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Pulling Ourselves Up by our Bootstraps: The Greenhouse Gas Value of Products, Enterprises and Industries

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  • von Kalckreuth, Ulf

Abstract

This paper presents a system of greenhouse gas indicators for markets and policymakers. The system is lean and informative. It condenses the relevant product and enterprise-specific information into a single number: the greenhouse gas (GHG) value. Like prices, GHG values are easy to understand, manage and communicate. The envisaged scenario is one in which, at all levels of production, goods and services have two tags - the financial price to pay and the GHG value. GHG values are interdependent. The value for any product will depend on the carbon costs of all inputs. This paper shows that the massive information processing this simultaneity involves can be handed over to the market. Analytically, the system of product-level indicators is solved for the reduced form, the vector of true GHG values. This vector is shown to be the fixed point to which measurement will converge if producers comput e GHG values using the information they have: data from their input providers if available, and estimates elsewhere. This amounts to a process of collective, decentralised learning. Technological changes will automatically be accounted for. A micro-simulation exercise is carried out based on sectoral information on production structure from Germany. The results indicate that convergence is fast. W ith appropriate institutional underpinning, the disclosure of GHG values by producers may become self-sustaining.
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  • von Kalckreuth, Ulf, 2022. "Pulling Ourselves Up by our Bootstraps: The Greenhouse Gas Value of Products, Enterprises and Industries," VfS Annual Conference 2022 (Basel): Big Data in Economics 264036, Verein für Socialpolitik / German Economic Association.
  • Handle: RePEc:zbw:vfsc22:264036
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    1. Konstantin Stadler & Richard Wood & Tatyana Bulavskaya & Carl†Johan Södersten & Moana Simas & Sarah Schmidt & Arkaitz Usubiaga & José Acosta†Fernández & Jeroen Kuenen & Martin Bruckner & Stefan, 2018. "EXIOBASE 3: Developing a Time Series of Detailed Environmentally Extended Multi†Regional Input†Output Tables," Journal of Industrial Ecology, Yale University, vol. 22(3), pages 502-515, June.
    2. Stefano Merciai & Jannick Schmidt, 2018. "Methodology for the Construction of Global Multi†Regional Hybrid Supply and Use Tables for the EXIOBASE v3 Database," Journal of Industrial Ecology, Yale University, vol. 22(3), pages 516-531, June.
    3. Kirsten S. Wiebe & Norihiko Yamano, 2016. "Estimating CO2 Emissions Embodied in Final Demand and Trade Using the OECD ICIO 2015: Methodology and Results," OECD Science, Technology and Industry Working Papers 2016/5, OECD Publishing.
    4. Stiglitz, Joseph E & Weiss, Andrew, 1981. "Credit Rationing in Markets with Imperfect Information," American Economic Review, American Economic Association, vol. 71(3), pages 393-410, June.
    5. United Nations, 2014. "System of Environmental-Economic Accounting 2012," World Bank Publications - Books, The World Bank Group, number 23959.
    6. Fabienne Fortanier & Guannan Miao & Ans Kolk & Niccolò Pisani, 2020. "Accounting for firm heterogeneity in global value chains," Journal of International Business Studies, Palgrave Macmillan;Academy of International Business, vol. 51(3), pages 432-453, April.
    7. Leontief, Wassily, 1970. "Environmental Repercussions and the Economic Structure: An Input-Output Approach," The Review of Economics and Statistics, MIT Press, vol. 52(3), pages 262-271, August.
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    More about this item

    JEL classification:

    • Q56 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environment and Development; Environment and Trade; Sustainability; Environmental Accounts and Accounting; Environmental Equity; Population Growth
    • Q51 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Valuation of Environmental Effects
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access

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