Unravelling the Influence of Household Characteristics and Decisions on their Carbon Footprint: A Quantile Regression Analysis

Raphaël Semet

Economie et Statistique / Economics and Statistics, 2024, issue 545, 27-46

Abstract: [eng] This study uses data from the 2017 French Household Budget Survey (enquête Budget de famille) and an input-output model to examine the carbon footprint distribution of French households. Using multivariate nested models and quantile regression techniques, it explores disparities in households carbon footprints stemming from socioeconomic characteristics (e.g., size, age, education), income, or household decisions (e.g., home energy source, dwelling type, car ownership). The findings show that the three dimensions are crucial for understanding carbon footprint differences. Other characteristics being equal, education, age and household size, influence carbon emissions. Household decisions also have great explanatory power, especially at the bottom of the distribution, while the type of urban unit (urban/peri-urban/rural) has no significant influence on carbon emissions.

Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:nse:ecosta:ecostat_2024_545_2

DOI: 10.24187/ecostat.2024.545.2127

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