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Measure or Management?—Resource Use Indicators for Policymakers Based on Microdata by Households

Author

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  • Johannes Buhl

    (Wuppertal Institut fuer Klima, Umwelt, Energie gGmbH, Division Sustainable Production and Consumption, Doeppersberg 19, 42103 Wuppertal, Germany)

  • Christa Liedtke

    (Wuppertal Institut fuer Klima, Umwelt, Energie gGmbH, Division Sustainable Production and Consumption, Doeppersberg 19, 42103 Wuppertal, Germany
    Industrial Design, Folkwang University of the Arts, Klemensborn 39, 45239 Essen, Germany)

  • Jens Teubler

    (Wuppertal Institut fuer Klima, Umwelt, Energie gGmbH, Division Sustainable Production and Consumption, Doeppersberg 19, 42103 Wuppertal, Germany)

  • Katrin Bienge

    (Wuppertal Institut fuer Klima, Umwelt, Energie gGmbH, Division Sustainable Production and Consumption, Doeppersberg 19, 42103 Wuppertal, Germany)

  • Nicholas Schmidt

    (Faculty of Management and Economics, Ruhr University Bochum, Universitätsstraße 150, 44801 Bochum, Germany)

Abstract

Sustainable Development Goal 12 (SDG 12) requires sustainable production and consumption. One indicator named in the SDG for resource use is the (national) material footprint. A method and disaggregated data basis that differentiates the material footprint for production and consumption according to, e.g., sectors, fields of consumption as well as socioeconomic criteria does not yet exist. We present two methods and its results for analyzing resource the consumption of private households based on microdata: (1) an indicator based on representative expenditure data in Germany and (2) an indicator based on survey data from a web tool. By these means, we aim to contribute to monitoring the Sustainable Development Goals, especially the sustainable management and efficient use of natural resources. Indicators based on microdata ensure that indicators can be disaggregated by socioeconomic characteristics like age, sex, income, or geographic location. Results from both methods show a right-skewed distribution of the Material Footprint in Germany and, for instance, an increasing Material Footprint with increasing household income. The methods enable researchers and policymakers to evaluate trends in resource use and to differentiate between lifestyles and along socioeconomic characteristics. This, in turn, would allow us to tailor sustainable consumption policies to household needs and restrictions.

Suggested Citation

  • Johannes Buhl & Christa Liedtke & Jens Teubler & Katrin Bienge & Nicholas Schmidt, 2018. "Measure or Management?—Resource Use Indicators for Policymakers Based on Microdata by Households," Sustainability, MDPI, vol. 10(12), pages 1-16, November.
    • Handle: RePEc:gam:jsusta:v:10:y:2018:i:12:p:4467-:d:186109
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    References listed on IDEAS

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    1. Richard Wood & Konstantin Stadler & Tatyana Bulavskaya & Stephan Lutter & Stefan Giljum & Arjan De Koning & Jeroen Kuenen & Helmut Schütz & José Acosta-Fernández & Arkaitz Usubiaga & Moana Simas & Olg, 2014. "Global Sustainability Accounting—Developing EXIOBASE for Multi-Regional Footprint Analysis," Sustainability, MDPI, vol. 7(1), pages 1-26, December.
    2. Johannes Buhl, 2014. "Revisiting Rebound Effects from Material Resource Use. Indications for Germany Considering Social Heterogeneity," Resources, MDPI, vol. 3(1), pages 1-17, February.
    3. Teubler, Jens & Buhl, Johannes & Lettenmeier, Michael & Greiff, Kathrin & Liedtke, Christa, 2018. "A Household's Burden – The Embodied Resource Use of Household Equipment in Germany," Ecological Economics, Elsevier, vol. 146(C), pages 96-105.
    4. Johannes Buhl & Jens Teubler & Christa Liedtke & Karin Stadler, 2017. "Der Ressourcenverbrauch privater Haushalte in NRW [The resource use of private households in North Rhine-Westphalia, Germany]," Sustainability Nexus Forum, Springer, vol. 25(3), pages 255-264, November.
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    Cited by:

    1. Johannes Buhl & Christa Liedtke & Sebastian Schuster & Katrin Bienge, 2020. "Predicting the Material Footprint in Germany between 2015 and 2020 via Seasonally Decomposed Autoregressive and Exponential Smoothing Algorithms," Resources, MDPI, vol. 9(11), pages 1-17, October.
    2. Florence Ziesemer & Alexandra Hüttel & Ingo Balderjahn, 2019. "Pioneers’ Insights into Governing Social Innovation for Sustainable Anti-Consumption," Sustainability, MDPI, vol. 11(23), pages 1-16, November.
    3. Jacksohn, Anke & Tovar Reaños, Miguel Angel & Pothen, Frank & Rehdanz, Katrin, 2024. "Corrigendum to “Trends in household demand and greenhouse gas footprints in Germany: Evidence from microdata of the last 20 years” [Ecological Economics 208 (2023) 1077575]," Ecological Economics, Elsevier, vol. 216(C).

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