A. Introduction

1. The evolution of property prices has important implications for macroeconomic outcomes in Hong Kong SAR. Property price declines, as those experienced during the past five years, have been amplified through balance-sheet effects depressing consumption and investment. On the fiscal front, government revenues from land leases have declined substantially as developers have lowered their reservation price. Finally, the decline in property prices has also contributed to the continued deflation in the region. Policy measures and discussions, then, need to build upon an assessment of the outlook for property prices in Hong Kong SAR. This paper attempts to provide such an assessment.

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

3. In the near term, supply factors could contribute to reduce excess inventory in the residential market and relieve some of the downward price pressure. Starting 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 of China 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 rates, and better medical care and education services.

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

5. The rest of the chapter is structured as follows. Section B describes the macroeconomic impact of property prices in Hong Kong SAR. Section C describes recent developments in the real estate sector, focusing particularly on recent government measures aimed at stabilizing the property market. Section D presents estimates of fundamental prices in the housing sector, compares them to current prices, and projects the evolution of fundamental prices forward under different scenarios. Section E concludes.

B. Macroeconomic Implications of Changes in Property Prices

6. The macroeconomic impacts of changes in property prices in Hong Kong SAR have been quantified recently by Peng et al. (2001), who analyzed the period 1984-2000. Their results indicate that a ten percent drop in property prices reduces private consumption growth by ¼ percentage point and investment growth by ¼ percentage points, 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 existence of a “balance-sheet” or “net worth” channel through which property prices play an important role as a determinant of the demand for credit.²

7. 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 the demand for land by developers and contributed to lower land prices. Revenues from stamp duties have fallen as a result of lower property prices and reduced transaction volumes. The recent suspension of land sales announced in November 2002, while intended to redress the imbalance in property market prices, has cut off one important source of fiscal revenues just when the government faces serious challenges on the fiscal front.³

8. The stock market has been affected by the decline in property prices as real estate firms account for over 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 exposure of the five largest Hong Kong SAR banks range from 20-40 percent of their equity base. However, it is believed that banks’ earnings and equity base could withstand further property price declines in the range of 10-15 percent without a significant increase in vulnerability.⁴

9. On the other hand, the decline of property prices in Hong Kong SAR has helped to improve competitiveness. However, office occupancy costs are still high relative to other financial centers in the region. A recent survey indicates that, by end-2002, occupancy costs of US$59 per square feet per annum placed Hong Kong SAR as the second most expensive city in the East Asia region. In contrast, office occupancy costs in Beijing, Singapore, and Shenzhen amounted to US$41, US$34, and US$29 per square feet per annum, respectively.

C. Recent Developments in the Property Market

10. Prices in the property market, regardless of sector and geographic distribution, have experienced a sustained price decline since 1997 (Figure II. 1).⁵ The main factors responsible for this decline are widely regarded as being 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 of China.

Property Price Indices

(1980 Q1=100)

Citation: IMF Staff Country Reports 2003, 142; 10.5089/9781451816846.002.A002

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Property Price Indices

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Citation: IMF Staff Country Reports 2003, 142; 10.5089/9781451816846.002.A002

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Property Price Indices

(1980 Q1=100)

Citation: IMF Staff Country Reports 2003, 142; 10.5089/9781451816846.002.A002

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11. 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 sub-prime rate levels helped primary market sales to reach a four-year high of 27,000 units in 2002, well above the average of 19,000 units in 1999-2001. However, prices continue to decline because of aggressive sales tactics including price cuts, cash rebates, and developer-provided subsidies. Increased sales in the primary market came at the expense of reduced transactions in the secondary market, where transactions declined by 5 percent in the past year.

12. Excess vacant office space and weak demand have caused rental rates for office space to fall steadily by more than 50 percent since their 1997 peaks (Figure II.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 during the pre-Asian crisis period. In the next two years, the completion of new office buildings would increase the inventory of available office space and contribute to keep rental rates down.

Rental Indices

(1980 Q1=100)

Citation: IMF Staff Country Reports 2003, 142; 10.5089/9781451816846.002.A002

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Rental Indices

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Citation: IMF Staff Country Reports 2003, 142; 10.5089/9781451816846.002.A002

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Rental Indices

(1980 Q1=100)

Citation: IMF Staff Country Reports 2003, 142; 10.5089/9781451816846.002.A002

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13. In the past year, rental rates in the retail sector have been less affected than in the office sector thanks to increased tourism spending, especially by tourists from the Mainland of China, 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

14. In the past, the government has played an active role in the property market by supplying subsidized housing and controlling the land supply. Table II.1 chronicles the major measures targeting 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 Hong Kong SAR government unveiled a property policy package focused on the supply side of the property market.

Table II.1:

Major Housing Measures, 1997-2003

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

Table II.1:

Major Housing Measures, 1997-2003

October 1997	Housing Policy Plan aimed at increasing home ownership. Key measures include increasing land supply, increased supply of subsidized housing, non-interest loans through the Home Starter Loan Scheme, and shortening of waiting time for public rental housing.
May 1998	Relaxation of anti-speculative administrative measures on the sale and pre-sale of flats.
June 1998	Suspension of land sales for nine months.
September 1998	Further relaxation of anti-speculative measures by removing restrictions on deposits and payments on the purchase of flats.
April 1999	Resumption of land sale. Introduction of the Application List system.
June 2000	Reduction in supply of subsidized flats; increase of subsidized loans.
February 2001	Tightening of eligibility requirements for subsidized flats; further relaxation of anti-speculative measures.
September 2001	Nine month moratorium on HOS/PSPS sales replaced by additional homeownership loans; administrative freeze on allocation of new sites for HOS/PSPS development.
June 2002	Resumption of HOS sales but supply reduced.
November 2002	Moratorium on land sales until after 2003; phase out of HOS after end-2003; land sales conducted only through the application list starting 2004.
January 2003	Replacement of HPLS and HSLS with HALS: tightening of maximum income eligibility for those not living in public rental housing; lowering of maximum loan amount.

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

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Table II.1:

Major Housing Measures, 1997-2003

October 1997	Housing Policy Plan aimed at increasing home ownership. Key measures include increasing land supply, increased supply of subsidized housing, non-interest loans through the Home Starter Loan Scheme, and shortening of waiting time for public rental housing.
May 1998	Relaxation of anti-speculative administrative measures on the sale and pre-sale of flats.
June 1998	Suspension of land sales for nine months.
September 1998	Further relaxation of anti-speculative measures by removing restrictions on deposits and payments on the purchase of flats.
April 1999	Resumption of land sale. Introduction of the Application List system.
June 2000	Reduction in supply of subsidized flats; increase of subsidized loans.
February 2001	Tightening of eligibility requirements for subsidized flats; further relaxation of anti-speculative measures.
September 2001	Nine month moratorium on HOS/PSPS sales replaced by additional homeownership loans; administrative freeze on allocation of new sites for HOS/PSPS development.
June 2002	Resumption of HOS sales but supply reduced.
November 2002	Moratorium on land sales until after 2003; phase out of HOS after end-2003; land sales conducted only through the application list starting 2004.
January 2003	Replacement of HPLS and HSLS with HALS: tightening of maximum income eligibility for those not living in public rental housing; lowering of maximum loan amount.

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

15. 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 end-2003; and ending the construction and sale of flats under the Home Ownership Scheme (HOS) from 2003 onwards. In the short term, these measures are believed to have only a negligible impact on housing prices, as most residential construction for the next three years has already been started.

16. In January 2, 2003, the government implemented the new Home Assistance Loan Scheme (HALS). This new scheme provides no-interest loans to low-income families for purchasing private residential units and replaces two similar schemes, the Home Purchase Loan Scheme (HPLS) and the Home Starter Loan Scheme (HSLS). The main differences relative to the previous schemes are the lowering of the maximum income ceiling for families not living in public housing units, and a general reduction of the loan amount 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. While the new scheme provides incentives for purchasing private units, past experience with the HPLS suggest that the HALS quota may not be fully used.

17. With respect to the land sale process, starting in 2004 land sales will only be triggered 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 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 bid submitted and accepted by the government.

D. Fundamental Housing Prices

18. Fundamental prices in the residential sector are estimated using the methodology first proposed by Abraham and Hendershott (1986) and used subsequently by Kalra et al. (2000), and Peng (2002). In 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.

19. Following the econometric specification of Kalra et al. (2002), 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 of 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:

where P and P^* are the market and fundamental price respectively, and e is an i.i.d. 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, as 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-buster”, which causes prices to revert to their fundamental value.

20. 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 differing 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 II.2, and the corresponding paths for fundamental prices are presented in Figure II.3. It should be noted, though, that these results have been obtained from model specifications that do not include supply factors such as the provision of public housing in the future, nor current excess inventory of unsold units.⁶ In addition, the availability of cheaper housing across the border in Shenzhen has not been modeled explicitly in the model because of a lack of historical data.

Table II.2.

Speculative Bubble Model of Real Property Prices

Note: The only difference among the three specifications shown in this table

^*/Significant at 5 percent confidence level.

^**/Significant at 10 percent confidence level.

Table II.2.

Speculative Bubble Model of Real Property Prices

Variable		(1)	(2)	(3)
Constant		0.017*	0.006	0.024*
		(0.009)	(0.008)	(0.007)
	Real disposable income	0.264 **	--	--
		(0.160)
	Real GDP growth rate	--	0.434 *	--
			(0.138)
	Changes in unemployment rate	--	--	-0.023 **
				(0.013)
Change in real rental rate		1.115*	0.848*	1.028*
		(0.222)	(0.230)	(0.216)
Change in real rental rate (-1)		-0.820*	-0.847*	-0.691*
		(0.260)	(0.245)	(0.239)
Change in real rental rate (-2)		0.023	-0.002	0.071
		(0.214)	(0.207)	(0.207)
Best lending rate		-0.454*	-0.408*	-0.480*
		(0.132)	(0.121)	(0.127)
Change in real housing price (-1)		0.381*	0.378*	0.382*
		(0.129)	(0.134)	(0.130)
Fundamental price gap		-0.182*	-0.213*	-0.204*
		(0.064)	(0.068)	(0.067)
Adjusted R-squared		0.611	0.614	0.619
S.E. of regression		0.039	0.039	0.039
Durbin-Watson statistic		2.159	2.046	2.144
Number of observations		66	66	66

Note: The only difference among the three specifications shown in this table

^*/Significant at 5 percent confidence level.

^**/Significant at 10 percent confidence level.

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Table II.2.

Speculative Bubble Model of Real Property Prices

Variable		(1)	(2)	(3)
Constant		0.017*	0.006	0.024*
		(0.009)	(0.008)	(0.007)
	Real disposable income	0.264 **	--	--
		(0.160)
	Real GDP growth rate	--	0.434 *	--
			(0.138)
	Changes in unemployment rate	--	--	-0.023 **
				(0.013)
Change in real rental rate		1.115*	0.848*	1.028*
		(0.222)	(0.230)	(0.216)
Change in real rental rate (-1)		-0.820*	-0.847*	-0.691*
		(0.260)	(0.245)	(0.239)
Change in real rental rate (-2)		0.023	-0.002	0.071
		(0.214)	(0.207)	(0.207)
Best lending rate		-0.454*	-0.408*	-0.480*
		(0.132)	(0.121)	(0.127)
Change in real housing price (-1)		0.381*	0.378*	0.382*
		(0.129)	(0.134)	(0.130)
Fundamental price gap		-0.182*	-0.213*	-0.204*
		(0.064)	(0.068)	(0.067)
Adjusted R-squared		0.611	0.614	0.619
S.E. of regression		0.039	0.039	0.039
Durbin-Watson statistic		2.159	2.046	2.144
Number of observations		66	66	66

Note: The only difference among the three specifications shown in this table

^*/Significant at 5 percent confidence level.

^**/Significant at 10 percent confidence level.

Residential Property Prices

Citation: IMF Staff Country Reports 2003, 142; 10.5089/9781451816846.002.A002

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Residential Property Prices

Citation: IMF Staff Country Reports 2003, 142; 10.5089/9781451816846.002.A002

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Residential Property Prices

Citation: IMF Staff Country Reports 2003, 142; 10.5089/9781451816846.002.A002

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21. Table II.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, as a one percent change in housing prices results in a 2½ percent increase in property prices in the long run ceteris paribus. However, the bubble-buster coefficient associated with the fundamental price gap is negative, and suggests the existence of price correction mechanisms in the housing market. These results are consistent with previous findings by Kalra et al. (2000) and Peng (2002).

22. Figure II.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 ½ 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 ½ percent and 1½ percent relative to fundamental levels respectively. But note that the differences in results across these alternative specifications are quite small.⁷ 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.

23. 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 II.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 as well as 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. However, fundamental prices are projected to increase, especially in 2004, if GDP growth and/or rental rates were to strengthen significantly. It is worth reemphasizing 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, in particular, to analyze the impact of property prices in neighboring Shenzhen on property prices in Hong Kong SAR.

Table II.3:

Scenarios for Housing Prices Projections ^1/

Sources: Staff estimates.

^1/All numbers in percentage points

Table II.3:

Scenarios for Housing Prices Projections ^1/

		Scenario 1		Scenario 2		Scenario 3		Scenario 4
		(Benchmark)
		2003	2004	2003	2004	2003	2004	2003	2004
GDP specification
Assumptions
	Real GDP growth	2.2	3.1	4.5	6.0	2.2	3.1	2.2	3.1
	Best lending rate	7.0	7.0	7.0	7.0	7.0	5.0	7.0	7.0
	Real rental rate growth	-2.0	-2.0	-2.0	-2.0	-2.0	-2.0	0.0	5.0
Implied price changes
	Market prices	-7.2	-3.5	-2.2	2.9	-5.9	0.0	-3.3	0.0
	Fundamental prices	-5.3	-3.8	-1.3	1.3	-4.3	-1.1	-2.3	-0.7
Unemployment specification
Assumptions
	Unemployment rate	7.4	7.0	7.0	6.8	7.4	7.0	7.4	7.0
	Best lending rate	7.0	7.0	7.0	7.0	7.0	5.0	7.0	7.0
	Real rental rate growth	-2.0	-2.0	-2.0	-2.0	-2.0	-2.0	0.0	5.0
Implied price changes
	Market prices	-11.6	-6.7	-10.4	-7.4	-10.1	-2.7	-4.5	7.5
	Fundamental prices	-7.9	-6.5	-7.0	-7.0	-6.7	-3.4	-2.3	4.8

Sources: Staff estimates.

^1/All numbers in percentage points

View Table

Table II.3:

Scenarios for Housing Prices Projections ^1/

		Scenario 1		Scenario 2		Scenario 3		Scenario 4
		(Benchmark)
		2003	2004	2003	2004	2003	2004	2003	2004
GDP specification
Assumptions
	Real GDP growth	2.2	3.1	4.5	6.0	2.2	3.1	2.2	3.1
	Best lending rate	7.0	7.0	7.0	7.0	7.0	5.0	7.0	7.0
	Real rental rate growth	-2.0	-2.0	-2.0	-2.0	-2.0	-2.0	0.0	5.0
Implied price changes
	Market prices	-7.2	-3.5	-2.2	2.9	-5.9	0.0	-3.3	0.0
	Fundamental prices	-5.3	-3.8	-1.3	1.3	-4.3	-1.1	-2.3	-0.7
Unemployment specification
Assumptions
	Unemployment rate	7.4	7.0	7.0	6.8	7.4	7.0	7.4	7.0
	Best lending rate	7.0	7.0	7.0	7.0	7.0	5.0	7.0	7.0
	Real rental rate growth	-2.0	-2.0	-2.0	-2.0	-2.0	-2.0	0.0	5.0
Implied price changes
	Market prices	-11.6	-6.7	-10.4	-7.4	-10.1	-2.7	-4.5	7.5
	Fundamental prices	-7.9	-6.5	-7.0	-7.0	-6.7	-3.4	-2.3	4.8

Sources: Staff estimates.

^1/All numbers in percentage points

E. Conclusions

24. The analysis undertaken in this paper 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. While property prices now appear to be at levels consistent with demand-side fundamentals, further weaknesses in housing prices cannot be ruled out if the economy remains weak.