Over-reaction in Macroeconomic Expectations / Pedro Bordalo, Nicola Gennaioli, Yueran Ma, Andrei Shleifer.

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Bordalo, Pedro

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Material type: Text

TextSeries: Working Paper Series (National Bureau of Economic Research) ; no. w24932.Publication details: Cambridge, Mass. National Bureau of Economic Research 2018.Description: 1 online resource: illustrations (black and white)Subject(s):

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Abstract: We study the rationality of individual and consensus professional forecasts of macroeconomic and financial variables using the methodology of Coibion and Gorodnichenko (2015), which examines predictability of forecast errors from forecast revisions. We report two key findings: forecasters typically over-react to their individual news, while consensus forecasts under-react to average forecaster news. To reconcile these findings, we combine the diagnostic expectations model of belief formation from Bordalo, Gennaioli, and Shleifer (2018) with Woodford's (2003) noisy information model of belief dispersion. The forward looking nature of diagnostic expectations yields additional implications, which we also test and confirm. A structural estimation exercise indicates that our model captures important variation in the data, yielding a value for the belief distortion parameter similar to estimates obtained in other settings

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Item type	Home library	Collection	Call number	Status	Date due	Barcode	Item holds
Working Paper	Biblioteca Digital	Colección NBER	nber w24932 (Browse shelf(Opens below))	Not For Loan

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August 2018.

We study the rationality of individual and consensus professional forecasts of macroeconomic and financial variables using the methodology of Coibion and Gorodnichenko (2015), which examines predictability of forecast errors from forecast revisions. We report two key findings: forecasters typically over-react to their individual news, while consensus forecasts under-react to average forecaster news. To reconcile these findings, we combine the diagnostic expectations model of belief formation from Bordalo, Gennaioli, and Shleifer (2018) with Woodford's (2003) noisy information model of belief dispersion. The forward looking nature of diagnostic expectations yields additional implications, which we also test and confirm. A structural estimation exercise indicates that our model captures important variation in the data, yielding a value for the belief distortion parameter similar to estimates obtained in other settings