Economic and Business Forecasting: Analyzing and Interpreting Econometric Results

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. INDICE: 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

• ISBN: 978-1-118-49709-8
• Editorial: John Wiley & Sons
• Encuadernacion: Cartoné
• Páginas: 400
• Fecha Publicación: 30/04/2014
• Nº Volúmenes: 1
• Idioma: Inglés