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Dynamic panel data models: a guide to microdata methods and practice

TLDR
In this article, the focus is on panels where a large number of individuals or firms are observed for a small number of time periods, typical of applications with microeconomic data, and the emphasis is on single equation models with autoregressive dynamics and explanatory variables.
Abstract
This paper reviews econometric methods for dynamic panel data models, and presents examples that illustrate the use of these procedures. The focus is on panels where a large number of individuals or firms are observed for a small number of time periods, typical of applications with microeconomic data. The emphasis is on single equation models with autoregressive dynamics and explanatory variables that are not strictly exogenous, and hence on the Generalised Method of Moments estimators that are widely used in this context. Two examples using firm-level panels are discussed in detail: a simple autoregressive model for investment rates; and a basic production function.

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Determinants of Nonperforming Loans in Central, Eastern and Southeastern Europe

TL;DR: In this article, the authors provided a macroeconomic model for nonperforming loans (NPLs) for the Central, Eastern and Southeastern European (CESEE) countries based on panel data for Bulgaria, Croatia, the Czech Republic, Hungary, Poland, Romania, Russia, Slovakia and Ukraine.
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The effects of financial crisis on fiscal positions

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Fostering the Development of European Regions: A Spatial Dynamic Panel Data Analysis of the Impact of Cohesion Policy

TL;DR: Bouayad-Agha et al. as discussed by the authors used a conditional-convergence econometric model to investigate whether cohesion policy affects European economies and found that Objective 1 programmes have a direct effect on regional gross domestic product per capita growth rates, whereas total Structural Funds do not.
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