To Build or not to Build? Capital stocks and climate policy

TY - JOUR

T1 - To Build or not to Build? Capital stocks and climate policy

AU - Baldwin, Elizabeth

AU - Cai, Yongyang

AU - Kuralbayeva, Karlygash

PY - 2020/3

Y1 - 2020/3

N2 - We investigate (i) the impact of emission reduction policy on investment in polluting infrastructure, such as coal-fired power stations and (ii) optimal subsidies for “clean” alternatives with “learning” spillovers. We build a general theoretical model, and embed it in a fully calibrated integrated assessment model. Because emission reduction policy reduces investments in polluting assets, short-term emission reductions are enhanced—our “irreversibility effect”. Thus, “stranded assets” in this fuel-using sector have distinctive properties. We also provide a simple formula for how the optimal subsidy to deployment of a “clean” sector depends on its rate of “learning-by-doing” and on its socially-optimal growth. So, if the sector should grow faster for other reasons, its optimal subsidy is increased, showing that its optimal growth rate is faster still—our “acceleration effect”. Our calibrations show that, to limit global climate change to 2○C warming, investments in coal-fired power stations must end very soon. Considering second-best settings, we show that carbon taxes achieve stringent policy targets more efficiently, but subsidies to the “clean” sector deliver higher welfare, and are more efficient, when policy targets are more mild.

AB - We investigate (i) the impact of emission reduction policy on investment in polluting infrastructure, such as coal-fired power stations and (ii) optimal subsidies for “clean” alternatives with “learning” spillovers. We build a general theoretical model, and embed it in a fully calibrated integrated assessment model. Because emission reduction policy reduces investments in polluting assets, short-term emission reductions are enhanced—our “irreversibility effect”. Thus, “stranded assets” in this fuel-using sector have distinctive properties. We also provide a simple formula for how the optimal subsidy to deployment of a “clean” sector depends on its rate of “learning-by-doing” and on its socially-optimal growth. So, if the sector should grow faster for other reasons, its optimal subsidy is increased, showing that its optimal growth rate is faster still—our “acceleration effect”. Our calibrations show that, to limit global climate change to 2○C warming, investments in coal-fired power stations must end very soon. Considering second-best settings, we show that carbon taxes achieve stringent policy targets more efficiently, but subsidies to the “clean” sector deliver higher welfare, and are more efficient, when policy targets are more mild.

KW - Carbon budget

KW - Clean and dirty energy inputs

KW - Climate policies

KW - Green paradox

KW - Infrastructure

KW - O44

KW - Q54

KW - Q58

KW - Renewable energy

KW - Stranded assets

UR - http://www.scopus.com/inward/record.url?scp=85068498569&partnerID=8YFLogxK

U2 - 10.1016/j.jeem.2019.05.001

DO - 10.1016/j.jeem.2019.05.001

M3 - Article

SN - 0095-0696

VL - 100

JO - JOURNAL OF ENVIRONMENTAL ECONOMICS AND MANAGEMENT

JF - JOURNAL OF ENVIRONMENTAL ECONOMICS AND MANAGEMENT

M1 - 102235

ER -