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R for Economic Research (2e) is the updated and expanded edition of a widely read resource on practical economic analysis in R. The first edition reached more than 40,000 readers in over 50 countries, helping students, economists, analysts, and data scientists develop the technical skills required for professional work in applied economics.

This second edition reflects both the evolution of the R ecosystem and the increasing demands of real-world analytical work. In addition to improved clarity and structure, it introduces several new chapters covering:

• high-frequency data;

• Bayesian inference;

• tools for working with large datasets;

• machine learning models;

• dimensionality reduction;

• state-space models and nowcasting.

A major enhancement of this edition is the companion package R4ER2data, which includes all datasets used throughout the book, enabling readers to reproduce every example with ease.

More than a technical reference, R for Economic Research (2e) guides readers through the practical intersection of programming and applied econometrics. It shows how to use R to:

• clean and prepare data for economic analysis;

• perform essential time series transformations such as seasonal adjustment and deflation;

• estimate and interpret widely used econometric and statistical models;

• analyze economic relationships with rigor and transparency;

• build forecasts that are interpretable, defensible, and aligned with economic reasoning.

Written for readers with at least an intermediate proficiency in R, this book is ideal for:

• early- and mid-career economists;

• quantitative and financial analysts;

• graduate students working with economic data;

• data scientists applying R in applied contexts;

• professionals seeking to strengthen their analytical capabilities with practical and modern methods.

If you work with economic data and want to apply R effectively to real analytical challenges, R for Economic Research (2e) provides the practical foundation you need.

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