Bias in macroeconomic forecasts

By Roy Batchelor. 2007

137 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/364631d43041034aa34417dc548e98a215f6ad12

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Economics and Econometrics

Citations in the corpus

The Role of Media for Inflation Forecast Disagreement of Households and Professionals (2012, unknown): “The important role of the media for belief formation is underlined by Blinder and Krueger (2004). Based on a representative survey of U.S. households, these authors find that television and newspaper news are the predominant information sources that households consult to form their expectations abou”
Uncertainty and disagreement in economic prediction : the Bank of England Survey of External Forecasters (2008, unknown): “Batchelor and Dua (1996) call the preferred measure the root mean subjective variance (RMSV ) and note that it is more consistent with an assumption of quadratic utility than the average standard deviation.”
Accuracy, Unbiasedness and Efficiency of Professional Macroeconomic Forecasts: An empirical Comparison for the G7 (2011, unknown): “Notable exceptions are Lahiri and Sheng (2008), who propose a model for disagreement among forecasters and estimate this based on individual forecasts on GDP growth from the Consensus Economics data set; Batchelor (2007) , who uses a similar disaggregated data set to analyze the bias in forecasts f”
Expert Political Judgment : How Good Is It ? How Can We Know ? (2012, background): “It is not surprising then that Batchelor (2007) finds that "Private sector forecasters also have incentives to bias their forecasts towards optimism or pessimism,” so as to stand out from the crowd, though we believe this is not the key explanation for the existence of hedgehogs.”
Evolution of Forecast Disagreement in a Bayesian Learning Model (2008, methodology): “10 Batchelor and Dua (1991) reported that the single most important forecasting technique used by the Blue Chip panel was judgment (51%), followed by econometric modeling (28%), and time series analysis (21%).”