Do Macro Variables, Asset Markets or Surveys Forecast Inflation Better?

By Andrew Ang, Geert Bekaert, Min Wei. 2007

920 citations recorded by the source corpus.

Surveys do! We examine the forecasting power of four alternative methods of forecasting U.S. inflation out-of-sample: time series ARIMA models; regressions using real activity measures motivated from the Phillips curve; term structure models that include linear, non-linear, and arbitrage-free specifications; and survey-based measures. We also investigate several optimal methods of combining forecasts. Our results show that surveys outperform the other forecasting methods and that the term structure specifications perform relatively poorly. We find little evidence that combining forecasts using means or medians, or using optimal weights with prior information produces superior forecasts to survey information alone. When combining forecasts, the data consistently places the highest weights on survey information.

Subfields: Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/09f4c91422b877d694f39367d033d0684002e3a4

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Citations in the corpus

International Capital Flows and U.S. Interest Rates (2005, background): “11 Ang, Bekaert, and Wei (2005) show that surveys forecast inflation quite well.”
Information Rigidity and the Expectations Formation Process: A Simple Framework and New Facts (2012, positive): “Ang et al. (2007) similarly find that professional forecasts outperform a variety of model-based forecasts, asset-pricing implied forecasts and consumer forecasts.”
Real-Time Inflation Forecasting in a Changing World (2009, positive): “Ang et al. (2006) and Diebold et al. (2006) argue that at the quarterly frequency term structure dynamics can be efficiently summarized by two factors: level and slope. We approximate the term structure through the 3-month and 6-month Treasury Bill rates plus the 1-year to 5-year Fama and Bliss (198”
Inflation Risk and the Inflation Risk Premium (2010, positive): “Source: Ang et al. (2008). The dark line represents the inflation risk premium and the lighter lines a 90% confidence interval around the premium estimate.”
The Term Structure of Inflation Expectations (2012, background): “Ang, Bekaert, and Wei (2007) find that raw surveys dominate term-structure models for forecasts about inflation that are made one year in advance.”
The Determinants of Stock and Bond Return Comovements (2010, methodology): “The regime variable can capture structural changes in the variance of fundamental shocks as identified for instance by Sims and Zha (2005) and Ang, Bekaert, and Wei (2007b) and/or the Great Moderation phenomenon.”
Do Inflation Expectations Propagate the Inflationary Impact of Real Oil Price Shocks?: Evidence from the Michigan Survey (2015, positive): “2 For example, Ang et al. (2007) show that the Michigan Survey provides good inflation forecasts.”
Phillips Curve Inflation Forecasts (2008, methodology): “Ang, Bekaert, and Wei (2007) also considered survey forecasts, and their most striking result is that survey forecasts (the Michigan, Livingston, and Survey of Professional Forecasters surveys) perform very well: for the inflation measures that the survey respondents are asked to forecast, the…”
Accounting Earnings and Gross Domestic Product (2014, positive): “The SPF is the longest and most well-regarded publicly available survey of quarterly macroeconomic forecasts, and it has been widely used in prior research (e.g., Sims, 2002; Ang et al., 2007).”
Alternative tests for correct specification of conditional predictive densities (2019, methodology): “(3) tests the correct specification of the forecasting model evaluated at the parameter values obtained conditional on the estimation procedure.”