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Inflation and Inflation Uncertainty in Growth Model of Barro: An Application of Random Forest Model

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  • Houcine Senoussi

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  • Houcine Senoussi, 2021. "Inflation and Inflation Uncertainty in Growth Model of Barro: An Application of Random Forest Model," International Econometric Review (IER), Economic Research Association, vol. 13(1), pages 4-23, March.
    • Handle: RePEc:erh:journl:v:13:y:2021:i:1:p:4-23
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    3. Hal R. Varian, 2014. "Big Data: New Tricks for Econometrics," Journal of Economic Perspectives, American Economic Association, vol. 28(2), pages 3-28, Spring.
    4. Eklund, Jana & Kapetanios, George, 2008. "A review of forecasting techniques for large datasets," National Institute Economic Review, Cambridge University Press, vol. 203, pages 109-115, January.
    5. Gill Hammond, 2012. "State of the art of inflation targeting," Handbooks, Centre for Central Banking Studies, Bank of England, edition 4, number 29, April.
    6. Akinsola Foluso A. & Odhiambo Nicholas M., 2017. "Inflation and Economic Growth: a Review of The International Literature," Comparative Economic Research, Sciendo, vol. 20(3), pages 41-56, September.
    7. Robert J. Barro, 1991. "Economic Growth in a Cross Section of Countries," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 106(2), pages 407-443.
    8. Sidika Basci & Asad Zaman & Arzdar Kiraci, 2010. "Variance Estimates and Model Selection," International Econometric Review (IER), Economic Research Association, vol. 2(2), pages 57-72, September.
    9. David F. Hendry & Hans‐Martin Krolzig, 2004. "We Ran One Regression," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 66(5), pages 799-810, December.
    10. Sala-i-Martin, Xavier, 1997. "I Just Ran Two Million Regressions," American Economic Review, American Economic Association, vol. 87(2), pages 178-183, May.
    11. Marcelo C. Medeiros & Gabriel F. R. Vasconcelos & Álvaro Veiga & Eduardo Zilberman, 2021. "Forecasting Inflation in a Data-Rich Environment: The Benefits of Machine Learning Methods," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 39(1), pages 98-119, January.
    12. David F. Hendry & Hans-Martin Krolzig, 2004. "We Ran One Regression," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 66(5), pages 799-810, December.
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