Statistics and Econometric Models: Testing, Confidence Regions, Model Selection, and Asymptotic Theory by Christian Gour

Introduction

Statistics and Econometric Models: Testing, Confidence Regions, Model Selection, and Asymptotic Theory is the second volume of a comprehensive two-part work by renowned econometrician Christian Gourieroux. Published by Cambridge University Press, this hardcover edition is an indispensable resource for graduate students, researchers, and professionals in economics, statistics, and data science. Tailored for Indian readers and students pursuing advanced studies in econometrics, the book bridges classical statistical inference with modern econometric techniques, offering a rigorous yet intuitive approach to testing hypotheses, constructing confidence regions, selecting models, and understanding asymptotic theory.

Book Overview

This volume focuses on the inferential tools that underpin empirical research in economics and related fields. It systematically covers hypothesis testing, confidence interval and region construction, model selection criteria, and the asymptotic properties of estimators and test statistics. Gourieroux explains complex concepts with clarity, using numerous real-world examples from economics to illustrate theoretical results. The book is designed to be self-contained, building upon the foundations laid in Volume 1, which dealt with estimation and prediction. Together, the two volumes provide a complete course in modern econometrics, suitable for both classroom teaching and self-study.

Key Highlights

• Comprehensive Coverage: Delves deeply into testing procedures, including Wald, likelihood ratio, and Lagrange multiplier tests, with detailed derivations and applications.
• Asymptotic Theory: Provides a thorough treatment of asymptotic distributions, consistency, and efficiency of estimators and test statistics, essential for large-sample inference.
• Model Selection: Explores information criteria such as AIC and BIC, along with practical strategies for choosing between competing econometric models.
• Confidence Regions: Offers step-by-step guidance on constructing confidence intervals and regions for parameters in linear and nonlinear models.
• Intuitive Exposition: Mathematical rigor is balanced with intuitive explanations and numerous worked examples, making the material accessible to Indian students with a basic background in statistics and econometrics.

Inside the Book

The book is organized into thematic chapters that progress from foundational concepts to advanced topics. Early chapters review the principles of hypothesis testing and the Neyman-Pearson lemma, then extend to multivariate and composite hypotheses. Subsequent chapters cover confidence regions for linear and nonlinear models, including bootstrap methods. A significant portion is dedicated to model selection, where Gourieroux discusses criteria like AIC, BIC, and cross-validation, along with their asymptotic properties. The final chapters delve into asymptotic theory, including uniform convergence, stochastic equicontinuity, and the application of central limit theorems in econometric contexts. Each chapter concludes with exercises that reinforce learning and encourage practical application.

Key Topics

• Hypothesis testing: Wald, likelihood ratio, and score tests
• Confidence intervals and regions for linear and nonlinear parameters
• Model selection criteria: AIC, BIC, and penalized likelihood
• Asymptotic distributions and consistency of estimators
• Large-sample theory for M-estimators and GMM
• Bootstrap methods for inference
• Testing in the presence of nuisance parameters
• Specification testing and diagnostic checks

Reader Benefits

Indian readers will find this book particularly valuable for its rigorous treatment of econometric inference, which is essential for conducting empirical research in Indian economics, policy analysis, and finance. The intuitive explanations help bridge the gap between theory and application, enabling students to confidently apply tests and model selection in their own work. The inclusion of numerous examples from economics ensures relevance to Indian contexts, such as analyzing consumption patterns, inflation dynamics, or market behavior. The hardcover format makes it a durable reference for libraries and personal collections.

Learning Outcomes

By studying this volume, readers will be able to: formulate and test economic hypotheses using classical and modern methods; construct and interpret confidence regions for parameters in linear and nonlinear models; select appropriate econometric models using information criteria; understand the asymptotic properties of estimators and test statistics; apply bootstrap techniques for inference when standard assumptions fail; and critically evaluate empirical studies in economics and social sciences.

Who Should Read

This book is ideal for graduate students in economics, statistics, and data science programs across Indian universities. It is also highly recommended for researchers and practitioners in government agencies, central banks, financial institutions, and consulting firms who need a solid foundation in econometric inference. Professionals in data analytics and quantitative research will benefit from the rigorous yet accessible treatment of asymptotic theory and model selection.

About the Author

Christian Gourieroux is a distinguished French econometrician and professor at the University of Toronto and the Centre de Recherche en Economie et Statistique (CREST) in Paris. He has made seminal contributions to econometric theory, including the development of simulation-based estimation methods and the analysis of qualitative and limited dependent variable models. His textbooks are widely used in graduate programs worldwide for their clarity and depth.

About the Publisher

Cambridge University Press is a world-leading academic publisher with a strong reputation for producing high-quality scholarly books in economics, statistics, and mathematics. This hardcover edition reflects their commitment to rigorous editing, clear typesetting, and durable binding, ensuring it remains a reliable resource for years to come.

Conclusion

Statistics and Econometric Models: Testing, Confidence Regions, Model Selection, and Asymptotic Theory is an essential addition to the library of any serious student or practitioner of econometrics. With its thorough coverage, intuitive exposition, and practical examples, this volume equips readers with the tools needed to conduct robust inference and model selection in empirical research. Order your hardcover copy from Bookshops.in today and deepen your understanding of modern econometric methods.