本研究使用了2019年家庭收支調查表估計家庭碳排放量。透過此家庭碳排放量，我們用OLS回歸和分量回歸，分析了家庭收入與總/直接/間接碳排放的關係。分析結果顯示控制詳細的家庭收入來源可以使我們更好的瞭解家庭收入如何影響碳排放。OLS回歸結果表明，除了家戶雜項收入外，其他家庭收入來源係數均顯著為正。分量回歸的結果主要表明，家庭收入對較高碳排放量家庭的影響更大。家庭特徵可以看到家戶戶長年齡、男戶長家戶、家庭成員人數、戶長教育程度與家庭總碳排放量呈正相關。家戶65歲以上人口數與家庭總碳排放量呈負相關。此外，結果表明家戶所得對家庭間接碳排放的影響大於對家庭直接碳排放的影響。因此，促進購買二手物品和低碳足跡產品可能會成為未來的重要目標。

In this study, we estimated household carbon emissions using the 2019 Survey of Family Income and Expenditure. By estimating household carbon emissions, we analyzed the relationship between household income and direct/indirect carbon emission through dividing income sources into six categories with OLS regression and quantile regression. The results provide better understanding of how household incomes affect carbon emissions with detailed household income compositions. The OLS regression results show that the coefficients of household income sources are significantly positive except the household income from miscellaneous income. The results from the quantile regression mainly shows that household incomes have higher effects on higher household carbon emission quantiles. With respect to household characteristics, the age of household heads, male-headed households, the number of household members, and the educational attainment of household heads is positively correlated with household total carbon emission. The number of persons above 65 years old is negatively correlated with the household total carbon emission. Furthermore, the results shows that the effects of household income on household indirect carbon emission are larger than that on household direct carbon emission. Thus, promotion to purchase second-handed items and low carbon footprint products can become an important target in the future.

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