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Wiley & SAS Business Series

The Wiley & SAS Business Series presents books that help senior-level managers with their critical management decisions.

Titles in the Wiley & SAS Business Series include:

  1. Activity-Based Management for Financial Institutions: Driving Bottom-Line Results by Brent Bahnub
  2. Big Data Analytics: Turning Big Data into Big Money by Frank Ohlhorst
  3. Branded! How Retailers Engage Consumers with Social Media and Mobility by Bernie Brennan and Lori Schafer
  4. Business Analytics for Customer Intelligence by Gert Laursen
  5. Business Analytics for Managers: Taking Business Intelligence beyond Reporting by Gert Laursen and Jesper Thorlund
  6. The Business Forecasting Deal: Exposing Bad Practices and Providing Practical Solutions by Michael Gilliland
  7. Business Intelligence Success Factors: Tools for Aligning Your Business in the Global Economy by Olivia Parr Rud
  8. CIO Best Practices: Enabling Strategic Value with Information Technology, second edition by Joe Stenzel
  9. Connecting Organizational Silos: Taking Knowledge Flow Management to the Next Level with Social Media by Frank Leistner
  10. Credit Risk Assessment: The New Lending System for Borrowers, Lenders, and Investors by Clark Abrahams and Mingyuan Zhang
  11. Credit Risk Scorecards: Developing and Implementing Intelligent Credit Scoring by Naeem Siddiqi
  12. The Data Asset: How Smart Companies Govern Their Data for Business Success by Tony Fisher
  13. Delivering Business Analytics: Practical Guidelines for Best Practice by Evan Stubbs
  14. Demand-Driven Forecasting: A Structured Approach to Forecasting, Second Edition by Charles Chase
  15. Demand-Driven Inventory Optimization and Replenishment: Creating a More Efficient Supply Chain by Robert A. Davis
  16. Economic and Business Forecasting: Analyzing and Interpreting Econometric Results by John Silvia, Azhar Iqbal, Kaylyn Swankoski, Sarah Watt, and Sam Bullard
  17. The Executive’s Guide to Enterprise Social Media Strategy: How Social Networks Are Radically Transforming Your Business by David Thomas and Mike Barlow
  18. Executive’s Guide to Solvency II by David Buckham, Jason Wahl, and Stuart Rose
  19. Fair Lending Compliance: Intelligence and Implications for Credit Risk Management by Clark R. Abrahams and Mingyuan Zhang
  20. Foreign Currency Financial Reporting from Euros to Yen to Yuan: A Guide to Fundamental Concepts and Practical Applications by Robert Rowan
  21. Health Analytics: Gaining the Insights to Transform Health Care by Jason Burke
  22. Human Capital Analytics: How to Harness the Potential of Your Organization’s Greatest Asset by Gene Pease, Boyce Byerly, and Jac Fitz-enz
  23. Information Revolution: Using the Information Evolution Model to Grow Your Business by Jim Davis, Gloria J. Miller, and Allan Russell
  24. Killer Analytics: Top 20 Metrics Missing from Your Balance Sheet by Mark G. Brown
  25. Implement, Improve and Expand Your Statewide Longitudinal Data System: Creating a Culture of Data in Education by Jamie McQuiggan and Armistead Sapp
  26. Manufacturing Best Practices: Optimizing Productivity and Product Quality by Bobby Hull
  27. Marketing Automation: Practical Steps to More Effective Direct Marketing by Jeff LeSueur
  28. Mastering Organizational Knowledge Flow: How to Make Knowledge Sharing Work by Frank Leistner
  29. The New Know: Innovation Powered by Analytics by Thornton May
  30. Performance Management: Integrating Strategy Execution, Methodologies, Risk, and Analytics by Gary Cokins
  31. Predictive Business Analytics: Forward-Looking Capabilities to Improve Business Performance by Lawrence Maisel and Gary Cokins
  32. Retail Analytics: The Secret Weapon by Emmett Cox
  33. Social Network Analysis in Telecommunications by Carlos Andre Reis Pinheiro
  34. Statistical Thinking: Improving Business Performance, second edition by Roger W. Hoerl and Ronald D. Snee
  35. Taming the Big Data Tidal Wave: Finding Opportunities in Huge Data Streams with Advanced Analytics by Bill Franks
  36. Too Big to Ignore: The Business Case for Big Data by Phil Simon
  37. The Value of Business Analytics: Identifying the Path to Profitability by Evan Stubbs
  38. Visual Six Sigma: Making Data Analysis Lean by Ian Cox, Marie A. Gaudard, Philip J. Ramsey, Mia L. Stephens, and Leo Wright
  39. Win with Advanced Business Analytics: Creating Business Value from Your Data by Jean Paul Isson and Jesse Harriott

For more information on any of the above titles, please visit

Economic and Business Forecasting

Analyzing and Interpreting Econometric Results


John Silvia

Azhar Iqbal

Kaylyn Swankoski

Sarah Watt

Sam Bullard



Wiley Logo

To Tiffani Kaliko, Penny and Sherman

Shahkora and Mohammad Iqbal, Nargis, Saeeda, Shahid and Noreen

And to the family and friends who remain our wellsprings of inspiration

If a man will begin with certainties, he shall end in doubts, but if he will content to begin with doubts, he shall end in certainties.

—Francis Bacon, The Advancement of Learning, 1605


Due to the Great Recession (2007–2009) and the accompanying financial crisis, the premium on effective economic analysis, especially the identification of time series and then accurate forecasting of economic and financial variables, has significantly increased. Our approach provides a comprehensive yet practical process to quantify and accurately forecast key economic and financial variables. Therefore, the timing of this book is appropriate in a post-2008 world, where the behavior of traditional economic relationships must be reexamined since many appear out of character with the past. The value proposition is clear: The framework and techniques advanced here are the techniques we use as practitioners. These techniques will help decision makers identify and characterize the patterns of behavior in key economic series to better forecast these essential economic series and their relationships to other economic series.

This book is for the broad audience of practitioners as well as undergraduate and graduate students with an applied economics focus. This book introduces statistical techniques that can help practitioners characterize the behavior of economic relationships. Chapters 1 to 3 provide a review of basic economic and financial fundamentals that decision makers in both the private and public sectors need to know. Our belief is that before an analyst attempts any statistical analysis, there should be a clear understanding of the data under study. Chapter 4 provides the tools that an analyst will employ to effectively characterize an economic series. One relationship of interest is the ability of leading indicators to predict the pattern of the business cycle, particularly the onset of a recession. Another way to characterize economic relationships is to reflect on the current trend of any economic series of interest relative to the average behavior over prior cycles. In a third approach, we may be interested in identifying the possibility of a structural change in an economic time series to test if the past history of a variable would be different over time.

Different economic and financial variables exhibit differential behavior over the business cycle and over time. In this book we focus on a select set of major economic and financial variables, such as economic growth, final sales, employment, inflation, interest rates, corporate profits, financial ratios, and the exchange value of the dollar.

Our analysis then extends the text into the relationships between different time series. This analysis begins with Chapter 5, and then in Chapters 6 and 7 we take a look at the SAS® software employed in our analysis. We also examine these variables’ patterns over the business cycle, with an emphasis on their recent history, using econometric techniques and the statistical software SAS as a template for the reader to apply to variables of interest. These variables form the core of an effective decision-making process in both the private and public sectors. Chapter 8 provides techniques that an analyst can employ and contains numerous examples of our techniques in action.

Our approach has several advantages. First, effective decision making involves an analysis of the behavior of select economic and financial variables. By choosing a small set of economic factors, we provide a template for decision making that can be easily applicable to a broader set of variables for future study in many economic fields. Our focus is on the importance of a limited, but central, set of select economic and financial variables that provide special insights into economic performance, along with the empirical evidence of their vital role to the economy and financial markets.

Second, using a small set of simple data descriptors and econometric techniques to characterize and describe the behavior of economic variables provides value in a number of contexts. We can examine the behavior of any particular economic series in numerous ways so that the analysis is less subject to personal beliefs and biases. This helps overcome the confirmation bias of many decision makers who search for the results they want to see from any analysis. Many analysts may search for the comfortable, familiar historical statistical relationships in a post-2008 era when, in fact, many of those relationships have vanished.

Third, our detailed discussion about SAS and its applications creates a valuable starting point for researchers. We provide a practical forecasting framework for important everyday applications. Finally, our work discusses SAS results and identifies econometric issues and solutions that are of interest to addressing a number of economic and business issues. One outgrowth of our experience with many of these issues is reviewed in Chapter 9, where we focus on our 10 commandments of applied time series forecasting. Chapters 10 and 11 build on these commandments with a focus on single equations in Chapter 10 and multiple equations in Chapter 11.

The net result is the application of econometrics in a way that contributes to effective decision making in both the private and public sectors. In Chapter 12 we focus on model-based forecasting applied to make long-term forecasts for the next five to 10 years, which reflects the reality of determining the real sustainability of projects and their profitability overtime. Chapter 13 then highlights the risks and challenges of such forecasting. Finally in Chapter 14 we illustrate some of the lessons we have learned in recent years as we identify and understand the changes that are ongoing in the twenty-first-century economy. As an additional resource, there is a test bank to accompany this text.

This book is dedicated first to young professional economists and aspiring students who wish to provide a thoughtful statistical basis for better decision making in their careers, whether it is in the public or the private sector. This book is also aimed to serve professional analysts who wish to provide statistical support for effective decision making. This work reflects the years of experience of the authors whose work contains a focus on simple yet practical techniques needed for efficient decision making without extensive theoretical and mathematical refinements that are ancillary to effective decision making. That we leave for authors with the luxury of time and tenure. The techniques in the text are being used in our work every day. They have brought us numerous forecasting awards and published papers that reflect the practical undertakings required of young professionals who wish to add value to the decision-making process in their organizations.


We would like to thank all the people who have supported us through the writing and publication of this book. Special thanks to Larry Rothstein and Zachary Griffiths, for without their help this book would not have been possible. We also wish to express our gratitude for the many people at Wells Fargo who have supported this project, including Diane Schumaker-Krieg and John Shrewsberry, as well as the technical support staff at Wells Fargo. Thank you Robert Crow, editor of Business Economics, and the referees of that journal as well as the referees of articles that have appeared in other journals; you have improved the quality of our research over the years. We are grateful for the instructors and students who have come into our lives and taught and inspired us (Nuzhat Ahmad, M. S. Butt, Kajal Lahiri, Asad Zaman, Adil Siddique, Ambreen Fatima, Hasan N. Saleem, Jon Schuller, and Anika Khan).