【摘要】 应对气候变化是21世纪人类可持续发展的核心议题之一。本文研究了一国气温冲击通过贸易网络对其他国家（或地区）经济增长的溢出效应，发现贸易网络的溢出效应在总效应中占比高达64.91%。在本文理论模型中，气温冲击对经济增长的影响被分解为直接效应和贸易网络溢出效应，揭示了气温冲击通过贸易网络的传导对经济增长的影响与机制。基于全球气温观测数据和国际贸易数据，本文运用社会网络因果推断方法，识别和估计了本国气温冲击的直接效应和邻国气温冲击的贸易网络溢出效应。本文研究发现，一国的经济增长不仅受本国气温冲击的显著影响，还通过贸易网络受到邻国气温冲击的溢出影响。安慰剂分析等检验验证了这一结论的稳健性。低收入国家、非热带国家、经济规模小国、沿海国家和能源富裕国家受到的负面网络溢出效应更强。机制分析表明，本国气温冲击通过降低资本存量与劳动生产率对一国经济增长产生负面影响，而贸易邻国气温冲击主要通过降低本国贸易流量对一国经济增长产生负面影响。进一步从行业分析表明，贸易邻国气温冲击主要通过农业和制造业对本国产生溢出效应。反事实模拟分析显示，若高强度气温冲击持续发生，2035年全球实际GDP的累计潜在损失约为2023年的0.4641%，而中国则为0.7264%，世界各国可以通过调整贸易结构减少全球气温冲击的损失。本文结论对于中国优化贸易网络以规避气候风险具有政策启示意义。更多还原

【Abstract】 Addressing climate change constitutes one of the core challenges for human sustainable development in the 21st century. In the absence of necessary climate change mitigation and adaptation measures, the average global temperature is projected to rise by 0.04° C per year, leading to a decline in world real GDP per capita by more than 7% by 2100(Kahn et al., 2021). Therefore,examining the impact of temperature shocks on a country’s economic growth holds substantial theoretical and practical significance for averting macroeconomic volatility caused by climate change and advancing the green transition of economic and industrial structures.However, while existing studies, such as Dell et al.(2012) and Burke et al.(2015), have found that domestic temperature shocks affect domestic economic growth, they ignored the spillover effects caused by temperature shocks through cross-regional linkage networks. Nor have they explored the mechanism of trade networks as the core transmission channel. So, they could not explain the global transmission of temperature shocks under globalization. This paper uses the network causal inference to analyze both the direct effects and network spillover effects of temperature shocks from the trade network perspective, and discusses how the structure of trade networks influences the spillover effects through counterfactual simulations.Based on Eaton & Kortum(2002), Carvalho et al.(2021), and Dell et al.(2012), we construct an international trade model with multi-country and multi-sector heterogeneities, which incorporates external temperature shocks and linkages within intermediate goods trade networks to analyze their impact on economic growth. Our model reveals the internal mechanism through which a country’s temperature shocks are transmitted to its trading partners via the trade network. Specifically, a domestic temperature shock reduces a country’s output by affecting its capital stock and labor productivity, representing the direct effect of temperature shocks. When a domestic temperature shock leads to a decline in a country’s output, it reduces the supply of key intermediate goods to its trading partners, which in turn leads to a decrease in the output of those partner countries, ultimately reducing the output of all countries within the trade network. This constitutes the spillover effect of temperature shocks.Empirically, we use the social network causal inference method proposed by Forastiere(2021,2024) to relax the Stable Unit Treatment Value Assumption(SUTVA) in existing mainstream approaches. By estimating the joint propensity scores(JPS) of domestic and trading partners’ temperature shocks, both the direct effect of a country’s own temperature shocks and the spillover effect of temperature shocks from its trading partners could be accurately identified and estimated. The empirical results indicate that a country’s temperature shocks exert a negative impact on the economic growth of its trading partners through trade network spillovers, with this spillover effect accounting for 64.91% of the total effect. Placebo test and other checks verify the robustness of our conclusion. Moreover, the negative spillover effects are more pronounced for low-income countries, non-tropical countries, small economies, coastal countries, and energy abundant countries. Mechanism analysis reveals that a country’s temperature shocks reduce its own capital stock and labor productivity, thereby dampening domestic economic growth, while temperature shocks from its trading partners primarily exert negative impacts on its agricultural and manufacturing sectors by reducing its trade flows.Finally, based on existing climate change prediction data and the estimation results of the network causal model, we simulate the paths of global and China’s economic growth under temperature shocks from both static and dynamic perspectives for different scenarios, including adjustments to trade weights and trade chain disruptions. The results indicate that if high-intensity temperature shocks persist, the cumulative potential loss of world real GDP by 2035 will be approximately 0.46% of the 2023 level, while for China, this figure will reach 0.73%. The direct loss of China caused by domestic temperature shock is lower than the global average loss, while the indirect loss of China caused by trading partners’ temperature shocks is greater than the global average loss. This paper provides a novel framework for predicting how temperature shocks impact long-term global economic growth and offers valuable policy implications for China to mitigate climate risks through optimizing the structure of its trade network.更多还原