Estimation in nonlinear time series models has mainly been performed by least squares or maximum likelihood (ML) methods. The paper suggests and studies the performance of generalized method of moments (GMM) and indirect estimators for the autoregressive asymmetric moving average model. Both...

This short paper proposes a simultaneous equations model formulation for time series of count data. Some of the basic moment properties of the model are obtained. The inclusion of real valued exogenous variables is suggested to be through the parameters of the model. Some remarks on the...

The paper suggests and studies count data models corresponding to previously studied spatial econometric models for continuous variables. A novel way of incorporating spatial weights is considered for both time and space dynamic models with or without simultaneity. The paper also contains a...

The paper considers conditional duration models in which durations are in continuous time but measured in grouped or discretized form. This feature of recorded durations in combination with a frequently traded stock is expected to negatively influence the performance of conventional estimators....

The paper introduces a new approach to incorporating time dependent overdispersion for Poisson related regression models. To handle the added flexibility in conditional heteroskedasticity in time series count data some wellknown estimators are adapted and a GMM type estimator is suggested. The...

The integer-valued moving average model is advanced to model the number of transactions in intra-day data of stocks. The conditional mean and variance properties are discussed and model extensions to include, e.g., explanatory variables are offered. Least squares and generalized method of moment...

The integer-valued AR(1) model is generalized to encompass some of the more likely features of economic time series of count data. The generalizations come at the price of loosing exact distributional properties. For most specifications the first and second order both conditional and...

The impact of news from the Moscow and New York stock exchanges on the daily returns and volatilities of Baltic stock market indices is studied. A nonlinear time series model that accounts for asymmetries in conditional mean and variance functions is used for the empirical work. News from New...

The paper proposes two estimation approaches for duration models that are subject to right censored observations and selection effects. Main focus is on accelerated duration models and the estimators that are of the limited information type, i.e. they are not based on a fully specified selection...