We use the EM algorithm to derive recursive expressions for maximum likelihood location and scale estimators for Tukey's corner distributions, in particular the one-wild. This now enables optimal estimation for the triefficiency criterion used to appraise robust estimators. The effect of...

In this paper, we introduce the simulated maximum likelihood method for identifying behavioral heuristics of heterogeneous agents in the baseline three-equation New Keynesian model. The method is extended to multivariate macroeconomic optimization problems, and the estimation procedure is...

This paper considers estimation of parameters of diffusion terms from CIR models for estimation of stock prices. Feasibility of some known methods are tested for Monte-Carlo simulated data and for the historical prices, including individual stocks and stock indexes

Semiparametric correction for a sample selection bias in the presence of endogenous truncation is known to be much more difficult in the case of a binary selection variable than in the case of a continuous selection variable. This paper proposes a simple bandwidth-free semiparametric methodology...

In this article, we have tested the volatility of the returns of the spot exchange rate of AUD/USD for changing conditional variances by using a log likelihood model. Generalized autoregressive conditional heteroskedastic models, (GARCH) with t-distributed errors, and exponential generalized...

This work proposes a globally convergent algorithm, based on gradient projections, for maximum likelihood (ML) estimation under linear equality and inequality restrictions (constraints) on parameters. The proposed algorithm has wide applicability, and as an important special case its application...

The purpose of the present paper is to study in which cases the method of maximum likelihood is more preferential than other estimation methods of unknown distribution parameters, and also when it is necessary to use the Akaike or the RMSE criteria for selection of statistical models.The...

We consider the Fractional Vector Error Correction model proposed in Avarucci (2007), which is characterized by a richer lag structure than the models proposed in Granger (1986) and Johansen (2008, 2009). In particular, we discuss the properties of the model of Avarucci (2007) (FECM) in...