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What You Match Does Matter: The Effects of Data on DSGE Estimation

  • Pablo A. Guerron

    ()

    (Department of Economics, North Carolina State University)

This paper explores the effects of using alternative data sets for the estimation of DSGE models. I find that the estimated structural parameters and the model's outcomes are sensitive to the variables used for estimation. Depending on the set of variables the point estimate for habit formation ranges from 0.70 to 0.97. Similarly, the interest-smoothing coefficient in the Taylor rule fluctuates between 0.06 and 0.76. In terms of the model's predictions, if interest rates are excluded during estimation, the estimated structural coefficients are such that the model forecasts a strong deflation following an expansionary monetary expansion. More importanlty, three ways to assess different observable sets are proposed. Based on these measures, I find that that including the price of investment in the data set delivers the best results.

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File URL: ftp://ftp.ncsu.edu/pub/ncsu/economics/RePEc/pdf/whatvariables.pdf
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Paper provided by North Carolina State University, Department of Economics in its series Working Paper Series with number 012.

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Length: 46 pages
Date of creation: Jul 2007
Date of revision:
Handle: RePEc:ncs:wpaper:012
Note: First draft 2007-06
Contact details of provider: Phone: (919) 515-3274
Web page: http://www.mgt.ncsu.edu/faculty/economics.html

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  18. Julio Rotemberg & Michael Woodford, 1997. "An Optimization-Based Econometric Framework for the Evaluation of Monetary Policy," NBER Chapters, in: NBER Macroeconomics Annual 1997, Volume 12, pages 297-361 National Bureau of Economic Research, Inc.
  19. Jonas D. M. Fisher, 2006. "The Dynamic Effects of Neutral and Investment-Specific Technology Shocks," Journal of Political Economy, University of Chicago Press, vol. 114(3), pages 413-451, June.
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