Maximum likelihood estimation for dynamic factor models with missing data

Maximum Likelihood Estimation in Graphical Models with Missing Values

Quasi Maximum-Likelihood Estimation of Dynamic Panel Data Models

This paper establishes the almost sure convergence and asymptotic normality of levels and differenced quasi maximum-likelihood (QML) estimators of dynamic panel data models. The QML estimators are robust with respect to initial conditions, conditional and time-series heteroskedasticity, and misspecification of the log-likelihood. The paper also provides an ECME algorithm for calculating levels ...

Maximum likelihood estimation of large factor model on datasets with arbitrary pattern of missing data

In this paper we show how to estimate a large dynamic factor model on datasets with an arbitrary pattern of missing data. The framework allows to handle efficiently and in an automatic manner sets of indicators characterized by different publication delays, frequencies and sample lengths. This can be relevant e.g. for young economies for which many indicators are compiled only since recently. W...

Estimation of Dynamic Models with Nonparametric Simulated Maximum Likelihood

We propose a simulated maximum likelihood estimator (SMLE) for general stochastic dynamic models based on nonparametric kernel methods. The method requires that, while the actual likelihood function cannot be written down, we can still simulate observations from the model. From the simulated observations, we estimate the unknown density of the model nonparametrically by kernel methods, and then...

Maximum Likelihood Estimation of Nonlinear Structural Equation Models with Ignorable Missing Data

The existing maximum likelihood theory and its computer software in structural equation modeling are established on the basis of linear relationships among latent variables with fully observed data. However, in social and behavioral sciences, nonlinear relationships among the latent variables are important for establishing more meaningful models and it is very common to encounter missing data. ...