Inside the Crystal Ball: How to Make and Use Forecasts
Format: PDF / Kindle (mobi) / ePub
A practical guide to understanding economic forecasts
In Inside the Crystal Ball: How to Make and Use Forecasts, UBS Chief U.S. Economist Maury Harris helps readers improve their own forecasting abilities by examining the elements and processes that characterize successful and failed forecasts. The book:
• Provides insights from Maury Harris, named among Bloomberg's 50 Most Influential People in Global Finance.
• Demonstrates "best practices" in the assembly and evaluation of forecasts. Harris walks readers through the real-life steps he and other successful forecasters take in preparing their projections. These valuable procedures can help forecast users evaluate forecasts and forecasters as inputs for making their own specific business and investment decisions.
• Emphasizes the critical role of judgment in improving projections derived from purely statistical methodologies. Harris explores the prerequisites for sound forecasting judgment—a good sense of history and an understanding of contemporary theoretical frameworks—in readable and illuminating detail.
• Addresses everyday forecasting issues, including the credibility of government statistics and analyses, fickle consumers, and volatile business spirits. Harris also offers procedural guidelines for special circumstances, such as natural disasters, terrorist threats, gyrating oil and stock prices, and international economic crises.
• Evaluates major contemporary forecasting issues—including the now commonplace hypothesis of sustained economic sluggishness, possible inflation outcomes in an environment of falling unemployment, and projecting interest rates when central banks implement unprecedented low interest rate and quantitative easing (QE) policies.
• Brings to life Harris's own experiences and those of other leading economists in his almost four-decade career as a professional economist and forecaster. Dr. Harris presents his personal recipes for long-term credibility and commercial success to anyone offering advice about the future.
applying judgment to a statistical forecast is to examine a model’s in-sample errors. Attempt to determine what was happening when the model went off track. Often this entails reviewing the history of the period when the model erred. Possible periodic causal factors not picked up by a model’s statistical drivers include domestic public policy and political uncertainty surrounding elections, or some international development such as war or a jump in oil prices. The home price collapse
about the future to clients, bosses, colleagues, and anyone else whom we need to convince or whom we want to retain as a loyal listener. As such, this book shows you how to evaluate advice about the future more effectively. Its focus on the nonmathematical, judgmental element of forecasting is an ideal practitioners’ supplement to standard statistical forecasting texts. Forecasting in the worlds of business, marketing, and finance often hinges on assumptions about the U.S. economy and U.S.
turn sour, leveraged lenders and investors experience cash shortfalls that must be addressed by selling less risky and more liquid investments. In this setting, lenders are setting tighter credit standards and asset prices are falling, leading to an exacerbated financial crisis that “feeds on itself” and triggers recession. While Minsky’s description of the financial roots of the business cycle was a familiar history, mainstream economists had trouble accepting FIH. This was partly because of
analytical risks of overreacting, as well as underreacting, to leverage trends. My experience is that forecasters who almost always bemoan rising household leverage have often underestimated consumer-spending growth. Second, forecasters’ and regulators’ scrutiny of financial sector leverage has much improved since the Great Recession. This is partly because Minsky’s followers were eventually proven right about the potentially disastrous economic consequences of leverage when it becomes too high
domestic product (GDP) =C+I+G+X−M Consumer spending (C) = (I + G + X)/(s + t + m) Multiplier (see explanation in text) = 1/(s + t + m) GDP C I G X M s t m = Gross Domestic Product = Consumer spending = Investment in inventories, housing, plant and equipment = Government spending = Exports = Imports = Marginal propensity to save = Marginal tax rate = Marginal propensity to import Figure 6.8 Key Formulas in Standard Keynesian GDP Model than the forecast sum of government spending, fixed