This book introduces modern series methods with a focus on applications in econometrics and statistics. It explores how new orthogonal series techniques can address challenges in model building and estimation, particularly for variables with unbounded support, nonparametric nonstationary data, and high-dimensional models. By extending traditional series methods, which are typically limited to variables with bounded supports, this book provides tools to tackle emerging problems in econometrics and statistics effectively.

The book is organized into the following key parts. Part one provides the mathematical foundation for modern series methods, offering the theoretical background needed for their application. Part two introduces fundamental econometric concepts, including conditional expectations and regression models, within the context of modern series techniques. The last part, part four examines advanced topics, such as the connections between series methods and generalized functions, and compares series methods with kernel methods, highlighting their respective strengths and use cases. With a balanced mix of theory and practical insights, this book is ideal for researchers, practitioners, and students looking to deepen their understanding of series methods and their applications in econometrics, statistics, and related fields.

About the Author

Professor Chaohua Dong is Professor of Econometrics in the School of Statistics and Mathematics at Zhongnan University of Economics and Law, China. After finishing his PhD study at the University of Adelaide in 2011, he jointed the Department of Econometrics and Business Statistics, Monash University, as a research fellow. In 2015 he moved back to the Southwestern University of Finance and Economics, as a lecturer and then promoted to Associate Professor and then Full Professor. By the end of 2018 he jointed the current affiliation as a Professor in Econometrics.

Chaohua Dong’s research interest includes high dimensional econometrics, non- and semiparametric methods, nonstationary time series, panel data models and applied microeconomics. He has published a series of papers in top tier international journals in the fields of econometrics and statistics; he also teach a number of courses at different levels from undergraduate to PhD including mathematical statistics, probability theory and mathematical statistics, introductory econometrics, nonparametric econometrics and selected lecture in the frontier of econometrics. In addition, he is a member of financial risk management council in China system engineering association.

Professor Jiti Gao is Donald Cochrane Chair of Business and Economics at the Monash Business School, and Professor of Econometrics and Statistics in the Department of Econometrics and Business Statistics at Monash University. Professor Jiti Gao was an Australian Professorial Fellow between January 2010-December 2014. Since September 2011, he becomes an Elected Fellow of the Academy of the Social Sciences in Australia. He is also an Elected Fellow of the International Association for Applied Econometrics and a named Fellow of The Journal of Econometrics. Currently, he is a Co-Editor of the World Scientific Book Series on Econometrics and Statistics, and on several editorial boards of leading international journals, such as Econometric Theory and Journal of Business and Economic Statistics.

Jiti Gao’s recent research interests include Non- and Semi-Parametric Models and Methods, Nonlinear Time Series and Panel Data Econometrics. Since January 2000, he has published three books, four book chapters and over 100 articles by leading international journals in economics, econometrics, finance and statistics, including Annals of Statistics, Journal of Business and Economic Statistics, Journal of Econometrics, Journal of the American Statistical Association, and Journal of the Royal Statistical Society Series B.

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