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...

This paper analyzes how interaction effects can be consistently estimated under economically plausible assumptions in linear panel models with a fixed Tdimension. We advocate for a correlated interaction term estimator (CITE) and show that it is consistent under conditions that are not...

This paper provides a new methodology for the analysis of multiple long run relations in panel data models where the cross section dimension, n, is large relative to the time series dimension, T. For panel data models with large n researchers have focussed on panels with a single long run...

This paper analyzes price elasticities in the Austrian market for mobile telecommunications services using data on firm specific tariffs. Both static and a dynamic panel data approaches lead to consistent results which provide evidence for a relatively elastic demand. Furthermore, some basic...

This paper analyses price elasticities in the Austrian market for mobile telecommunications services using data on firm specific tariffs in the period between January 1998 and March 2002. Dynamic panel data regressions are used to estimate short-run and long-run demand elasticities for business...

This paper considers alternative approaches to the analysis of large panel data models in the presence of error cross section dependence. A popular method for modelling such dependence uses a factor error structure. Such models raise new problems for estimation and inference. This paper compares...

Factor models can cope with many variables without running into scarce degrees of freedom problems often faced in a regression-based analysis. In this article we review recent work on dynamic factor models that have become popular in macroeconomic policy analysis and forecasting. By means of an...

This paper proposes a parametric approach to estimating a dynamic binary response panel data model that allows for endogenous contemporaneous regressors. Such a model is of particular value for settings in which one wants to estimate the effects of an endogenous treatment on a binary outcome. In...

The issue of EDC became increasingly important in the field of development economics primarily because EDC has been occurring more frequent after the deregulation of global financial flows in the 1970s (Tiruneh 2004, Jones 2015) hitting mostly MICs and LICs. Assessing the probability of an EDC...

We propose a new Bayesian Markov switching regression model for multi-dimensional arrays (tensors) of binary time series. We assume a zero-inflated logit dynamics with time-varying parameters and apply it to multi-layer temporal networks. The original contribution is threefold. First, in order...