Implications of Partial Information for Applied Macroeconomic Modelling

Adrian Pagan and Tim Robinson

Melbourne Institute Working Paper Series from Melbourne Institute of Applied Economic and Social Research, The University of Melbourne

Abstract: Implications of partial information for applied macroeconomic modelling along four dimensions are shown, and analysis provided on how they can be addressed. First, when permanent shocks are present a Vector Error-Correction Model including latent, as well as observed, variables is required to capture macroeconomic dynamics. Second, the assumption in Dynamic Stochastic General Equilibrium models that shocks are autocorrelated provides identifying information usable in Structural Vector AutoRe-gressions. Third, estimating models with more shocks than observed variables must yield correlated estimated structural shocks. Fourth, including measurement error, as commonly specified, implies a lack of co-integration between variables, even when actually present

Keywords: SVAR; Partial Information; Identification; Measurement Error; DSGE. (search for similar items in EconPapers)
JEL-codes: C51 C52 E37 (search for similar items in EconPapers)
Pages: 34pp
Date: 2019-10
New Economics Papers: this item is included in nep-ecm and nep-mac
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Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:iae:iaewps:wp2019n12

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