Macroeconomic expectations and time varying heterogeneity: Evidence from individual survey data

Imane El Ouadghiri () and Remzi Uctum
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Imane El Ouadghiri: EconomiX - EconomiX - UPN - Université Paris Nanterre - CNRS - Centre National de la Recherche Scientifique

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Abstract: The goal of this paper is to investigate forecast heterogeneity and time variability in the formation of expectations using disaggregated monthly survey data on macroeconomic indicators provided by Bloomberg from June 1998 to August 2017. We show that our panel of forecasters are not rational and are moderately heterogeneous and thus confirm that previously well-established results on asset prices hold for macroeconomic indicators. The estimation of our flexible hybrid forecast model-defined at any time as a combination of the extrapolative, regressive, adaptive and interactive heuristics-using the Bai and Perron (1998) methodology reveals a significant timedependence in the structural model with some inertia in extrapolative and adaptive profiles. Changes in the formation of expectations are triggered mostly by financial shocks, and uncertainty is dealt with by using complex processes in which the fundamentalist component overweighs chartist activity. Forecasters whose models combine different relevant rules and display high temporal flexibility provide the most accurate forecasts. Authorities can then stabilize the domestic markets by encouraging fundamentalists' forecasts through increased transparency policy.

Keywords: dynamic heterogeneity; flexible forecast model; formation of expectations; individual survey data; macroeconomic indicators (search for similar items in EconPapers)
Date: 2020
New Economics Papers: this item is included in nep-cwa, nep-isf, nep-mac and nep-ore
Note: View the original document on HAL open archive server: https://hal.science/hal-03319091
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Published in Applied Economics, 2020, 52 (23), pp.2443-2459. ⟨10.1080/00036846.2019.1691713⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-03319091

DOI: 10.1080/00036846.2019.1691713

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