TY  - BOOK
AU  - Silvia,John E.
AU  - Azhar,Iqbal
AU  - Swankoski,Kaylyn
AU  - Watt,Sarah
AU  - Bullard,Sam
AU  - Iqbal,Azhar
TI  - Economic and Business Forecasting: Analyzing and Interpreting Econometric
T2  - Wiley and SAS Business Ser.
SN  - 9781118569542
AV  - HB3730 .S484 2014 
U1  - 330.01330.01/5195 
PY  - 2014///
CY  - Somerset
PB  - John Wiley & Sons, Incorporated
KW  - Business forecasting
KW  - Decision making
KW  - Econometrics
KW  - Economic forecasting
KW  - Electronic books
N1  - Intro -- Economic and Business Forecasting: Analyzing and Interpreting Econometric Results -- Copyright -- Contents -- Preface -- Acknowledgments -- Chapter 1: Creating Harmony Out of Noisy Data -- Effective Decision Making: Characterize the Data -- Part IA: Identifying Trend in a Time Series: GDP and Public Deficits -- Part IB: Identifying the Cycle for a Time Series -- Part IC: Identifying the Subcycles of Economic Behavior: Use of the HP Filter -- Part ID: Spotting Structural Breaks in a Time Series -- Part IE: Unit Root Tests -- Part IF: Modeling the Cycle -- Part IG: Cointegration and Error Correction Model -- Part IH: Causality-What Drives What? -- Part II: Measuring Volatility: ARCH/GARCH -- Part IIA: Forecasting with a Regression Model -- Part IIB: Forecasting Recession/Regime Switch as Either/or Outcomes -- Part IIC: Forecasting with Vector Autoregression -- Part IID: Forecast Evaluation -- 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 -- Return on Equity -- Return on Assets -- Corporate Profits as a Percentage of GDP -- Liquidity Ratios -- Leverage Ratios; Investment Valuation Ratio -- Summary -- Chapter 4: Characterizing a Time Series -- Why Characterize a Time Series? -- How to Characterize a Time Series -- Putting Simple Statistical Measures to Work -- Identifying a Time Trend in a Series -- Identifying the Cycle in a Time Series -- Testing for a Unit Root -- Structural Change: A New Normal? -- Separating Cycle and Trend in a Time Series: The Hodrick-Prescott Filter -- Application: Judging Economic Volatility -- Look at the Data -- Putting Simple Statistical Measures to Work -- Corporate Profits -- Focus on the Labor Market Using Monthly Data -- Financial Market Volatility: Assessing Risk -- Summary -- Chapter 5: Characterizing a Relationship between Time Series -- Important Test Statistics in Identifying Statistically Significant Relationships -- Level of Significance and p-value -- The t-Value or t-Test -- The F-Test -- R2 and Adjusted R2 -- White Noise/Autocorrelation Detection Tests -- Model Selection Criteria: The AIC and SIC -- Simple Econometric Techniques to Determine a Statistical Relationship -- Correlation Analysis -- Regression Analysis -- Advanced Econometric Techniques to Determine a Statistical Relationship -- Cointegration Analysis -- The Error Correction Model -- The Granger Causality Test -- The ARCH/GARCH Model -- Summary -- Additional Reading -- Chapter 6: Characterizing a Time Series Using SAS Software -- Tips for SAS Users -- The Data Step -- The Proc Step -- Seasonal Adjustment in SAS -- Calculating the Mean, Standard Deviation, and Stability Ratio of a Variable -- Identifying a Time Trend in a Time Series -- Identifying Cyclical Behavior in a Time Series -- 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; Testing for a Structural Break: The Dummy Variable Approach -- Testing for a Structural Break: The Chow Test -- Testing for a Structural Break: The State-Space Approach -- The Application of the HP Filter -- Application: Benchmarking the Housing Bust, Bear Stearns, and Lehman Brothers -- 2006: The Housing Bust -- 2007: Bear Stearns and the Overnight Market for Risk -- 2008: Lehman and the Financial Crisis -- Summary -- Chapter 8: Characterizing a Relationship Using SAS -- Useful Tips for an Applied Time Series Analysis -- Converting a Dataset from One Frequency to Another -- The Correlation Analysis -- The Regression Analysis -- The Cointegration and ECM Analysis -- The Error Correction Model -- The Granger Causality Test -- The ARCH/GARCH Model -- Application: Did the Great Recession Alter Credit Benchmarks? -- Delinquency Rates: Identifying Change Post-Great Recession -- Patterns in Charge-off Rates: Identifying Differences in the Character of Trends -- Breakdown of the Monetary Policy Transmission Mechanism -- Summary -- 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 -- Symmetric versus Asymmetric Loss Function -- Linear versus Nonlinear Loss Function -- Commandment 4: Rationalize the Forecast Horizon -- Short-Term Forecasting -- Long-Term Forecasting -- 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 -- Summary; Chapter 10: A Single-Equation Approach to Model-Based Forecasting -- The Unconditional (Atheoretical) Approach -- The Box-Jenkins Forecasting Methodology -- Application of the Box-Jenkins Methodology -- The Conditional (Theoretical) Approach -- A Case Study of the Taylor Rule -- What About Strong Growth? -- Recession Forecast Using a Probit Model -- Application of the 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 versus Consensus Forecast: Is There an Advantage? -- The Econometrics of Real-Time Short-Term Forecasting: The BVAR Approach -- The Bayesian Vector Autoregression Model -- Forecast Evaluation: Real-Time Measures -- A SAS Application of the BVAR Approach: A Case Study of the Employment Forecast -- Forecasting in Real Time: Issues Related to the Data and the Model Selection -- The Functional Form of the Variables -- The Selection of the Best Model Specification -- Timing of the Release: A Dependent Variable and Predictors -- Case Study: WFC versus 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 -- A Small-Scale Macro Model: Equation 12.1 -- The Model with Oil Price Shock -- Summary -- 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 -- Summary -- Chapter 14: Putting the Analysis to Work in the Twenty-First-Century Economy; Benchmarking Economic Growth -- Benchmarks: Economic Growth and the Labor Market -- Testing, Not Assuming, Economic Values for Good Decision Making -- Our Benchmark for Real GDP Growth: 2.75 Percent -- Industrial Production: Another Case of Stationary Behavior -- Employment: Jobs in the Twenty-first Century -- Unemployment Rate Measured by U-3: A Surprising Result of Stationarity -- Employment Growth: Surprisingly Stationary Despite Impressions -- The Beveridge Curve: Yet to Shift Inward -- Structural Change in the U.S. Labor Market: Two Illustrations -- Inflation -- Inflation and Inflation Expectations -- Inflation: A (Small) Bias to the Upside -- Interest Rates -- Inflation and Real Yields: A Signal of Financial Imbalances -- Imbalances between Bond Yields and Equity Earnings -- Healthy Bond Issuance Consistent with Functioning Credit Market Expansion -- Two-Year Treasury Yield: Benchmark for the Short End of Yield Curve -- Adjusting the Two-Year Treasury Yield to Achieve Stationarity -- 10-Year Treasury Yields: Not Mean Reverting -- A Note of Caution on Patterns of Interest Rates -- Business Credit: Patterns Reminiscent of Cyclical Recovery -- Profits -- Corporate Profits: Surprising Stability -- Financial Market Volatility: Assessing Risk -- Dollar -- Dollar Exchange Rate: A Strong Dollar Is Not the Real Story -- Volatility in the Dollar over Time -- Economic Policy: Impact of Fiscal Policy and the Evolution of the U.S. Economy -- Large and Persistent Deficits: A Brave New World of Fiscal Policy -- Budget Limits with 2.75 Percent Trend Economic Growth -- The Long-Term Deficit Bias and Its Economic Implications -- Interest Rates Trend Reversal: Test to Come Ahead -- Credit Imbalance: The U.S. Treasury Market -- Summary -- Appendix: Useful References for SAS Users -- About the Authors -- Index
N2  - 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
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