  • Assessing the Strength and Effectiveness of Renewable Electricity Feed-In Tariffs

    1. 1. Assessing the Strength andEffectiveness of Renewable ElectricityFeed-in TariffsJoe Indvik, ICF InternationalSteffen Jenner, Harvard UniversityFelix Groba, DIW BerlinUSAEE/IAEE 2011 North American Conference:"Redefining the Energy Economy: Changing Roles ofIndustry, Government and Research"1
    2. 2. Background Renewable electricity (RES-E) is rapidlyexpanding in magnitude and geographic scope Literature generally claims that governmentincentives are justified by... Climate and pollution externalities Barriers to entry Energy security concerns
    3. 3. RES-E Policy LeversPrice QuantityInvestmentInvestment subsidiesTax creditsLow interest/ soft loansTendering systems for investment grantsGeneration Feed-in tariffsRenewable portfolio standards (RPS)Tendering systems for long term contracts3
    4. 4.  Price-based RES-E production incentive Funded by state budget and/or electricity priceincrease Helps renewables achieve grid parityEverything you need to know about FIT’sin 60 secondsRES-EGeneratorGridElectricity PriceState budgetTariffContract€4
    5. 5. Years of RES-E policy enactment in Europe:Feed-in tariffQuotaBECZ BGHU EE IEIT DK GR FR LT NL MT RO BGDE IT LU ES AT PT GB SE SI SK CY1990 1992 1993 1994 1998 2001 2002 2003 2004 2005 20065
    6. 6. FIT Policies and RES-E Capacity0200040006000800010000120001400005101520251998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008FIT policiesenactedAnnual RES-Ecapacity added** Solar PV and onshore windCorrelation = 0.87 Causation?PoliciesMegawatts6
    7. 7. 7Have feed-in tariffs significantlyincreased onshore wind power andsolar PV deployment in Europe?
    8. 8. The Traditional ApproachCapacity Added = β1(Policy Dummy) + β2(Some Controls)Inevitably, β1 is positiveand highly significant.So the policyis effective!Except for...Two Problems1Policy Heterogeneity“Not all FIT’s are created equal.”Omitted Variables Bias“What you don’t see can hurt you.”2Linear OLS pooled cross-section regression:8
    9. 9. Problem 1: Omitted Variables Bias9
    10. 10. Establishing CausalityPolicyCapacityGrowthPoliticalEnvironmentNaturalResourcesSocio-EconomicsElectricityPricesOtherPoliciesRegion TransmissionUnobservedState TraitsBroaderTrendsBias10
    11. 11. Our Modelln(Added Capacityist) = β0 + β1SFITist + β2INCRQMTSHAREst+ βxZist + βyWist + μs + uistIncremental ShareMeasure of quotastringency developed byYin and Powers (2009)Policy ControlsSuite of binary policycontrol variables forother RES-E policiesSocio-Economic ControlsSuite of socioeconomiccontrolsCountry Fixed EffectsControls for countrycharacteristics that donot change over timeAdded CapacityAdditional RES-Enameplate generationcapacity added each yearfor energy technology i, in country s, in year t.FIT StrengthOur new measure of thegeneration incentiveprovided by a FIT11
    12. 12. Problem 2: Policy Heterogeneity12
    13. 13. 1/0Binary Variable: The kingof renewable energy policyanalysis thus far.DurationMagnitudeElectricity price Risk anduncertaintyBinary variables do not accurately represent the trueproduction incentive created by a policyBuy what does it neglect?Production cost13
    14. 14. SFIT: A more nuanced approachContract DurationTariff AmountFIT contract length(years)Size of FIT contractestablished in year t(Eurocents/kWh)Electricity PriceWholesale marketprice of electricity(Eurocents/kWh)Capacity LifetimeLifetime of PV or windcapacity installed in year t(years)Generation CostAverage lifetime cost ofelectricity production(Eurocents/kWh)14for energy technology i, in country s, in year t.
    15. 15. SFIT: A more nuanced approachExpected profit overthe lifetime of capacityinstalled under a FITcontractExpected generationcost over the lifetimeof capacity= ROI15for energy technology i, in country s, in year t.
    16. 16. Results of Cross-Sectional RegressionsDependent Variable: Added RES-E Capacity (ln)Solar Photovoltaic Onshore Wind(1) (2) (3) (4)Binary FIT 0.654***(0.184)1.011***(0.215)SFIT 1.025***(0.128)0.412***(0.151)Binary Tax or Grant -0.109(0.186)0.179(0.167)0.179(0.325)-0.305(0.337)Binary Tendering Scheme -0.567**(0.239)0.131(0.210)0.235(0.399)0.138(0.409)INCRQMTSHARE, ln -8.402**(3.978)-1.079(3.051)5.154(4.745)-3.121(4.329)GDP per capita, ln 0.990**(0.450)-0.165(0.341)3.672***(0.376)3.847***(0.377)Area, ln 0.509***(0.101)0.387***(0.071)1.086***(0.094)1.129***(0.088)Net import ratio, ln -0.314*(0.186)0.018(0.167)0.005(0.245)0.002(0.262)Energy cons. per capita, ln 0.076(0.429)0.305(0.373)-2.011***(0.510)-1.780***(0.509)Nuclear share, ln -0.322(0.524)-0.008(0.444)-0.728(0.795)-1.224(0.759)Oil share, ln -20.501(15.250)-19.261*(10.868)-22.747*(11.842)-12.115(11.626)Natural gas share, ln 1.160(1.111)1.259(0.878)1.760*(1.067)1.020(1.024)Coal share, ln 0.755(0.672)0.671(0.459)2.614***(0.592)2.957***(0.599)EU 2001 binary -0.121(0.226)0.114(0.175)-0.177(0.302)-0.144(0.307)N 253 253 264 264R2 0.328 0.575 0.665 0.654PolicyVariablesSocio-EconomicControlsFuel MixVariablesFeed-in tariffs appear todrive RES-E development.Cannot be interpreted ascausal because of OVB*** <1% significance, ** <5% significance, * <10% significanceHow do the results changewhen we control for fixedcountry characteristics?
    17. 17. Results of Fixed-Effects RegressionsDependent Variable: Added RES-E Capacity (ln)Solar Photovoltaic Onshore Wind(1) (2) (3) (4)Binary FIT 0.068(0.197)0.758***(0.280)SFIT 0.743***(0.106)0.262*(0.156)Binary Tax or Grant -0.327(0.380)-0.411(0.342)0.052(0.531)0.037(0.541)Binary Tendering Scheme 0.052(0.286)-0.047(0.258)-0.946**(0.406)-1.090***(0.407)INCRQMTSHARE, ln 4.600(5.584)1.544(5.062)-3.500(7.864)-5.754(7.928)GDP per capita, ln 0.689(0.699)-0.073(0.630)3.187***(0.912)2.626**(1.130)Area, ln(dropped) (dropped) (dropped) (dropped)Net import ratio, ln -0.145(0.252)-0.019(0.229)-0.117(0.350)-0.152(0.353)Energy cons. per capita, ln -1.038(1.590)-1.550(1.427)-0.809(2.137)0.937(2.142)Nuclear share, ln -1.929(1.534)-2.517*(1.386)-0.281(2.147)0.355(2.163)Oil share, ln 98.175***(32.774)76.960***(29.643)11.882(46.330)13.754(46.867)Natural gas share, ln 4.235***(1.142)2.391**(1.060)2.162(1.621)1.257(1.614)Coal share, ln -10.249***(2.477)-6.480***(2.288)3.427(3.386)3.518(3.511)EU 2001 binary -0.064(0.192)0.080(0.174)-0.212(0.267)-0.220(0.270)N Yes Yes Yes YesR2 253 253 264 264*** <1% significance, ** <5% significance, * <10% significanceCoefficients on FIT variables areuniversally lowerUnobserved countrycharacteristics positively bias thepooled cross-section results17
    18. 18. Results of Fixed-Effects RegressionsDependent Variable: Added RES-E Capacity (ln)Solar Photovoltaic Onshore Wind(1) (2) (3) (4)Binary FIT 0.068(0.197)0.758***(0.280)SFIT 0.743***(0.106)0.262*(0.156)Binary Tax or Grant -0.327(0.380)-0.411(0.342)0.052(0.531)0.037(0.541)Binary Tendering Scheme 0.052(0.286)-0.047(0.258)-0.946**(0.406)-1.090***(0.407)INCRQMTSHARE, ln 4.600(5.584)1.544(5.062)-3.500(7.864)-5.754(7.928)GDP per capita, ln 0.689(0.699)-0.073(0.630)3.187***(0.912)2.626**(1.130)Area, ln(dropped) (dropped) (dropped) (dropped)Net import ratio, ln -0.145(0.252)-0.019(0.229)-0.117(0.350)-0.152(0.353)Energy cons. per capita, ln -1.038(1.590)-1.550(1.427)-0.809(2.137)0.937(2.142)Nuclear share, ln -1.929(1.534)-2.517*(1.386)-0.281(2.147)0.355(2.163)Oil share, ln 98.175***(32.774)76.960***(29.643)11.882(46.330)13.754(46.867)Natural gas share, ln 4.235***(1.142)2.391**(1.060)2.162(1.621)1.257(1.614)Coal share, ln -10.249***(2.477)-6.480***(2.288)3.427(3.386)3.518(3.511)EU 2001 binary -0.064(0.192)0.080(0.174)-0.212(0.267)-0.220(0.270)N Yes Yes Yes YesR2 253 253 264 264*** <1% significance, ** <5% significance, * <10% significanceFor a 10 percentage point increase in ROIprovided by a FIT, countries will install• 7.4% more solar PV capacity per year• 2.6% more onshore wind capacity per yearEven when innate country traitsare controlled for, FIT policieshave driven RES-E developmentsince 199818
    19. 19. Results of Fixed-Effects RegressionsDependent Variable: Added RES-E Capacity (ln)Solar Photovoltaic Onshore Wind(1) (2) (3) (4)Binary FIT 0.068(0.197)0.758***(0.280)SFIT 0.743***(0.106)0.262*(0.156)Binary Tax or Grant -0.327(0.380)-0.411(0.342)0.052(0.531)0.037(0.541)Binary Tendering Scheme 0.052(0.286)-0.047(0.258)-0.946**(0.406)-1.090***(0.407)INCRQMTSHARE, ln 4.600(5.584)1.544(5.062)-3.500(7.864)-5.754(7.928)GDP per capita, ln 0.689(0.699)-0.073(0.630)3.187***(0.912)2.626**(1.130)Area, ln(dropped) (dropped) (dropped) (dropped)Net import ratio, ln -0.145(0.252)-0.019(0.229)-0.117(0.350)-0.152(0.353)Energy cons. per capita, ln -1.038(1.590)-1.550(1.427)-0.809(2.137)0.937(2.142)Nuclear share, ln -1.929(1.534)-2.517*(1.386)-0.281(2.147)0.355(2.163)Oil share, ln 98.175***(32.774)76.960***(29.643)11.882(46.330)13.754(46.867)Natural gas share, ln 4.235***(1.142)2.391**(1.060)2.162(1.621)1.257(1.614)Coal share, ln -10.249***(2.477)-6.480***(2.288)3.427(3.386)3.518(3.511)EU 2001 binary -0.064(0.192)0.080(0.174)-0.212(0.267)-0.220(0.270)N Yes Yes Yes YesR2 253 253 264 264*** <1% significance, ** <5% significance, * <10% significanceNo statistically significantrelationship between FITenactment and solar PVdevelopment once countrycharacteristics are controlled forHighly significant when SFIT isused instead of binaryBinary variables obscure the truerelationship between FIT policiesand solar PV development19
    20. 20. If you take one thing away from this paper, let it be...FIT VariableFixed Effects?Model 1:Cross-sectional ApproachModel 2:Fixed Effects ApproachModel 3:Nuanced ApproachDo FITs work?Binary Binary SFITYesYesVariesTooWellNo YesOverstateseffectivenessUnderstateseffectivenessJust rightNuanced indicators and smart controls are key foraccuracy and consistency in energy policy analysis 20
    21. 21. Conclusion Feed-in tariffs have driven solar PV and onshorewind power development in Europe since 1998. Controlling for policy design elements andcountry characteristics is crucial. Policy design matters more than the enactmentof a policy alone!21
    22. 22. Thank you! Questions?Joe Indvik, ICF Internationaljoe.indvik@gmail.com515-230-4665Steffen Jenner, Harvard Universitysteffen.jenner@googlemail.com857-756-0361Felix Groba, DIW Berlinfgroba@diw.de+49-30-89789-68122
    23. 23. Data SourcesCapacity: Eurostat and the UN Energy Statistics DatabasePolicy: GreenX (University of Vienna) and supplemental sourcesCost: GreenX (University of Vienna)• 2006 – 2009 actual• 2010 – 2020 projected• 1998 – 2005 linearly extrapolated

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