Contents
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?
Gross Private Domestic Investment
Net Exports of Goods and Services
Real Final Sales and Gross Domestic Purchases
The Labor Market: Always a Core Issue
Data Revision: A Special Consideration
Marrying the Labor Market Indicators Together
Consumer Price Index: A Society's Inflation Benchmark
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
Chapter 4 Characterizing a Time Series
Why Characterize a Time Series?
How to Characterize a Time Series
Application: Judging Economic Volatility
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
Chapter 6 Characterizing a Time Series Using SAS Software
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 HP Filter
Application: Benchmarking the Housing Bust, Bear Stearns, and Lehman Brothers
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?
Chapter 9 The 10 Commandments of Applied Time Series Forecasting for Business and Economics
Commandment 1: Know What You Are Forecasting
Commandment 2: Understand the Purpose of Forecasting
Commandment 3: Acknowledge the Cost of the Forecast Error
Commandment 4: Rationalize the Forecast Horizon
Commandment 5: Understand the Choice of Variables
Commandment 6: Rationalize the Forecasting Model Used
Commandment 7: Know How to Present the Results
Commandment 8: Know How to Decipher the Forecast Results
Commandment 9: Understand the Importance of Recursive Methods
Commandment 10: Understand Forecasting Models Evolve over Time
Chapter 10 A Single-Equation Approach to Model-Based Forecasting
The Unconditional (Atheoretical) Approach
The Conditional (Theoretical) Approach
Recession Forecast Using a Probit Model
Chapter 11 A Multiple-Equations Approach to Model-Based Forecasting
The Importance of the Real-Time Short-Term Forecasting
The Individual Forecast versus 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 versus Bloomberg
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
Chapter 13 The Risks of Model-Based Forecasting: Modeling, Assessing, and Remodeling
Risks to Short-Term Forecasting: There Is No Magic Bullet
Risks of Long-Term Forecasting: Black Swan versus a Group of Black Swans
Model-Based Forecasting and the Great Recession/Financial Crisis: Worst-Case Scenario versus Panic
Chapter 14 Putting the Analysis to Work in the Twenty-First-Century Economy
Industrial Production: Another Case of Stationary Behavior
Employment: Jobs in the Twenty-First Century
Imbalances between Bond Yields and Equity Earnings
A Note of Caution on Patterns of Interest Rates
Business Credit: Patterns Reminiscent of Cyclical Recovery
Financial Market Volatility: Assessing Risk
Economic Policy: Impact of Fiscal Policy and the Evolution of the U.S. Economy
The Long-Term Deficit Bias and Its Economic Implications