Climate Policy and Innovation: A Quantitative Macroeconomic Analysis

Fried, Stephanie

doi:10.1257/mac.20150289

Cited by 76 publications

(96 citation statements)

References 34 publications

(50 reference statements)

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“…More recently, the focus has shifted to including measures for green energy in analyzing drivers of technical change. For instance, Fried (2018) analyses a dynamic, general equilibrium model that has endogenous innovation in fossil, green, and non-energy inputs.…”

Section: Scenario Designmentioning

confidence: 99%

The Heat Is on: A Framework for Measuring Financial Stress Under Disruptive Energy Transition Scenarios

et al. 2019

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Section: Scenario Designmentioning

confidence: 99%

The Heat Is on: A Framework for Measuring Financial Stress Under Disruptive Energy Transition Scenarios

et al. 2019

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“…Heutel, Moreno-Cruz, andShayegh (2016, 2018) and Keith, Wagner, and Zabel (2017) Cronin, Fullerton, and Sexton (2019) study redistributions from a carbon tax. Fried (2018) finds that a carbon tax induces large changes in innovation, and the innovation response increases the effectiveness of the policy at reducing emissions. Meng and Rode (2019) evaluate the social cost of lobbying over climate policy.…”

Section: Model Uncertainty and Scenario Uncertaintymentioning

confidence: 99%

The Role of Uncertainty and Risk in Climate Change Economics

Chari¹

2018

Preprint

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Integrated Assessment Models (IAMs) of the climate and economy aim to analyze the impact and efficacy of policies that aim to control climate change, such as carbon taxes and subsidies. A major characteristic of IAMs is that their geophysical sector determines the mean surface temperature increase over the preindustrial level, which in turn determines the damage function. Most of the existing IAMs are perfect-foresight forward-looking models, assuming that we know all of the future information. However, there are significant uncertainties in the climate and economic system, including parameter uncertainty, model uncertainty, climate tipping risks, economic risks, and ambiguity. For example, climate sensitivity, a well-known parameter that measures how much the equilibrium temperature will change if the atmospheric carbon concentration doubles, can range from one to ten in the literature. Climate damages are also uncertain: some researchers assume that climate damages are proportional to instantaneous output, while others assume that climate damages have a more persistent impact on economic growth. The spatial distribution of climate damages is also uncertain.Climate tipping risks represent (nearly) irreversible climate events that may lead to significant changes in the climate system, such as the Greenland ice sheet collapse, while the conditions, probability of tipping, duration, and associated damage are also uncertain. Technological progress in carbon capture and storage, adaptation, renewable energy, and energy efficiency are uncertain too. Future international cooperation and implementation of international agreements in controlling climate change may vary over time, possibly due to economic risks, natural disasters, or social conflict. In the face of these uncertainties, policymakers have to provide a decision that considers important factors such as risk aversion, inequality aversion, and sustainability of the economy and ecosystem. Solving this problem may require richer and more realistic models than standard IAMs, and advanced computational methods. The recent literature has shown that these uncertainties can be incorporated into IAMs and may change optimal climate policies significantly.(2017) argue that policymakers need a numerical value for the social cost of carbon (SCC) for policy evaluation and implementation, and producing a credible numerical value requires sophisticated computer models, i.e. IAMs. Brock and Hansen (2018) stress: "Defenses for policies that combat climate damage externalities induced by human activity need not require precise knowledge of the magnitude or timing of the potential adverse impacts. ...Waiting for precise knowledge of the eventual consequences of continued or expanded human induced CO2 emissions could make mitigation or adaptation extremely costly." Goulder (2020) calls for urgent and stronger policy action to address global climate change. This review focuses on recent work about the role of uncertainty in controlling climate change. Here I use a broad perspective...

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“…For renewables, a productivity growth rate of 5 percent is used (i.e., costs halve every 15 years). Fried (2018) estimates that induced innovation increases the price-responsiveness of US CO2 emissions by about a fifth. 89 The degree of substitution among fossil and non-fossil generation sources is, however, limited in practice, for example, due to the intermittency of renewables, their location away from population centers, and public opposition to nuclear power.…”

Section: (Ii) Power Sector Electricity Consumptionmentioning

confidence: 99%

Mitigation Policies for the Paris Agreement: An Assessment for G20 Countries

Parry¹,

Mylonas²,

Vernon³

2018

IMF Working Papers

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Following submission of greenhouse gas (GHG) mitigation commitments or pledges (by 190 countries) for the 2015 Paris Agreement, policymakers are considering specific actions for their implementation. To help guide policy, it is helpful to have a quantitative framework for understanding: i) the main impacts (on GHGs, fiscal balances, the domestic environment, economic welfare, and distributional incidence) of emissions pricing; ii) trade-offs between pricing and other (commonly used) mitigation instruments; and iii) why/to what extent needed policies and their impacts differ across countries. This paper provides an illustrative sense of this information for G20 member countries (which account for about 80 percent of global emissions) under plausible (though inevitably uncertain) projections for future fuel use and price responsiveness. Quantitative results underscore the generally strong case for (comprehensive) pricing over other instruments, its small net costs or often net benefits (when domestic environmental gains are considered), but also the potentially wide dispersion (and hence inefficiency) in emissions prices implied by countries' mitigation commitments. JEL Classification Numbers: Q48, Q54, Q58, H23

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Climate Policy and Innovation: A Quantitative Macroeconomic Analysis

Cited by 76 publications

References 34 publications

The Heat Is on: A Framework for Measuring Financial Stress Under Disruptive Energy Transition Scenarios

The Heat Is on: A Framework for Measuring Financial Stress Under Disruptive Energy Transition Scenarios

The Role of Uncertainty and Risk in Climate Change Economics

Mitigation Policies for the Paris Agreement: An Assessment for G20 Countries

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