The application of nonlinear fixed effects models in econometrics has often been avoided for two reasons, one methodological, one practical. The methodological question centers on a incidental parametres problem that raises questions about the statistical properties of the estimator. The...

We find a condition for the normalized sequence of independent and identically distriubted random nuclear operators to satisfy the Central Limit Theorem.

This paper "tests" the performance of the approaches of Watson (1993), DeJong, Ingram and Whiteman (1996), Canova and De Nicolo (1995) and Ortega (1998) for evaluating stochastic dynamic general equilibrium models using Monte Carlo techniques. It asks: Do different model evaluation methodologies...

This paper shows which statistical techniques can be used to validate simulation models, depending on which real-life data are available. Concerning this availability, three situations are distinguished (i) no data, (ii) only output data, and (iii) both input and output data. In case (i) - no...

We propose a new method, the "Auto-SLEX" method, for analyzing bivariate non-stationary processes. The Auto-SLEX method is a procedure that automatically segments the time series into approximatively stationary blocks and automatically estimates the time-varying spectra and coherence.

This paper provides a brief survey of the bootstrap and its use in econometrics. As an introduction, the paper gives a description of the basics of the method, with a special emphasis on boostrap testing. A fairly large amount of space is devoted to discuss why bootstrap tests provide...

Spatial statistical models are applied in many problems for which dependence in observed random variables is not easily explained by a direct scientific mechanism. In such situations there may be a latent spatial process that acts to produce the observed spatial pattern. We present methods for...

We study the influence of measurement error specification on estimation results in the context of continuous-time models of the term structure of interest rates. For this purpose, we estimate a two-factor mean-reverting stochastic model of the recent evolution of the Spanish term structure. The...

We consider a kernel based approach to nonlinear canonical correlation analysis and its implementation for time series. We deduce a test procedure of the reversibility hypothesis. The method is applied to the analysis of stochastic differential equation from high frequency data on stock returns.

We decompose a stationary Markov process (X^t) as: X^t = a^o + [Sommation from j=1 to infinity) a^j Z^(j,t), where the Z^j 's processes admit ARMA specifications. These decompositions are deduced from a nonlinear canonical decomposition of the joint distribution of (X^t, X^(t-1)).