Disagreement versus Uncertainty: Evidence from Distribution Forecasts

We use a cross-section of economic survey forecasts to predict the distribution of US macro variables in real time. This generalizes the existing literature, which uses disagreement (i.e., the cross-sectional variance of survey forecasts) to predict uncertainty (i.e., the conditional variance of future macroeconomic quantities). Our results show that cross-sectional information can be helpful for distribution forecasting, but this information needs to be modeled in a statistically efficient way in order to avoid overfitting. A simple one-parameter model which exploits time variation in the cross-section of survey point forecasts is found to perform well in practice.

[1]  Michael P. Clements.  Forecast Uncertainty—Ex Ante and Ex Post: U.S. Inflation and Output Growth , 2014 .

[2]  S. Hall,et al.  Combining density forecasts , 2007 .

[3]  R Core Team,et al.  R: A language and environment for statistical computing. , 2014 .

[4]  Charles F. Manski,et al.  Comparing the Point Predictions and Subjective Probability Distributions of Professional Forecasters , 2006 .

[5]  Dean Croushore,et al.  A real-time data set for macroeconomists , 2001 .

[6]  Tilmann Gneiting,et al.  Predicting Inflation: Professional Experts Versus No-Change Forecasts , 2010 .

[7]  Sylvia Frühwirth-Schnatter,et al.  Finite Mixture and Markov Switching Models , 2006 .

[8]  K. Lahiri,et al.  Measuring Forecast Uncertainty by Disagreement: The Missing Link , 2008 .

[9]  K. Lahiri,et al.  Evolution of Forecast Disagreement in a Bayesian Learning Model , 2007 .

[10]  William A. Bomberger.  Disagreement as a Measure of Uncertainty , 1996 .

[11]  F. Diebold,et al.  Comparing Predictive Accuracy , 1994, Business Cycles.

[12]  Allan Timmermann,et al.  Optimal Forecast Combination Under Regime Switching , 2004 .

[13]  M. Stone.  The Opinion Pool , 1961 .

[14]  C. Manski,et al.  Assessing the temporal variation of macroeconomic forecasts by a panel of changing composition , 2011 .

[15]  Jon Faust,et al.  Comparing Greenbook and Reduced Form Forecasts Using a Large Realtime Dataset , 2007 .

[16]  T. Gneiting,et al.  The continuous ranked probability score for circular variables and its application to mesoscale forecast ensemble verification , 2006 .

[17]  Todd E. Clark,et al.  Macroeconomic Forecasting Performance under Alternative Specifications of Time-Varying Volatility , 2015 .

[18]  Andrew J. Patton,et al.  Why do forecasters disagree? Lessons from the term structure of cross-sectional dispersion , 2010 .

[19]  G. Koop,et al.  Bayesian Multivariate Time Series Methods for Empirical Macroeconomics , 2009 .

[20]  M. C. Jones,et al.  A reliable data-based bandwidth selection method for kernel density estimation , 1991 .

[21]  Todd E. Clark,et al.  Advances in Forecast Evaluation , 2011 .

[22]  Allan Timmermann,et al.  Forecast Combination With Entry and Exit of Experts , 2006 .

[23]  A. Raftery,et al.  Using Bayesian Model Averaging to Calibrate Forecast Ensembles , 2005 .

[24]  Dean Croushore.  The Survey of Professional Forecasters , 1993 .

[25]  Ronnie Sadka,et al.  Analyst Disagreement, Mispricing and Liquidity , 2007 .

[26]  C. Granger,et al.  Handbook of Economic Forecasting , 2006 .

[27]  J. Geweke,et al.  Optimal Prediction Pools , 2008 .

[28]  W. Newey,et al.  Automatic Lag Selection in Covariance Matrix Estimation , 1994 .

[29]  Francesco Ravazzolo,et al.  The Macroeconomic Forecasting Performance of Autoregressive Models with Alternative Specifications of Time-Varying Volatility , 2012 .

[30]  Paolo Giordani,et al.  In!ation forecast uncertainty , 2003 .

[31]  Thomas H. McCurdy,et al.  Do High-Frequency Measures of Volatility Improve Forecasts of Return Distributions? , 2008 .

[32]  Dirk P. Kroese,et al.  Kernel density estimation via diffusion , 2010, 1011.2602.

[33]  Paolo Giordani,et al.  Inflation Forecast Uncertainty , 2001 .

[34]  R. L. Winkler,et al.  Scoring Rules for Continuous Probability Distributions , 1976 .

[35]  J. Geweke,et al.  Contemporary Bayesian Econometrics and Statistics , 2005 .

[36]  Frieder Mokinski,et al.  Forecasting with Bayesian Vector Autoregressions Estimated Using Professional Forecasts , 2016 .

[37]  Jonathan H. Wright.  EVALUATING REAL-TIME VAR FORECASTS WITH AN INFORMATIVE DEMOCRATIC PRIOR: VAR WITH INFORMATIVE DEMOCRATIC PRIOR , 2013 .

[38]  J. Wolfers,et al.  Disagreement about Inflation Expectations , 2003, NBER Macroeconomics Annual.

[39]  M. Hashem Pesaran,et al.  Chapter 14 Survey Expectations , 2006 .

[40]  K. Wallis,et al.  Uncertainty and Disagreement in Economic Prediction: The Bank of England Survey of External Forecasters , 2008 .

[41]  Olivier Coibion,et al.  What Can Survey Forecasts Tell Us About Informational Rigidities? , 2008 .

[42]  Giorgio E. Primiceri,et al.  Time Varying Structural Vector Autoregressions and Monetary Policy , 2002 .

[43]  W. Newey,et al.  A Simple, Positive Semi-Definite, Heteroskedasticity and Autocorrelationconsistent Covariance Matrix , 1986 .

[44]  Kenneth F. Wallis,et al.  An Assessment of Bank of England and National Institute Inflation Forecast Uncertainties , 2004, National Institute Economic Review.

[45]  Jonathan H. Wright.  Evaluating Real-Time VAR Forecasts with an Informative Democratic Prior , 2010 .

[46]  D. Giannone,et al.  Now-Casting and the Real-time Data Flow , 2012, SSRN Electronic Journal.

[47]  W. Wien,et al.  Econometric Computing with HC and HAC Covariance Matrix Estimators , 2004 .

[48]  Giorgio E. Primiceri.  Time Varying Structural Vector Autoregressions and Monetary Policy , 2002 .

[49]  B. Hansen.  Autoregressive Conditional Density Estimation , 1994 .

[50]  W. Newey,et al.  A Simple, Positive Semi-Definite, Heteroskedasticity and Autocorrelationconsistent Covariance Matrix , 1986 .

[51]  琢史 大久保.  ズームアップ経済統計 マクロ経済データは真に無料の時代に(アメリカ・セントルイス連銀「Federal Reserve Economic Data」) , 2015 .

[52]  M. Pesaran,et al.  Survey Expectations , 2005, SSRN Electronic Journal.

[53]  A. Raftery,et al.  Strictly Proper Scoring Rules, Prediction, and Estimation , 2007 .

[54]  T. Gneiting,et al.  Combining Predictive Distributions , 2011, 1106.1638.

[55]  Ingmar Nolte,et al.  Sell-Side Analysts' Career Concerns During Banking Stresses , 2014 .

[56]  Michael P. Clements,et al.  Measuring Macroeconomic Uncertainty: US Inflation and Output Growth , 2014 .

[57]  Dean Croushore,et al.  Forecasting with Real-Time Macroeconomic Data , 2006 .

[58]  Antonello D'Agostino,et al.  Are Some Forecasters Really Better Than Others , 2012 .