{"product_id":"economic-and-business-forecasting-isbn-9781118497098","title":"Economic and Business Forecasting","description":"\u003cb\u003eDiscover the secrets to applying simple econometric techniques to improve forecasting\u003c\/b\u003e \u003cp\u003eEquipping analysts, practitioners, and graduate students with a statistical framework to make effective decisions based on the application of simple economic and statistical methods, \u003ci\u003eEconomic and Business Forecasting\u003c\/i\u003e 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.\u003c\/p\u003e \u003cul\u003e \u003cli\u003ePresents the economic and financial variables that offer unique insights into economic performance\u003c\/li\u003e \u003cli\u003eHighlights the econometric techniques that can be used to characterize variables\u003c\/li\u003e \u003cli\u003eExplores the application of SAS software, complete with simple explanations of SAS-code and output\u003c\/li\u003e \u003cli\u003eIdentifies key econometric issues with practical solutions to those problems\u003c\/li\u003e \u003c\/ul\u003e \u003cp\u003ePresenting 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.\u003c\/p\u003e \u003cp\u003ePreface xiii\u003c\/p\u003e \u003cp\u003eAcknowledgments xvii\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 1 Creating Harmony Out of Noisy Data 1\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eEffective Decision Making: Characterize the Data 2\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 2 First, Understand the Data 27\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eGrowth: How Is the Economy Doing Overall? 30\u003c\/p\u003e \u003cp\u003ePersonal Consumption 31\u003c\/p\u003e \u003cp\u003eGross Private Domestic Investment 33\u003c\/p\u003e \u003cp\u003eGovernment Purchases 35\u003c\/p\u003e \u003cp\u003eNet Exports of Goods and Services 36\u003c\/p\u003e \u003cp\u003eReal Final Sales and Gross Domestic Purchases 37\u003c\/p\u003e \u003cp\u003eThe Labor Market: Always a Core Issue 37\u003c\/p\u003e \u003cp\u003eEstablishment Survey 39\u003c\/p\u003e \u003cp\u003eData Revision: A Special Consideration 42\u003c\/p\u003e \u003cp\u003eThe Household Survey 43\u003c\/p\u003e \u003cp\u003eMarrying the Labor Market Indicators Together 48\u003c\/p\u003e \u003cp\u003eJobless Claims 48\u003c\/p\u003e \u003cp\u003eInflation 49\u003c\/p\u003e \u003cp\u003eConsumer Price Index: A Society’s Inflation Benchmark 50\u003c\/p\u003e \u003cp\u003eProducer Price Index 53\u003c\/p\u003e \u003cp\u003ePersonal Consumption Expenditure Deflator: The Inflation Benchmark for Monetary Policy 55\u003c\/p\u003e \u003cp\u003eInterest Rates: Price of Credit 56\u003c\/p\u003e \u003cp\u003eThe Dollar and Exchange Rates: The United States in a Global Economy 58\u003c\/p\u003e \u003cp\u003eCorporate Profits 60\u003c\/p\u003e \u003cp\u003eSummary 62\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 3 Financial Ratios 63\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eProfitability Ratios 64\u003c\/p\u003e \u003cp\u003eSummary 73\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 4 Characterizing a Time Series 75\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eWhy Characterize a Time Series? 76\u003c\/p\u003e \u003cp\u003eHow to Characterize a Time Series 77\u003c\/p\u003e \u003cp\u003eApplication: Judging Economic Volatility 101\u003c\/p\u003e \u003cp\u003eSummary 109\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 5 Characterizing a Relationship between Time Series 111\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eImportant Test Statistics in Identifying Statistically Significant Relationships 115\u003c\/p\u003e \u003cp\u003eSimple Econometric Techniques to Determine a Statistical Relationship 119\u003c\/p\u003e \u003cp\u003eAdvanced Econometric Techniques to Determine a Statistical Relationship 120\u003c\/p\u003e \u003cp\u003eSummary 126\u003c\/p\u003e \u003cp\u003eAdditional Reading 127\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 6 Characterizing a Time Series Using SAS Software 129\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eTips for SAS Users 130\u003c\/p\u003e \u003cp\u003eThe DATA Step 131\u003c\/p\u003e \u003cp\u003eThe PROC Step 135\u003c\/p\u003e \u003cp\u003eSummary 156\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 7 Testing for a Unit Root and Structural Break Using SAS Software 157\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eTesting a Unit Root in a Time Series: A Case Study of the U.S. CPI 158\u003c\/p\u003e \u003cp\u003eIdentifying a Structural Change in a Time Series 162\u003c\/p\u003e \u003cp\u003eThe Application of the HP Filter 169\u003c\/p\u003e \u003cp\u003eApplication: Benchmarking the Housing Bust, Bear Stearns, and Lehman Brothers 172\u003c\/p\u003e \u003cp\u003eSummary 177\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 8 Characterizing a Relationship Using SAS 179\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eUseful Tips for an Applied Time Series Analysis 179\u003c\/p\u003e \u003cp\u003eConverting a Dataset from One Frequency to Another 182\u003c\/p\u003e \u003cp\u003eApplication: Did the Great Recession Alter Credit Benchmarks? 215\u003c\/p\u003e \u003cp\u003eSummary 221\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 9 The 10 Commandments of Applied Time Series Forecasting for Business and Economics 223\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eCommandment 1: Know What You Are Forecasting 224\u003c\/p\u003e \u003cp\u003eCommandment 2: Understand the Purpose of Forecasting 226\u003c\/p\u003e \u003cp\u003eCommandment 3: Acknowledge the Cost of the Forecast Error 226\u003c\/p\u003e \u003cp\u003eCommandment 4: Rationalize the Forecast Horizon 229\u003c\/p\u003e \u003cp\u003eCommandment 5: Understand the Choice of Variables 231\u003c\/p\u003e \u003cp\u003eCommandment 6: Rationalize the Forecasting Model Used 232\u003c\/p\u003e \u003cp\u003eCommandment 7: Know How to Present the Results 234\u003c\/p\u003e \u003cp\u003eCommandment 8: Know How to Decipher the Forecast Results 235\u003c\/p\u003e \u003cp\u003eCommandment 9: Understand the Importance of Recursive Methods 238\u003c\/p\u003e \u003cp\u003eCommandment 10: Understand Forecasting Models Evolve over Time 239\u003c\/p\u003e \u003cp\u003eSummary 240\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 10 A Single-Equation Approach to Model-Based Forecasting 241\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eThe Unconditional (Atheoretical) Approach 242\u003c\/p\u003e \u003cp\u003eThe Conditional (Theoretical) Approach 251\u003c\/p\u003e \u003cp\u003eRecession Forecast Using a Probit Model 257\u003c\/p\u003e \u003cp\u003eSummary 261\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 11 A Multiple-Equations Approach to Model-Based Forecasting 263\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eThe Importance of the Real-Time Short-Term Forecasting 265\u003c\/p\u003e \u003cp\u003eThe Individual Forecast versus Consensus Forecast: Is There an Advantage? 266\u003c\/p\u003e \u003cp\u003eThe Econometrics of Real-Time Short-Term Forecasting: The BVAR Approach 268\u003c\/p\u003e \u003cp\u003eForecasting in Real Time: Issues Related to the Data and the Model Selection 275\u003c\/p\u003e \u003cp\u003eCase Study: WFC versus Bloomberg 280\u003c\/p\u003e \u003cp\u003eSummary 288\u003c\/p\u003e \u003cp\u003eAppendix 11A: List of Variables 289\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 12 A Multiple-Equations Approach to Long-Term Forecasting 291\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eThe Unconditional Long-Term Forecasting: The BVAR Model 293\u003c\/p\u003e \u003cp\u003eThe BVAR Model with Housing Starts 296\u003c\/p\u003e \u003cp\u003eThe Model without Oil Price Shock 298\u003c\/p\u003e \u003cp\u003eThe Model with Oil Price Shock 304\u003c\/p\u003e \u003cp\u003eSummary 306\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 13 The Risks of Model-Based Forecasting: Modeling, Assessing, and Remodeling 307\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eRisks to Short-Term Forecasting: There Is No Magic Bullet 308\u003c\/p\u003e \u003cp\u003eRisks of Long-Term Forecasting: Black Swan versus a Group of Black Swans 310\u003c\/p\u003e \u003cp\u003eModel-Based Forecasting and the Great Recession\/Financial Crisis: Worst-Case Scenario versus Panic 314\u003c\/p\u003e \u003cp\u003eSummary 315\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 14 Putting the Analysis to Work in the Twenty-First-Century Economy 317\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eBenchmarking Economic Growth 318\u003c\/p\u003e \u003cp\u003eIndustrial Production: Another Case of Stationary Behavior 322\u003c\/p\u003e \u003cp\u003eEmployment: Jobs in the Twenty-First Century 324\u003c\/p\u003e \u003cp\u003eInflation 331\u003c\/p\u003e \u003cp\u003eInterest Rates 337\u003c\/p\u003e \u003cp\u003eImbalances between Bond Yields and Equity Earnings 338\u003c\/p\u003e \u003cp\u003eA Note of Caution on Patterns of Interest Rates 345\u003c\/p\u003e \u003cp\u003eBusiness Credit: Patterns Reminiscent of Cyclical Recovery 347\u003c\/p\u003e \u003cp\u003eProfits 348\u003c\/p\u003e \u003cp\u003eFinancial Market Volatility: Assessing Risk 349\u003c\/p\u003e \u003cp\u003eDollar 351\u003c\/p\u003e \u003cp\u003eEconomic Policy: Impact of Fiscal Policy and the Evolution of the U.S. Economy 353\u003c\/p\u003e \u003cp\u003eThe Long-Term Deficit Bias and Its Economic Implications 358\u003c\/p\u003e \u003cp\u003eSummary 362\u003c\/p\u003e \u003cp\u003eAppendix: Useful References for SAS Users 365\u003c\/p\u003e \u003cp\u003eAbout the Authors 367\u003c\/p\u003e \u003cp\u003eIndex 369\u003c\/p\u003e \u003cp\u003e\u003cb\u003eJOHN E. SILVIA\u003c\/b\u003e 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. \u003c\/p\u003e\u003cp\u003e\u003cb\u003eAZHAR IQBAL\u003c\/b\u003e 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. \u003c\/p\u003e\u003cp\u003e\u003cb\u003eSAM BULLARD \u003c\/b\u003eis a Managing Director and Senior Economist at Wells Fargo Securities providing analysis and commentary on financial markets and macroeconomic developments. \u003c\/p\u003e\u003cp\u003e\u003cb\u003eSARAH WATT\u003c\/b\u003e 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. \u003c\/p\u003e\u003cp\u003e\u003cb\u003eKAYLYN SWANKOSKI\u003c\/b\u003e is an Economic Analyst at Wells Fargo Securities.  \u003c\/p\u003e\u003cp\u003eDue to the Great Recession and the accompanying financial crisis, the premium on effective economic analysis, especially the two aspects of that analysis and accurate forecasting of economic and financial variables, has significantly increased. \u003ci\u003eEconomic and Business Forecasting\u003c\/i\u003e introduces statistical techniques that can help characterize the behavior of economic relationships, testing whether certain series such as output, employment, profits, and interest rates exhibit a steady pace of growth over time, or if that pace has drifted. \u003c\/p\u003e \u003cp\u003eFocused on a select set of major economic and financial variables—such as economic growth, final sales, employment, inflation, interest rates, corporate profits, financial ratios and the exchange value of the dollar—\u003ci\u003eEconomic and Business Forecasting\u003c\/i\u003e employs econometric techniques and the statistical software SAS\u003csup\u003e™\u003c\/sup\u003e serves as a template for readers to apply to variables of interest. These variables form the core of an effective decision-making process in both the private and public sectors. \u003c\/p\u003e\u003cp\u003eProviding a practical forecasting framework for important everyday applications, this book considers questions including: \u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eHow can we identify economic series that appear to be behaving in typical cyclical fashion compared to those that are not?\u003c\/li\u003e \u003cli\u003eWhy have exceptionally low mortgage interest rates not spurred a pickup in housing as in prior recoveries?\u003c\/li\u003e \u003cli\u003e\tIf a time series displays a cyclical component, how does it behave as we move through the business cycle?\u003c\/li\u003e \u003cli\u003e\tDo turning points in the time series lead or lag those of other series?\u003c\/li\u003e\n\u003c\/ul\u003e \u003cp\u003eDiscover the secrets to applying simple econometric techniques to improve forecasting with the proven guidance found in \u003ci\u003eEconomic and Business Forecasting.\u003c\/i\u003e\u003c\/p\u003e","brand":"Wiley","offers":[{"title":"Default Title","offer_id":47989101199589,"sku":"NP9781118497098","price":75.0,"currency_code":"USD","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/1842\/7735\/files\/9781118497098.jpg?v=1761782800","url":"https:\/\/k12savings.com\/es\/products\/economic-and-business-forecasting-isbn-9781118497098","provider":"K12savings","version":"1.0","type":"link"}