GPM6: The Global Projection Model with 6 Regions

By Ioan Carabenciov, Charles Freedman, Roberto Garcia-Saltos, Douglas Laxton, Ondrej Kamenik, Petar Manchev

April 10, 2013

Preview Citation

Format: Chicago

Ioan Carabenciov, Charles Freedman, Roberto Garcia-Saltos, Douglas Laxton, Ondrej Kamenik, and Petar Manchev. GPM6: The Global Projection Model with 6 Regions, (USA: International Monetary Fund, 2013) accessed December 21, 2024

Disclaimer: This Working Paper should not be reported as representing the views of the IMF.The views expressed in this Working Paper are those of the author(s) and do not necessarily represent those of the IMF or IMF policy. Working Papers describe research in progress by the author(s) and are published to elicit comments and to further debate

Summary

This is the sixth of a series of papers that are being written as part of a project to estimate a small quarterly Global Projection Model (GPM). The GPM project is designed to improve the toolkit to which economists have access for studying both own-country and cross-country linkages. In this paper, we add three more regions and make a number of other changes to a previously estimated small quarterly projection model of the US, euro area, and Japanese economies. The model is estimated with Bayesian techniques, which provide a very efficient way of imposing restrictions to produce both plausible dynamics and sensible forecasting properties.

Subject: Central bank policy rate, Financial services, Foreign exchange, Inflation, Output gap, Prices, Production, Real exchange rates, Real interest rates

Keywords: Asia and Pacific, Bayesian Estimation, Central bank policy rate, Demand shock, Exchange rate, Gap variable, Global, Inflation, Inflation equation, Macroeconomic Modeling, Monetary Policy, Nominal interest rate, Output gap, Output gap equation, Rate of inflation, Real exchange rates, Real interest rates, WP

Publication Details

Pages:

79
Volume:

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DOI:

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Issue:

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Series:

Working Paper No. 2013/087
Stock No:

WPIEA2013087
ISBN:

9781484318942
ISSN:

1018-5941

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