We develop a generic and transparent calibration strategy for simple climate models used in economics. The goal is to choose the free model parameters such as to best match the output of large-scale Earth System Models from the Coupled Model Intercomparison Project, run on pre-defined emissions scenarios. We propose to jointly use four different test cases that are considered pivotal in the climate science literature: two highly idealized tests to separately examine the carbon cycle and the temperature response, and two tests closer to real scenarios, incorporating gradual changes in CO2 emissions and exogenous forcings. To illustrate the applicability of our method, we re-calibrate the free parameters of the climate part of the seminal DICE-2016 model for three different CMIP5 model responses: the multi-model mean as well as two CMIP5 models that exhibit extreme but still permissible equilibrium climate sensitivities. As an additional novelty, our calibrations of DICE-2016 allow for an arbitrary time step in the model explicitly. By applying our comprehensive suite of tests, we i) confirm that both the temperature equations and the carbon cycle in DICE-2016 are miscalibrated and ii) we show that by re-calibrating coefficients all CMIP5 targets considered can be well matched. Finally, we apply the economic model from DICE-2016 in combination with the newly calibrated climate model to compute the social cost of carbon and optimal warming. We find the social cost of carbon to be similar to DICE-2016, while the optimal long-run temperature is almost one degree lower. The social cost of carbon turns out to be much less sensitive to the discount rate than in DICE-2016. We explain how the model's climate part relates to these differences. As the temperature in DICE-2016 under optimal mitigation falls outside the range of CMIP5 projections, we caution that one might want to be skeptical about policy advice based on DICE-2016.

In a sample of U.S. firms, we find strong evidence that firms' implied cost of equity is decreasing in a novel proxy of firm-level climate change sentiments of earnings call participants, supporting prior literature that shows investors demand higher returns from their investments in brown firms and lower returns from that in green firms. This effect, however, is particularly pronounced for the firm-years headquartered in the states experiencing higher than median per-capita energy related CO2 emissions, those headquartered in climate related disaster intensive counties and those headquartered in RED and SWING states, supporting “boomerang hypothesis” that green firms are hedged against potential changes in local climate standards and thus enjoy considerably cheaper financing in the localities marred with greenhouse gas emission concerns, climate related physical disasters, and climate unfriendly political environment. We utilize the variation in regionwide and statewide public beliefs about scientists' beliefs regarding the occurrence of global warming as an instrument to address endogeneity issues, among other tests.

This paper explores global perceptions and understanding of climate change and policies, examining factors that influence support for climate action and the impact of different types of information. We conduct large-scale surveys with 40,000 respondents from 20 countries, providing new international data on attitudes toward climate change and respondents’ socioeconomic backgrounds and lifestyles. We identify three key perceptions affecting policy support: perceived effectiveness of policies in reducing emissions, their impact on low-income households, and their effect on respondents’ households (self-interest). Educational videos clarifying policy mechanisms increase support for climate policies; those merely highlighting climate change’s impacts do not.

In this study, we consider for the first time whether and how stock liquidity impacts corporate climate performance in China. We find that an increase in stock liquidity is highly associated with lower carbon emissions. To address endogeneity concerns, we exploit a unique quasi-natural experiment in China— the stock market liberalization (Shanghai-Shenzhen Hong Kong Stock Connect). Using difference-in-differences (DID) estimations, we find that carbon emissions for treatment firms substantially decrease after the stock market liberalization. The impact of stock liquidity is more pronounced for enterprises facing severe financial constraints, greater equity dependence, and operating in pollution-intensive sectors. Similarly, we find that external monitoring, carbon abatement investment, and green innovation are plausible channels through which stock liquidity drives carbon emissions reduction. We further find that the sensitivity of corporate climate performance to improved stock liquidity becomes stronger following the Paris Agreement. Overall, we uncover new evidence on the impact of stock liquidity on corporate climate performance, expanding our understanding of the role of financial markets towards a greener economy.

This study examines how government procurement impacts firms’ environmental disclosures and whether they have tangible effects. Using a triple-difference research design that exploits the exogenous increase in federal funding allocations to counties based on population census revisions, we find that firms with high exposure to government contracts significantly increase climate disclosure following expanded procurement opportunities. We also document that enhanced disclosure is characterized by a positive tone that emphasizes firms’ green investment and commitment to climate adaptation. The effect is more pronounced in counties with a greater increase in procurement volume and when firms have lower ex ante sustainability performance. Finally, we find firms that increase climate disclosure are more likely to earn government contracts, and they undertake real actions by reducing toxic emissions and enhancing the development of green products. Overall our results suggest government procurement promotes corporate climate responsibility by incentivizing firms to undertake climate mitigation actions.

We examine firms' trade‐offs in their voluntary disclosure decisions following negative media coverage of climate change incidents. By combining a keyword discovery algorithm and a fine‐tuned BERT model, we identify “hard” and “soft” climate disclosures on Twitter. Our findings indicate that firms tend to issue climate tweets as a rapid response to negative climate incidents. Additionally, firms with a history of hard climate change disclosure, as measured by ESG reports, are more likely to issue climate‐related responses than firms without such a history. Furthermore, we show that prior hard disclosure is associated with hard responses when the incident receives moderate media attention, but with soft responses when the incident receives low media attention. Our findings provide empirical insights for dynamic disclosure theory by illustrating how prior disclosure shapes firms' response strategies to negative media coverage.

Trade policy is often cast as a solution to the free‐riding problem in international climate agreements. This paper examines the extent to which trade policy can deliver on this promise. We incorporate global supply chains of carbon and climate externalities into a multi‐country, multi‐industry general equilibrium trade model. By deriving theoretical formulas for optimal carbon and border taxes, we quantify the maximum efficacy of two trade policy solutions to the free‐riding problem. Adding optimal carbon border taxes to existing tariffs proves largely ineffective, delivering only 3.4% of what could be achieved under globally optimal carbon pricing. In contrast, Nordhaus's (2015) climate club framework, in which border taxes are used as contingent penalties to deter free‐riding, can achieve 33–68% of the globally optimal carbon reduction, depending on the initial coalition (EU, EU + US, or EU + US + China). In all cases, the climate club ensures universal compliance, thereby preserving free trade.

We consider the effects of climate change on seasonally migrant populations that herd livestock—i.e. transhumant pastoralists—in Africa. Traditionally, transhumant pastoralists benefit from a cooperative relationship with sedentary agriculturalists whereby arable land is used for crop farming in the wet season and animal grazing in the dry season. Rainfall scarcity can disrupt this arrangement by inducing pastoral groups to migrate to agricultural lands before the harvest, causing conflict to emerge. We examine this hypothesis by combining ethnographic information on the traditional locations of transhumant pastoralists and sedentary agriculturalists with high-resolution data on the location and timing of rainfall and violent conflict events in Africa from 1989 to 2018. We find that reduced rainfall in the territory of transhumant pastoralists leads to conflict in neighbouring areas. Consistent with the proposed mechanism, the conflicts are concentrated in agricultural areas; they occur during the wet season and not the dry season; and they are due to rainfall’s impact on plant biomass growth. Since pastoralists tend to be Muslim and agriculturalists Christian, this mechanism accounts for a sizable proportion of the rapid rise in religious conflict observed in recent decades. Regarding policy responses, we find that development aid projects tend not to mitigate the effects that we document. By contrast, the effects are reduced when transhumant pastoralists have greater power in national government, suggesting that more equal political representation is conducive to peace.

We examine the effect of voluntary climate risk disclosure on Credit Default Swap (CDS) premiums. We develop a structural model, in which climate-related disclosures serve as an information source reducing climate change uncertainty. The model predicts a negative relation between the informativeness of climate risk disclosure and the CDS premium, and asymmetric effects of positive and negative disclosure tone on the CDS premium. Using climate risk measures quantified from earnings call transcripts, we provide evidence supporting these predictions with causal inference. Our study suggests that climate risk is priced in the CDS market, where investors pay attention to climate risk disclosures.

As early as 2015, financial regulators were developing disclosure frameworks aimed at enabling capital markets to price climate risks. Yet the literature on sustainability disclosure offers little insight into how regulatory agendas change, instead focusing on how nongovernmental organizations drive voluntary disclosure. To address this deficiency, this paper charts how financial regulators came to embrace climate risk, analyzing how an array of non‐state initiatives became coordinated in highlighting climate‐related impairment risks. This coordination is conceptualized via scholarship on decentered regulation, allowing a first, theoretical, contribution by constructing and demonstrating one analytical approach to studying substantive change on sustainability. This paper draws on a 25‐month participant observation of a United Nations standard‐setting project, supported by semi‐structured interviews. This allows a second, empirical, contribution by mapping how an accounting device, the so‐called “carbon budget” (the maximum amount of cumulative greenhouse gas emissions that limits the probability of exceeding 2°C of warming to 20%), coordinated this array of non‐state action toward resolving a core trade‐off: if we burn our current fossil fuel reserves, we will exceed our warming targets. The paper then shows how these coordinated efforts pressured regulatory authorities to intervene on how finance affects and is affected by climate change.