Microfounded forecasting

Wagner Gaglianone and João Issler

No 766, FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) from EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil)

Abstract: Our focus is on information in expectation surveys that can now be built on thousands (or millions) of respondents on an almost continuous-time basis (big data) and in continuous macroeconomic surveys with a limited number of respondents. We show that, under standard microeconomic and econometric techniques, survey forecasts are an affine function of the conditional expectation of the target variable. This is true whether or not the survey respondent knows the data-generating process (DGP) of the target variable or the econometrician knows the respondents individual loss function. If the econometrician has a mean-squared-error risk function, we show that asymptotically efficient forecasts of the target variable can be built using Hansens (Econometrica, 1982) generalized method of moments in a panel-data context, when N and T diverge or when T diverges with N xed. Sequential asymptotic results are obtained using Phillips and Moon s (Econometrica, 1999) framework. Possible extensions are also discussed.

Date: 2015-05
New Economics Papers: this item is included in nep-for
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Citations: View citations in EconPapers (4)

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Related works:
Working Paper: Microfounded forecasting (2019)
Working Paper: Microfounded Forecasting (2014)
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Persistent link: https://EconPapers.repec.org/RePEc:fgv:epgewp:766

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