Narrow Results

Climate change will push the weather experienced by people affected outside the bounds of historic norms, resulting in unprecedented weather events. But people and firms should be able to learn from their experience of unusual weather and adjust their expectations about the climate distribution accordingly. The efficiency of this learning process gives an upper bound on the rate at which adaptation can occur and is therefore important in determining the adjustment costs associated with climate change. Learning about climate change requires people to infer the state of a changing probability distribution (climate) given annual draws from that distribution (weather). If the climate is stationary, it can be inferred from the distribution of historic weather observations, but if it is changing, the inference problem is more challenging. This paper first develops different learning models, including an efficient hierarchical Bayesian model in which the observer learns whether the climate is changing and, if it is, the functional form that describes that change. I contrast this with a less efficient but simpler learning model in which observers react to past changes but are unable to anticipate future changes. I propose a general metric of learning costs based on the average, discounted squared difference between beliefs and the true climate state and use climate model output to calculate this metric for two emissions scenarios, finding substantial relative differences between learning models and scenarios but small absolute values. Geographic differences arise from spatial patterns of warming rates and natural weather variability (noise). Finally, I present results from an experimental game simulating the adaptation decision, which suggests that people are able to learn about a trending climate and respond proactively.

Future carbon dioxide (CO₂) emissions under a carbon tax depend on the time-path of the economy under baseline (business-as-usual) conditions as well as the extent to which the policy reduces emissions relative to the baseline. Considerable uncertainties surround the baseline forecasts for fuel prices, energy efficiency (energy-GDP ratios), and GDP, as evidenced by the significant ranges in the forecasts by government agencies and research institutions in the U.S. This paper assesses the significance of these uncertainties to the path of CO₂ emissions under a carbon tax. We do this by examining the emissions levels and quantities of abatement that result from the E3 general equilibrium model under a range of alternative baseline forecasts for fuel prices, energy efficiency, and GDP, where the different baselines are produced through suitable changes to key model parameters. In addition, we consider how the time-profile of the carbon tax needed to achieve specified CO₂ abatement targets is affected by such forecast-linked changes in parameters.

We find that the sensitivity of baseline emissions to alternative forecasts depends on the particular forecasted variable under consideration. Baseline CO₂ emissions are highly sensitive to alternative scenarios related to the rate of energy efficiency improvements in the nonenergy sector and the rate of general economic growth. In contrast, such emissions are much less sensitive to alternative scenarios related to the productivity of fossil fuel production. The extent of abatement from the baseline is generally fairly insensitive to changes in the scenarios for time-paths of fuel prices, energy-efficiency and GDP. We also find that short-term emissions targets can be achieved with relatively moderate carbon taxes under all of the baseline scenarios considered.

About 140 countries have announced or are considering net zero targets. To explore the implications of such targets, we apply an integrated earth system–economic model to investigate illustrative net zero emissions scenarios. Given the technologies as characterized in our modeling framework, we find that with net zero targets afforestation in earlier years and biomass energy with carbon capture and storage (BECCS) technology in later years are important negative emissions technologies, allowing continued emissions from hard-to-reduce sectors and sources. With the entire world achieving net zero by 2050 a very rapid scale-up of BECCS is required, increasing mitigation costs through mid-century substantially, compared with a scenario where some countries achieve net zero by 2050 while others continue some emissions in the latter half of the century. The scenarios slightly overshoot 1.5^∘C at mid-century but are at or below 1.5^∘C by 2100 with median climate response. Accounting for climate uncertainty, global achievement of net zero by 2050 essentially guarantees that the 1.5^∘C target will be achieved, compared to having a 50–50 chance in the scenario without net zero. This indicates a tradeoff between policy costs and likelihood of achieving 1.5^∘C.

This study looks at carbon emissions among the Association of Southeast Asian Nations (ASEAN) countries during the period 2000–2019. Through panel data using both pooled ordinary least squares (OLS) and panel least square regressions, the Environmental Kuznets Curve (EKC) hypothesis is tested as well as a model which includes GDP per capita, foreign direct investment (FDI), energy use, trade and an interaction term between FDI and energy use. The interaction term is built from and being expanded from the existing FDI–energy nexus. A cointegration test is also conducted to find out whether there exists a long-run relationship among the variables. The findings indicate that as a whole region, ASEAN observes the EKC hypothesis but different results occur when categories of oil versus non-oil exporting and Cambodia, Laos, Myanmar, Vietnam (CLMV) versus non-CLMV countries are defined. In ASEAN overall, the pooled and panel data regressions suggest GDP per capita, FDI and energy use would increase emissions. In contrast, trade would reduce carbon emissions. The interaction term of FDI and energy was found to be a mediating variable and it was statistically significant. Policy implications are discussed.