2018
DOI: 10.1016/j.jmacro.2018.09.002
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Disagreement between FOMC members and the Fed’s staff: New insights based on a counterfactual interest rate

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Cited by 7 publications
(2 citation statements)
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“…This work on the forecast heterogeneity of monetary policy committee member is related to a broader literature about monetary policy disagreement based on political affiliation (Bordo & Istrefi, 2018), career backgrounds (Eichler & Lahner, 2014), and regional conditions (Coibion & Goldstein, 2012; Jung & Latsos, 2015; Meade & Sheets, 2005). Policy preferences and forecast disagreement interact in important ways; for example, hawkishness is associated with higher‐than‐consensus inflation forecasts (Bennani et al., 2018; Eichler & Lahner, 2014; McCracken, 2010; Schultefrankenfeld, 2020). Moreover, non‐voting FOMC members may have strategic motives in forecasting, as they systematically overpredict inflation relative to the consensus if they prefer tighter monetary policy (Tillmann, 2011) and “anti‐herd” their inflation forecasts (Rülke & Tillmann, 2011).…”
Section: Forecasting Frameworkmentioning
confidence: 99%
“…This work on the forecast heterogeneity of monetary policy committee member is related to a broader literature about monetary policy disagreement based on political affiliation (Bordo & Istrefi, 2018), career backgrounds (Eichler & Lahner, 2014), and regional conditions (Coibion & Goldstein, 2012; Jung & Latsos, 2015; Meade & Sheets, 2005). Policy preferences and forecast disagreement interact in important ways; for example, hawkishness is associated with higher‐than‐consensus inflation forecasts (Bennani et al., 2018; Eichler & Lahner, 2014; McCracken, 2010; Schultefrankenfeld, 2020). Moreover, non‐voting FOMC members may have strategic motives in forecasting, as they systematically overpredict inflation relative to the consensus if they prefer tighter monetary policy (Tillmann, 2011) and “anti‐herd” their inflation forecasts (Rülke & Tillmann, 2011).…”
Section: Forecasting Frameworkmentioning
confidence: 99%
“…Similar techniques have been used to analyze the informational content of FOMC transcripts (see Bailey & Schonhardt‐Bailey, 2008; Schonhardt‐Bailey, 2013; Fligstein et al., 2014; Hansen et al., 2018; Bennani & Romelli, 2021; Acosta,2023, among others).…”
mentioning
confidence: 99%