Advanced Econometrics with Stata, EViews, R, and SPSS: Applications in Economics, Finance, Statistics, Artificial Intelligence, and Decision Analytics

Description

Econometrics is no longer just about estimating equations—it is the science of transforming data into knowledge, uncertainty into insight, and evidence into intelligent decision-making.

In an era driven by artificial intelligence, big data, predictive analytics, and computational intelligence, the ability to build reliable econometric models has become one of the most valuable skills across academia, government, finance, business, and scientific research. This book has been written to meet the demands of this new generation of quantitative analysis.

Advanced Econometrics with Stata, EViews, R, and SPSS is a comprehensive international reference that seamlessly integrates classical econometric theory with modern computational methods, artificial intelligence, machine learning, and evidence-based decision analytics. Designed for postgraduate students, doctoral scholars, researchers, university faculty, economists, statisticians, financial analysts, data scientists, policymakers, and industry professionals, the book offers a complete roadmap from fundamental theory to cutting-edge applications.

Structured into 11 comprehensive parts and 31 advanced chapters, this volume systematically explores the evolution of econometric thought, mathematical foundations, statistical inference, research design, structural modeling, model diagnostics, causal inference, time-series analysis, panel data methods, computational econometrics, machine learning, and intelligent forecasting systems. Every chapter combines rigorous theory with practical implementation using Stata, EViews, R, and SPSS, enabling readers to bridge the gap between academic concepts and real-world empirical research.

What distinguishes this book is its interdisciplinary perspective. Rather than treating econometrics as an isolated statistical discipline, it demonstrates how quantitative methods are transforming economics, finance, banking, business intelligence, public policy, sustainable development, agriculture, healthcare, and digital innovation. Readers learn not only how econometric models are developed, but also how they are applied to solve complex global challenges through data-driven reasoning and predictive intelligence.

To strengthen practical understanding, the book features 20 international case studies inspired by real-world applications, including macroeconomic forecasting, central banking, financial risk management, digital banking, economic growth analysis, policy evaluation, precision agriculture, and AI-assisted predictive modeling. Complementing these applications are more than 50 professionally designed diagrams, 25 Screenshots for Software, over 100 analytical flowcharts, mathematical derivations, software implementation guides, diagnostic frameworks, and reproducible research workflows, making complex concepts accessible through structured visual learning.

Whether your goal is publishing in leading journals, conducting doctoral research, developing forecasting models, evaluating public policies, or applying artificial intelligence to quantitative research, this book provides the theoretical depth, computational expertise, and analytical framework required for success.

More than a textbook, this is a next-generation guide to modern econometric science—where mathematics meets computation, data becomes intelligence, and econometric models drive the future of research, policy, finance, and global decision-making.

What's New in This International Edition?

This International Edition has been completely redesigned, substantially expanded, and updated to reflect the latest advances in econometric science, computational statistics, artificial intelligence, and quantitative decision analytics.

About the Author

Author
Om Krishna

Current Position
Assistant Professor of Economics

National Editorial Board Member
T T International Publication, India

Independent Researcher
RP&GS Research & Policy Initiative, India

Indian General Reviewer
ARTIKLE.In Journals

Peer–Reviewer
Global Research Consortium (GRC)
International Forum for Humanities and Social Research

Academic & Research Expertise
Agricultural Economics, Econometrics & Quantitative Methods, Public Finance & Policy Analysis, Development Economics, Environmental & Resource Economics, International Economics, Digital Economy & AI in Economics, Institutional & Political Economy, Agricultural Policy & Rural Development
He has contributed to multiple manuscripts, copyright-registered works, and international academic discussions. He is proficient in econometric software such as Stata, EViews, R, and SPSS.

Co-Authors & Contributors

1. Dr. Alexander J.A. Morgan
Expertise: Econometrics, Financial Econometrics, Time Series Analysis, Macroeconomic Modeling
Affiliation: Department of Economics, Global Institute of Quantitative Studies
Focus Areas: Panel data models, volatility modeling, macro-financial linkages, forecasting systems
________________________________________
2. Dr. Sofia S. Martinez
Expertise: Applied Statistics, Data Science, R Programming, Multivariate Analysis
Affiliation: School of Data Analytics and Computational Economics
Focus Areas: Statistical modeling, machine learning integration in econometrics, high-dimensional data systems
________________________________________
3. Dr. Wei F. Zhang
Expertise: Artificial Intelligence in Economics, Machine Learning, Econometrics, Big Data Analytics
Affiliation: Center for AI and Economic Systems Research
Focus Areas: Predictive modeling, neural econometrics, algorithmic decision systems, data-driven policy analysis
________________________________________
4. Dr. Anita S. Sharma
Expertise: Applied Econometrics, Development Economics, Policy Evaluation
Affiliation: Institute of Economic Research and Public Policy
Focus Areas: Impact evaluation, causal inference, micro-econometric methods, development policy modeling
________________________________________
5. Dr. Michael E. O’Connor
Expertise: Financial Markets, Risk Analytics, Derivatives Pricing, EViews Modeling
Affiliation: School of Finance and Quantitative Economics
Focus Areas: Market volatility modeling, risk forecasting, financial time series, econometric software applications
________________________________________
6. Dr. Fatima R. Al-Hassan
Expertise: Agricultural Economics, Environmental Econometrics, Sustainability Analytics
Affiliation: Global Institute for Climate and Resource Economics
Focus Areas: Climate-economy models, agricultural productivity, environmental impact assessment, resource efficiency
________________________________________
7. Dr. Lucas Y. Bennett
Expertise: Statistical Computing, SPSS Applications, Econometric Software Systems
Affiliation: Department of Computational Statistics
Focus Areas: Software-based econometric workflows, applied statistical computing, survey data analysis
________________________________________
8. Dr. Isabella I. Rossi
Expertise: Behavioral Economics, Decision Analytics, Experimental Econometrics
Affiliation: European School of Economics and Behavioral Research
Focus Areas: Choice modeling, behavioral data analysis, experimental design, decision theory applications
________________________________________
9. Prof. James K.O. Williams
Expertise: Advanced Econometrics Theory, Panel Data, Structural Modeling
Affiliation: Department of Economics, International University of Quantitative Research
Focus Areas: Structural econometric models, causal inference frameworks, advanced regression techniques
________________________________________
10. Dr. Li Me Na Chen
Expertise: Data Engineering for Econometrics, Digital Economy, AI-driven Policy Analytics
Affiliation: Institute for Digital Economic Systems
Focus Areas: Data pipelines, economic intelligence systems, digital platforms, AI-supported policy design
________________________________________
✦ Editor’s Note
This volume is a collaborative effort integrating theoretical econometrics with practical computational tools, including Stata, EViews, R, and SPSS, supported by modern advances in Artificial Intelligence, machine learning, and decision analytics. The contributors represent a global network of scholars bridging academic research and real-world economic applications.

Book Details

ISBN: 9798185807798

Publisher: RP&GS PUBLICATION HOUSE

Number of Pages: 548

Dimensions: 8.27"x11.69"

Interior Pages: B&W

Binding: Paperback (Perfect Binding)

Availability: In Stock (Print on Demand)

Ratings & Reviews