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Improving the Finite Sample Performance of Autoregression Estimators in Dynamic Factor Models: A Bootstrap Approach

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  • Mototsugu Shintani

    (University of Tokyo and Vanderbilt University)

  • Zi-yi Guo

    (Vanderbilt University)

Abstract

We investigate the finite sample properties of the estimator of a persistence parameter of an unobservable common factor when the factor is estimated by the principal components method. When the number of cross-sectional observations is not sufficiently large, relative to the number of time series observations, the autoregressive coefficient estimator of a positively autocorrelated factor is biased downward and the bias becomes larger for a more persistent factor. Based on theoretical and simulation analyses, we show that bootstrap procedures are e¤ective in reducing the bias, and bootstrap confidence intervals outperform naive asymptotic confidence intervals in terms of the coverage probability.

Suggested Citation

  • Mototsugu Shintani & Zi-yi Guo, 2015. "Improving the Finite Sample Performance of Autoregression Estimators in Dynamic Factor Models: A Bootstrap Approach," Vanderbilt University Department of Economics Working Papers 15-00013, Vanderbilt University Department of Economics.
    • Handle: RePEc:van:wpaper:vuecon-sub-15-00015
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    References listed on IDEAS

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    1. Yohei Yamamoto, 2019. "Bootstrap inference for impulse response functions in factor‐augmented vector autoregressions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(2), pages 247-267, March.
    2. Shintani, Mototsugu, 2008. "A dynamic factor approach to nonlinear stability analysis," Journal of Economic Dynamics and Control, Elsevier, vol. 32(9), pages 2788-2808, September.
    3. Moon, H.R.Hyungsik Roger & Perron, Benoit, 2004. "Testing for a unit root in panels with dynamic factors," Journal of Econometrics, Elsevier, vol. 122(1), pages 81-126, September.
    4. Jushan Bai & Serena Ng, 2004. "A PANIC Attack on Unit Roots and Cointegration," Econometrica, Econometric Society, vol. 72(4), pages 1127-1177, July.
    5. Marc P. Giannoni & Jean Boivin, 2005. "DSGE Models in a Data-Rich Environment," Computing in Economics and Finance 2005 431, Society for Computational Economics.
    6. Chang-Jin Kim & Charles R. Nelson, 1998. "Business Cycle Turning Points, A New Coincident Index, And Tests Of Duration Dependence Based On A Dynamic Factor Model With Regime Switching," The Review of Economics and Statistics, MIT Press, vol. 80(2), pages 188-201, May.
    7. Michael Woodford, 1999. "Optimal Monetary Policy Inertia," Manchester School, University of Manchester, vol. 67(s1), pages 1-35.
    8. MacKinnon, James G. & Smith Jr., Anthony A., 1998. "Approximate bias correction in econometrics," Journal of Econometrics, Elsevier, vol. 85(2), pages 205-230, August.
    9. Marcellino, Massimiliano & Stock, James H. & Watson, Mark W., 2003. "Macroeconomic forecasting in the Euro area: Country specific versus area-wide information," European Economic Review, Elsevier, vol. 47(1), pages 1-18, February.
    10. Ireland, Peter N., 2001. "Technology shocks and the business cycle: On empirical investigation," Journal of Economic Dynamics and Control, Elsevier, vol. 25(5), pages 703-719, May.
    11. repec:bla:manchs:v:67:y:1999:i:0:p:1-35 is not listed on IDEAS
    12. Goncalves, Silvia & White, Halbert, 2005. "Bootstrap Standard Error Estimates for Linear Regression," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 970-979, September.
    13. Michael Woodford, 1999. "Optimal monetary policy inertia," Proceedings, Federal Reserve Bank of San Francisco.
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    Cited by:

    1. Zi‐Yi Guo, 2021. "Out‐of‐sample performance of bias‐corrected estimators for diffusion processes," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(2), pages 243-268, March.
    2. Yohei Yamamoto, 2019. "Bootstrap inference for impulse response functions in factor‐augmented vector autoregressions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(2), pages 247-267, March.
    3. Maldonado, Javier & Ruiz Ortega, Esther, 2017. "Accurate Subsampling Intervals of Principal Components Factors," DES - Working Papers. Statistics and Econometrics. WS 23974, Universidad Carlos III de Madrid. Departamento de Estadística.
    4. Javier Maldonado & Esther Ruiz, 2021. "Accurate Confidence Regions for Principal Components Factors," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 83(6), pages 1432-1453, December.
    5. Bin Xu & Boqiang Lin, 2021. "Large fluctuations of China's commodity prices: Main sources and heterogeneous effects," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(2), pages 2074-2089, April.

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    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling

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