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Political uncertainty in a data-rich environment

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  • Scheffel, Eric Michael

Abstract

We asses the general robustness of previous findings claiming that policy uncertainty exerts non-trivial influences on the US economy. Measuring the dynamic effects from a shock to policy uncertainty within a FAVAR model permits gauging the response of many more variables to policy uncertainty than is possible in a simple VAR model. Our results summarized by impulse responses are all corrected for small sample bias using a bootstrap-after-bootstrap method. Our findings support the view of policy uncertainty exerting a statistically significant influence on the economy, which is however not always as economically significant for a number of variables as found in previous studies.

Suggested Citation

  • Scheffel, Eric Michael, 2012. "Political uncertainty in a data-rich environment," MPRA Paper 37318, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:37318
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    References listed on IDEAS

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    1. Kapetanios, George & Marcellino, Massimiliano, 2010. "Factor-GMM estimation with large sets of possibly weak instruments," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2655-2675, November.
    2. Banerjee, Anindya & Marcellino, Massimiliano, 2008. "Factor-augmented Error Correction Models," CEPR Discussion Papers 6707, C.E.P.R. Discussion Papers.
    3. Runkle, David E, 1987. "Vector Autoregressions and Reality," Journal of Business & Economic Statistics, American Statistical Association, vol. 5(4), pages 437-442, October.
    4. Runkle, David E, 1987. "Vector Autoregressions and Reality: Reply," Journal of Business & Economic Statistics, American Statistical Association, vol. 5(4), pages 454-454, October.
    5. Nikolaos Askitas & Klaus F. Zimmermann, 2009. "Google Econometrics and Unemployment Forecasting," Applied Economics Quarterly (formerly: Konjunkturpolitik), Duncker & Humblot, Berlin, vol. 55(2), pages 107-120.
    6. Bai, Jushan & Ng, Serena, 2010. "Instrumental Variable Estimation In A Data Rich Environment," Econometric Theory, Cambridge University Press, vol. 26(6), pages 1577-1606, December.
    7. Francisco J. Buera & Alexander Monge‐Naranjo & Giorgio E. Primiceri, 2011. "Learning the Wealth of Nations," Econometrica, Econometric Society, vol. 79(1), pages 1-45, January.
    8. David E. Runkle, 1987. "Vector autoregressions and reality," Staff Report 107, Federal Reserve Bank of Minneapolis.
    9. Sims, Christopher A., 1992. "Interpreting the macroeconomic time series facts : The effects of monetary policy," European Economic Review, Elsevier, vol. 36(5), pages 975-1000, June.
    10. James H. Stock & Mark W. Watson, 2005. "Implications of Dynamic Factor Models for VAR Analysis," NBER Working Papers 11467, National Bureau of Economic Research, Inc.
    11. Bernanke, Ben S & Blinder, Alan S, 1992. "The Federal Funds Rate and the Channels of Monetary Transmission," American Economic Review, American Economic Association, vol. 82(4), pages 901-921, September.
    12. Jushan Bai & Serena Ng, 2002. "Determining the Number of Factors in Approximate Factor Models," Econometrica, Econometric Society, vol. 70(1), pages 191-221, January.
    13. 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.
    14. Jesús Fernández-Villaverde & Pablo Guerrón-Quintana & Keith Kuester & Juan Rubio-Ramírez, 2015. "Fiscal Volatility Shocks and Economic Activity," American Economic Review, American Economic Association, vol. 105(11), pages 3352-3384, November.
    15. Stock, James H. & Watson, Mark W., 1999. "Forecasting inflation," Journal of Monetary Economics, Elsevier, vol. 44(2), pages 293-335, October.
    16. Robert B. Litterman, 1979. "Techniques of forecasting using vector autoregressions," Working Papers 115, Federal Reserve Bank of Minneapolis.
    17. Ben S. Bernanke & Ilian Mihov, 1998. "Measuring Monetary Policy," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 113(3), pages 869-902.
    18. Sims, Christopher A, 1980. "Macroeconomics and Reality," Econometrica, Econometric Society, vol. 48(1), pages 1-48, January.
    19. Bernanke, Ben S. & Boivin, Jean, 2003. "Monetary policy in a data-rich environment," Journal of Monetary Economics, Elsevier, vol. 50(3), pages 525-546, April.
    20. M. Ayhan Kose & Christopher Otrok & Charles H. Whiteman, 2003. "International Business Cycles: World, Region, and Country-Specific Factors," American Economic Review, American Economic Association, vol. 93(4), pages 1216-1239, September.
    21. Scott R. Baker & Nicholas Bloom & Steven J. Davis, 2012. "Policy uncertainty: a new indicator," CentrePiece - The magazine for economic performance 362, Centre for Economic Performance, LSE.
    22. Gary M. Koop, 2013. "Forecasting with Medium and Large Bayesian VARS," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 28(2), pages 177-203, March.
    23. Mario Forni & Marc Hallin & Marco Lippi & Lucrezia Reichlin, 2000. "The Generalized Dynamic-Factor Model: Identification And Estimation," The Review of Economics and Statistics, MIT Press, vol. 82(4), pages 540-554, November.
    24. Bai, Jushan & Ng, Serena, 2008. "Large Dimensional Factor Analysis," Foundations and Trends(R) in Econometrics, now publishers, vol. 3(2), pages 89-163, June.
    25. Ben S. Bernanke, 1983. "Irreversibility, Uncertainty, and Cyclical Investment," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 98(1), pages 85-106.
    26. D'Amuri, Francesco/FD & Marcucci, Juri/JM, 2009. ""Google it!" Forecasting the US unemployment rate with a Google job search index," MPRA Paper 18248, University Library of Munich, Germany.
    27. Nicholas Bloom, 2009. "The Impact of Uncertainty Shocks," Econometrica, Econometric Society, vol. 77(3), pages 623-685, May.
    28. Marc P. Giannoni & Jean Boivin, 2005. "DSGE Models in a Data-Rich Environment," Computing in Economics and Finance 2005 431, Society for Computational Economics.
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    Keywords

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    JEL classification:

    • E22 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Investment; Capital; Intangible Capital; Capacity
    • H41 - Public Economics - - Publicly Provided Goods - - - Public Goods
    • E23 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Production
    • E21 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Consumption; Saving; Wealth

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