Previous research has largely overlooked electricity trade when estimating marginal emission factors (MEFs), despite its growing significance in Europe and beyond. This study introduces a robust and consistent econometric framework to accurately estimate the MEFs for trade, demand, and different supply technologies in a highly interconnected market. We use exogenous supply shocks (variations in wind electricity) in adjacent markets as an instrument for trade flows, which are endogenous to CO2 emissions, to generate unbiased MEF estimates. Our analysis, applied to high-frequency and publicly accessible data from Germany, reveals that exports are predominantly driven by lignite and hard coal, leading to considerable additional emissions. We further demonstrate that disregarding trade or ignoring its reverse causality results in substantial estimation biases. Unbiased MEF estimates are essential for shaping informed and effective policy decisions aimed at mitigating the environmental impact of energy systems in interconnected markets.

中文翻译：

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超越国界：估算电力交易的边际排放因子

在估计边际排放因子 （MEF） 时，以前的研究在很大程度上忽视了电力贸易，尽管它在欧洲及其他地区的重要性越来越大。本研究引入了一个稳健且一致的计量经济学框架，以准确估计高度互联市场中贸易、需求和不同供应技术的 MEF。我们使用相邻市场的外生供应冲击（风电的变化）作为贸易流动的工具，这是 CO2 排放的内生性，以生成无偏的 MEF 估计。我们的分析应用于来自德国的高频和公开访问的数据，表明出口主要由褐煤和硬煤驱动，导致相当大的额外排放。我们进一步证明，忽视贸易或忽略其反向因果关系会导致巨大的估计偏差。公正的 MEF 估计对于制定明智和有效的政策决策至关重要，这些决策旨在减轻相互关联的市场中能源系统对环境的影响。