At the core of scientific research lies the testing of theoretical frameworks against real-world data and the generation of findings that contribute meaningfully to the field of economics. Given the complex nature of economic relationships, empirically testing abstract theories and producing policy-relevant insights hold great significance. At this juncture, econometrics emerges as an indispensable discipline that integrates the analytical power of economics with statistical and mathematical methods, making it possible to apply theoretical models to concrete data.

In today’s world, with the rapid advancement of data technologies, increasing computational power, and the emergence of new statistical methodologies, econometrics has gone far beyond being merely a tool for analyzing economic phenomena. It has evolved into a broader field of application, interacting with data science, artificial intelligence, and machine learning. These developments have made it essential to revisit traditional econometric methods and to consider them alongside contemporary approaches.

In this context, the volume titled “Theoretical and Empirical Analyses with Traditional and Contemporary Econometric Approaches”, which we have the honor of editing, has been prepared as a comprehensive source encompassing both classical and modern methodologies in econometrics. The book presents theoretical and empirical contributions across a broad spectrum—from the historical evolution of econometric modeling to fundamental concepts and advanced analytical techniques.

The chapters in this volume cover a wide methodological range, including simple and multiple regression analyses, time series and panel data models, stationarity, cointegration, and causality tests, as well as structural break analyses and dynamic panel models. In addition, special attention has been given to contemporary topics that have gained importance in recent years, such as nonlinear relationships, Bayesian approaches, and forecasting performance measures.

Another key strength of this book is its emphasis on practical implementation. Beyond theoretical discussions, the book demonstrates the empirical applicability of econometric methods using software such as R, Python, GAUSS, EViews, and Stata. This enables readers not only to learn the theoretical foundations but also to gain experience in interpreting statistical outputs in practice.

The primary goal of this work is to serve as a comprehensive reference guide for both graduate students who are taking their first steps into econometrics and for academics seeking to enrich their research with contemporary methodologies. Accordingly, the book aims to guide researchers through the stages of theoretical model formulation, data analysis, model selection, and interpretation of results.

Furthermore, the chapters of this book include original empirical studies that offer rich perspectives not only from a methodological standpoint but also through their applications in macroeconomics, finance, international trade, development economics, and environmental economics. In doing so, the volume highlights the multidimensional nature of econometrics, integrating its theoretical and applied dimensions.

We firmly believe that this book will serve as a valuable reference for graduate students, academics, and applied researchers with an interest in econometrics. We would like to express our sincere gratitude to all contributing authors for their diligent academic efforts and to all academic partners and the publishing team for their invaluable support throughout the publication process.

With the belief that the sharing of scientific knowledge and interdisciplinary collaboration will open new horizons for the advancement of econometrics…