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VAR meets DSGE; Uncovering the Monetary Transmission Mechanism in Low-Income Countries

Author

Listed:
  • Bin Grace Li
  • Stephen A. O'Connell
  • Christopher S Adam
  • Andrew Berg
  • Peter J Montiel

Abstract

VAR methods suggest that the monetary transmission mechanism may be weak and unreliable in low-income countries (LICs). But are structural VARs identified via short-run restrictions capable of detecting a transmission mechanism when one exists, under research conditions typical of these countries? Using small DSGEs as data-generating processes, we assess the impact on VAR-based inference of short data samples, measurement error, high-frequency supply shocks, and other features of the LIC environment. The impact of these features on finite-sample bias appears to be relatively modest when identification is valid—a strong caveat, especially in LICs. However, many of these features undermine the precision of estimated impulse responses to monetary policy shocks, and cumulatively they suggest that “insignificant” results can be expected even when the underlying transmission mechanism is strong.

Suggested Citation

  • Bin Grace Li & Stephen A. O'Connell & Christopher S Adam & Andrew Berg & Peter J Montiel, 2016. "VAR meets DSGE; Uncovering the Monetary Transmission Mechanism in Low-Income Countries," IMF Working Papers 16/90, International Monetary Fund.
  • Handle: RePEc:imf:imfwpa:16/90
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    References listed on IDEAS

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    1. Mishra, Prachi & Montiel, Peter & Pedroni, Peter & Spilimbergo, Antonio, 2014. "Monetary policy and bank lending rates in low-income countries: Heterogeneous panel estimates," Journal of Development Economics, Elsevier, vol. 111(C), pages 117-131.
    2. Michal Andrle & Andrew Berg & R. Armando Morales & Rafael Portillo & Jan Vlcek, 2015. "On the Sources of Inflation in Kenya: A Model-Based Approach," South African Journal of Economics, Economic Society of South Africa, vol. 83(4), pages 475-505, December.
    3. Kim, Soyoung & Roubini, Nouriel, 2000. "Exchange rate anomalies in the industrial countries: A solution with a structural VAR approach," Journal of Monetary Economics, Elsevier, vol. 45(3), pages 561-586, June.
    4. Waggoner, Daniel F. & Zha, Tao, 2003. "A Gibbs sampler for structural vector autoregressions," Journal of Economic Dynamics and Control, Elsevier, vol. 28(2), pages 349-366, November.
    5. Shanaka J Peiris & Magnus Saxegaard, 2007. "An Estimated DSGE Model for Monetary Policy Analysis in Low-Income Countries," IMF Working Papers 07/282, International Monetary Fund.
    6. Nelson, Edward, 2002. "Direct effects of base money on aggregate demand: theory and evidence," Journal of Monetary Economics, Elsevier, vol. 49(4), pages 687-708, May.
    7. Alfredo Baldini & Jaromir Benes & Andrew Berg & Mai C. Dao & Rafael A. Portillo, 2015. "Monetary Policy in Low Income Countries in the Face of The Global Crisis: A Structural Analysis," Pacific Economic Review, Wiley Blackwell, vol. 20(1), pages 149-192, February.
    8. Michal Andrle & Andrew Berg & Enrico G Berkes & Rafael A Portillo & Jan Vlcek & R. Armando Morales, 2013. "Money Targeting in a Modern Forecasting and Policy Analysis System; an Application to Kenya," IMF Working Papers 13/239, International Monetary Fund.
    9. Levin, Andrew T., 2014. "The design and communication of systematic monetary policy strategies," Journal of Economic Dynamics and Control, Elsevier, vol. 49(C), pages 52-69.
    10. Jaromír Beneš & Jaromír Hurník & David Vávra, 2008. "Exchange Rate Management and Inflation Targeting: Modeling the Exchange Rate in Reduced-Form New Keynesian Models," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 58(03-04), pages 166-194, May.
    11. Prachi Mishra & Peter J Montiel & Antonio Spilimbergo, 2012. "Monetary Transmission in Low-Income Countries: Effectiveness and Policy Implications," IMF Economic Review, Palgrave Macmillan;International Monetary Fund, vol. 60(2), pages 270-302, July.
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