Economic and Business Forecasting Analyzing and Interpreting Econometric Results

Equipping analysts, practitioners, and graduate students with a statistical framework to make effective decisions based on the application of simple economic and statistical methods, Economic and Business Forecasting offers a comprehensive and practical approach to quantifying and accurate forecasting of key variables. Using simple econometric techniques, author John E. Silvia focuses on a select set of major economic and financial variables, revealing how to optimally use statistical software as a template to apply to your own variables of interest.

• Presents the economic and financial variables that offer unique insights into economic performance
• Highlights the econometric techniques that can be used to characterize variables
• Explores the application of SAS software, complete with simple explanations of SAS-code and output
• Identifies key econometric issues with practical solutions to those problems

Presenting the "ten commandments" for economic and business forecasting, this book provides you with a practical forecasting framework you can use for important everyday business applications.

JOHN E. SILVIA is a Managing Director and the Chief Economist for Wells Fargo Securities. In 2010, he was recognized for the Best Inflation Forecast, the Best Overall Forecast, and the Best Personal Consumption Expenditures Forecast by The Federal Reserve Bank of Chicago.

AZHAR IQBAL is an Econometrician and Vice President at Wells Fargo Securities where he provides quantitative analysis to the Economics group as well as modeling and forecasting of macro and financial variables. He has spoken at the American Economic Association, Econometric Society, and other international conferences.

SAM BULLARD is a Managing Director and Senior Economist at Wells Fargo Securities providing analysis and commentary on financial markets and macroeconomic developments.

SARAH WATT is an Economist with Wells Fargo Securities. She covers the U.S. macro economy, including labor market trends. She also works closely with senior members of her team to produce special reports and regional economic commentary on several U.S. states.

KAYLYN SWANKOSKI is an Economic Analyst at Wells Fargo Securities.

Preface

Acknowledgments

Chapter 1: Creating Harmony Out of Noisy Data

Effective Decision Making: Characterize the Data

Chapter 2: First, Understand the Data

Growth: How is the Economy Doing Overall?

Personal Consumption

Gross Private Domestic Investment

Government Purchases

Net Exports of Goods and Services

Real Final Sales and Gross Domestic Purchases

The Labor Market: Always a Core Issue

Establishment Survey

Data Revision: A Special Consideration

The Household Survey

Marrying the Labor Market Indicators Together

Jobless Claims

Inflation

Consumer Price Index: A Society’s Inflation Benchmark

Producer Price Index

Personal Consumption Expenditure Deflator: The Inflation Benchmark for Monetary Policy

Interest Rates: Price of Credit

The Dollar and Exchange Rates: The United States in a Global Economy

Corporate Profits

Summary

Chapter 3: Financial Ratios

Profitability Ratios

Summary

Chapter 4: Characterizing a Time Series

Why Characterize a Time Series?

How to Characterize a Time Series

Application: Judging Economic Volatility

Summary

Chapter 5: Characterizing a Relationship between Time Series

Important Test Statistics in Identifying Statistically Significant Relationships

Simple Econometric Techniques to Determine a Statistical Relationship

Advanced Econometric Techniques to Determine a Statistical Relationship

Summary

Additional Reading

Chapter 6: Characterizing a Time Series Using SAS Software

Tips for SAS Users

The DATA Step

The PROC Step

Summary

Chapter 7: Testing for a Unit Root and Structural Break Using SAS Software

Testing a Unit Root in a Time Series: A Case Study of the U.S. CPI

Identifying a Structural Change in a Time Series

The Application of the H-P Filter

Application: Benchmarking the Housing Bust, Bear Stearns and Lehman Brothers

Summary

Appendix 7A: The State-Space Approach to Testing for a Structural Break

Chapter 8: Characterizing a Relationship Using SAS

Useful Tips for an Applied Time Series Analysis

Converting a Dataset from One Frequency to Another

Application: Did the Great Recession Alter Credit Benchmarks?

Summary

Chapter 9: The Ten Commandments of Applied Time Series Forecasting for Business and Economics

Objective of the Forecast: What Are You Forecasting?

What is the Purpose of Forecasting?

Cost of Forecast Error: The Loss Function

Forecast Horizon: How Far Out to Forecast

The Choice of Variables: Quality vs. Quantity

Forecasting Modeling: How Do You Choose the Forecast Methods?

How Do You Present the Results?

Evaluating the Forecast Results

Recursive Methods: The Controlled-Forecasting Experiment

There is No-Silver Bullet: Forecasting Models Evolve Over Time

Summary

Chapter 10: A Single-Equation Approach to Model-Based Forecasting

The Unconditional (A-Theoretical) Approach

The Conditional (Theoretical) Approach

Recession Forecast Using a Probit Model

Summary

Chapter 11: A Multiple-Equations Approach to Model-Based Forecasting

The Importance of the Real-Time Short-term Forecasting

The Individual Forecast vs. Consensus Forecast: Is There an Advantage?

The Econometrics of Real-Time Short-term Forecasting: The BVAR Approach

Forecasting in Real-Time: Issues Related to the Data and the Model Selection

Case Study: WFC vs. Bloomberg

Summary

Appendix 11A: List of Variables

Chapter 12: A Multiple-Equations Approach to Long-Term Forecasting

The Unconditional Long-term Forecasting: The BVAR Model

The BVAR Model with Housing Starts

The Model without Oil Price Shock

The Model with Oil Price Shock

Summary

Chapter 13: The Risks of Model-Based Forecasting: Modeling, Assessing and Remodeling

Risks to the short-term Forecasting: There is no Magic Bullet

13.2 Risks of Long-term Forecasting: Black Swan vs. a Group of Black Swans

13.3 Model-Based Forecasting and the Great Recession/Financial Crisis: Worst-case Scenario vs. Panic

Summary

Chapter 14: Putting the Analysis to Work in the 21^st Century Economy

Benchmarking Economic Growth

Industrial Production: Another Case of Stationary Behavior

Employment: Jobs in the 21^st Century

Inflation

Interest Rates

Imbalances Between Bond Yields and Equity Earnings

A Note of Caution on Patterns of Interest Rates

Business Credit: Patterns Reminiscent of Cyclical Recovery

Profits

Financial Market Volatility: Assessing Risk

Dollar

Economic Policy—Impact of Fiscal Policy and the Evolution of the U.S. Economy

The Long-Term Deficit Bias and Its Economic Implications

Summary

Appendix: Useful References for SAS Users

About the Authors

Index

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