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Sources of Fluctuations in Emerging Markets: Structural Estimation with Mixed Frequency Data

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  • Sebastian Rondeau

    (Columbia University)

Abstract

This study explores the sources of aggregate fluctuations in emerging markets. For that purpose, I estimate a standard small open economy model for 18 countries combining annual and quarterly series. The proposed mixed frequency strategy allows us to extend the sample period typically back to 1950 exploiting annual datasets, while keeping the information present in shorter quarterly series. Importantly, I find that transitory technology shocks are the main driver of fluctuations in emerging markets, accounting for about 48% of output growth variance. In turn, permanent productivity shocks come in second place, explaining around 35% of output fluctuations. Conversely, in developed countries permanent technology shocks play a predominant role. In order to assess the relative merits of the mixed frequency estimation strategy, I perform a Monte Carlo experiment for a representative emerging economy. Interestingly, I find that estimations based only on short quarterly series exhibit large upward bias for the contribution of permanent technology shocks. Further, I show that the mixed frequency estimation delivers substantial efficiency gains and drastically reduces this bias.

Suggested Citation

  • Sebastian Rondeau, 2012. "Sources of Fluctuations in Emerging Markets: Structural Estimation with Mixed Frequency Data," 2012 Meeting Papers 1156, Society for Economic Dynamics.
  • Handle: RePEc:red:sed012:1156
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    References listed on IDEAS

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    Cited by:

    1. Foroni, Claudia & Gelain, Paolo & Marcellino, Massimiliano, 2022. "The financial accelerator mechanism: does frequency matter?," Working Paper Series 2637, European Central Bank.
    2. Xianning WANG & Jingrong DONG & Zhi XIAO & Guanjie HE, 2019. "A novel spatial mixed frequency forecasting model with application to Chinese regional GDP," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 54-77, June.
    3. Wataru Miyamoto & Thuy Lan Nguyen, 2016. "Business Cycles in Small, Open Economies: Evidence from Panel Data Between 1900 and 2013," Staff Working Papers 16-48, Bank of Canada.
    4. Fossati, Sebastian, 2014. "Output Growth and Commodity Prices in Latin America: What Has Changed?," Working Papers 2014-11, University of Alberta, Department of Economics.
    5. Dutu, Richard, 2016. "Why has economic growth slowed down in Indonesia? An investigation into the Indonesian business cycle using an estimated DSGE model," Journal of Asian Economics, Elsevier, vol. 45(C), pages 46-55.
    6. Ruey Yau & C. James Hueng, 2019. "Nowcasting GDP Growth for Small Open Economies with a Mixed-Frequency Structural Model," Computational Economics, Springer;Society for Computational Economics, vol. 54(1), pages 177-198, June.
    7. Wataru Miyamoto & Thuy Lan Nguyen, 2017. "Business Cycles In Small Open Economies: Evidence From Panel Data Between 1900 And 2013," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 58(3), pages 1007-1044, August.

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