IDEAS home Printed from https://ideas.repec.org/p/cwl/cwldpp/1345.html
   My bibliography  Save this paper

Bootstrapping Macroeconometric Models

Author

Abstract

This paper outlines a bootstrapping approach to the estimation and analysis of macroeconometric models. It integrates for dynamic, nonlinear, simultaneous equation models the bootstrapping approach to evaluating estimators initiated by Efron (1979) and the stochastic simulation approach to evaluating models' properties initiated by Adelman and Adelman (1959). It also estimates for a particular model the gain in coverage accuracy from using bootstrap confidence intervals over asymptotic confidence intervals.

Suggested Citation

  • Ray C. Fair, 2001. "Bootstrapping Macroeconometric Models," Cowles Foundation Discussion Papers 1345, Cowles Foundation for Research in Economics, Yale University, revised Jun 2003.
  • Handle: RePEc:cwl:cwldpp:1345
    Note: CFP 1195.
    as

    Download full text from publisher

    File URL: https://cowles.yale.edu/sites/default/files/files/pub/d13/d1345.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Runkle, David E, 1987. "Vector Autoregressions and Reality," Journal of Business & Economic Statistics, American Statistical Association, vol. 5(4), pages 437-442, October.
    2. repec:sae:niesru:v:164:y::i:1:p:90-99 is not listed on IDEAS
    3. Fair, Ray C & Taylor, John B, 1983. "Solution and Maximum Likelihood Estimation of Dynamic Nonlinear Rational Expectations Models," Econometrica, Econometric Society, vol. 51(4), pages 1169-1185, July.
    4. Yoel Haitovsky & Neil Wallace, 1972. "A Study of Discretionary and Nondiscretionary Monetary and Fiscal Policies in the Context of Stochastic Macroeconometric Models," NBER Chapters, in: Economic Research: Retrospect and Prospect, Volume 1, The Business Cycle Today, pages 261-309, National Bureau of Economic Research, Inc.
    5. Michael K. Evans & Lawrence R. Klein & Mitsuo Saito & Michael D. McCarthy, 1972. "Short-Run Prediction and Long-Run Simulation of the Wharton Model," NBER Chapters, in: Econometric Models of Cyclical Behavior, Volumes 1 and 2, pages 139-200, National Bureau of Economic Research, Inc.
    6. Fair, Ray C, 1980. "Estimating the Expected Predictive Accuracy of Econometric Models," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 21(2), pages 355-378, June.
    7. Calzolari, Giorgio & Corsi, Paolo, 1977. "Stochastic simulation as a validation tool for econometric models," MPRA Paper 21226, University Library of Munich, Germany.
    8. Bianchi, Carlo & Calzolari, Giorgio & Corsi, Paolo, 1976. "Divergences in the results of stochastic and deterministic simulation of an Italian non linear econometric model," MPRA Paper 21287, University Library of Munich, Germany.
    9. Härdle, Wolfgang & Horowitz, Joel L. & Kreiss, Jens-Peter, 2001. "Bootstrap methods for time series," SFB 373 Discussion Papers 2001,59, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    10. Runkle, David E, 1987. "Vector Autoregressions and Reality: Reply," Journal of Business & Economic Statistics, American Statistical Association, vol. 5(4), pages 454-454, October.
    11. Jeremy Berkowitz & Lutz Kilian, 2000. "Recent developments in bootstrapping time series," Econometric Reviews, Taylor & Francis Journals, vol. 19(1), pages 1-48.
    12. T. Muench & A. Rolnick & N. Wallace, 1974. "Tests for Structural Change and Prediction Intervals for the reduced Forms of Two Structural Models of the U.S.: The FRB-MIT and Michigan Quarterly Models," NBER Chapters, in: Annals of Economic and Social Measurement, Volume 3, number 3, pages 491-519, National Bureau of Economic Research, Inc.
    13. David E. Runkle, 1987. "Vector autoregressions and reality," Staff Report 107, Federal Reserve Bank of Minneapolis.
    14. Andrews, Donald W K & Ploberger, Werner, 1994. "Optimal Tests When a Nuisance Parameter Is Present Only under the Alternative," Econometrica, Econometric Society, vol. 62(6), pages 1383-1414, November.
    15. Fair, Ray C, 1993. "Testing the Rational Expectations Hypothesis in Macroeconometric Models," Oxford Economic Papers, Oxford University Press, vol. 45(2), pages 169-190, April.
    16. Lutz Kilian, 1998. "Small-Sample Confidence Intervals For Impulse Response Functions," The Review of Economics and Statistics, MIT Press, vol. 80(2), pages 218-230, May.
    17. Brown, Bryan W & Mariano, Roberto S, 1984. "Residual-Based Procedures for Prediction and Estimation in a Nonlinear Simultaneous System," Econometrica, Econometric Society, vol. 52(2), pages 321-343, March.
    18. Joel L. Horowitz, 1996. "Bootstrap Methods in Econometrics: Theory and Numerical Performance," Econometrics 9602009, University Library of Munich, Germany, revised 05 Mar 1996.
    19. Hall, Peter & Horowitz, Joel L, 1996. "Bootstrap Critical Values for Tests Based on Generalized-Method-of-Moments Estimators," Econometrica, Econometric Society, vol. 64(4), pages 891-916, July.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Selva Demiralp & Kevin D. Hoover & Stephen J. Perez, 2008. "A Bootstrap Method for Identifying and Evaluating a Structural Vector Autoregression," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 70(4), pages 509-533, August.
    2. Fair, Ray C., 2021. "Trade models and macroeconomics," Economic Modelling, Elsevier, vol. 94(C), pages 296-302.
    3. Bhattacharjee, Arnab & Jensen-Butler, Chris, 2013. "Estimation of the spatial weights matrix under structural constraints," Regional Science and Urban Economics, Elsevier, vol. 43(4), pages 617-634.
    4. Debby Lanser & Henk Kranendonk, 2008. "Investigating uncertainty in macroeconomic forecasts by stochastic simulation," CPB Discussion Paper 112, CPB Netherlands Bureau for Economic Policy Analysis.
    5. Dag Kolsrud, 2008. "Stochastic Ceteris Paribus Simulations," Computational Economics, Springer;Society for Computational Economics, vol. 31(1), pages 21-43, February.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Monika Blaszkiewicz-Schwartzman, 2007. "Explaining Exchange Rate Movements in New Member States of the European Union: Nominal and Real Convergence," Money Macro and Finance (MMF) Research Group Conference 2006 144, Money Macro and Finance Research Group.
    2. Jeremy Berkowitz & Lutz Kilian, 2000. "Recent developments in bootstrapping time series," Econometric Reviews, Taylor & Francis Journals, vol. 19(1), pages 1-48.
    3. Calzolari, Giorgio, 1987. "La varianza delle previsioni nei modelli econometrici [Forecast variance in econometric models]," MPRA Paper 23866, University Library of Munich, Germany.
    4. Phillips, Kerk L. & Spencer, David E., 2011. "Bootstrapping structural VARs: Avoiding a potential bias in confidence intervals for impulse response functions," Journal of Macroeconomics, Elsevier, vol. 33(4), pages 582-594.
    5. Fresoli, Diego & Ruiz, Esther & Pascual, Lorenzo, 2015. "Bootstrap multi-step forecasts of non-Gaussian VAR models," International Journal of Forecasting, Elsevier, vol. 31(3), pages 834-848.
    6. Kilian, Lutz & Chang, Pao-Li, 2000. "How accurate are confidence intervals for impulse responses in large VAR models?," Economics Letters, Elsevier, vol. 69(3), pages 299-307, December.
    7. Fair, Ray C., 1986. "Evaluating the predictive accuracy of models," Handbook of Econometrics, in: Z. Griliches† & M. D. Intriligator (ed.), Handbook of Econometrics, edition 1, volume 3, chapter 33, pages 1979-1995, Elsevier.
    8. Brüggemann, Ralf & Jentsch, Carsten & Trenkler, Carsten, 2016. "Inference in VARs with conditional heteroskedasticity of unknown form," Journal of Econometrics, Elsevier, vol. 191(1), pages 69-85.
    9. Jonathan H. Wright, 2000. "Exact confidence intervals for impulse responses in a Gaussian vector autoregression," International Finance Discussion Papers 682, Board of Governors of the Federal Reserve System (U.S.).
    10. Jon Faust & John H. Rogers & Eric Swanson & Jonathan H. Wright, 2003. "Identifying the Effects of Monetary Policy Shocks on Exchange Rates Using High Frequency Data," Journal of the European Economic Association, MIT Press, vol. 1(5), pages 1031-1057, September.
    11. El-Shagi, Makram & Zhang, Lin, 2020. "Trade effects of silver price fluctuations in 19th-century China: A macro approach," China Economic Review, Elsevier, vol. 63(C).
    12. Carrillo, Julio A., 2012. "How well does sticky information explain the dynamics of inflation, output, and real wages?," Journal of Economic Dynamics and Control, Elsevier, vol. 36(6), pages 830-850.
    13. Lise Pichette, 2004. "Are Wealth Effects Important for Canada," Bank of Canada Review, Bank of Canada, vol. 2004(Spring), pages 29-35.
    14. Sergio Ocampo & Norberto Rodríguez, 2011. "An Introductory Review of a Structural VAR-X Estimation and Applications," BORRADORES DE ECONOMIA 009200, BANCO DE LA REPÚBLICA.
    15. Granger, Clive W. J. & Jeon, Yongil, 2004. "Thick modeling," Economic Modelling, Elsevier, vol. 21(2), pages 323-343, March.
    16. Pesavento, Elena & Rossi, Barbara, 2007. "Impulse response confidence intervals for persistent data: What have we learned?," Journal of Economic Dynamics and Control, Elsevier, vol. 31(7), pages 2398-2412, July.
    17. Stefan Bruder, 2018. "Inference for structural impulse responses in SVAR-GARCH models," ECON - Working Papers 281, Department of Economics - University of Zurich.
    18. Wright, Jonathan H., 1999. "Frequency domain inference for univariate impulse responses," Economics Letters, Elsevier, vol. 63(3), pages 269-277, June.
    19. Gajda, Jan B. & Markowski, Aleksander, 1998. "Model Evaluation Using Stochastic Simulations: The Case of the Econometric Model KOSMOS," Working Papers 61, National Institute of Economic Research.
    20. Scheffel, Eric Michael, 2012. "Political uncertainty in a data-rich environment," MPRA Paper 37318, University Library of Munich, Germany.

    More about this item

    Keywords

    Bootstrapping; stochastic simulation;

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:cwl:cwldpp:1345. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: . General contact details of provider: https://edirc.repec.org/data/cowleus.html .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Matthew Regan (email available below). General contact details of provider: https://edirc.repec.org/data/cowleus.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.