The Renewable Fuel Standard in Competitive Equilibrium: Market and Welfare Effects

Moschini, GianCarlo; Lapan, Harvey E.

doi:10.1093/ajae/aax041

Cited by 23 publications

(15 citation statements)

References 38 publications

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“…Hence, given the unfeasibility of scaling up cellulosic biofuel production, a possible avenue for expanding total biofuel consumption is to promote use of biodiesel, which is not constrained by the blend wall (Irwin and Good, 2016). Insofar as soybean oil is the marginal fuel for biodiesel production, as analyzed in Moschini, Lapan and Kim (2017), expanding biodiesel production will require more soybeans. Because of the strong negative cross-elasticity of acreage response, as characterized in this paper, expanded demand for soybeans will put upward pressure on both soybean and corn prices.…”

Section: Discussionmentioning

confidence: 99%

“…Most of this responsiveness is due to acreage allocation decisions, as we find that the yield supply response to price is essentially nil. The model also identifies cross-price effects between corn and soybeans, which are emerging as important parameters because of the RFS: as conventional ethanol mandates have reached their statutory maximum, increasing amounts of biodiesel have been mandated (which increases the demand for vegetable oil and, consequently, oilseeds) (Moschini, Lapan, and Kim 2017). Cross-price elasticities are found to be relatively large: the cross-price elasticity between corn and soybeans at the mean is estimated to be -0.31, and that between soybeans and corn to be -0.50 in the short run (the long-run counterparts are -0.23 and -0.32, respectively).…”

Section: Introductionmentioning

confidence: 99%

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The Dynamics of Supply: U.S. Corn and Soybeans in the Biofuel Era

Moschini

2018

Land Economics

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We estimate U.S. corn and soybean supply responses by exploiting the large exogenous price variations associated with implementation of the Renewable Fuel Standard. We focus on recent years and on the twelve Midwestern states, and estimate a system of dynamic equations that is consistent with the role of crop rotation. Corn and soybean acreages respond more in the short run than in the long run. Cross-price elasticities of acreage responses are negative and fairly large in absolute value such that, when corn and soybean prices move together, the response of total acreage allocated to these two crops is extremely inelastic. AbstractWe estimate U.S. corn and soybean supply responses by exploiting the large exogenous price variations associated with implementation of the Renewable Fuel Standard. We focus on recent years and on the twelve Midwestern states, and estimate a system of dynamic equations that is consistent with the role of crop rotation. Corn and soybean acreages respond more in the short run than in the long run. Cross-price elasticities of acreage responses are negative and fairly large in absolute value such that, when corn and soybean prices move together, the response of total acreage allocated to these two crops is extremely inelastic.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

The Dynamics of Supply: U.S. Corn and Soybeans in the Biofuel Era

Moschini

2018

Land Economics

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“…A complete assessment of fuel market impacts of the RFS would estimate fuel price and demand changes due to the policy, any associated deadweight loss to consumers, the loss in gasoline producers' surplus, and the gain in biofuels' producer surplus. Moschini, Lapan and Kim (2017) provide an example of such an exercise. Rather than studying welfare outcomes, RIAs typically conduct cost-benefit analyses.…”

Section: Fuel Market Impacts: Addressing Price Uncertaintymentioning

confidence: 99%

Designing Climate Policy: Lessons from the Renewable Fuel Standard and the Blend Wall

Lade

Lawell

Smith³

2018

American J Agri Economics

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Many policies mandate renewable energy production to combat global climate change. These policies often differ significantly from first-best policy prescriptions. Among the largest renewable energy mandates enacted to date is the Renewable Fuel Standard (RFS), which mandates biofuel consumption far beyond what is feasible with current technology and infrastructure. In this article, we critically review the methods used by the Environmental Protection Agency to project nearand long-term compliance costs under the RFS, and draw lessons from the RFS experience to date that would improve the program's efficiency. The lessons are meant to inform both future RFS rulemaking and the design of future climate policies. We draw two lessons specific to the RFS. (1) Incorporate uncertainty into rulemaking. Make, implement, and analyze policy with a view towards what might happen, rather than a projection of what will happen. (2) Implement multiyear rules. Multi-year rulemaking allows for longer periods between major regulatory decisions and sends greater certainty to markets. We also make two more general recommendations. (3) Tie waiver authority to compliance costs or include cost containment provisions. Explicit and transparent cost containment mechanisms send a stable policy signal to markets. (4) Fund research and development of new technologies directly rather than mandating them. Future technological advancement is uncertain, and mandating new technologies has proven to be largely ineffective to date, particularly in fuel markets.

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“…Given the assumed 74% average ethanol content of E85, and the U.S. Energy Information Administration (EIA) energy content of gasoline and ethanol (see, e.g.,Moschini, Lapan, and Kim 2017), then 1.25…”

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confidence: 99%

“…The gasoline wholesale price is from EIA, https://www.eia.gov/dnav/pet/pet_pri_refoth_dcu_nus_a.htm. It is the "Motor Gasoline" price under "Sales for Resale" category.11 The ethanol wholesale price is the ethanol rack price in Omaha, Nebraska.12 The average gasoline motor fuel tax is fromMoschini, Lapan, and Kim (2017). We do not consider the per-unit marketing/retailing costs.…”

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confidence: 99%

Pass-through of the policy-induced E85 subsidy: Insights from Hotelling's model

Luo

Moschini

2019

Energy Economics

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We build a structural model of imperfect competition for a retail market that supplies both low-ethanol (E10) and high-ethanol (E85) gasoline blends. The model permits us to study some impacts of the E85 subsidy induced by the U.S. Renewable Fuel Standard, specifically how the pass-through of this subsidy to retail prices is affected by market power. The model is rooted in Hotelling's horizontal differentiation framework, which is extended to also represent the imperfect substitutability between E10 and E85 (a vertical product differentiation attribute). The model naturally captures two sources of imperfect competition in the fuel market-refueling stations' market power arising from their spatial location, and limited availability of E85 stations. We derive both analytical and numerical solutions for Nash equilibrium outcomes under various scenarios. In our baseline parameterization, when the penetration of E85 stations is incomplete, we find that the pass-through rate is about 0.7. Complete penetration of E85 stations leads to near complete pass-through, notwithstanding the market power enjoyed by stations because of their spatial location. With monopolistic market power (e.g., collusion), however, with full penetration of E85 stations the pass-through rate is lower. Moreover, when market power only arises from location differentiation (duopoly model with full penetration of E85), the pass-through rate converges to one as the subsidy gets large, whereas it converges to zero if a station has exclusivity in selling E85 (partial penetration of E85) or there is collusion/monopoly power from collusion.

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The Renewable Fuel Standard in Competitive Equilibrium: Market and Welfare Effects

Cited by 23 publications

References 38 publications

The Dynamics of Supply: U.S. Corn and Soybeans in the Biofuel Era

The Dynamics of Supply: U.S. Corn and Soybeans in the Biofuel Era

Designing Climate Policy: Lessons from the Renewable Fuel Standard and the Blend Wall

Pass-through of the policy-induced E85 subsidy: Insights from Hotelling's model

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