Dispersion and uncertainty in density forecasts: Evidence from surveys of professional forecasters

• Main Author: LI, You
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2018
• Subjects: Econometrics
• Online Access: https://ink.library.smu.edu.sg/etd_coll/148; https://ink.library.smu.edu.sg/cgi/viewcontent.cgi?article=1150&context=etd_coll
• Institution: Singapore Management University

This dissertation studies patterns of dispersion in density forecasts as reported in surveys of professional forecasters. We pay special attention to the role of uncertainty in explaining dispersion in professional forecasters’ density forecasts of real output growth and inflation. We also consider the relationship between survey design and forecaster behavior. The last chapter describes future research exploring the characteristics of forecaster expectations using probability integral transforms. As a starting point, chapter one gives a summary of the literature that tries to answer, using data from survey of forecasters, the following three key questions: Why do forecasters disagree? What do density forecasts reveal in addition to point forecasts? Does disagreement serve as a good proxy for forecaster uncertainty? This chapter provides an overview of the studies and briefly discusses how this dissertation can make contributions to the literature. Chapter two explores the role of uncertainty in explaining dispersion in professional forecasters’ density forecasts of real output growth and inflation. We consider three separate notions of uncertainty: general macroeconomic uncertainty (the fact that macroeconomic variables are easier to forecast at some time than others), policy uncertainty, and forecaster uncertainty. The main finding is that dispersion in individual density forecasts is related to overall macroeconomic uncertainty and policy uncertainty, while forecaster uncertainty (which we define as the average in the uncertainty expressed by individual forecasters) appears to have little role in forecast dispersion. Chapter three examines the relationship between survey design and forecasters’ behavior by exploiting changes to the probability bins provided to forecasters at the solicitation of density forecasts. We consider three important surveys, namely Survey of Professional Forecasters by the Philadelphia Fed (USSPF), Survey of Professional Forecasters by the European Central Bank (ECBSPF), and Survey of External Forecasters by Bank of England (SEF). While the adjustment of forecast bins can reasonably arise from the fluctuation of underlying macroeconomic variable, there are also cases where the modification is neutral to the economic environment. Our analysis examines how disagreement and forecaster uncertainty respond to these two different categories of survey changes. The results suggest that disagreement only responds to changes caused by real economy. Uncertainty responds to both and the effect is more persistent. These empirical facts highlight the importance of behavioral perspective when inferences are drawn from professional forecasts. I summarize our conclusion in Chapter four, and describe future research plan exploring the features of forecaster uncertainty using probability integral transforms (“z-statistics”), a commonly-used test for density forecast optimality. We focus on the shape of the distribution of z-statistics, which is informative about the confidence level as well as bias (optimism or pessimism) of forecasters. There is evidence of significant hysteresis and that survey scheme greatly affects the performance of density forecasts.