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Christian FRANCQ (Crest and Université Lille 3)
Estimating the marginal law of a time series with applications to heavy tailed distributions, with Jean-Michel Zakoïan
Abstract: In absence of precise information on the dynamics of a stationary time series, a natural estimator for a parametric marginal distribution is obtained by maximization of the "quasi marginal" likelihood, which is a likelihood written as if the observations were independent. We study the effect of the (neglected) dynamics on the asymptotic behavior of this estimator. The consistency and asymptotic normality of the estimator are established under mild assumptions on the dependence structure. Applications of the asymptotic results to the estimation of stable, generalized extreme value and generalized Pareto distributions are proposed. The theoretical results are illustrated on financial index returns.

Stéphane AURAY (Crest - Ensai)
Wars as Large Depreciation Shocks, with Aurélien Eyquem and Frédéric Jouneau-Sion
Abstract: In this paper, we propose a theoretical framework to investigate the impact of conflicts and wars on key macroeconomic aggregates and welfare. Using a panel data with 12 countries from 1875 onwards we first show that consumption drops more than output during conflicts, while the opposite is true during "peaceful" recessions. To handle both cases, we build a variation of a Real Business Cycle model first proposed by Hercowitz and Sampson [1991]. We extend the initial model to account for specific shocks that destroy capital stocks { as conflicts do{ by assuming an (exogenously) time{varying depreciation rate of the stock of capital. In addition to these shocks, the model also imbeds generalized TFP shocks capturing standard technological factors as well as the potential effects of human losses on production. The model is able to reproduce the different responses of macroeconomic aggregate to productivity shocks during peaceful periods as well as their responses during conflicts. We describe how these two sources of randomness in the model may be extracted from the available data, and analyze how they interact. We conclude that conflicts have significant and persistent inffluence on generalized TFP shocks, while the "reverse" effect is not statistically significant. Finally, we show that the welfare costs of conflicts such as World War II are substantially larger than the welfare costs of business cycles usually reported in the literature.

Jean Yves PITARAKIS (Southampton University)
Regime Specic Predictability in Predictive Regressions, with Jesus Gonzalo
Abstract: Predictive regressions are linear specications linking a noisy variable such as stock returns to past values of a very persistent regressor with the aim of assessing the presence of predictability. Key complications that arise are the potential presence of endogeneity and the poor adequacy of asymptotic approximations. In this paper we develop tests for uncovering the presence of predictability in such models when the strength or direction of predictability may alternate across different economically meaningful episodes. An empirical application reconsiders the Dividend Yield based return predictability and documents a strong predictability that is countercyclical, occurring solely during bad economic times.

Guillaume LEPAGE (Crest-Ensae)
Maximum Likelihood Estimation for Conditionally Heteroscedastic Models when the Innovation Process is in the Domain of Attraction of a Stable Law

Adriana CORNEA (Imperial College Business School)
Bootstrapping with fat-tailed asymmetries, with Karim Abadir

David VEREDAS (ECARES et Université libre de Bruxelles)
(Very) Fast Estimation and Testing for (very) Large Dimensional Heavy-Tailed Elliptical Distributions, with Yves Dominicy and Hiroaki Ogata
Abstract: We propose a quantile-based method to estimate the parameters of an elliptical distribution (i.e. location, dispersion and tail index) and a battery of tests for model adequacy. Estimation is applicable and very fast for vast dimensions since the estimators for the location vector and the dispersion matrix have closed-form expressions. The tests for model adequacy test the null hypothesis of correct specification of one or several level contours. A Monte Carlo study to three classes of elliptical distributions (Gaussian, Student-t and elliptical stable) for dimensions 20, 200 and 2000 reveals the goodness of the method, both in terms of computational time and for finite samples. An empirical applications to financial data illustrate the usefulness of the method.

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