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Statistical evidence of tax fraud on the carbon allowances market

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The aim of this paper is to show evidence and to quantify with forensic econometric methods the impact of the Value Added Tax fraud on European carbon allowances markets. This fraud mainly occurred at the beginning of between the end of 2008 and the beginning of 2009. In this paper, we explore the financial mechanisms of the fraud and the impact on the market behavior as well as the reflexion on its econometric features. In a previous work, we showed that the European carbon market is strongly influenced by fundamentals factors as oil, energy, gas, coal and equity prices. Therefore, we calibrated Arbitrage Pricing Theory-like models and showed that they have a good forecast capacity. Those models enabled us to quantify the impact of each factor on the market. In this study, we focused more precisely on the benchmark contract for European carbon emissions prices over 2008 and 2009. We observed that during the first semester of 2009, there is a significant drop in our model performances and robustness and that the part of market volatility explained by fundamentals reduced. Therefore, we identified the period where the market was driven by VAT fraud movements and we were able to measure the value of this fraud. Soon after governments passed a law that cut the possibility of fraud occurrence the performance of the model improved rapidly. We estimate the impact of the VAT extortion on the carbon market at 1.3 billion euros

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  • Marius-Cristian Frunza & Dominique Guegan & Antonin Lassoudière, 2010. "Statistical evidence of tax fraud on the carbon allowances market," Documents de travail du Centre d'Economie de la Sorbonne 10069, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
  • Handle: RePEc:mse:cesdoc:10069
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    1. Abdou Kâ Diongue & Dominique Guegan & Rodney C. Wolff, 2010. "BL-GARCH model with elliptical distributed innovations," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00368340, HAL.
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    Keywords

    Carbon; EUA; energy; arbitrage pricing theory; switching regimes; hidden Markov Chain Model; forecast;

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