Overall Objectives
Research Program
Application Domains
Software and Platforms
New Results
Bilateral Contracts and Grants with Industry
Partnerships and Cooperations
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Section: New Results

Computing environmental accounts from the consumer's viewpoint using Input Output Analysis

The Russian-American economist Wassily Leontief introduced Input-Output Analysis (IOA) in the 30's and was awarded the Nobel prize in economy in 1973 for this contribution. IOA is a macro-economic tool which investigates the links and retroactions between the sectors of an economy. It makes it possible to allocate production factors (labor, capital etc.) and environmental externalities of production processes (depletion on resources, emission of pollutants etc.) to final consumption. Our first task was to reproduce the results from various studies on the carbon footprint of France. We couldn't reproduce the results from Analyse des impacts environnementaux de la consommation des ménages et des marges de manœuvre pour réduire ces impacts (Ademe, 2012). We underlined a mistake in the mathematical formulas presented in the annex of the paper but couldn't concur it was indeed the source of discrepancy because we were not granted access to the raw data of the study. Our results are however in line with the papers originating from the statistical service of the ministry of ecology (SOeS, J-L Pasquier).

Because working on excel sheets, although widespread in a large number of agencies, proves very inefficient, we started to work on the development of a software called Wassily (see "new results" section) that would automatize the critical calculations. We prepared databases on input-output tables and air emissions of several European countries based on Eurostat data and started to work on the architecture of the software with Julien Alapetite. In parallel, we reviewed the downscaling and regionalizing techniques in the IO literature and looked for the necessary information concerning the Rhône-Alpes region. We concluded that enough data was available in order to carry out downscaling but that data was still too scarce for the finer levels of regionalizing.