The evolution of property prices has important implications for macroeconomic outcomes in Hong Kong SAR. Property price declines, such as those experienced during the past five years, have been amplified through balance-sheet effects, thereby depressing consumption and investment. On the fiscal front, government revenues from land leases have declined substantially as developers have lowered their reservation prices. Finally, the decline in property prices has also contributed to the continued deflation in the region. An assessment of the outlook for property prices in Hong Kong SAR is thus of considerable importance from a broader macroeconomic perspective.

The evolution of property prices has important implications for macroeconomic outcomes in Hong Kong SAR. Property price declines, such as those experienced during the past five years, have been amplified through balance-sheet effects, thereby depressing consumption and investment. On the fiscal front, government revenues from land leases have declined substantially as developers have lowered their reservation prices. Finally, the decline in property prices has also contributed to the continued deflation in the region. An assessment of the outlook for property prices in Hong Kong SAR is thus of considerable importance from a broader macroeconomic perspective.

Recovery in the property sector will depend upon both domestic and global economic conditions, as well as on successful integration with the mainland of China. On the one hand, although the inventory of unsold units and vacant office and commercial space remains relatively high by historical standards, a strong economic recovery and the associated boost in aggregate demand could go a long way toward correcting the imbalances. On the other hand, excess property inventory could continue to pose a major problem for the recovery of the aggregate price level in a weak economy.

In the near term, supply factors could contribute to reducing excess inventory in the residential market and relieve some of the downward price pressure. Starting in 2003, the supply of government-subsidized housing will be scaled down drastically. Also, private construction will likely slow down. Although the possible effects of continued price convergence with the mainland remain a concern, most market analysts believe that the availability of low-cost housing in Shenzhen does not contribute to increased effective supply in the housing market of Hong Kong SAR. In their view, the existence of a “Hong Kong SAR premium” is justified by the region’s lower crime rate and better medical care and education services.

Econometric analysis suggests that current housing prices are approximately consistent with fundamental factors; future prospects remain uncertain, however. Results obtained using different model specifications and a variety of scenarios suggest that current prices are approximately in line with demand-side fundamentals. Continued weaknesses in housing prices cannot be ruled out, however, unless the economic recovery strengthens significantly.

Macroeconomic Implications of Changes in Property Prices

The macroeconomic impacts of changes in property prices in Hong Kong SAR have been quantified recently by Peng, Cheung, and Leung (2001), based on data for 1984–2000. Their results indicate that a 10 percent drop in property prices reduces private consumption growth by 1 percentage point and investment growth by one-fourth of 1 percentage point, after controlling for the effects of other variables including changes in GDP and asset prices. Empirical evidence also suggests that total bank lending adjusts to changes in property prices (Gerlach and Peng, 2002), supporting the view that there is a “balance-sheet” or “net-worth” channel through which property prices play an important role in determining the demand for credit.1

Government revenue in Hong Kong SAR is highly dependent on property-related income through both land sales and stamp duties. The dwindling demand for housing has, in turn, reduced developers’ demand for land and contributed to lower land prices. Revenues from stamp duties have fallen as a result of lower property prices and reduced transaction volumes. The suspension of land sales announced in November 2002, although intended to redress the imbalance in property market prices, has cut off one important source of revenues just when the government faces serious fiscal challenges.

The stock market has been affected by the decline in property prices, since real estate firms account for more than 20 percent of total market capitalization. Hence, developments in the property sector affect both households’ and banks’ investment portfolios. In addition, market analysts have reported that the aggregate real estate exposures of the five largest Hong Kong SAR banks range between 20 and 40 percent of their equity bases. It is believed, however, that banks’ earnings and equity bases could withstand further property price declines of 10–15 percent without a significant increase in their vulnerability.2

At the same time, the decline of property prices in Hong Kong SAR has helped to improve competitiveness. But office-occupancy costs are still high relative to other financial centers in the region. A recent survey indicates that by the end of 2002, occupancy costs of US$59 per square foot per annum made Hong Kong SAR the second most expensive city in East Asia. In contrast, annual office-occupancy costs in Beijing, Singapore, and Shenzhen were US$41, US$34, and US$29 per square foot, respectively.

Recent Developments in Property Market

Prices in the property market, regardless of sectoral and geographic distribution, have experienced a sustained decline since their peak in 1997 (Figure 4.1).3 The main reasons for this decline are widely considered to be the weak economic performance of Hong Kong SAR’s economy following the financial turbulence in 1997–98; overbuilding; and, possibly, increased integration with the mainland.

Figure 4.1.
Figure 4.1.

Property Price Indices

(1980: Q1 = 100)

Sources: Primark Datastream LLC; and IMF staff calculations.

The year 2002 witnessed a significant pickup in the volume of primary market transactions in the residential sector, owing to the low-interest-rate environment. High affordability ratios and mortgage rates at subprime levels helped primary-market sales to reach a four-year high of 27,000 units in 2002, well above the annual average of 19,000 units for 1999–2001. Prices have continued to decline, however, because of aggressive sales tactics including price cuts, cash rebates, and developer-provided subsidies. Increased sales in the primary market have come at the expense of reduced transactions in the secondary market, where transactions declined by 5 percent in 2002.

Excess vacant office space and weak demand have caused rental rates for office space to fall steadily, dropping by more than 50 percent since their 1997 peaks (Figure 4.2). Weak global economic conditions have depressed the business prospects of the financial services, insurance, and trading industries and reduced demand for office space. As a result, vacancy rates reached 10 percent by the third quarter of 2002, well above the 4 percent average vacancy rate seen before the Asian crisis. In the next two years, the completion of new office buildings is expected to increase the inventory of available office space and contribute to keeping rental rates down.

Figure 4.2.
Figure 4.2.

Rental Indices

(1980: Q1 = 100)

Sources: Primark Datastream LLC; and IMF staff calculations.

In the past year, rental rates in the retail sector have been less affected than in the office sector owing to increased spending on tourism, especially by visitors from the mainland, which helped to offset faltering domestic consumption. Properties located close to major transportation hubs and enjoying high foot traffic benefited the most. Excess inventory is less of a problem in this sector.

Government Measures

In the past, the government has played an active role in the property market by supplying subsidized housing and controlling the land supply. Table 4.1 chronicles the major measures that have targeted the housing sector since 1997. Since 1998, the government has reduced its role as a provider of subsidized public housing while encouraging private house ownership. On November 13, 2002, the government unveiled a property policy package focused on the supply side of the market.

Table 4.1.

Major Policy Measures in Property Market, 1997–2003

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Sources: Hong Kong SAR government publications; Morgan Stanley Dean Witter.

Two important measures included in the November 2002 policy package were the temporary halt in land sales, through the suspension of the scheduled land auctions and the Application List and tenders from the Mass Transit Railway Corporation (MTRC) and the Kowloon-Canton Railway Corporation (KCRC), until the end of 2003; and the termination of the construction and sale of flats under the Home Ownership Scheme (HOS) from 2003 onward. In the short term, these measures are likely to have only a negligible impact on housing prices, since most residential construction that will be completed during the next three years has already been started.

On January 2, 2003, the government implemented the new Home Assistance Loan Scheme (HALS). This scheme provides no-interest loans to low-income families for the purchase of private residential units and replaces two similar schemes, the Home Purchase Loan Scheme (HPLS) and the Home Starter Loan Scheme (HSLS). The HALS’s main differences from the previous schemes are the lowering of the maximum income ceiling for families not living in public housing units and a general reduction in loan amounts to account for the decline in property prices. The initial quota is 10,000 cases per year, though it is difficult to project whether the quota will be fully used. Although the new scheme provides incentives for purchasing private units, past experience with the HPLS suggests that the HALS quota may not be fully used.

Starting in 2004, land sales will be triggered only through the application list system. Under this system, the government announces in advance what lots will be available for sale (by auction or tender) in the coming year. An interested party can trigger the auction of a lot by submitting a price bid acceptable to the government. The land is then auctioned or tendered publicly to the highest bidder. In the absence of other interested parties, the party that triggers the auction is awarded the land for the price it bid, after acceptance by the government.

Fundamental Housing Prices

Fundamental prices in the residential sector are estimated using the methodology first proposed by Abraham and Hendershott (1996) and subsequently used by Kalra and others (2000) and Peng (2002). Using this methodology, the growth rate of property prices can be decomposed into a fundamental component, which is a linear function of variables determining demand and supply, and a bubble component, which is a function of lagged prices and the gap between fundamental and past price levels.

Following the econometric specification of Kalra and others (2000), it is assumed that the growth rate in residential property prices, p, can be decomposed into the growth rate of the fundamental or equilibrium price, p*, and an adjustment term, θ:


The fundamental price growth rate is a linear function of changes in disposable real income or some appropriate proxy, dpi, contemporaneous and lagged values of changes in the real rental rate, rr, and the level of the real best lending rate, blr, which is a proxy for mortgage rates:


The adjustment term, θ, is given by the following equation:

θt=λ0+λ1pt-1+λ2( logP t-1 -logPt-1* )+ϵt,(3 )

where P and P* are the market and fundamental price, respectively, and ε is an i.i.d. (independent and indentically distributed) error term. The log difference of the market price and the fundamental price is defined as the fundamental price gap. If λ1 is positive, the second term in equation (3) can be interpreted as a bubble component, since higher prices in the previous period are carried over to the next period. If λ2 is negative, the third term in equation (3) can be interpreted as a mean-reverting term or “bubble-burster” that causes prices to revert to their fundamental values.

The choice of explanatory variables in equation (2) is guided by their role in determining housing demand. Equations (2) and (3) were estimated for three different specifications that differed in the choice of proxy for disposable income: real household disposable income, real GDP, and the unemployment rate. The estimation results for the three specifications are presented in Table 4.2, the corresponding paths for fundamental prices in Figure 4.3. It should be noted, though, that these results have been obtained from model specifications that include neither supply factors, such as the provision of public housing in the future, nor current excess inventory of unsold units.4 In addition, the availability of cheaper housing across the border in Shenzhen has not been included explicitly in the model because of a lack of historical data.

Figure 4.3.
Figure 4.3.

Residential Property Prices

(Logarithm of price index, 1980: Q1 = 100) 4.20

Sources: Primark Datastream LLC; and IMF staff calculations.
Table 4.2.

Speculative-Bubble Model of Real Property Prices

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Sources: Primark Datastream LLC; and IMF staff calculations.Notes: The only difference among the three specifications shown in this table is the choice of proxy for disposable income.

denotes significance at 5 percent confidence level.

denotes significance at 10 percent confidence level.

Table 4.2 shows that for the three different model specifications analyzed, all explanatory variables enter with the expected sign and are statistically significant. Furthermore, the magnitudes of the coefficients on all explanatory variables, excluding the proxy for disposable income, are rather similar across different model specifications. The results suggest that bubbles in the housing market in Hong Kong SAR occurred in the past, since, ceteris paribus, a 1 percent change in housing prices results in a 21/2 percent increase in property prices in the long run. The bubble-burster coefficient associated with the fundamental price gap is negative, however, which suggests the existence of price-correction mechanisms in the housing market. These results are consistent with previous findings by Kalra and others (2000) and Peng (2002).

Figure 4.3 shows that from the first quarter of 2000 until the first quarter of 2002, housing prices in Hong Kong SAR were below levels consistent with fundamental demand factors (fundamental levels) for all model specifications. During 2002, different model specifications delivered different conclusions. On the one hand, housing prices are just one-half of 1 percent above fundamental levels according to the disposable-income specification. On the other hand, the GDP and unemployment specifications suggest that housing prices are undervalued by one-half of 1 percent and 11/2 percent, respectively, relative to fundamental levels. But note that the differences in results across these alternative specifications are quite small.5 Overall, given data-measurement errors and uncertainty regarding the correct specification of the model, it seems reasonable to assert that by the third quarter of 2002, housing prices were approximately in line with fundamentals.

Uncertainty in the model-parameter estimates as well as in the macroeconomic forecasts suggests that out-of-sample projections from these model specifications should be interpreted with considerable caution. Table 4.3 provides some illustrative calculations to show how, using IMF staff projections of real GDP growth and unemployment rates, the GDP and unemployment specifications can be used to project how fundamental prices and market prices would evolve under different scenarios. These scenarios suggest that additional small declines in fundamental prices may occur in 2003 if the economy remains weak. Fundamental prices are projected to increase, however, especially in 2004, if GDP growth and/or rental rates strengthen significantly. It is worth reemphasizing, in this context, that the evolution of supply factors could substantially alter the price dynamics predicted by this model, which does not account explicitly for the impact of such factors. Further work integrating both demand factors and supply factors could be helpful, particularly in analyzing the impact of property prices in neighboring Shenzhen on property prices in Hong Kong SAR.

Table 4.3.

Scenarios for Housing-Price Projections:

(In percentage points)

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Sources: Primark Datastream LLC; and IMF staff calculations.


The analysis undertaken in this section suggests that in the housing market, prices are roughly at levels consistent with those determined by demand factors such as personal disposable income, rental rates, and interest rates. This analysis has focused on demand-side factors, since updated and historically consistent data on key supply-side variables were difficult to obtain. Nevertheless, the results are in line with those reported in an earlier study by Peng (2002), which were obtained using a similar model that included supply-related explanatory variables. Although property prices now appear to be at levels consistent with demand-side fundamentals, further weaknesses in housing prices cannot be ruled out if Hong Kong SAR’s economy remains weak.


The “balance-sheet” or “net-worth” channel view explains the relationship between asset prices and economic activity through the value of collateral: in the presence of credit-market frictions, access to credit depends on the ability of the borrower to collateralize the loan, which, in turn, depends on current asset prices. This channel gives rise to a “financial accelerator” mechanism: declines in asset prices reduce creditworthiness, and the contraction in credit causes a fall in consumption and investment. Future economic activity is negatively affected, which, in turn, increases downward pressure on asset prices. See Kiyotaki and Moore (1997) and Bernanke and others (1999).


This shortcoming is addressed in the study by Peng (2002). The results reported here, however, are similar to those reported in the Peng study. Furthermore, the use of the best lending rate rather than the mortgage-rate series used by Peng did not alter the results substantially.


The standard deviation of the point estimates ranges between 0.60 and 0.70.

Meeting the Challenges of Integration with the Mainland