Applied Time Series Econometrics with Gretl: A Practical Guide Using Price Transmission Applications provides a comprehensive introduction to applied time series econometrics through a unique combination of theory, empirical applications, and step-by-step implementation using the open-source software Gretl.
Unlike traditional econometrics textbooks that emphasize mathematical derivations, this book focuses on practical empirical analysis, enabling readers to develop the skills required to estimate, interpret, and evaluate time series econometric models using real-world data.
The book uses price transmission analysis in agri-food markets as a unifying empirical framework while demonstrating econometric techniques that are applicable across economics, finance, energy, business, and related disciplines.
Topics covered include:
Time series components, stationarity and unit root testingDistributed lag and dynamic regression modelsCointegration by the Engle-Granger and Johansen methodsError Correction Models (ECM)Asymmetric Error Correction Models (AECM)Vector Autoregressive (VAR) modelsVector Error Correction Models (VECM)Granger causality testingImpulse response functions and forecast error variance decompositionResidual diagnostics, robust standard errors and parameter stabilityEvery chapter combines theoretical explanations with detailed Gretl implementation, screenshots, interpretation of results, and practical examples, allowing readers to reproduce the analyses and apply the methods to their own research.
All empirical applications use a single dataset of producer and retail prices, which is openly available, so every figure and every number printed in the book can be reproduced in Gretl.
This book is intended for undergraduate and postgraduate students, researchers, instructors, and practitioners in economics, agricultural economics, finance, business, and other social sciences who seek a practical and accessible introduction to modern time series econometrics.
This volume is the first book in the Applied Time Series Econometrics Series.