For both deterministic or stochastic regressors, as well as parametric nonlinear or linear regression functions, we prove the weak consistency of the coefficient estimators for the Type I censored quantile regression model under different censoring mechanisms with censoring points depending on...

We propose using a Bayesian time-varying coefficient model estimated with Markov chain-Monte Carlo methods to measure contagion empirically. The proposed measure works in the joint presence of heteroskedasticity and omitted variables and does not require knowledge of the timing of the crisis. It...

This paper extends the Bayesian Model Averaging framework to panel data models where the lagged dependent variable as well as endogenous variables appear as regressors. We propose a Limited Information Bayesian Model Averaging (LIBMA) methodology and then test it using simulated data. Simulation...

This paper discusses the estimation of models of the term structure of interest rates. After reviewing the term structure models, specifically the Nelson-Siegel Model and Affine Term- Structure Model, this paper estimates the terms structure of Treasury bond yields for the United States with...

This paper examines the relative performance of some popular nonlinearity tests when applied to time series generated by Markov switching autoregressive models. The nonlinearity tests considered include RESET-type tests, the Keenan test, the Tsay test, the McLeod--Li test, the BDS test, the...

This paper reviews recent advances in the specification and estimation of Bayesian Vector Autoregressive models (BVARs). After describing the Bayesian principle of estimation, we first present the methodology originally developed by Litterman (1986) and Doan et al. (1984) and review alternative...

This paper investigates the generalized parametric measurement methods of aggregate operational risk in compliance with the regulatory capital standards for operational risk in the New Basel Capital Accord ("Basel II"). Operational risk is commonly defined as the risk of loss resulting from...

This paper examines the relative performance of some popular nonlinearity tests when applied to time series generated by Markov switching autoregressive models. The nonlinearity tests considered include RESET-type tests, the Keenan test, the Tsay test, the McLeod--Li test, the BDS test, the...

The common practice to calculate wind generation capacity values relies more on heuristic approximations than true system estimations. In this paper we proposed a more accurate method. In the first part of our analysis, a Monte Carlo simulation was created based on Markov chains to provide an...

The variability of wind power production poses the greatest challenge in the integration of large-scale wind power in power systems. Furthermore, larger-scale penetration implies a wider geographical spreading of installed wind power, resulting in reduced variability and the smoothing effect of...