Data insufficiency and reporting threshold are two main issues in operational risk modelling. When these conditions are present, maximum likelihood estimation (MLE) may produce very poor parameter estimates. In this study, we first investigate four methods to estimate the parameters of truncated...

We derive distribution free tests based on the Maximum Entropy densities to test the null hypotheses of symmetry and normality. The proposed tests are derived from maximizing the differential entropy subject to moment constraints. By exploiting the equivalence between Maximum Entropy and Maximum...

This study proposes an information-theoretic deconvolution method to approximate the entire distribution of individual treatment effect. This method uses higher-order information implied by the standard average treatment effect estimator to construct a maximum entropy approximation to the...

Spot electricity prices are very volatile, particularly due to the fact that electricity cannot be economically stored and requires immediate delivery. However, the inability to store electricity means that fluctuations in demand and supply are often transmitted directly into spot prices of...

In this paper we study the finite sample behavior of the Hill estimator under α-stable distributions. Using large Monte Carlo simulations we show that the Hill estimator overestimates the true tail exponent and can hardly be used on samples with small length. Utilizing our results, we introduce...

We consider structural vector autoregressions identified through stochastic volatility. Our focus is on whether a particular structural shock is identified by heteroskedasticity without the need to impose any sign or exclusion restrictions. Three contributions emerge from our exercise: (i) a set...

This paper compares two methods for undertaking likelihood-based inference in dynamic equilibrium economies: a Sequential Monte Carlo filter proposed by Fernandez-Villaverde and Rubio-Ramirez (2004) and the Kalman filter. The Sequential Monte Carlo filter exploits the nonlinear structure of the...

For p 4 and one observation X on a p-dimensional spherically symmetric distribution, minimax estimators of Theta whose risks are smaller than the risk of X (the best invariant estimator) are found when the loss is a nondecreasing concave function of quadratic loss. For n observations X1, X2, ......

In this paper we consider the ducial argument of Fisher from the point of view of constructing e cient approximations of (or importance distributions to) posterior distributions in econometric models with intractable likelihood functions. The importance or proposal distributions are used along...

In this paper we take up Bayesian inference in multivariate stable distributions through innovative multivariate stable copulae. The problem that the characteristic function is defined through a difficult object, the spectral measure is completely bypassed by our approach. The new methods are...