Price of Long-Run Temperature Shifts in Capital Markets

Bansal, Ravi; Kiku, Dana; Ochoa, Marcelo

doi:10.3386/w22529

Cited by 151 publications

(111 citation statements)

References 39 publications

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“…Lower dividends lead then to a drop in equity prices. This confirms most recent empirical evidence suggesting that temperature shocks have a negative impact on asset prices (see Bansal et al, 2016;Balvers et al, 2017). As a result, the agent demands more of the risk-free asset, and the increased demand leads to a decline in the risk-free rate (Panel B), which is also in line with our empirical findings (Figure 3,Panel B).…”

Section: Inspecting the Mechanismsupporting

confidence: 82%

Temperature shocks and welfare costs

Donadelli

Jüppner

Riedel

et al. 2017

Journal of Economic Dynamics and Control

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This paper examines the welfare implications of rising temperatures. Using a standard VAR, we empirically show that a temperature shock has a sizable, negative and statistically significant impact on TFP, output, and labor productivity. We rationalize these findings within a production economy featuring long-run temperature risk. In the model, macro-aggregates drop in response to a temperature shock, consistent with the novel evidence in the data. Such adverse effects are long-lasting. Over a 50-year horizon, a one-standard deviation temperature shock lowers both cumulative output and labor productivity growth by 1.4 percentage points. Based on the model, we also show that temperature risk is associated with non-negligible welfare costs which amount to 18.4% of the agent's lifetime utility and grow exponentially with the size of the impact of temperature on TFP. Finally, we show that faster adaptation to temperature shocks results in lower welfare costs. These welfare benefits become substantially higher in the presence of permanent improvements in the speed of adaptation.JEL classification: E30, G12, Q0

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Section: Inspecting the Mechanismsupporting

confidence: 82%

Temperature shocks and welfare costs

Donadelli

Jüppner

Riedel

et al. 2017

Journal of Economic Dynamics and Control

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“…Similarly, Bansal et al. () find evidence of the significant negative impact of temperature‐induced disasters on asset valuations. When companies recognise climate‐related risk in the financial statements, it is expected to affect reported earnings and the carrying value of assets, as any future impact of the risks is accounted for in the recognised and/or disclosed financial information.…”

Section: Future Studies Related To Climate Risk Of Potential Interestmentioning

confidence: 91%

Climate‐related Risk and Financial Statements: Implications for Regulators, Preparers, Auditors and Users

Michaelides

Rose

et al. 2019

Australian Accounting Review

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Interest among investors in understanding climate‐related risk from companies’ management has increased in recent years. Despite this, climate‐related risks are currently predominantly discussed outside the financial statements, if at all. However, as set out in the Australian Accounting Standards Board (AASB)/International Accounting Standards Board's (IASB) Practice Statement 2 Making Materiality Judgements (APS/PS 2), qualitative external factors such as the industry in which the entity operates and investor expectations may make such risks ‘material’ and warrant disclosures when preparing financial statements, regardless of their numerical impact. The AASB and the AUASB expect that directors, preparers and auditors will be considering APS/PS 2 when preparing and auditing financial statements. This paper provides an outline of the guidance and motivation behind the issuance of the bulletin on climate‐related risk disclosures, key takeaways and recommendations, and the AASB's and AUASB's suggestions on the type of evidence that would be useful for standard setters.

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“…The second strand in the literature our paper is related to is the literature on climate change economics and especially to the part that considers non-expected utility and the part that looks at analytic approaches to solve their models. Bansal, Kiku, and Ochoa (2016) propose a climate model based on the Long-Run-Risk (LRR) model of Bansal and Yaron (2004). In the LRR-model, the agent has Epstein-Zin preferences and the consumption growth contains persistent shocks.…”

Section: Related Literaturementioning

confidence: 99%

“…In the LRR-model, the agent has Epstein-Zin preferences and the consumption growth contains persistent shocks. Bansal et al (2016) model climate disasters as a jump process that affects both consumption itself and the growth rate of consumption. They show that the outcomes of their model are very sensitive to choices of the EIS.…”

Section: Related Literaturementioning

confidence: 99%

“…But that simplification comes at a cost: there is empirical evidence that the EIS is well above one (Van Binsbergen, Fernández-Villaverde, Koijen, and Rubio-Ramírez (2012); Vissing-Jørgensen and Attanasio (2003)), which as we will demonstrate, has a major impact on the SCC. Also in the finance literature (Bansal et al (2016); Barro (2009)) and in climate change models with recursive preferences (Jensen and Traeger (2014); Cai, Judd, and Lontzek (2015)) values of the EIS between 1.5 and 2 are often used. Given the large impact of changes in the EIS given risk aversion on intertemporal choice it seems to us important to study how deviating from unit elasticity affects intertemporal choices and the long term stochastic discount factor.…”

Section: Related Literaturementioning

confidence: 99%

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Discounting the Future: on Climate Change, Ambiguity Aversion and Epstein-Zin Preferences

Olijslagers

Wijnbergen

2019

SSRN Journal

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We focus on the effect of preference specifications on the current day valuation of future outcomes. Specifically, we analyze the effect of risk aversion, ambiguity aversion and the elasticity of intertemporal substitution on the willingness to pay to avoid climate change risk. The first part of the paper analyzes a general disaster (jump) risk model with a constant arrival rate of disasters. This provides useful intuition in how preferences influence valuation of long-term risk. The second part of the paper extends this model with a climate model and a temperature dependent arrival rate. Since the model yields closed form solutions up to solving an integral, our model does not suffer from the curse of dimensionality of numerical IAMs with several state variables. Introducing Epstein-Zin preferences with an elasticity of substitution higher than one and ambiguity aversion leads to much larger estimates of the social cost of carbon than obtained under power utility. The dominant parameters are the risk aversion coefficient and the elasticity of intertemporal substitution. Ambiguity aversion is of second order importance. JEL codes: Q51, Q54, G12, G13 1 For a very different (and strongly worded) view focusing on the social welfare aspects of the rate of time preference rather than on individual preferences, see Chichilnisky, Hammond, and Stern (2018);Stern (2015) who look at a positive rate of time preference as discrimination between generations that happen to have been born at different moments in time.2 This list is not exhaustive, but is used to give an idea of the nature of an IAM. 3 The references do not contain the most recent versions of the IAMs.1. Power utility, no ambiguity aversion r 1 = r P ow − γλm − λ(e −γ(µ J − 1 2 γσ 2 J ) − 1) 2. SDU utility, no ambiguity aversion3. Power utility, ambiguity aversion r 3 = r SDU − γλ * m * − λ * (e −γ(µ J +b * σ 2 J − 1 2 γσ 2 J ) − 1) 4. SDU utility, ambiguity aversion r 4 = r

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Price of Long-Run Temperature Shifts in Capital Markets

Cited by 151 publications

References 39 publications

Temperature shocks and welfare costs

Temperature shocks and welfare costs

Climate‐related Risk and Financial Statements: Implications for Regulators, Preparers, Auditors and Users

Discounting the Future: on Climate Change, Ambiguity Aversion and Epstein-Zin Preferences

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