Global Identification of Linearized DSGE Models

NBP Working Paper No. 170

40 Pages Posted: 26 Feb 2014

See all articles by Andrzej Kociecki

Andrzej Kociecki

National Bank of Poland

Marcin Kolasa

National Bank of Poland; Warsaw School of Economics (SGH)

Date Written: February 24, 2014

Abstract

This paper introduces a time domain framework to analyze global identification of stochastically nonsingular DSGE models. A formal identification condition is established that relies on the restrictions linking the observationally equivalent minimal state space representations and on the inherent constraints imposed by them on deep model parameters. We next develop an algorithm that checks global identification by searching for observationally equivalent model parametrizations. The algorithm is efficient as the identification conditions it employs shrink considerably the space of candidate deep parameter points and does not require solving the model at each of these points. We also derive two complementary necessary conditions for global identification. Their usefulness and the working of the algorithm are illustrated with an example.

Keywords: global identification, DSGE models

JEL Classification: C13, C51, E32

Suggested Citation

Kociecki, Andrzej and Kolasa, Marcin, Global Identification of Linearized DSGE Models (February 24, 2014). NBP Working Paper No. 170, Available at SSRN: https://ssrn.com/abstract=2400330 or http://dx.doi.org/10.2139/ssrn.2400330

Andrzej Kociecki (Contact Author)

National Bank of Poland ( email )

00-919 Warsaw
Poland

Marcin Kolasa

National Bank of Poland ( email )

00-919 Warsaw
Poland

Warsaw School of Economics (SGH) ( email )

aleja Niepodleglosci 162
PL-Warsaw, 02-554
Poland

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