Taking the highway or the green road? Conditional temperature forecasts under alternative SSP scenarios
利用贝叶斯VAR框架，在二氧化碳和甲烷排放等气候驱动因素上施加等式和不等式约束，生成到2050年的条件温度预测。通过反事实情景分析发现，高排放情景下条件预测与无条件预测路径相似，而高减排情景下2040年后温度增速显著放缓，但排放变化的影响存在较大滞后。
In this paper, using the Bayesian VAR framework suggested by Chan et al. (2025), we produce conditional temperature forecasts up until 2050, by exploiting both equality and inequality constraints on climate drivers like carbon dioxide or methane emissions. Engaging in a counterfactual scenario analysis by imposing a Shared Socioeconomic Pathways (SSPs) scenario of “business-as-usual”, with no mitigation and high emissions, we observe that conditional and unconditional forecasts would follow a similar path. Instead, if a high mitigation with low emissions scenario were to be followed, the conditional temperature paths would remain below the unconditional trajectory after 2040, i.e. temperatures increases can potentially slow down in a meaningful way, but the lags for changes in emissions to have an effect are quite substantial. The latter should be taken into account greatly when designing response policies to climate change.