Advanced Panel Data Analysis
Theorical framework overview and applications with Stata and R
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Panel data analysis has become an essential tool in econometrics, finance, and social sciences, enabling researchers to account for both cross-sectional and temporal variations in data. This book, Advanced Panel Data Analysis: Theoretical Framework, Overview, and Applications with Stata and R, provides a comprehensive guide to both linear and nonlinear panel data models, combining rigorous theoretical foundations with practical implementation in Stata and R.The book is structured into four main parts. Chapter 1 introduces the fundamental concepts of panel data, highlighting its advantages over...
Panel data analysis has become an essential tool in econometrics, finance, and social sciences, enabling researchers to account for both cross-sectional and temporal variations in data. This book, Advanced Panel Data Analysis: Theoretical Framework, Overview, and Applications with Stata and R, provides a comprehensive guide to both linear and nonlinear panel data models, combining rigorous theoretical foundations with practical implementation in Stata and R.The book is structured into four main parts. Chapter 1 introduces the fundamental concepts of panel data, highlighting its advantages over purely cross-sectional or time-series methods. Chapter 2 focuses on cross-section dependence tests and unit root tests, covering first, second, and third-generation to assess stationarity and dependency issues in panel datasets.Chapter 3 explores linear panel data models, including individual effects models, dynamic panel models, the AutoRegressive Distributed Lag (ARDL) model, and cointegrated panel models, which are widely used in empirical research. Chapter 4 extends the discussion to nonlinear panel data models, such as PTR, PSTR, TARDL, Q-Q-regression.
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