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…mehr
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.
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.
Inhaltsangabe
Preface xiii Acknowledgments xvii Chapter 1 Creating Harmony Out of Noisy Data 1 Effective Decision Making: Characterize the Data 2 Chapter 2 First, Understand the Data 27 Growth: How Is the Economy Doing Overall? 30 Personal Consumption 31 Gross Private Domestic Investment 33 Government Purchases 35 Net Exports of Goods and Services 36 Real Final Sales and Gross Domestic Purchases 37 The Labor Market: Always a Core Issue 37 Establishment Survey 39 Data Revision: A Special Consideration 42 The Household Survey 43 Marrying the Labor Market Indicators Together 48 Jobless Claims 48 Inflation 49 Consumer Price Index: A Society's Inflation Benchmark 50 Producer Price Index 53 Personal Consumption Expenditure Deflator: The Inflation Benchmark for Monetary Policy 55 Interest Rates: Price of Credit 56 The Dollar and Exchange Rates: The United States in a Global Economy 58 Corporate Profits 60 Summary 62 Chapter 3 Financial Ratios 63 Profitability Ratios 64 Summary 73 Chapter 4 Characterizing a Time Series 75 Why Characterize a Time Series? 76 How to Characterize a Time Series 77 Application: Judging Economic Volatility 101 Summary 109 Chapter 5 Characterizing a Relationship between Time Series 111 Important Test Statistics in Identifying Statistically Significant Relationships 115 Simple Econometric Techniques to Determine a Statistical Relationship 119 Advanced Econometric Techniques to Determine a Statistical Relationship 120 Summary 126 Additional Reading 127 Chapter 6 Characterizing a Time Series Using SAS Software 129 Tips for SAS Users 130 The DATA Step 131 The PROC Step 135 Summary 156 Chapter 7 Testing for a Unit Root and Structural Break Using SAS Software 157 Testing a Unit Root in a Time Series: A Case Study of the U.S. CPI 158 Identifying a Structural Change in a Time Series 162 The Application of the HP Filter 169 Application: Benchmarking the Housing Bust, Bear Stearns, and Lehman Brothers 172 Summary 177 Chapter 8 Characterizing a Relationship Using SAS 179 Useful Tips for an Applied Time Series Analysis 179 Converting a Dataset from One Frequency to Another 182 Application: Did the Great Recession Alter Credit Benchmarks? 215 Summary 221 Chapter 9 The 10 Commandments of Applied Time Series Forecasting for Business and Economics 223 Commandment 1: Know What You Are Forecasting 224 Commandment 2: Understand the Purpose of Forecasting 226 Commandment 3: Acknowledge the Cost of the Forecast Error 226 Commandment 4: Rationalize the Forecast Horizon 229 Commandment 5: Understand the Choice of Variables 231 Commandment 6: Rationalize the Forecasting Model Used 232 Commandment 7: Know How to Present the Results 234 Commandment 8: Know How to Decipher the Forecast Results 235 Commandment 9: Understand the Importance of Recursive Methods 238 Commandment 10: Understand Forecasting Models Evolve over Time 239 Summary 240 Chapter 10 A Single-Equation Approach to Model-Based Forecasting 241 The Unconditional (Atheoretical) Approach 242 The Conditional (Theoretical) Approach 251 Recession Forecast Using a Probit Model 257 Summary 261 Chapter 11 A Multiple-Equations Approach to Model-Based Forecasting 263 The Importance of the Real-Time Short-Term Forecasting 265 The Individual Forecast versus Consensus Forecast: Is There an Advantage? 266 The Econometrics of Real-Time Short-Term Forecasting: The BVAR Approach 268 Forecasting in Real Time: Issues Related to the Data and the Model Selection 275 Case Study: WFC versus Bloomberg 280 Summary 288 Appendix 11A: List of Variables 289 Chapter 12 A Multiple-Equations Approach to Long-Term Forecasting 291 The Unconditional Long-Term Forecasting: The BVAR Model 293 The BVAR Model with Housing Starts 296 The Model without Oil Price Shock 298 The Model with Oil Price Shock 304 Summary 306 Chapter 13 The Risks of Model-Based Forecasting: Modeling, Assessing, and Remodeling 307 Risks to Short-Term Forecasting: There Is No Magic Bullet 308 Risks of Long-Term Forecasting: Black Swan versus a Group of Black Swans 310 Model-Based Forecasting and the Great Recession/Financial Crisis: Worst-Case Scenario versus Panic 314 Summary 315 Chapter 14 Putting the Analysis to Work in the Twenty-First-Century Economy 317 Benchmarking Economic Growth 318 Industrial Production: Another Case of Stationary Behavior 322 Employment: Jobs in the Twenty-First Century 324 Inflation 331 Interest Rates 337 Imbalances between Bond Yields and Equity Earnings 338 A Note of Caution on Patterns of Interest Rates 345 Business Credit: Patterns Reminiscent of Cyclical Recovery 347 Profits 348 Financial Market Volatility: Assessing Risk 349 Dollar 351 Economic Policy: Impact of Fiscal Policy and the Evolution of the U.S. Economy 353 The Long-Term Deficit Bias and Its Economic Implications 358 Summary 362 Appendix: Useful References for SAS Users 365 About the Authors 367 Index 369
Preface xiii Acknowledgments xvii Chapter 1 Creating Harmony Out of Noisy Data 1 Effective Decision Making: Characterize the Data 2 Chapter 2 First, Understand the Data 27 Growth: How Is the Economy Doing Overall? 30 Personal Consumption 31 Gross Private Domestic Investment 33 Government Purchases 35 Net Exports of Goods and Services 36 Real Final Sales and Gross Domestic Purchases 37 The Labor Market: Always a Core Issue 37 Establishment Survey 39 Data Revision: A Special Consideration 42 The Household Survey 43 Marrying the Labor Market Indicators Together 48 Jobless Claims 48 Inflation 49 Consumer Price Index: A Society's Inflation Benchmark 50 Producer Price Index 53 Personal Consumption Expenditure Deflator: The Inflation Benchmark for Monetary Policy 55 Interest Rates: Price of Credit 56 The Dollar and Exchange Rates: The United States in a Global Economy 58 Corporate Profits 60 Summary 62 Chapter 3 Financial Ratios 63 Profitability Ratios 64 Summary 73 Chapter 4 Characterizing a Time Series 75 Why Characterize a Time Series? 76 How to Characterize a Time Series 77 Application: Judging Economic Volatility 101 Summary 109 Chapter 5 Characterizing a Relationship between Time Series 111 Important Test Statistics in Identifying Statistically Significant Relationships 115 Simple Econometric Techniques to Determine a Statistical Relationship 119 Advanced Econometric Techniques to Determine a Statistical Relationship 120 Summary 126 Additional Reading 127 Chapter 6 Characterizing a Time Series Using SAS Software 129 Tips for SAS Users 130 The DATA Step 131 The PROC Step 135 Summary 156 Chapter 7 Testing for a Unit Root and Structural Break Using SAS Software 157 Testing a Unit Root in a Time Series: A Case Study of the U.S. CPI 158 Identifying a Structural Change in a Time Series 162 The Application of the HP Filter 169 Application: Benchmarking the Housing Bust, Bear Stearns, and Lehman Brothers 172 Summary 177 Chapter 8 Characterizing a Relationship Using SAS 179 Useful Tips for an Applied Time Series Analysis 179 Converting a Dataset from One Frequency to Another 182 Application: Did the Great Recession Alter Credit Benchmarks? 215 Summary 221 Chapter 9 The 10 Commandments of Applied Time Series Forecasting for Business and Economics 223 Commandment 1: Know What You Are Forecasting 224 Commandment 2: Understand the Purpose of Forecasting 226 Commandment 3: Acknowledge the Cost of the Forecast Error 226 Commandment 4: Rationalize the Forecast Horizon 229 Commandment 5: Understand the Choice of Variables 231 Commandment 6: Rationalize the Forecasting Model Used 232 Commandment 7: Know How to Present the Results 234 Commandment 8: Know How to Decipher the Forecast Results 235 Commandment 9: Understand the Importance of Recursive Methods 238 Commandment 10: Understand Forecasting Models Evolve over Time 239 Summary 240 Chapter 10 A Single-Equation Approach to Model-Based Forecasting 241 The Unconditional (Atheoretical) Approach 242 The Conditional (Theoretical) Approach 251 Recession Forecast Using a Probit Model 257 Summary 261 Chapter 11 A Multiple-Equations Approach to Model-Based Forecasting 263 The Importance of the Real-Time Short-Term Forecasting 265 The Individual Forecast versus Consensus Forecast: Is There an Advantage? 266 The Econometrics of Real-Time Short-Term Forecasting: The BVAR Approach 268 Forecasting in Real Time: Issues Related to the Data and the Model Selection 275 Case Study: WFC versus Bloomberg 280 Summary 288 Appendix 11A: List of Variables 289 Chapter 12 A Multiple-Equations Approach to Long-Term Forecasting 291 The Unconditional Long-Term Forecasting: The BVAR Model 293 The BVAR Model with Housing Starts 296 The Model without Oil Price Shock 298 The Model with Oil Price Shock 304 Summary 306 Chapter 13 The Risks of Model-Based Forecasting: Modeling, Assessing, and Remodeling 307 Risks to Short-Term Forecasting: There Is No Magic Bullet 308 Risks of Long-Term Forecasting: Black Swan versus a Group of Black Swans 310 Model-Based Forecasting and the Great Recession/Financial Crisis: Worst-Case Scenario versus Panic 314 Summary 315 Chapter 14 Putting the Analysis to Work in the Twenty-First-Century Economy 317 Benchmarking Economic Growth 318 Industrial Production: Another Case of Stationary Behavior 322 Employment: Jobs in the Twenty-First Century 324 Inflation 331 Interest Rates 337 Imbalances between Bond Yields and Equity Earnings 338 A Note of Caution on Patterns of Interest Rates 345 Business Credit: Patterns Reminiscent of Cyclical Recovery 347 Profits 348 Financial Market Volatility: Assessing Risk 349 Dollar 351 Economic Policy: Impact of Fiscal Policy and the Evolution of the U.S. Economy 353 The Long-Term Deficit Bias and Its Economic Implications 358 Summary 362 Appendix: Useful References for SAS Users 365 About the Authors 367 Index 369
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