This paper considers issues related to identification, inference, and computation in linearized dynamic stochastic general equilibrium (DSGE) models. We first provide a necessary and sufficient condition for the local identification of the structural parameters based on the (first and) second...

The paper deals with estimation of missing observations in possibly nonstationary ARIMA models. First, the model is assumed known, and the structure of the interpolation filter is analysed. Using the inverse or dual autocorrelation function it is seen how estimation of a missing observation is...

It is well-known that outliers exist in the type of multivariate data used by financial practitioners for portfolio construction and risk management. Typically, outliers are addressed prior to model fitting by applying some combination of trimming and/or Winsorization to each individual...

This paper extends the existing literature on linear quadratic adjustment cost (LQAC) models under rational expectations to the inferential issues arising when: (i) agents optimise with respect to a vector of endogenous variables; (ii) the behavioural equations stemming from the agent's...

This article surveys estimation in stationary time series models using the approach of optimal instrumentation. We review tools that allow construction and implementation of optimal instrumental variables estimators in various circumstances - in single- and multi-period models, in the absence...

The aim of this paper is to apply the methods of Symbolic Time Series Analysis (STSA) to series of inflation from a group of Latin-American economies. Starting with a partition of two inflation regimes, we use data symbolization for identifying temporal patterns. Afterwards the statistical...

In this paper, we prove the validity of an Edgeworth expansion to the distribution of the Whittle maximum likelihood estimator for stationary long-memory Gaussian models with unknown parameter theta in Theta subset R^{d_theta) . The error of the (s-2)-order expansion is shown to be...

This chapter presents a unified set of estimation methods for fitting a rich array of models describing dynamic relationships within a longitudinal data setting. The discussion surveys approaches for characterizing the micro dynamics of continuous dependent variables both over time and across...

The paper deals with estimation of missing observations in possibly nonstationary ARIMA models. First, the model is assumed known, and the structure of the interpolation filter is analysed. Using the inverse or dual autocorrelation function it is seen how estimation of a missing observation is...

The paper proposes an original class of conditionally heteroskedastic models aimed to capture contemporaneous asymmetry. Not only past up and down moves of stock market returns have different impacts on the conditional variance, but also, positive and negative changes are governed by different...