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Broad Monetary Condition Index: An Indicator for Short-Run Monetary Management in Vietnam

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Econometrics of Risk

Part of the book series: Studies in Computational Intelligence ((SCI,volume 583))

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Abstract

We construct broad monetary condition index (MCI) for monetary policy management in Vietnam. MCI is composed of key monetary transmission variables including interest rate, exchange rate, credit and stock market price. Weights of composite variables are derived from reduced form IS-PC framework and impulse response function based on vector autoregressive model with data in first difference form and difference-with-long-term-trend form. The best MCI is chosen based on three criteria: its causal relationship with output growth, its ability to explain output growth in short-run and its out-of-sample performance in forecasting output growth. Movement of chosen MCI indicates that the indicator has two essential characteristics of a supporting index for short-term monetary policy management, including quick responses to monetary policy changes and close relation with policy goal.

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Notes

  1. 1.

    Previously, Vietnam has multiple policy goals including economic growth, price control,..., indicated in Law on The State Bank of Vietnam 1997.

  2. 2.

    Such as Directive 02/2010/CT-NHNN, Directive 01/2011/CT-NHNN, Directive 01/2012/CT-NHNN, Directive 01/2013/CT-NHNN.

  3. 3.

    The formula is adjusted from the original formula (which is \(MCI_t = \theta _r(r_t - r_0) + \theta _e(e_t - e_0)\)) to appropriate with direct exchange rate quotation used in the paper.

  4. 4.

    We do not report estimation result of PC equation in the main contend of this paper.

  5. 5.

    Including China, Singapore, Japan, Korea, Thailand, Malaysia, Hong Kong, The United State, Indonesia, Germany, Australia, UK, France, Russia, Philippines, Taiwan and Netherland.

  6. 6.

    \({ REER}_t = \prod _{i=1}^{k}({ NER}_{it}\cdot \frac{P_{it}^*}{P_n})^{w_{it}}\) in which \({ NER}_i\) is nominal exchange rate of currency i against VND, \(w_i\) represent for attached trade weigh of currency i in currency basket, \(P^*_i\) represents for producer price index or whole sale price index of country i; \(P_n\) represent for consumer price index (CPI) of Vietnam.

  7. 7.

    The authors use three methods including: reduced-form IS-PC model, IRF based on VAR and factor analysis with data in first difference form and difference-with-long-term form.

  8. 8.

    The authors use IRF based on VAR and Dynamic factor model to calculated MCIs for 13 economies including China, Australia, HongKong, Indonesia, India, Japan, Korea, Malaysia, New Zealand, Philippines, Singapore, Thailand and Taiwan.

  9. 9.

    We determine lag of growth without INDEX  to apply the same lag of growth into various equation estimation, therefore, SSRs of estimated equation can reflect explaining ability of INDEX.

  10. 10.

    We also explore explanatory ability of other monetary variables to compare with that of calculated MCIs.

  11. 11.

    We do not forecast at four steps ahead because all coefficient of MCIs at foure steps ahead are not significant as presented in Table 8.

  12. 12.

    Previously reserve requirements were only applied to current deposits and under 24 month deposits.

  13. 13.

    Exchange rate quoted at commercial bank is determined by published interbank exchange rate from SBV and fluctuation band.

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Author information

Authors and Affiliations

  1. International Economics Faculty, Banking University, 39 Ham Nghi Street, District 1, Hochiminh, Vietnam

    Pham Thi Tuyet Trinh

  2. Faculty of Finance, Banking University, 39 Ham Nghi Street, District 1, Hochiminh, Vietnam

    Nguyen Thien Kim

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  1. Pham Thi Tuyet Trinh
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Correspondence to Pham Thi Tuyet Trinh .

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Editors and Affiliations

  1. Japan Advanced Institute of Science and Technology, Nomi, Japan

    Van-Nam Huynh

  2. Department of Computer Science, University of Texas at El Paso, El Paso, Texas, USA

    Vladik Kreinovich

  3. Faculty of Economics, Chiang Mai University, Chiang Mai, Thailand

    Songsak Sriboonchitta

  4. Faculty of Economics, Chiang Mai University, Chiang Mai, Thailand

    Komsan Suriya

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Trinh, P.T.T., Kim, N.T. (2015). Broad Monetary Condition Index: An Indicator for Short-Run Monetary Management in Vietnam. In: Huynh, VN., Kreinovich, V., Sriboonchitta, S., Suriya, K. (eds) Econometrics of Risk. Studies in Computational Intelligence, vol 583. Springer, Cham. https://doi.org/10.1007/978-3-319-13449-9_27

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  • DOI: https://doi.org/10.1007/978-3-319-13449-9_27

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