Economic and Business Forecasting Analyzing and Interpreting Econometric Results

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  • Edition: 1st
  • Format: Hardcover
  • Copyright: 2014-03-03
  • Publisher: Wiley

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Discover the secrets to applying simple econometric techniques to improve forecasting

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.

Table of 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?

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


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


Chapter 3: Financial Ratios

Profitability Ratios


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


Additional Reading

Chapter 6: Characterizing a Time Series Using SAS Software

Tips for SAS Users

The DATA Step

The PROC Step


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


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?


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


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


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


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 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


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

Benchmarking Economic Growth

Industrial Production: Another Case of Stationary Behavior

Employment: Jobs in the 21st Century


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


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


Appendix: Useful References for SAS Users

About the Authors


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