Mini-Workshop on Climate, Economics, and Climate Economics
To register please send an informal e-mail to ruth.haefliger@bf.uzh.ch (we need to know how many Gipfeli to order, if you do not e-mail us, you won't get any).
Also, send an e-mail if you want to follow on Zoom, we'll then send you a link before the conference (Not recommended, because no Gipfeli on Zoom).
Organizers: Doris Folini (ETHZ), Felix Kübler (UZH), Simon Scheidegger (Unil)
Program:
9.00 – 10.00: Fiscal Policy for Climate Change and Welfare
Authors: François Le Grand, Florian Oswald (Sciences Po), Xavier Ragot and Aurélien Saussay
Abstract: Fiscal policy offers a number of levers to reduce carbon emissions. Climate change mitigation can for example be implemented through carbon taxation on the production or consumption side, or through debt-financed public investments in emission-reducing infrastructure. Yet these various instruments may differ significantly in their cost-effectiveness in reducing emissions and in their distributional impacts among households. We develop a macroeconomic heterogeneous-agent model with environmental externalities to address both of these questions. In this model, households derive utility from the consumption of carbon-intensive and clean goods, and from the environmental damages resulting from CO2 emissions. In addition, CO2 emissions affect productivity and thus relative prices. We use household data on the distribution carbon-intensive goods consumption to estimate preference parameters. Starting from a realistic fiscal structure, we then implement various tax reforms to analyze their effects on both CO2 emissions and welfare along the income distribution.
10.30-11.30 Title: Long-range weather prediction under climate change: Are we prepared for extreme weather events?
Author: Daniela Domeisen (ETHZ/UNIL)
Abstract: Under climate change, extreme events such as heatwaves and precipitation extremes are becoming more frequent and more extreme. We are often not sufficiently prepared for these extremes, especially as many of them tend to be unprecedented under climate change, e.g. by becoming more extreme than ever before, or by occurring in places that have never before experienced extremes of a similar magnitude. It is therefore crucial to predict when such extremes may occur, as far in advance as possible. Extended-range weather prediction several weeks to months in advance uses global connections in the climate system, such as the coupling between the atmosphere and the ocean or between the tropics and midlatitudes. These connections provide additional knowledge of the probability of occurrence for extreme events. However, many of these coupling processes may change under climate change, posing an additional challenge for long-range prediction. This contribution gives an overview of the current possibilities in long-range weather prediction of extreme events, and how the preparedness for and prediction of these extremes may change in a changing climate.
11.30-12.30 : Climate Risks and the Pricing of Long-Dated Assets
Authors: Pauline Chikhani and Jean-Paul Renne (University of Lausanne and E4S)
Abstract: Long-term asset prices are affected by secular risks, among which climate risks figure prominently. This paper proposes a tractable stochastic integrated assessment model (IAM) that we use to investigate the effect of climate on asset returns, in the time and maturity dimensions. We derive formulas to price various assets, including equities and fixed-income products. Our results suggest, in particular, that climate risks will exert increasing downward pressure on long-term risk-free yields in the coming decades, the compression effect being of the order of magnitude of 100 basis points. This effect reflects lower growth and higher uncertainty resulting from climate change. We highlight the importance of climate risk premiums: investors demand higher average excess returns on assets more exposed to climate risks, which we illustrate in the context of assets exposed to sea-level rise.
Lunch
14.00-15.00 Title: The Fiscal Costs of Climate Change in the United States
Author: Lint Barrage (UCSB/ETHZ)
Abstract: This paper explores the fiscal impacts of climate change and their policy implications for the United States. I develop and empirically quantify a climate-macroeconomic model where climate change can affect (i) government consumption requirements (e.g., healthcare), (ii) transfer payments (e.g., income support), (iii) tax revenues, and where (iv) adaptation to sea level rise (e.g., sea walls) must be publicly financed. First, the paper presents a novel bottom-up quantification of fiscal costs based on literature synthesis and an empirical analysis of public healthcare costs associated with extreme temperatures and wildfires. Climate change is projected to increase total government consumption (transfer) requirements by around 2% (0.3%) by mid-century in a high emissions scenario, with healthcare accounting for the majority of cost increases. Second, I show theoretically that the social cost of carbon must account for climate impacts on both government consumption and household transfer payments if the marginal cost of public funds exceeds unity. Finally, the numerical results indicate that fiscal considerations are of first order importance for climate policy design. The elasticity of the social cost of carbon with respect to government consumption (transfer) impacts per degree warming is estimated to be around 20 (10). Accounting for fiscal considerations moreover increases the projected domestic U.S. welfare benefits of climate policy by up to a factor of three.
15.00-16.00 Reduced complexity climate models: status, applications and opportunities
Presenter: Chris Smith (University of Leeds and International Institute for Applied Systems Analysis (IIASA))
Abstract: Representing climate change in a coupled system such as an economic or integrated assessment model requires a reduced complexity climate model. The climate model must be efficient to run while at the same time representing the behavior of full-complexity Earth System Models, condensing the response of the Earth system into a manageable number of parameters. By varying the parameters and running the model lots of times, exploiting the model’s fast run time, large probabilistic ensembles that span the range of climate uncertainty can be produced. For the most recent IPCC report, several reduced complexity models were compared and evaluated for their ability to reproduce observed climate change (temperature, ocean heat uptake, CO2 concentrations) from a given emissions time series, as well as assessments of climate sensitivity and radiative forcing provided by the IPCC. Calibrating and constraining reduced complexity climate models increases confidence in their ability to adequately project future climate change, and three models (with appropriate calibrations and probabilistic distributions) were recommended to be used in the Working Group 3 report for assessing the climate response to over 1200 emissions pathways from integrated assessment models. Reduced complexity models are currently being developed to emulate regional climate, extremes, tipping points, and poorly represented components of the climate system such as land ice sheet melt contributing to sea-level rise. While benefit-cost models such as DICE are already being modified to update and re-calibrate their climate representation, a long-term goal is the inclusion of a climate component into a process-based integrated assessment model, where regional climates and impacts will affect the energy system and human decision making.
16.30-17.30 The climate in climate economics
Authors: Doris Folini (ETHZ), Felix Kübler, Aleksandra Malova, Simon Scheidegger
Abstract: To design optimal climate change mitigation strategies, economists rely on simplified climate models that provide a realistic quantitative link between CO2 emissions and global warming at low computational costs. In this paper, we propose a generic and transparent calibration and evaluation strategy for climate emulators that is based on freely and easily accessible state-of-the-art benchmark data from climate sciences and demonstrate the economic importance of a good climate emulator. The key idea we put forward is to calibrate the simplified climate models based on benchmark data from comprehensive global climate models that took part in the Coupled Model Intercomparison Project, Phase 5 (CMIP5). In particular, we propose to use four different test cases that are considered pivotal in the climate science literature: two highly idealized tests to separately calibrate and evaluate the carbon cycle and temperature response, an idealized test to quantify the transient climate response, and a final test to evaluate the performance for scenarios close to those arising from economic models, including exogenous forcing. As a concrete example, we re-calibrate the climate part of the widely used DICE-2016, fathoming the CMIP5 uncertainty range of model responses: the multi-model mean and extreme but still permissible climate sensitivity and carbon cycle responses. We demonstrate that the functional form of the climate emulator of the DICE-2016 model is fit for purpose, despite its simplicity, but its carbon cycle and temperature equations are miscalibrated, leading to the conclusion that one may want to be skeptical about policy predictions derived from DICE-2016. After applying our calibration strategy to DICE-2016, we find that the updated model predicts similar values for the social cost of carbon, but with a strongly reduced sensitivity to the discount rate and about one degree less long-term warming, a value compatible with ranges of CMIP5 scenarios.
We thank the University of Zurich and the Swiss National Science Foundation for financial support under Sinergia Project 189942. p3.snf.ch/Project-189942
Contact Zurichccfe@gmail.com with any questions about the project.