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Vietnam: Selected Issues

Author(s):
International Monetary Fund. Asia and Pacific Dept
Published Date:
July 2018
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Vietnam: Credit Growth and Asset Market Valuations1

Vietnam has experienced strong growth in credit and asset prices in recent years. This paper looks at recent developments in aggregate credit volumes, stock markets, and housing markets to examine whether financial market developments are in line with economic fundamentals. Overall, asset prices and credit growth appear to be stronger than warranted by fundamentals, suggesting the need for tighter policies including a lower credit growth target by the central bank. The analysis is, however, substantially constrained by the data weaknesses.

1. Vietnam has experienced strong growth in credit for several years and, more recently, in asset prices. Since a strong growth in financial variables can potentially signal overheating, it is important to assess the extent of their deviations from economic fundamentals. This paper looks at recent developments in aggregate credit volumes, stock markets, and housing markets to examine whether financial market developments are in line with economic fundamentals.

2. The analysis is constrained by data weaknesses. The analysis on credit growth is constrained by the lack of accurate data on sectoral credit growth, particularly those for real estate lending and lending to preferred sectors selected by the government. Furthermore, the analysis of stock markets cannot be extended to examine potential impacts of stock price corrections on the financial and corporate sector unless more granular data on individual bank and corporate balance sheet becomes available. Finally, official statistics for real estate prices are unavailable, and the large volatility in the housing price indices provided by private real estate firms and the small size of sample, makes the analysis less reliable.

A. Credit Growth

3. Credit-to-GDP ratios in Vietnam have increased for more than a decade (text Figure). While the ratios were around 30 percent in the early 2000s, they have significantly increased and reached around 130 percent in 2017. The HP filter trend (lambda = 400,000) shows a clear upward trend in the ratios, suggesting that Vietnam has been in the process of financial deepening. Around the trend of financial deepening, the credit-to-GDP ratios sharply increased after the global financial crisis in 2009–2010, experienced some corrections around the time Vietnam experienced a crisis in 2011 due to a real estate market bust, and have strongly increased again recently 2012, reflecting the government’s high annual credit growth targets.

Vietnam: Credit-to-GDP

(In Percent)

Sources: National authorities; and IMF staff calculations.

4. To assess whether credit growth has been excessive, the analysis examines two early warning indicators (EWI) for credit widely used in the literature. The first EWI is the deviation of credit-to-GDP ratios from its HP filter trend (the credit gap, hereafter), where the HP filter trend provides an estimation of the long-term trend of financial deepening. The credit gap is considered the most informative EWI for capturing excessively rapid increases (or decreases) in credit volume in the literature (e.g., Drehmann and Tsatsaronis 2014). Given its high predictive powers for crises, it is often recommended as a trigger for implementing or tightening macroprudential policies. The second EWI is the year-on-year percentage point changes in credit-to-GDP ratios (the credit growth gap, hereafter). While the credit growth gap is a less common EWI than the credit gap in the literature, the analysis by Gersl and Jasova (2018) empirically shows that the credit growth gap is more informative in predicting financial crises in emerging economies than the credit gap.

5. The EWIs in Vietnam indicate that credit has been growing faster than financial deepening. The credit gap was positive but still less than 10 percent in 2017, as compared to the more than 20 percent gap during the 2011 crisis (text Figure). The credit growth gap reached almost the same level as the one during the 2011 crisis in the mid-2016 but declined somewhat in 2017 due to both the higher nominal GDP growth and the lower credit growth. It is worth noting, however, that the aggregate credit data cannot capture risks associated with sectoral credit growth, such as very high credit growth rates in consumer loans in recent years. Also, there may be risks from directed credit, namely commercial banks being asked by the government to lend to preferred sectors at lower interest rates.

Vietnam: Credit Gap

(In Percent)

Sources: National authorities; and IMF staff calculations.

Vietnam: Credit Growth Gap

Sources: National authorities; and IMF staff calculations.

6. Under current projections for the economic outlook, the risk to financial stability could be contained if overall credit growth is tightened further. The government’s credit growth target for 2018 is set at 17 percent. Under the baseline scenario of nominal GDP growth of around 10.5 percent in 2018 and 2019, the credit gap and the credit growth gap will increase but still be around 6–7 percent and 7–9 percentage points in 2019. However, if credit growth were to accelerate to 20 percent in 2018 and 2019, the credit gap and the credit growth gap would swiftly rise to approach previous crisis level, thus posing a risk to financial stability. To close the credit gap to zero, credit growth should remain around 14 percent in 2018. In the long run, the credit growth target should be phased out along with adopting a monetary policy framework based on inflation targeting and open market operations, so that the credit growth is determined by a market-based mechanism.

7. A third approach to assessing excessive credit growth is to determine deviations from benchmark levels of credit-to-GDP ratios. The benchmark level of credit-to-GDP ratios, cratiou is assumed to be a function of per capita GDP and computed by the fitted values in the following regression analysis,

Here, incomei,t is per capita income in US dollar for country i in period t. 2 The deviations from fitted values of credit-to-GDP ratios are interpreted as an indication of excessive credit supply. Additional explanatory variables such as population, non-linear terms, etc. can be incorporated into these estimations to more precisely capture the improvements in economic fundamentals that foster financial development. 3 However, the simple regression model above provides a good framework for determining the benchmark because per capita GDP accounts for variations of the credit-to-GDP ratios across countries and periods very well (text Figure on next page) and because adding insignificant variables possibly poses a risk to overfitting.

8. The benchmarking exercise indicates that the recent increase in credit-to-GDP ratios may have been too rapid in Vietnam. The text Figure shows the benchmark level of credit-to-GDP ratios for Vietnam with 1.0- and 1.5-SD bands along with the actual values. The figure indicates that the credit-to-GDP ratios in Vietnam have grown at a faster pace than estimated by their per capita GDP. The ratios were within the 1.5-SD band after the correction during the 2011 crisis, but they are now outside the 1.5-SD band again reflecting the recent rapid credit growth. The same benchmarking exercise in selected countries (text Figure) shows large positive deviations from benchmark levels historically led to banking crises followed by sharp corrections in credit volumes. Past experiences in other countries also suggests that while large and positive deviations of credit-to-GDP ratios from their benchmark level usually ends with sharp corrections in credit volumes, in some cases substantial deviations from fundamentals can persist for a long time without a correction.

Vietnam: Credit-to-GDP Ratios

Sources: BIS; and IMF staff calculations.

Figure 1.Selected Economies: Credit-to-GDP Ratios Relative to Benchmark

B. Stock Markets

9. The stock market performance in Vietnam has been very strong. The year-on-year growth of stock prices on a US dollar basis was more than 15 percent in 2016 and more than 40 percent in 2017, much higher than the U.S. and ASEAN markets (text Figure). Market capitalization increased significantly but steadily both in terms of volume and valuation until 2016 (and the GDP ratios remained almost flat during this time), suggesting that the increases in the market capitalization were in line with real economic developments (text Figure).4 In 2017, however, the increase in market capitalization was more than 70 percent, much higher growth than past growth rates, and it was mostly due to an increase in valuation reflecting rapid increases in stock prices. As a result, in market capitalization increased sharply to around 70 percent of GDP at the end of 2017 from around 40 percent in 2016, driven by valuation.

Vietnam: Stock Price Index

(Year-on-Year Percent Change)

Sources: Bloomberg; and IMF staff calculations.

Vietnam: Market Capitalization

Sources: Bloomberg; and IMF staff calculations.

Vietnam: Growth of Total Market Capitalization

Sources: Bloomberg; and IMF staff calculations.

10. The sharp increase in valuation measures in 2017 suggests that the high stock prices are driven by elevated expectation of future growth. Substantial changes in valuation measures including the price-to-earnings ratios (PER), the price-to-book ratios (PBR) and the dividend yield suggest that the increase in stock prices are based on expectations of corporate performance in the future (text Figure). While valuation levels are not substantially higher than those in other countries, their large and rapid changes in 2017 implies that investors’ expectations for Vietnam have dramatically changed during 2017 and that if the elevated expectations for solid economic growth are not realized, the high stock prices could experience correction.

Vietnam: Price-to-Book Ratios and Dividend Yield

Sources: Bloomberg; and IMF staff calculations.

Vietnam: Price-to-Earnings Ratios

Sources: Bloomberg; and IMF staff calculations.

11. Continued progress in privatizing and reforming state-owned enterprises (SOE) will be critical. SOE privatization and reforms will not only support the high economic growth but also directly contribute to the performance of listed SOEs, which still dominate stock markets in Vietnam.5 Stock market corrections could affect the real economy through declines in IPOs, a slowdown in SOE equitization, and the deterioration in bank and corporate balance sheets, but more granular data are needed for further assessment of the impact through this channel.

C. Real Estate Prices

12. House price misalignment is assessed by the following two approaches. First, substantial changes in the Price-to-Rent ratios (house prices divided by rent indexes) can be interpreted as deviations from economic fundamentals due to, for instance, excessive and risky lending by banks to this sector. In this approach, rent represents the fundamental value of housing, and theoretically the ratios should be stationary (Poterba 1984). The second approach is a regression-based assessment (e.g., IMF 2004). In this approach, house price misalignment is estimated by the following conventional model for house price valuation:

Here, the affordability (affordi,t) is defined as house prices divided by per capita GDP, and represents a long-term relation between house prices and real economy. The estimation is conducted by (unbalanced) cross-country panel data for Asian emerging economies, namely Indonesia, South Korea, Malaysia, Philippines, Singapore, Thailand, China and Vietnam. Then, the deviations from the fitted values are interpreted as house price misalignment.6

13. Price-to-rent ratios show that the rise in housing prices in HCMC remain in line with economic fundamentals. Since 2015, the residential property price index in HCMC has continued to increase (text Figure). The price-to-rent ratios, however, have not significantly increased as in the previous crisis period in 2011, and they are now converging to the 2015 level due to the increase in rent, suggesting that the increase in house prices are justified by economic fundamentals (text Figures). Economic fundamentals which can justify the recent increase in property prices include: (1) the strong income growth of a growing middle class, and (2) a steady rate of urbanization supporting the demand for housing in a city area. In addition, government policy to provide mortgages at low interest rates to low income households through state-owned banks—while limited in scope—may have also helped support property prices.

Vietnam: Real Estate Prices

(2014=1.0)

Sources: Savills; National authorities; and IMF staff calculations.

Vietnam: Real Estate Prices

(2014=1.0)

Sources: Savills; National authorities; and IMF staff calculations.

Vietnam: Real Estate Price Estimation

Sources: Savills; and IMF staff calculations.

14. The regression based assessment indicates that Vietnam’s property price appears not to substantially deviate from the estimated trend in recent years (text Figure). This result suggests that the recent developments in property prices in Vietnam are in line with economic fundamentals, which is consistent with the analysis by price-to-rent ratios. Based on our forecast for per capita income and working age population in Vietnam, the model would suggest that real house prices will be almost flat or increase only moderately for the next several years as houses become more affordable in Vietnam.

15. House price misalignments based on regression analysis should be interpreted with caution in the case of Vietnam. For Asian countries other than Vietnam, the model can account for most of the variation in house prices, suggesting that income growth and demographic variables capture the behavior of housing prices well (text Figure). However, given the large deviations of the actual historical values from fitted values in Vietnam, the model does not seem to have strong predictive powers in Vietnam (text Figure in paragraph 14). Since the large deviations from fitted values may be explained by the low quality of real estate data in Vietnam, more reliable data for house prices are necessary for a more precise and comprehensive assessment.

Figure 2.Selected Economies: Real Estate Price Estimation

D. Conclusions

16. Overall, asset price and credit growth appear to be stronger than warranted by fundamentals. In particular, the central bank’s credit growth target should be decreased to avoid excessive risk taking by banks, and raising the target would not be warranted. Continued SOE and other growth-supporting reforms would help better align the rapid rise in stock market valuations with fundamentals. Finally, the SBV should develop a macroprudential policy framework including loan-to-value (LTV) and debt service-to-income (DSTI) requirements to deal with future possibilities of excessive exuberance in the real estate market.

References

    BarajasAdolfoThorstenBeckEraDabla-Norris andRezaYousefi. 2013. “Too Cold, Too Hot, or Just Right? Assessing Financial Sector Development Across the GlobeIMF Working Paper 13/81International Monetary FundWashington, DC.

    BeckThorsten andErikFeyen. 2013. “Benchmarking Financial Systems: Introducing the Financial Possibility FrontierPolicy Research Working Paper 6615World BankWashington, DC.

    DrehmannMathias andKostasTsatsaronis. 2014. “The Credit-to-GDP gap and Countercyclical Capital Buffers: Questions and AnswersBIS Quarterly Review March 2014.

    GerslAdam andMartinaJasova. 2018. “Credit-Based Early Warning Indicators of Banking Crises in Emerging MarketsEconomic Systems42(1) pp.1831.

    International Monetary Fund. 2004. World Economic OutlookChapter 1. Economic Prospects and Policy IssuesInternational Monetary FundWashington, DC.

    PoterbaJamesM.1984. “Tax Subsidies to Owner-Occupied Housing: an Asset-Market ApproachThe Quarterly Journal of Economics99(4) pp.729752

Prepared by Mitsuru Katagiri (MCM). The author thanks the seminar participants at the SBV for their thoughtful comments.

The data for credit-to-GDP ratios are taken from the BIS database of credit gaps (https://www.bis.org/statistics/c_gaps.htm). The estimation is conducted by the panel data for the average values of 1995–2004 and 2005–2016, and the dummy variables for Asian countries are added to control for their high credit- to-GDP ratios on average.

While other variables such as population, financial openness (Chinn-Ito index), and urbanization are arguably relevant explanatory variables for the level of financial development in the literature, they are not significant for the sample countries and periods here. For more details on the benchmark exercise of credit-to-GDP ratios, see Barajas et al. (2013) and Beck and Feyen (2013).

Market capitalization reflects the sum of the large three stock markets in Vietnam: The Ho Chi Minh City Stock Exchange (HOSE), Hanoi Stock Exchange (HNX), and the Unlisted Public Company Market (UPCoM). At the end of 2017, the HOSE was the dominant stock market in Vietnam and its share of total market capitalization in Vietnam was around 70 percent.

As of January 2018, the share of Top 5 and 10 firms in terms of market capitalization in HOSE and NHX, respectively, are 36 percent and 52 percent. Among these top 5 and 10 firms, 4 and 7 firms, respectively are SOEs.

The estimated equation gives the fitted values for the growth rate of house prices rather than those for the level of house prices. Hence, in this paper, the base level of house prices in each country is set to the historical average level of real house prices in data, and the fitted values for the level of house prices are calculated by extending the house prices using the estimated growth rate.

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