## _wp10274

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---

### I. Introduction and objectives
- During 2009, China’s residential property market prices turned around and grew rapidly, especially in several large- and medium-sized cities, as the impact of the global financial crisis subsided and domestic financial conditions relaxed.
- Price-to-rent ratios rose to new highs, and price-income ratios started to rise, reversing a declining trend.
- The paper compares movements in China’s residential property prices with those implied by market fundamentals using two approaches:
  - A panel regression linking prices to long-term fundamentals.
  - A relationship between price, rent, and ownership cost (user-cost).
- The user-cost measure is used to characterize price deviations in comparator countries and to discuss similarities and differences with China.

### Major findings
- National valuation
  - As of mid-2010, house prices are not significantly overvalued in China as a whole.
- City- and segment-level misalignment
  - The mass-market segment in a number of coastal cities—most clearly in Shanghai and Shenzhen—as well as a few inland cities, may be in the early stages of excessive price growth.
  - Early signs of price misalignment can also be detected in the luxury segment in Beijing and Nanjing.
- Persistence of deviations
  - Deviations from benchmark prices appear not to be persistent with a half life of around 1quarter on average for overall China.
  - Comparators: Hong Kong SAR (2–4 quarters) and Singapore (5 quarters).
  - This contrasts with several industrial economies before 2008—especially the U.S., New Zealand, and France—where deviations tended to persist far longer and led to large and abrupt adjustments.
- Impact of April 2010 policy measures
  - Policy measures taken by the Chinese government in April 2010 appear to have had some impact on price growth.
  - Gaps between market and fundamentals-implied prices have become smaller in a few cities.
  - In some cities, notably the mass market segments in Guangzhou, Tianjin, and Shenzhen, prices recently seem to have remained persistently misaligned.

### Market dynamics, leverage, and macro-financial exposure
- Mortgage and loan growth
  - Real estate loan growth in the prior year reached an all-time high reflecting development of the new mortgage market.
  - Mortgage loan growth was nearly 50percent, raising mortgage debt from 10 to around 15percent of nominal GDP in one year.
  - By late 2009, loans to property developers and mortgages together accounted for about 20percent of total loans.
- Real activity exposure
  - Real estate investment accounts for about 20percent of total investment and around 9percent of GDP.
  - Land sales are an important revenue source for local governments; in Beijing and Zhejiang, land sales accounted for as much as 30percent of government general revenue in 2009.
- Consumption and broader impacts
  - Despite growing importance to the real economy, housing prices have had a somewhat limited impact on consumption.
  - Housing price developments could notably impact private investment and local government revenue, especially in cities with high real estate investment.
- Implications
  - Growing importance of property in real activity and increased banking sector exposure highlight the need for early warning measures of misalignment.

### Interpretation of the misalignment measure
- The benchmark in the asset pricing approach is linked to market rent and a set of fundamental factors, providing an early warning indicator of market exuberance comparable across cities and over time.
- This measure is a sufficient (but not necessary) condition for detecting misalignment; serious misalignment may only become apparent after substantial and abrupt price declines.
- The measure has identified historical episodes outside China, including Hong Kong SAR during 1997 and several advanced markets more recently.

### Two empirical approaches and key parameter estimates
- Approaches used
  - Panel regression (dynamic OLS) for 35 cities (2000Q1–2009Q4) to estimate long-term equilibrium property prices using determinants: real lending interest rate, population density, real GDP per capita, land prices, and Shanghai Composite stock index.
  - Asset pricing / user-cost approach comparing market prices with benchmark prices implied by rent and ownership cost (imputed rent = ownership cost in frictionless equilibrium).
- Panel regression coefficients (Coefficient, t-statistic):
  - Constant: 5.291, 31.461
  - Real interest rate: -0.020, -2.616
  - Real GDP per capita: 0.058, 2.179
  - Population density: 0.0002, 6.888
  - Land price: 0.001, 9.541
  - Stock price: 0.302, 8.976
- Significant long-term determinants identified: real income per capita, real mortgage interest rate, wealth (Shanghai Composite market capitalization), past land prices, and urbanization/migration (population density).

### Asset-pricing/user-cost results and international comparators
- Benchmarking principle: annual market rent should equal annual cost of owning a property (user cost); deviations suggest potential overpayment and misalignment.
- International evidence (2002Q4–peak, selected metrics):
  - US: Annual avg. price growth 5.9 percent; Annual avg. benchmark price growth 3.2 percent; Difference 2.6 percent per annum; Deviation at peak 8.7 percent of benchmark price; Quarter at peak 2006Q4.
  - France: 9.6 percent; 4.5 percent; 5.1 percent per annum; 24.3 percent; 2008Q1.
  - New Zealand: 11.3 percent; 6.4 percent; 4.9 percent per annum; 25.2 percent; 2007Q4.
  - UK: 6.6 percent; 6.0 percent; 0.6 percent per annum; 7.1 percent; 2008Q1.
  - Australia: 5.3 percent; 4.0 percent; 1.3 percent per annum; 10.0 percent; 2008Q2.
- The methodology captures large persistent pre-crisis deviations in known bubble cases (US, France, New Zealand).

### Findings from China’s asset-pricing analysis (2010H1)
- Overall alignment
  - Overall real estate and overall residential market prices in China roughly aligned with benchmarks; prices rose alongside rents and falling user costs.
- Segments and cities with deviations > 10 percent from benchmark in 2010H1
  - Mass-market house prices in Shanghai and Shenzhen.
  - Luxury house prices in Beijing and Nanjing.
- Persistence and half-life of deviations (estimated)
  - Overall China: half life of deviation ≈ 1 quarter (estimated AR coefficient 0.32).
  - Beijing and Tianjin: deviations halve in around 1–2 quarters.
  - Shenzhen and Guangzhou: process could take roughly 4 quarters.
  - Shanghai: could take about 7 quarters.
  - Some cities (Guangzhou, Shenzhen, to some extent Tianjin) had deviations narrowed only by 2007 policy steps.
- Sensitivity of price-to-rent multiples to a 1 percent increase in user cost (approximate)
  - Beijing: Current User Cost 2.0; decline in P/R multiples 33.0
  - Hangzhou/Guangzhou/Shenzhen: Current User Cost 3.0; decline in P/R multiples 25.0
  - Shanghai/Tianjin: Current User Cost 3.6; decline in P/R multiples 21.0
  - Nanjing: Current User Cost 7.0; decline in P/R multiples 11.0
- Price and rent volatility (coefficients of variation, examples)
  - Beijing: C.V. (Rent) 0.11; C.V. (Price) 0.44
  - Shanghai: C.V. (Rent) 0.06; C.V. (Price) 0.31
  - Shenzhen: C.V. (Rent) 0.04; C.V. (Price) 0.44

### Mortgage market depth and growth (comparative fragment)
- Mortgage/NGDP (percent) and Average growth Rate (percent) for 2004–2007 and 2008–2009 (selected rows)
  - China: 10.4; 2.4 — 11.8; 16.1
  - US: 76.1; 4.2 — 76.3; (no growth rate given for 2008–2009 in table fragment)
  - UK: 80.4; 5.4 — 89.4; 2.5
  - France/Spain: 42.6; 11.5 — 51.8; 4.5
  - Australia: 82.3; 5.0 — 91.8; 4.3
  - New Zealand: 81.7; 8.7 — 96.7; 4.4
- China’s mortgage market expanded modestly until 2009, when mortgage loan to nominal GDP surged; continued growth at that magnitude could fuel further house price inflation and financial stability risks.

### Impact on real economy, banking sector, and government revenue
- Real economy
  - Private consumption: a 10 percent drop in property prices likely induces a 0.7 percent fall in private consumption (provincial panel 1994–2008).
  - Investment: a 10 percent drop in property prices can decrease investment by about 4 percent.
  - Real estate FAI share examples: around 50 percent in Beijing; less than 30 percent in Guangdong.
- Banking sector exposure
  - Direct exposure (late 2009): mortgage loans and developer loans account for less than 20 percent of total outstanding loans in China, compared with 51.6 percent in Hong Kong SAR and 56.6 percent in the US.
  - Developers’ funding: self-raised capital, advanced payment, and other sources accounted for about 60 percent of developers’ total funding in the first quarter of 2010 in 40 major cities.
  - Indirect exposure via industrial linkages: loans to sectors closely linked to property market accounted for about 24.0 percent of total loans in 2009.
  - Collateralized lending using property as collateral is significant anecdotally; property price corrections would reduce collateral values and hurt banks’ balance sheets if defaults occur.
- Government revenue
  - Land sales revenue is an important extra-budgetary revenue source; share varies across provinces (example: Chongqing’s land sales revenue > 30 percent of government general revenue; Shanghai’s < 10 percent in recent years).

### Policy discussion and recommendations
- Authorities’ capacity and risk assessment
  - Given authorities’ awareness and experience in containing excessive property price growth, the likelihood of financial instability precipitated by a housing price bust seems small.
- Structural drivers of rapid price growth
  - Structurally low real interest rates combined with rapid income and productivity growth.
  - Lack of property tax.
  - Increasing availability of mortgage financing.
  - Insufficient alternative investment vehicles.
- Policy options to limit propensity for property price inflation
  - Allow real interest rates to rise and respond more flexibly to macroeconomic conditions.
  - Implement a meaningful property tax.
  - Carefully monitor and react to rising leverage.
  - Maintain tight prudential standards, active monitoring of leverage, and robust financial sector supervision.
  - Broaden financial market development to provide alternative investment vehicles to housing.
- Trade-offs
  - Calibrated moves (e.g., higher real rates or tax changes) carry risk of precipitating asset price adjustment but can lower the probability of disorderly falls if well designed.
  - Credit controls and regulatory measures can temporarily lower prices and affect expectations but do not directly change benchmark prices; market prices can re-accelerate.

### Data, scope notes, and policy timeline highlights
- China’s private residential property market had existed for less than two decades at time of study.
- Price changes 2004–09 (two data sources)
  - NDRC: overall property prices in 35 cities approximately doubled during 2004–09.
  - NBS: reported prices in 70 cities increased by 31percent during the same period.
- Key historical policy actions (selected)
  - Jan 2007: Impose value-added taxes on land transactions.
  - Sep-2007: Raise the minimum down payment ratio to 40percent and the minimum mortgage rate to 110percent of the benchmark rate for second mortgage.
  - Oct-2008: Waive stamp duty on housing transactions and value added taxes on land transactions; Lower the minimum mortgages rate to 70percent of the benchmark rate and the down-payment ratio to 20percent.
  - Dec-2009: Extend the housing holding period to enjoy business tax exemption from 2 years to 5 years; Require developers to pay at least 50percent as the initial payment for land purchase.
  - Jan-2010: Set minimum down-payment ratio for the second mortgages at 40percent.
  - Apr-2010:
    - Raise minimum down-payment ratio for the first mortgage to 30percent for a residential property no more than 90 square meters.
    - Raise the down-payment ratio for the second mortgage to 50percent, and the minimum rate to 110percent of the benchmark rate.
    - The down-payment ratio and minimum mortgage rate for the third mortgage and above will be much higher.
    - Restrict mortgage lending to non-residents.
    - Increase land supply for residential properties.
  - Note: Some tightening measures launched in September and October 2010 at national and city levels are not displayed in the table; they reinforce April 2010 measures and over 10 major cities set upper limits on property units a household can purchase.
- Data sources used (selected)
  - Panel regression inputs: NDRC, NBS, PBOC, Shanghai Stock Exchange, CEIC, local government sources, staff estimates.
  - Asset pricing inputs: NDRC, Centaline, DTZ Property Research, CEIC, OECD.

### Conclusion
- Methods used: panel regression linking long-term fundamentals to prices; user-cost/rent-based benchmarks.
- Main conclusions
  - House prices were not significantly overvalued in China as a whole in 2010H1.
  - Mass-market in Shanghai and Shenzhen, and luxury in Beijing and Nanjing, showed signs of disconnection from fundamentals.
  - Housing correction risks concentrated on investment and local government revenue channels; consumption effects were limited.
  - Indicators of misalignment in China showed less persistence than in advanced economies before 2008 (e.g., U.S., New Zealand, France).
  - April 2010 policy measures appeared to have moderated price growth in some cities by 2010Q2, but lasting effectiveness was uncertain.
  - Addressing underlying structural drivers requires higher real interest rates, broader property taxation, and financial market development.

*Source: _wp10274 - REFERENCES (PDF).*

### References..............................................................................................................

### _wp10274 - References

### I. Introduction and objectives
- During 2009, China’s residential property market prices turned around and grew rapidly, especially in several large- and medium-sized cities, as the impact of the global financial crisis subsided and domestic financial conditions relaxed.
- Price-to-rent ratios rose to new highs, and price-income ratios started to rise, reversing a declining trend.
- The paper compares movements in China’s residential property prices with those implied by market fundamentals using two approaches:
  - A panel regression linking prices to long-term fundamentals.
  - A relationship between price, rent, and ownership cost.
- The paper uses the latter measure to characterize price deviations in comparator countries and to discuss similarities and differences with China.

### Major findings
- National valuation
  - As of mid-2010, house prices are not significantly overvalued in China as a whole.
- City- and segment-level misalignment
  - The mass-market segment in a number of coastal cities—most clearly in Shanghai and Shenzhen—as well as a few inland cities, may be in the early stages of excessive price growth.
  - Early signs of price misalignment can also be detected in the luxury segment in Beijing and Nanjing.
- Persistence of deviations
  - Deviations from benchmark prices appear not to be persistent with a half life of around 1quarter on average for overall China.
  - Comparators: Hong Kong SAR (2–4 quarters) and Singapore (5 quarters).
  - This contrasts with several industrial economies before 2008—especially the U.S., New Zealand, and France—where deviations tended to persist far longer and led to large and abrupt adjustments.
- Impact of April 2010 policy measures
  - Policy measures taken by the Chinese government in April 2010 appear to have had some impact on price growth.
  - Gaps between market and fundamentals-implied prices have become smaller in a few cities.
  - In some cities, notably the mass market segments in Guangzhou, Tianjin, and Shenzhen, prices recently seem to have remained persistently misaligned.

### Market dynamics, leverage, and macro-financial exposure
- Mortgage and loan growth
  - Real estate loan growth in the prior year reached an all-time high reflecting development of the new mortgage market.
  - Mortgage loan growth was nearly 50percent, raising mortgage debt from 10 to around 15percent of nominal GDP in one year.
  - By late 2009, loans to property developers and mortgages together accounted for about 20percent of total loans.
- Real activity exposure
  - Real estate investment accounts for about 20percent of total investment and around 9percent of GDP.
  - Land sales are an important revenue source for local governments; in Beijing and Zhejiang, land sales accounted for as much as 30percent of government general revenue in 2009.
- Consumption and broader impacts
  - Despite growing importance to the real economy, housing prices have had a somewhat limited impact on consumption.
  - Housing price developments could notably impact private investment and local government revenue, especially in cities with high real estate investment.
- Implications
  - Growing importance of property in real activity and increased banking sector exposure highlight the need for early warning measures of misalignment.

### Interpretation of the misalignment measure
- The benchmark in the asset pricing approach is linked to market rent and a set of fundamental factors, providing an early warning indicator of market exuberance comparable across cities and over time.
- This measure is a sufficient (but not necessary) condition for detecting misalignment; serious misalignment may only become apparent after substantial and abrupt price declines.
- The measure has identified historical episodes outside China, including Hong Kong SAR during 1997 and several advanced markets more recently.

### Policy discussion and recommendations
- Authorities’ capacity and risk assessment
  - Given authorities’ awareness and experience in containing excessive property price growth, the likelihood of financial instability precipitated by a housing price bust seems small.
- Structural drivers of rapid price growth
  - Structural factors that sustain propensity for rapid price growth include:
    - Structurally low real interest rates combined with rapid income and productivity growth.
    - Lack of property tax.
    - Increasing availability of mortgage financing.
    - Insufficient alternative investment vehicles.
- Policy options to limit propensity for property price inflation
  - Allow real interest rates to rise and respond more flexibly to macroeconomic conditions.
  - Implement a meaningful property tax.
  - Carefully monitor and react to rising leverage.
  - Maintain tight prudential standards, active monitoring of leverage, and robust financial sector supervision.
- Trade-offs
  - These policies carry some risk of asset price volatility during market adjustment, but failure to act increases the risk of a larger disconnect between asset prices and fundamentals.

### Data and scope notes
- China’s private residential property market is relatively new, existing for less than two decades at the time of study.
- Price changes 2004–09
  - NDRC: overall property prices in 35 cities approximately doubled during 2004–09.
  - NBS: reported prices in 70 cities increased by 31percent during the same period.
- Differences between NDRC and NBS data sources:
  - NDRC collects all transaction data available in 35 cities on all kinds of properties including residential and commercial buildings.
  - NBS takes 10,000 samples in 70 cities of newly constructed and secondary properties.
  - NBS data are mainly provided by real estate developers who may not necessarily report the truth of property market development.
- Historical policy actions
  - House prices rose from 2004 to 2007 until the government intervened by tightening loan-to-value ratios and raising mortgage interest rates throughout 2007.
  - In the wake of the global financial crisis, price-to-rent ratios fell but resumed increasing after credit conditions eased in late 2008 with measures to help first-time home buyers.

*Source: _wp10274 - References (excerpted content).*

### Appendix I for details). Price-to-rent ratios then reached their historical highs particularly in

### Appendix I for details). Price-to-rent ratios then reached their historical highs particularly in

### Price and rent trends
- Price-to-rent ratios reached historical highs particularly in larger cities such as Beijing, Shenzhen, and Shanghai.
- Relative to rent, housing prices have been rising faster in the mass market than in the luxury counterpart (notably observed in Shanghai).
- An average residential unit in China is now more expensive relative to rental costs than the same-sized units in comparator countries.
- Mortgage loan growth in 2009 was nearly 50 percent year-on-year, and mortgage loans rose from 10 to around 15 percent of nominal GDP in 2008.
- Despite rising house prices, housing affordability deterioration has been limited because of rapid growth in Chinese household disposable income and low costs of financing; however, price-to-income ratios in selected big cities stagnated since mid-2009 and started to rise, worsening affordability.

### Two empirical approaches to assess price misalignment
- Objective: gauge how far market prices deviate from levels supported by medium-term fundamentals and assess size and persistence of misalignment.
- Approaches used:
  - Panel regression (dynamic OLS) for 35 cities (2000Q1–2009Q4) to estimate long-term equilibrium property prices using determinants: real lending interest rate, population density, real GDP per capita, land prices, and Shanghai Composite stock index.
  - Asset pricing / user-cost approach comparing market prices with benchmark prices implied by rent and ownership cost (imputed rent = ownership cost in frictionless equilibrium).

### Panel regression results (Table 1 and key findings)
- Estimated coefficients (Coefficient, t-statistic):
  - Constant: 5.291, 31.461
  - Real interest rate: -0.020, -2.616
  - Real GDP per capita: 0.058, 2.179
  - Population density: 0.0002, 6.888
  - Land price: 0.001, 9.541
  - Stock price: 0.302, 8.976
- Key results:
  - Significant long-term determinants: real income per capita, real mortgage interest rate, wealth (Shanghai Composite market capitalization), past land prices, and urbanization/migration (population density).
  - Overall property prices roughly in line with long-term equilibrium before 2006.
  - Overvaluation signs in some large cities: Beijing, Shanghai, Shenzhen, Ningbo, Fuzhou, Xiamen, Wuhan, Kunming.
  - Undervaluation signs recently in cities including Nanjing, Hefei, Qingdao, Hohhot, Shenyang, Nanchang.

### Asset pricing (user-cost) approach and international comparators
- Benchmarking principle: annual market rent should equal annual cost of owning a property (user cost); deviations suggest potential overpayment and misalignment.
- Assumptions and parameter choices:
  - Risk-free rate: 5-year treasury bond yield (or equivalent).
  - Mortgage interest rate: nominal lending rate on housing loan (at least 5 years).
  - Maintenance/depreciation: constant annual depreciation rate of 2.5 percent.
  - Expected capital gains: average trend growth rates (a constant) representing “normal” expected future house price growth.
  - Risk premium: extracted from data assuming market price equals benchmark price on average; slow-moving component used.
- International evidence (Table 2, 2002Q4–peak):
  - US: Annual avg. price growth 5.9 percent; Annual avg. benchmark price growth 3.2 percent; Difference 2.6 percent per annum; Deviation at peak 8.7 percent of benchmark price; Quarter at peak 2006Q4.
  - France: 9.6 percent; 4.5 percent; 5.1 percent per annum; 24.3 percent; 2008Q1.
  - New Zealand: 11.3 percent; 6.4 percent; 4.9 percent per annum; 25.2 percent; 2007Q4.
  - UK: 6.6 percent; 6.0 percent; 0.6 percent per annum; 7.1 percent; 2008Q1.
  - Australia: 5.3 percent; 4.0 percent; 1.3 percent per annum; 10.0 percent; 2008Q2.
- The methodology captures large persistent pre-crisis deviations in known bubble cases (US, France, New Zealand).

### Findings from China’s asset-pricing analysis (mass market and high-end)
- Overall findings for 2010H1:
  - Overall real estate and overall residential market prices in China roughly aligned with benchmarks; prices rose alongside rents and falling user costs.
  - Mass-market house prices in Shanghai and Shenzhen, and luxury house prices in Beijing and Nanjing, were more than 10 percent away from benchmark levels in 2010H1, indicating potential early-stage excessive price growth.
  - Policy measures in April 2010 to cool markets were timely; by 2010Q2 price growth slowed and gaps narrowed in some cities.
- Persistence and half-life of deviations:
  - Overall China: estimated half life of deviation ≈ 1 quarter (estimated AR coefficient 0.32).
  - Beijing and Tianjin: deviations halve in around 1–2 quarters.
  - Shenzhen and Guangzhou: process could take roughly 4 quarters.
  - Shanghai: could take about 7 quarters.
  - Some cities (Guangzhou, Shenzhen, to some extent Tianjin) had deviations narrowed only by 2007 policy steps.
- Policy tightening in 2007 (e.g., lending rate multiplier from .85 to 1.1; down payment for second homes from 30 to 40 percent in 2007Q3) temporarily lowered prices or reduced inflation but did not change benchmark prices substantially.
- Sensitivity to user cost changes (Table 3):
  - Current User Cost (percent, approx.) and approximate decline in P/R multiples from a 1 percent increase in user cost:
    - Beijing: 2.0; 33.0
    - Hangzhou/Guangzhou/Shenzhen: 3.0; 25.0
    - Shanghai/Tianjin: 3.6; 21.0
    - Nanjing: 7.0; 11.0
- Coefficients of variation (Table 4) indicate prices are more volatile than rents in major cities (examples):
  - Beijing: C.V. (Rent) 0.11; C.V. (Price) 0.44
  - Shanghai: 0.06; 0.31
  - Shenzhen: 0.04; 0.44

### Mortgage market depth and growth (Table 5)
- Mortgage/NGDP (percent) and Average growth Rate (percent) for 2004–2007 and 2008–2009:
  - US: 76.1; 4.2 — 76.3; (no growth rate given for 2008–2009 in table fragment)
  - UK: 80.4; 5.4 — 89.4; 2.5
  - France/Spain: 42.6; 11.5 — 51.8; 4.5
  - Australia: 82.3; 5.0 — 91.8; 4.3
  - New Zealand: 81.7; 8.7 — 96.7; 4.4
  - China: 10.4; 2.4 — 11.8; 16.1
- China’s mortgage market expanded modestly until 2009, when mortgage loan to nominal GDP surged; continued growth at that magnitude could fuel further house price inflation and financial stability risks.

### Impact on real economy, banking sector, and government revenue
- Real economy:
  - Property price changes have limited impact on private consumption: a 10 percent drop in property prices likely induces a 0.7 percent fall in private consumption (provincial panel 1994–2008).
  - Investment is more sensitive: a 10 percent drop in property prices can decrease investment by about 4 percent.
  - Real estate FAI is a notable share of total FAI in some regions (e.g., around 50 percent in Beijing; less than 30 percent in Guangdong).
- Banking sector exposure:
  - Direct exposure (late 2009): mortgage loans and developer loans account for less than 20 percent of total outstanding loans in China, compared with 51.6 percent in Hong Kong SAR and 56.6 percent in the US.
  - Developers’ funding: self-raised capital, advanced payment, and other sources accounted for about 60 percent of developers’ total funding in the first quarter of 2010 in 40 major cities.
  - Indirect exposure via industrial linkages: cumulative input coefficients show strong links between construction and sectors such as metal smelting and rolling, non-metal mineral products, and chemicals; loans to sectors closely linked to property market accounted for about 24.0 percent of total loans in 2009.
  - Collateralized lending using property as collateral is significant anecdotally; property price corrections would reduce collateral values and hurt banks’ balance sheets if defaults occur.
- Government revenue:
  - Land sales revenue is an important extra-budgetary revenue source; share varies across provinces (examples: Chongqing’s land sales revenue > 30 percent of government general revenue; Shanghai’s < 10 percent in recent years).

### Policy implications
- No broad-based and significant over-valuation in China as a whole in 2010H1, but risks exist of deviations in large cities.
- Credit controls and regulatory measures can temporarily lower prices and affect expectations but do not directly change benchmark prices; market prices can re-accelerate.
- Structural drivers of high house price inflation:
  - Structurally low perceived cost of homeownership (negative real long-term interest rates for five quarters; real interest rate on 5-year Chinese government bond averaged 0.8 percent since 2001).
  - High saving rates and ample liquidity.
  - Lack of alternative investment vehicles and absence of a broad-based property tax.
  - High propensity among households to buy rather than rent; lower risk premium for owning.
- Recommended structural policies to reduce risk of disorderly adjustment:
  - Raise real interest rates.
  - Impose a meaningful property tax to increase carrying cost of homeownership.
  - Ensure leverage does not accelerate (monitor and manage loan-to-value dynamics).
  - Broaden financial market development to provide alternative investment vehicles to housing.
- Note: Calibrated moves (e.g., higher real rates or tax changes) carry risk of precipitating asset price adjustment but can lower the probability of disorderly falls if well designed.

### Conclusion
- Methods: panel regression linking long-term fundamentals to prices; user-cost/rent-based benchmarks.
- Main conclusions:
  - House prices not significantly overvalued in China as a whole in 2010H1.
  - Mass-market in Shanghai and Shenzhen, and luxury in Beijing and Nanjing, show signs of disconnection from fundamentals.
  - Housing correction risks concentrated on investment and local government revenue channels; consumption effects are limited.
  - Indicators of misalignment in China show less persistence than in advanced economies before 2008 (e.g., U.S., New Zealand, France).
  - April 2010 policy measures appear to have moderated price growth in some cities by 2010Q2, but lasting effectiveness is uncertain.
  - Addressing underlying structural drivers requires higher real interest rates, broader property taxation, and financial market development.

*Sources: CEIC Data Company Ltd.; NDRC; NBS; DTZ Property Research; OECD; and authors’ calculations.*

### REFERENCES

### _wp10274 - REFERENCES

### References (selected)
- Dai, S., 2009, “Research on land finance and the usage of the landof local government,” Journal of Fujian Normal University(Philosophyand Social Science Edition), No. 4, General No.157.
- Fostel, A., and J. Geanakoplos, 2008, “Leverage cycles and the anxious economy,” American Economic Review98:4, pp. 1211-1244.
- Geanakoplos, J., 2010, “The leverage cycle,” Cowles Foundation Discussion Paper No. 1715R, Yale University, New Haven, (January).
- Geanakoplos, J., 2010, “Solving the present crisis and managing the leverage cycle,” Cowles Foundation Discussion Paper No. 1751, Yale University, New Haven, (January).
- Glindro, E. T, T. Subhanij, J. Szeto, and H. Zhu, 2008, “Determinants of house pries in nine Asia-Pacific economies,” BIS Working Paper No.263.
- Ha, J., and Z. Zhang, 2010, “The prospect of the Renminbi and its impact on various industries”, China International Capital Corporation Ltd, Macroeconomic Report, 22 (March), in Chinese.
- Harding, J., S. Rosenthal, and C. Sirmans, 2007, “Depreciation of housing capital, maintenance and house price inflation: Estimates from a repeat sales model,” Journal of urban Economics, 61:2, (March), pp. 193-217.
- He, D., W. Zhang, and J. Shek, 2007, “How efficient has been China’s investment? Empirical evidence from national and provincial data,” Pacific Economic Review, 12(5), 597-617.
- Himmelberg, C., C. Mayer, and T. Sinai, 2005, “Assessing high house prices: Bubbles, fundamentals and misperceptions,” Journal of Economic Perspective, 19:4, Fall, pp. 67-92.
- Hong Kong Property Review, 2010, Rating and Valuation Department, the Government of Hong Kong SAR.
- Hui, H., 2009, “The impact of property market developments on the real economyof Malaysia,” International Research Journal of Finance and Economics, Issue 30.
- IMF, 2003, “When bubbles burst,” in World Economic OutlookApril 2003: Growth and Institutions, World Economic and Financial Surveys, International MonetaryFund, Chapter 2.
- Leung, C., and L. Liu, 2005, “An empirical analysis of the fair value of Hong Kong’s residential propertyprices,” HKMA Research Memorandum.
- Leung, F., K. Chow, and G. Han, 2008, “Long-term and short-term determinants of property prices in Hong Kong,” the Hong Kong MonetaryAuthorityWorking Paper 15/2008.
- Meng, N., 2001, “Private residential propertymarket and the macro-economy,” Economic Survey of Singapore.
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### Appendix: Selected Real Estate Measures in China — Policy timeline
- Tightening measures
  - Jan 2007: Impose value-added taxes on land transactions.
  - Sep-2007: Raise the minimum down payment ratio to 40percent and the minimum mortgage rate to 110percent of the benchmark rate for second mortgage.
    - Minimum down payment ratio and mortgage rates are higher for third mortgage loans.
  - Apr-2008: Impose tax on capital gains on advanced payments of housing purchases.
  - Jun-2008: Impose personal income taxes on corporate purchasing properties for individuals.
  - Aug-2008: Forbid loans for land purchases and for idle projects.
- Supportive policies
  - Oct-2008:
    - Waive stamp duty on housing transactions and value added taxes on land transactions.
    - Lower the minimum mortgages rate to 70percent of the benchmark rate and the down-payment ratio to 20percent.
  - Dec-2008:
    - Extend preferential policies for first home purchases to second home purchases.
    - Shorten the housing holding period to enjoy business tax exemption from 5 years to 2 years.
  - May-2009: Reduce developers' capital requirement for economic and commodity housing investment to 20percent.
- Tightening measures (continued)
  - Dec-2009:
    - Extend the housing holding period to enjoy business tax exemption from 2 years to 5 years.
    - Require developers to pay at least 50percent as the initial payment for land purchase.
  - Jan-2010: Set minimum down-payment ratio for the second mortgages at 40percent.
  - Apr-2010:
    - Raise minimum down-payment ratio for the first mortgage to 30percent for a residential property no more than 90 square meters.
    - Raise the down-payment ratio for the second mortgage to 50percent, and the minimum rate to 110percent of the benchmark rate.
    - The down-payment ratio and minimum mortgage rate for the third mortgage and above will be much higher.
    - Restrict mortgage lending to non-residents.
    - Increase land supply for residential properties.
- Note:
  - 1/ Some tightening measures launched in September and October 2010 in national and city levels are not displayed in the table. Basically, these measures reinforce those introduced in April 2010. In addition, more than 10 major cities (i.e., Beijing, Shanghai, Hangzhou, Guangzhou, Shenzhen, Nanjing, Ningbo, Fuzhou, Xiamen, Tianjin, Haikou, and Sanya) have set the upper limits of property units a household can purchase.

### Table A1: Description of data used in panel regression (series and sources)
- Real property price
  - Source: NDRC, NBS, staff estimates
  - Data structure: Nominal price deflated by city-specific CPI
- Real GDP
  - Source: NBS, staff estimates
  - Data structure: Nominal GDP deflated by city-specific CPI
- Real interest rate
  - Source: PBOC, staff estimates
  - Data structure: Nominal lending rate for over 5 years - national level inflation rate
- Land price index
  - Source: NBS
  - Data structure: 1998=100.
- Population density
  - Source: NBS, Local government website, Staff estimates
  - Data structure: Resident population divided by the size of a city.
    - Subordinate prefectures and counties of a city but far way from the urban area are excluded from the calculation. Owing to the annual population data, density is the same for four quarters in the same year.
- Stock index
  - Source: Shanghai Stock Exchange
- Real final consumption
  - Source: NBS
  - Data structure: Nominal final consumption deflated by city-specific CPI
- Real fixed asset investment
  - Source: NBS, staff estimates
  - Data structure: Fitted value obtained by regressing actaul real fixed asset investment (FAI) on real gross capital formation (GCF), where real FAI and GCF are obtained by deflating nominal FAI and nominal GCF by investment deflator.
- Real cost of capital
  - Source: PBOC, NBS, Staff estimates
  - Data structure: Real interest rates + depreciation rate - growth rate differentials between investment deflator and GDP deflator) * investment deflator relative to GDP deflator/ (1 - tax rate).

### Table A2: Sources of data used in the asset pricing approach
- 1. Industrial countries
  - House price and rent: OECD
  - Income, interest rates, household size: CEIC
- 2. China
  - Mass market, house price: NDRC
  - Mass market, rent: Centaline
  - Luxury segment, house price: DTZ Property Research and NBS
  - Luxury segment, rent: DTZ Property Research and NBS
  - Income, interest rates, household size: CEIC
- 3. Hong Kong SAR
  - CEIC
  - Private residential flat completion: Housing Department, Government of Hong Kong SAR
- 4. Singapore (all data)
  - CEIC

*Source: _wp10274 - REFERENCES (PDF).*

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_Source: https://www.imf.org/-/media/websites/imf/imported-full-text-pdf/external/pubs/ft/wp/2010/_wp10274.pdf_