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Evaluating the Quarterly Projection Model: A Preliminary Investigation

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  • Robert Amano1
  • Kim McPhail
  • Hope Pioro
  • Andrew Rennison
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    File URL: http://www.bankofcanada.ca/wp-content/uploads/2010/02/wp02-20.pdf
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    Paper provided by Bank of Canada in its series Working Papers with number 02-20.

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    Length: 77 pages Abstract: This paper summarizes the results of recent research evaluating the Bank of Canada's Quarterly Projection Model (QPM). Because QPM consists of a steady-state model and a dynamic model, our evaluation work consists of two parts. The first part assesses the calibration of QPM's core steady-state using a variant of Canova's (1994, 1995) Monte Carlo approach. Using parameter values drawn from prior distributions, we assess QPM's sensitivity to various plausible parameter values. Our approach differs somewhat from the recent literature in that it specifically takes into account the uncertainty that surrounds the estimates of the steady-state values we are trying to evaluate. Instead of attempting to match exactly the desired properties of the data, we calculate confidence intervals around the mean of the variable we wish to match, subsequently discarding parameterizations that result in simulated data falling outside this interval. The second part of the evaluation uses artificial data, generated stochastically with QPM, to test the dynamic model's ability to replicate key historical moments. Autocorrelations, reduced-form regressions, and temporal bivariate correlations are used to compare historical data with data produced by QPM. We also assess the sensitivity of our results to the structure of the stochastic shocks and the specification of the monetary policy rule. The results of the two evaluations reveal some strengths and weaknesses in the model. For example, while most of the parameter calibrations in the steady-state model appear reasonable, there are some parameters for which other values may be more appropriate. Similarly, while the dynamic model can replicate most of the key historical moments, some work is required to develop the linkages between foreign and domestic variables. (1) Also affiliated with the Center for Research on Economic Fluctuations and Employment, Université du Québec à Montréal, Montréal, Québec, H3C 3P8, Canada
    Date of creation: 2002
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    Handle: RePEc:bca:bocawp:02-20

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    Keywords: Economic models;

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    1. Kydland, Finn E & Prescott, Edward C, 1982. "Time to Build and Aggregate Fluctuations," Econometrica, Econometric Society, Econometric Society, vol. 50(6), pages 1345-70, November.
    2. Martin Eichenbaum & Lawrence J. Christiano, 1992. "Liquidity Effects, Monetary Policy, and the Business Cycle," NBER Working Papers 4129, National Bureau of Economic Research, Inc.
    3. Douglas W. Elmendorf & N. Gregory Mankiw, 1998. "Government Debt," Harvard Institute of Economic Research Working Papers 1820, Harvard - Institute of Economic Research.
    4. Rowe, Nicholas & Yetman, James, 2000. "Identifying Policy-makers' Objectives: An Application to the Bank of Canada," Working Papers, Bank of Canada 00-11, Bank of Canada.
    5. Harrison, Glenn W. & Jones, Richard & Kimbell, Larry J. & Wigle, Randal, 1993. "How robust is applied general equilibrium analysis?," Journal of Policy Modeling, Elsevier, Elsevier, vol. 15(1), pages 99-115, February.
    6. Timothy Cogley & James M. Nason, 1993. "Effects of the Hodrick-Prescott filter on trend and difference stationary time series: implications for business cycle research," Working Papers in Applied Economic Theory 93-01, Federal Reserve Bank of San Francisco.
    7. Coletti, D. & Hunt, B. & Rose, D. & Tetlow, R., 1996. "The Bank of Canada's New Quarterly Projection Model. Part 3 , the Dynamic Model : QPM," Technical Reports, Bank of Canada 75, Bank of Canada.
    8. Harrison, Glenn W & Vinod, H D, 1992. "The Sensitivity Analysis of Applied General Equilibrium Models: Completely Randomized Factorial Sampling Designs," The Review of Economics and Statistics, MIT Press, vol. 74(2), pages 357-62, May.
    9. Touhami Abdelkhalek & Jean-Marie Dufour, 1998. "Statistical Inference For Computable General Equilibrium Models, With Application To A Model Of The Moroccan Economy," The Review of Economics and Statistics, MIT Press, vol. 80(4), pages 520-534, November.
    10. Geweke, John, 1988. "Antithetic acceleration of Monte Carlo integration in Bayesian inference," Journal of Econometrics, Elsevier, Elsevier, vol. 38(1-2), pages 73-89.
    11. Shoven,John B. & Whalley,John, 1992. "Applying General Equilibrium," Cambridge Books, Cambridge University Press, number 9780521266550, 9.
    12. Canova, Fabio, 1994. "Statistical Inference in Calibrated Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., John Wiley & Sons, Ltd., vol. 9(S), pages S123-44, Suppl. De.
    13. George C. Davis & Maria Cristina Espinoza, 1998. "A Unified Approach to Sensitivity Analysis in Equilibrium Displacement Models," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, Agricultural and Applied Economics Association, vol. 80(4), pages 868-879.
    14. Singleton, Kenneth J., 1988. "Econometric issues in the analysis of equilibrium business cycle models," Journal of Monetary Economics, Elsevier, Elsevier, vol. 21(2-3), pages 361-386.
    15. McFadden, Daniel, 1989. "A Method of Simulated Moments for Estimation of Discrete Response Models without Numerical Integration," Econometrica, Econometric Society, Econometric Society, vol. 57(5), pages 995-1026, September.
    16. Blanchard, Olivier J, 1985. "Debt, Deficits, and Finite Horizons," Journal of Political Economy, University of Chicago Press, University of Chicago Press, vol. 93(2), pages 223-47, April.
    17. Lucas, Robert Jr, 1976. "Econometric policy evaluation: A critique," Carnegie-Rochester Conference Series on Public Policy, Elsevier, Elsevier, vol. 1(1), pages 19-46, January.
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