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Asset Price Booms, "Fat Tails," and Monetary Policy in East Asia

Author

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  • Maria Socorro Gochoco-Bautista

    (Professor of Economics, University of the Philippines, School of Economics, Diliman, Quezon City, Philippines 1101.)

Abstract

This study provides empirical evidence for the proposition that asset price booms matter because they tend to bring about the worst output, price, and inflation outcomes in the case of eight East Asian countries, namely, Hong Kong SAR, Indonesia, Japan, Korea, Malaysia, the Philippines, Singapore, and Thailand. The main findings are: (i) asset price booms in housing and equity markets, especially in housing, significantly lower the conditional mean of real output growth and raise those of the price-level gap and inflation, and also raise the conditional variance of all three variables; and (ii) expected real output and price-level outcomes that are obtained without conditioning on asset price booms, or are obtained conditionally on asset price booms using the normal distribution, both underestimate the risk of the worst outcomes occurring and lead to less pessimistic but misleading inferences. These findings are not premised on the ability of central bankers to be able to identify correctly asset bubbles ex ante. One possible implication for monetary policy is that central bankers ought to be wary about the occurrence of any large increase in asset prices and consider an approach that is ex ante more compatible with risk management. (c) 2009 The Earth Institute at Columbia University and the Massachusetts Institute of Technology.

Suggested Citation

  • Maria Socorro Gochoco-Bautista, 2009. "Asset Price Booms, "Fat Tails," and Monetary Policy in East Asia," Asian Economic Papers, MIT Press, vol. 8(1), pages 69-98, Winter.
  • Handle: RePEc:tpr:asiaec:v:8:y:2009:i:1:p:69-98
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    Cited by:

    1. Phouphet Kyophilavong & Gazi Salah Uddin & Muhammad Shahbaz & Charles Harvie & Teerawat Charoenrat, 2019. "Money Demand in a Dollarized Economy: Evidence from Laos PDR," Asian Economic Papers, MIT Press, vol. 18(1), pages 99-115, Winter/Sp.
    2. Eita, Joel Hinaunye & Ngobese, Sibusiso Blessing & Muteba Mwamba, John Weirstrass, 2020. "An empirical analysis of systemic and macroeconomic risk in South Africa: an application of the quantile regression," MPRA Paper 101493, University Library of Munich, Germany.
    3. Borgy, Vladimir & Clerc, Laurent & Renne, Jean-Paul, 2014. "Measuring aggregate risk: Can we robustly identify asset-price boom–bust cycles?," Journal of Banking & Finance, Elsevier, vol. 46(C), pages 132-150.

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