Are government policies effective in promoting deployment of renewable electricity resources?

Shrimali, Gireesh; Kniefel, Joshua

doi:10.1016/j.enpol.2011.06.055

“…Much work has been done in this area. However, results are contradictory, varying from showing the impact of RPS policies on renewable deployment as positively significant (Menz and Vachon, 2006;Yin and Powers, 2010) to insignificant (Carley 2009) to negatively significant (Shrimali and Kneifel, 2011). Thus, there is a need to explain these contradictory results and establish a robust answer to the question of RPS impact on in-state RES-E deployment.…”

Section: Introductionmentioning

confidence: 92%

Have State Renewable Portfolio Standards Really Worked? Synthesizing Past Policy Assessments to Build an Integrated Econometric Analysis of RPS effectiveness in the U.S.

Shrimali

¹

,

Jenner

²

,

Groba

³

et al. 2012

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. CA 93940, gshrimali@miis.edu, Tübingen Univ., Melanchthonstr. 36, 72076 Tübingen, Germany, steffen.jenner@uni-tuebingen.de, Tel.: +49-7071-29-72927. c German Institute of Economic Research, Mohrenstr. 58, 10117 Berlin, Germany, fgroba@diw.de, Tel.: +49-30-89789-681. d Harvard University, 79 JFK Street, Cambridge, MA 02138, gabe_chan@hksphd.harvard.edu, Tel.: +1-415-533-6103. e ICF International, 1725 I Street N.W., Washington, D.C. 20006, joe.indvik@gmail.com, Tel.: +1-515-230-4665. Abstract: Renewable portfolio standards (RPS) are the most popular U.S. state-level policies for promoting deployment of renewable electricity (RES-E). While several econometric studies have estimated the effect of RPS on in-state RES-E deployment, results are contradictory. We reconcile these studies and move toward a definitive answer to the question of RPS effectiveness. We conduct an analysis using time series cross sectional regressions -including the most nuanced controls for policy design features to date -and nonparametric matching analysis. We find that higher RPS stringency does not necessarily drive more RES-E deployment. We examine several RPS design features and market characteristics (including REC unbundling, RPS in neighboring states, out-of-state renewable energy purchases) that may explain the gap between effective and ineffective policies. We also investigate other RES-E policies and technology-specific effects. Ultimately, we show that RPS effectiveness is largely explained by a combination of policy design, market context, and inter-state trading effects. Terms of use: Documents in

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“…For example, Carley (2009) finds that RPS implementation does not predict the percentage of energy generation from renewable sources, though the number of years a state maintains an RPS is a significant determinant of total renewable energy capacity development. Shrimali and Kneifel (2011) find that RPS policies actually appear to reduce the penetration of some RES-E technologies and overall RES-E capacity, while they increase the penetration of others. These results call into question the effectiveness of RPS policies once non-policy state characteristics have been controlled for.…”

Section: Literature Reviewmentioning

confidence: 99%

“…With the exception of Menz and Vachon (2006) and Shrimali and Kneifel (2011), previous studies have used total RES-E data or the renewable energy share of total energy supply and therefore do not distinguish between the relative contribution of different energy technologies. We obtained capacity data from the UN Energy Statistics Database (2011).…”

Section: Dependent Variable Selectionmentioning

confidence: 99%

Assessing the strength and effectiveness of renewable electricity feed-in tariffs in European Union countries

Jenner

¹

,

Groba

²

,

Indvik

³

2013

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. We develop a new indicator for FIT strength that captures variability in tariff size, contract duration, digression rate, electricity price, and electricity generation cost to estimate the resulting return on investment. We then regress this indicator on added RES-E capacity using a fixed effects specification. We find that FIT policies have driven solar PV and onshore wind capacity development in the EU. However, this effect is overstated without controls for country characteristics and may be concealed without accounting for the unique design of each policy. We provide empirical evidence that the interaction of policy design and market dynamics are more important determinants of RES-E development than policy enactment alone. Terms of use: Documents in

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“…Other independent variables act as controls and are classified into three categories (socioeconomic, electricity market and policy/tax factors). This is a stark contrast with Marques et al (2010) or Shrimali and Kniefel (2011), which mainly focused on the impact of tax and policy tools on renewable energies using, among other things, prices as control variables. We will also consider a more general specification than them.…”

Section: Independent Variablesmentioning

confidence: 86%

“…substitutability. Using U.S. data, Shrimali and Kniefel (2011) find a significant negative relationship between the share of nonrenewable (wind, solar, biomass and geothermal) capacity and the total net generation, i.e. complementarity: "The flexible natural gas based plants are used for overcoming the intermittency issues inherent in renewable power generation -in particular wind, the dominant renewable source."…”

Section: Introductionmentioning

confidence: 99%

Non-Renewable and Intermittent Renewable Energy Sources: Friends and Foes?

Baranès

¹

,

Jacqmin

²

,

Poudou

³

2015

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This paper studies the links between non-renewable and intermittent renewable energy sources in the production of electricity. We argue that the relationship between the price of natural gas and investments in solar and wind capacity is represented by a bell-shaped curve, as opposed to being linear. Hence, for relatively low natural gas prices, the two modes of production are substitutes. After a price threshold is reached, the two are complementary. A theoretical model explains this as the trade-o↵ resulting from two forces: the input price di↵erential of these two modes of production and the risks related to the unpredictable nature of renewable energy. Using U.S. state-level data from 1998 to 2012, we find that this relationship is robust to various empirical specifications.

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Are government policies effective in promoting deployment of renewable electricity resources?

Cited by 181 publications

References 25 publications

Have State Renewable Portfolio Standards Really Worked? Synthesizing Past Policy Assessments to Build an Integrated Econometric Analysis of RPS effectiveness in the U.S.

Have State Renewable Portfolio Standards Really Worked? Synthesizing Past Policy Assessments to Build an Integrated Econometric Analysis of RPS effectiveness in the U.S.

Assessing the strength and effectiveness of renewable electricity feed-in tariffs in European Union countries

Non-Renewable and Intermittent Renewable Energy Sources: Friends and Foes?

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