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Estimating Demand for Narrow Money and Broad Money

Author

Listed:
  • Daryl Ho

    (Research Department, Hong Kong Monetary Authority)

  • Jimmy Shek

    (Research Department, Hong Kong Monetary Authority)

  • Andrew Tsang

    (Research Department, Hong Kong Monetary Authority)

Abstract

Under the Linked Exchange Rate system, both Hong Kong dollar (HKD) narrow money (M1) and broad money (M2 and M3) are endogenously determined by factors such as economic activity and capital flows. Although these monetary aggregates do not provide any indication of the policy stance of the Hong Kong Monetary Authority (HKMA), they do contain leading information about output growth and inflation. This paper provides an updated analysis of the determinants of the demand for HKD M1 and M3 with three main objectives. First is to build a framework to better understand and interpret the behaviour of key HKD monetary aggregates. Second is to offer an explanation of the recent movements in M1 and M3. Third is to make use of the information content contained in these monetary aggregates to explain inflation and output. The significant decline in HKD M1 since the beginning of 2005 could be wellexplained by our model. Specifically, the model suggests that demand for M1 tends to become increasingly sensitive to interest rates when they are approaching zero. This non-linear feature of the demand for M1 helps explain the sharp increase in M1 between 2002 and 2004, and the subsequent, rapid decline in M1 since the beginning of 2005. As for the broad money demand model, it can be used to construct a money gap indicator, which is found to be useful in explaining CPI inflation and output gap. This money gap indicator can be used to gauge the impact of an autonomous increase in the stock of broad money (due to capital inflows, for example) on inflation and output.

Suggested Citation

  • Daryl Ho & Jimmy Shek & Andrew Tsang, 2006. "Estimating Demand for Narrow Money and Broad Money," Working Papers 0602, Hong Kong Monetary Authority.
  • Handle: RePEc:hkg:wpaper:0602
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    File URL: http://www.info.gov.hk/hkma/eng/research/RM02-2006.pdf
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    Cited by:

    1. Zhou, Wei & O'Neill, Eoghan & Moncaster, Alice & Reiner, David M. & Guthrie, Peter, 2020. "Forecasting urban residential stock turnover dynamics using system dynamics and Bayesian model averaging," Applied Energy, Elsevier, vol. 275(C).

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