Detection of structural breaks in linear dynamic panel data models

Detection of structural breaks in linear dynamic panel data models

This paper develops a method for testing for the presence of a single structural break in dynamic panel data models with a multi-factor error structure. The test statistic is developed by combining a modified version of the GMM approach of Robertson and Sarafidis (2015) with the testing procedure of De Wachter and Tzavalis (2012). We focus on the case where N is large and T fixed. The asymptoti...

Dynamic Panel Data Analysis Of European Tourism Demand In Malaysia

Non-Response in Dynamic Panel Data Models

This paper stresses the links that exist between concepts that are used in the theory of model reduction and concepts that arise in the missing data literature. This connection motivates the extension of the missing at random (MAR) and the missing completely at random (MCAR) concepts from a static setting, as introduced by Rubin (1976), to the case of dynamic panel data models. Using this exten...

Statistical inference in dynamic panel data models

T.W. Anderson and his collaborators have made seminal contributions to inference with instrumental variables and to dynamic panel data models. We review these contributions and the extensive economic and statistical literature that these contributions spawned. We describe our recent work in these two areas, presenting new approaches to (a) making valid inferences in the presence of weak instrum...

Aggregation of Linear Models for Panel Data

We study the impact of individual and temporal aggregation in linear static and dynamic models for panel data in terms of model specification and efficiency of the estimated parameters. Model wise we find that i) individual aggregation does not affect the model structure but temporal aggregation may introduce residual autocorrelation, and ii) individual aggregation entails heteroskedasticity wh...