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Purpose – The purpose of this chapter is twofold: to forecast gross domestic product (GDP) using nonparametric method, known as multivariate k-nearest neighbors method, and to provide asymptotic properties for this method.

Methodology/approach – We consider monthly and quarterly macroeconomic variables, and to match the quarterly GDP, we estimate the missing monthly economic variables using multivariate k-nearest neighbors method and parametric vector autoregressive (VAR) modeling. Then linking these monthly macroeconomic variables through the use of bridge equations, we can produce nowcasting and forecasting of GDP.

Findings – Using multivariate k-nearest neighbors method, we provide a forecast of the euro area monthly economic indicator and quarterly GDP, which is better than that obtained with a competitive linear VAR modeling. We also provide the asymptotic normality of this k-nearest neighbors regression estimator for dependent time series, as a confidence interval for point forecast in time series.

Originality/value of chapter – We provide a new theoretical result for nonparametric method and propose a novel methodology for forecasting using macroeconomic data.

The aim of this paper is to show evidence and to quantify with forensic econometric methods the impact of the missing trader fraud (MTF) on European carbon allowances markets. This fraud occurred mainly between the end of 2008 and the beginning of 2009. In this paper, the financial mechanisms of the fraud are explored and the impact on the market behaviour, as well as the consequences on its econometric features.

In a previous work, the first and second authors showed that the European carbon market is strongly influenced by fundamentals factors as oil, energy, gas, coal and equities. Therefore, the authors calibrated arbitrage pricing theory‐like models. These models enabled the impact of each factor on the market to be quantified. In this study, the authors focused more precisely on spot prices quoted on Paris‐based Bluenext market over 2008 and 2009. During this period, a significant drop in performances and robustness of the model and a reduced sensitivity of carbon prices to fundamentals was observed.

The authors identify the period where the market was driven by MTF movements and 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. The authors estimate the impact of the value added tax extortion on the carbon market at €1.3 billion.

This paper describes the first study that attempts to prove and quantify scientifically the MTF on emission markets.

During the global financial crisis of 2008–2009, most developed and emerging economies and financial markets have recorded important financial losses. Those economies have experienced momentous corrections, and their assets were significantly devaluated, implying many losses and bankruptcies for banks, investors, and firms. Overall, despite continuing efforts made by governments and central banks to support their financial systems, most financial markets (stock markets, derivative markets, monetary markets, and currency markets) have been strongly affected by this crisis. Furthermore, the rapid transmission of the US subprime crisis to several European and Asian developed and emerging countries and the transformation into a global financial and economic crisis have revealed a high level of financial integration and linkage with the US market. The financial shocks have also induced negative feedbacks to macroeconomic indicators, suggesting significant relationships between financial markets and macroeconomies.

The purpose of this paper is to recognize the effect of the VAT fraud upon the market prices and to assess the occurrence of money laundering on the carbon emissions market. The paper presents an analytic breakdown of the MTIC pocketed funds and estimates the bearish impact of the VAT trade on the carbon prices. The VAT carousel could also be used for all the steps of money laundering given the lack of control and surveillance of various trading firms.

In a previous work by Frunza and Guégan it was shown that the European carbon market is strongly influenced by fundamentals factors such as oil, energy, gas, coal and equities. Using public market prices and volumes for both futures and spot exchanges, the model allows us to assess and quantify the spread between the observed carbon prices and the theoretical fundamental prices. The dataset analysis reveals that the spot volumes remained abnormally high compared to an empirical economic level, even after the end of the VAT fraud on the organised exchange. These abnormal volumes could be explained by the occurrence of speculative trading linked to the money laundering.

Findings present an analytic breakdown of the MTIC pocketed funds and a bearish impact of 2‐3 euros upon the carbon prices. The paper also explains the origin of a relative persistence of high volumes on the spot market by proposing a model of placement, layering and integration steps on the carbon emissions market, similar to the VAT carousel.

This paper is the first study that quantifies the market manipulation effect due to VAT fraud. The work is also unique as it provides the first estimation of money laundered on the carbon emission market.