2015
DOI: 10.5547/2160-5890.4.2.gshr
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Evaluating Renewable Portfolio Standards for In-State Renewable Deployment: Accounting for Policy Heterogeneity

Abstract: Yin and Powers (2010). Further, there is an emerging series of studies focusing on other regions. Marques et al. (2010; 2011) and Groba et al. (2011) study the effect of renewable energy policy in the EU. Salim and Rafiq (2012) conduct a similar study for several major emerging economies.

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Cited by 25 publications
(15 citation statements)
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“…However, due to limitations on appropriate data availability we measure the effects of these polices in an aggregate sense in terms of policy presence or absence at the state level disregarding state specific policy structure. Previous literature has documented (Dijkgraaf et al 2018;Bowen and Lacombe 2017;Shrimali et al 2015) that heterogeneity of policy specifics across jurisdictions can have a significant effect on estimated effectiveness.…”
Section: Caveatsmentioning
confidence: 99%
“…However, due to limitations on appropriate data availability we measure the effects of these polices in an aggregate sense in terms of policy presence or absence at the state level disregarding state specific policy structure. Previous literature has documented (Dijkgraaf et al 2018;Bowen and Lacombe 2017;Shrimali et al 2015) that heterogeneity of policy specifics across jurisdictions can have a significant effect on estimated effectiveness.…”
Section: Caveatsmentioning
confidence: 99%
“…13. In line with this conclusion, Shrimali et al (2015), who econometrically analyze the effectiveness of RPS policies in the USA, show that modeling of specific RPS design features is essential, as not doing so may lead to misperceptions. (2011a), who compare quantity-driven instruments (like tenders and Tradable Green Certificates (TGCs) based on quotas 10 ) and price-driven instruments (like FITs) in European countries, state that FIT policy instruments are more effective than others in the deployment of less mature technologies, like solar PV technology, because they tend to have low administration costs, are relatively easy to implement and are technology focused.…”
Section: Introductionmentioning
confidence: 85%
“…(Shrimali, Chan, et al, 2015;Yin and Powers 2010). By adjusting the estimates for existing renewable electricity capacity, this measure captures the utilities' need to add new renewable energy generation capacity to their portfolio (Shrimali, Chan, et al, 2015). Specifically, we use the incremental requirement in wind energy generation mandated by an RPS policy.…”
Section: Explanatory Variable: State Renewable Energy Policymentioning
confidence: 99%