62 research outputs found

    Elenco degli argomenti trattati a lezione

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    List of topics discussed during classes

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    Iterative and Recursive Estimation in Structural Non-Adaptive Models

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    An inference method, called latent backfitting is proposed. It appears well suited for econometric models where the structural relationships of interest define the observed endogenous variables as a known function of unobserved state variables and unknown parameters. This nonlinear state space specification paves the way for iterative or recursive EM-like strategies. In the E-steps the state variables are forecasted given the observations and a value of the parameters. In the M-steps these forecasts are used to deduce estimators of the unknown parameters from the statistical model of latent variables. The proposed iterative/recursive estimation is particularly useful for latent regression models and for dynamic equilibrium models involving latent state variables. Practical implementation issues are discussed through the example of term structure models of interest rates. Nous proposons une méthode d'inférence appelée «latent backfitting». Cette méthode est spécialement conçue pour les modèles économétriques dans lesquels les relations structurelles d'intérêt définissent les variables endogènes observées comme une fonction connue des variables d'états non observées et des paramètres inconnus. Cette spécification espace-état non linéaire ouvre la voie à des stratégies itératives ou récursives de type EM. Dans l'étape E, les variables d'état sont prédites à partir des observations et des valeurs des paramètres. Dans l'étape M, ces prévisions sont utilisées pour déduire des estimateurs des paramètres inconnus à partir du modèle statistique des variables latentes. L'estimation itérative/récursive proposée est particulièrement utile pour les modèles avec équation de régression latente et les modèles dynamiques d'équilibre utilisant des variables d'état latentes. Les questions relatives à l'application de ces méthodes sont analysées à travers l'exemple des modèles de structure par termes des taux d'intérêt.Asset Pricing Models, Latent Variables, Estimation, Iterative or Recursive Algorithms, Modèles d'évaluation d'actifs financiers, variables latentes, estimation, algorithmes itératifs ou récursifs

    Efficient Importance Sampling Maximum Likelihood Estimation of Stochastic Differential Equations

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    This paper considers ML estimation of a diffusion process observed discretely. Since the exact loglikelihood is generally not available, it must be approximated. We review the most efficient approaches in the literature, and point to some drawbacks. We propose to approximate the loglikelihood using the EIS strategy (Richard and Zhang, 1998), and detail its implementation for univariate homogeneous processes. Some Monte Carlo experiments evaluate its performance against an alternative IS strategy (Durham and Gallant, 2002), showing that EIS is at least equivalent, if not superior, while allowing a greater flexibility needed when examining more complicated models

    Entry-Exit Timing and Profit Sharing

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    We analyze the effects of two compound investment options, a shut down and a reopening option, on a Aoki's profit sharing firm organization. Whilst the introduction of a credible threat of shutting down weakens labour's position in the bargaining and favors the shareholders on profit sharing, the option to reopen the plant acts in the opposite direction, reducing the abandoning threat and reinforcing the workers' bargaining power. More specifically, as long as an increase in uncertainty leads to an increase in the benefit from reopening, and hence in the firm's market value, the overall result implies a weakening of the shut down threat and the profit distribution process becomes more favorable to workers

    Income inequality and banking crises: Testing the level hypothesis directly

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    We perform an empirical analysis to investigate the relationship between income inequality and the occurrence of banking crises on a panel of 33 advanced countries in the period 1970\u20132011. Differently from other empirical studies, we focus on levels rather than growth rates of income inequality. We find a statistically significant and positive relationship between the value of the Gini index and the probability of banking crises. This result is confirmed when income distribution is summarized by the top 1% income share

    Securitization, covered bonds and the risk taking behavior of European banks

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    This study investigates the impact of securitization and the issuance of covered bonds on the credit risk taking behavior of banks. We collected data for seven major European economies for the period between 2001 and 2014, that is, both before and after the global financial crisis of 2008. In this paper. we address self-selection concerns about the endogeneity of the decision to securitize or issue covered bonds by using the Covariance Balancing Propensity Score method. We inquire whether securitizing banks hold portfolios that contain riskier assets than those of banks that issue covered bonds and whether the risk taking behavior of banks changed after the recent financial crisis. Our results suggest that European banks typically view securitization as a financing rather than a risk management tool. Therefore, our findings do not support the conventional wisdom that the absence of skin in the game causes banks to assume more risk. Instead, we find evidence that securitizing banks have been opting for lower risk asset portfolios after the 2008 crisis

    Algorithmic collusion, genuine and spurious

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    We clarify the difference between the asynchronous pricing algorithms analyzed by Asker, Fershtman and Pakes (2021) and those considered in the previous literature. The difference lies in the way the algorithms explore: randomly or mechanically. We reaffirm that with random exploration, asynchronous pricing algorithms learn genuinely collusive strategies

    Algorithmic collusion with imperfect monitoring

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    Published online: 14 February 2021We show that if they are allowed enough time to complete the learning, Q-learning algorithms can learn to collude in an environment with imperfect monitoring adapted from Green and Porter (1984), without having been instructed to do so, and without communicating with one another. Collusion is sustained by punishments that take the form of “price wars” triggered by the observation of low prices. The punishments have a finite duration, being harsher initially and then gradually fading away. Such punishments are triggered both by deviations and by adverse demand shocks
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