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Bayesian Estimation of a DSGE Model with Inventories

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  • Marcel Foerster

    (University of Giessen)

Abstract

This paper introduces inventories in an otherwise standard Dynamic Stochastic General Equilibrium Model (DSGE) of the business cycle. Firms accumulate inventories to facilitate sales, but face a cost of doing so in terms of costly storage of intermediate goods. The paper’s main contribution is to present a DSGE model with inventories that is estimated using Bayesian methods. Based on U.S. data we show that accounting for inventory dynamics has a significant impact on parameter estimates and impulse responses. Our analysis also reveals that the contribution of structural shocks to variations in the observable variables changes significantly when we allow for inventories. Moreover, we find that inventories enter the Phillips curve as an additional and significant driving variable of inflation and make the inflation process less backward-looking.

Suggested Citation

  • Marcel Foerster, 2011. "Bayesian Estimation of a DSGE Model with Inventories," MAGKS Papers on Economics 201123, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    • Handle: RePEc:mar:magkse:201123
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    File URL: https://www.uni-marburg.de/en/fb02/research-groups/economics/macroeconomics/research/magks-joint-discussion-papers-in-economics/papers/2011-papers/23-2011_foerster.pdf
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    More about this item

    Keywords

    Inventories; Bayesian Estimation; DSGE model; Business Cycles;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • E20 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - General (includes Measurement and Data)
    • E30 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - General (includes Measurement and Data)

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