## wp17248

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### Role and size of real estate in the economy
- Real estate investment rose from about 4 percent of GDP in 1997 to the peak of 15 percent of GDP in 2014; residential investment accounts for over two thirds of total real estate investment.
- Bank lending to the sector makes up 25 percent of total bank loans and about half of all new loans in 2016.
- Real estate–related upstream and downstream linkages account for about a quarter of GDP.
- Land sales accounted for about 30 percent of local government revenue in 2016; general government net spending financed by land sales is about 9 percent of the headline revenue in 2016.
- Government subsidies on social housing totaled nearly 6 million apartment units in 2015-2017.

### Heterogeneity across city tiers and recent cycle dynamics
- Top-tier cities show pronounced price volatility but small share of inventory and investment; smaller cities constitute over half of residential real estate investment with much lower price increases during 2013-16.
- Nationwide 70-city new residential property price: up about 10 percent y/y in nominal terms in June 2017 (8.5 percent in real terms, 13 percent weighted by population, and 16 percent weighted by sales value at city-tier levels).
- Tier-1 cities experienced price surges as high as 55 percent y/y in early 2016; tier-2 cities saw nearly 20 percent y/y at the peak.
- Property sales rose 22.5 percent y/y in 2016 and 16 percent in the first half of 2017.
- Total sales in the easing cycle reached near 1.6 billion square meters since May 2015, versus 1.3 billion in 2012-13.
- Real estate investment trough was 1.2 percent y/y in December 2015; overall real estate investment stands at about 10 percent of GDP (below the 15 percent 2014 peak).
- Nationwide housing inventory ratio declined sharply to about 18-20 months from 30 months at the 2014 peak; inventory ratio fell from a peak of 3½-4 years to about 2½-3 years as of the first half of 2017, with unsold floor space remaining high in absolute terms.
- Land sales volume by local governments to residential developers contracted by half since 2014 (floor space measure), despite a recent recovery in land sales value.

### Credit, leverage, and signs of speculation
- Mortgage share in total new bank loans rose from 20-30 percent in 2013-2015 to nearly 50 percent in 2016.
- Annual growth rate of mortgage loans rose from 17 percent in 2014 to 35 percent y/y.
- Down payment patterns: 40 percent of buyers of a first home have a down payment ratio of 25 percent or higher.
- Average loan-to-value ratio (net new mortgage to property sales ratio) increased from less than 15 percent in 2012 to 48 percent in 2016.
- Household debt rose from less than 20 percent of GDP in 2008 to 46 percent by end-2016; mortgages account for more than half of outstanding household debt.
- Emerging speculation: about 18 percent of residential home sales in 2016 were related to investment demand (second homes), versus 6-10 percent between 2012-2015; implies about 10-15 percent of new mortgage borrowing are from buyers of second homes.
- Effective mortgage rate was 4.49 percent (and 5.4 percent for second-home buyers) in March 2017, about 160 basis points lower than in early 2014.

### Recent policy tightening and observed effects
- Key measures (differentiated across cities):
  - Tighter down-payment requirements: several tier-1 and 2 cities set minimum down payments at least 30 percent and often 50-70 percent for second homes.
  - Home purchase restrictions for non-local residents and for second/third homes in tier-1 and tier-2 markets.
  - Financing restrictions: limits on shadow funds and informal lending to developers/down payments; tightened bond issuance for developers; window guidance to banks to limit mortgage lending and enforce down payment and collateral requirements.
  - Land supply measures: tightened bidding rules, higher deposits, measures to prevent hoarding; some cities considered targeted land-use flexibility.
  - Public messaging to anchor expectations and warn of real estate market bubble.
- Observed impacts:
  - Moderation in sequential month-on-month price rises, new mortgage loans, and real estate sales.
  - Empirical analysis indicates changes to down payment requirements have been effective in dampening price cycles.

### Risks of a housing market correction — magnitudes and channels
- Price deviation: nationwide house prices deviate about 5 percent from long-term trend (HP filter); large tier-1 cities deviate about 10-15 percent.
- Affordability: price-to-income ratios in large cities at over 15-25 times city-level disposable household income; national average price-to-income ratios have been declining since 2010 and are about half of large cities; rental yields in tier-1 cities are low at less than 3 percent.
- Debt servicing: effective mortgage rate 4.49 percent (5.4 percent for second-home buyers) in March 2017; 160 basis points lower than early 2014 — aggregate buffers may mask deterioration for new buyers in top-tier cities.

Scenario of a correction and macro impacts:
- A correction of house prices by 10-15 percent (from currently 5 percent above long-term trend to about 5 to 10 percent below trend) could:
  - Real estate investment: potentially slow fixed asset investment by about 11 percentage points or about 6 percent in growth of real estate gross fixed capital formation in national accounts.
  - GDP: residential real estate contributes roughly 9½ percent of GDP; deceleration of real estate investment growth alone could reduce GDP growth by 0.6 percentage points.
  - Private consumption: price correction of 10-15 percent likely subtract 0.1-0.2 percentage points from growth in 2017-18; combined with investment impact could reduce growth by some 0.9 percentage points.
  - Fiscal: weaken local government finances heavily due to reliance on land sales; tighter local spending would have knock-on effects on growth.
  - Capital flows: weakening property returns could trigger capital outflows as households shift to foreign assets, adding depreciation pressures.

Financial stability channels and vulnerabilities:
- Banking sector exposure: household mortgages and loans to property developers represent a total of 15 percent of bank assets; corporate loans collateralized by property or land make up another 10 percent of bank assets.
  - Mortgage delinquency risk: mortgage credit has increased sharply relative to property sales; mortgage default rate historically low; all household mortgages are recourse loans.
  - Collateral devaluation and concentration risks: top five provinces account for 44 percent of national property sales.
  - Liquidity pressures: capital outflows could strain banks and bank-sponsored WMPs, unravelling maturity transformation.
- Shadow banking: shadow products exposed to property may face redemptions and defaults, cascading liquidity stress through the intermediation ladder; risks from informal channels financing down payments.
- Real estate developers:
  - Smaller developers are particularly leveraged, funding land purchases with borrowed funds from shadow banks; Deutsche Bank sensitivity: a 10 percent decline in housing sales raises debt-to-EBITDA of lowest-quartile developers by 14 percentage points to 74 percent, versus 2 percentage points for top quartile.
  - Large developers face refinancing pressures: onshore and offshore bond maturities rise from $5 billion in 2017 to $10 billion in 2018 and $30 billion by 2020; RMB depreciation would increase refinancing costs.
- Expected outcome: increased impaired loans and deterioration of profitability and capitalization for financial institutions; weakest links likely highly leveraged small developers and small city-level banks exposed to weak developers.

### Other impacts and feedback loops
- Social: housing is about 60 percent of household wealth; boom-bust could disproportionately hurt low-income groups, cause job losses in low-skill construction, increase delinquency among marginal young buyers, intensify income inequality and slow rebalancing.
- Feedback loop: rising collateral boosts lending and demand; busts reverse the loop with amplified real economy and asset quality effects. Government retains significant control and likely to stabilize markets if needed.

### Policy implications and recommendations
- General stance: smooth deflation of real estate market while containing risky mortgage lending; macro-prudential measures are broadly appropriate and effective ex-ante.
- Continue differentiated, local-condition–tailored macro-prudential policies (LTV/minimum down payments) as first line of defense; empirical evidence confirms down payment changes (especially for second homes) reduce price cycles.
- Expand macro-prudential toolkit:
  - Active use of DSTI (debt servicing to income) caps to ensure affordability and restrain use of unsecured loans to meet down payments; adjust CBRC 2004 guidelines (previously monthly mortgage payment to income <50 percent and monthly total debt payment to income <55 percent) toward international norm of 30-50 percent and extend caps to loans from non-bank financial institutions.
  - Calibrate DSTI to account for adverse distributional impacts on younger and poorer households; use stress testing of household debt servicing capacity to interest rate and income shocks.
  - Consider sectoral capital requirements (risk weights or LGD floors) on banks’ exposures to real estate, tightened during booms to raise cost of funding for developers and build buffers; note potential for arbitrage to nonbanks and limited effectiveness for large developers reliant less on bank funding.
- Strengthen data collection and monitoring:
  - Collect granular indicators: distribution of mortgage loans by LTV and borrower characteristics, borrowers’ debt servicing capacity, cross-sectional NPL differences, shares of banks’ and nonbanks’ loans to real estate and households, qualitative indicators on financial sector risk-taking.
- Reduce reliance on administrative measures over medium term:
  - Administrative tools (purchase restrictions, funding restrictions) can be effective short-term but risk abrupt distortions and circumvention and can disproportionately harm migrants and urbanization efforts.
- Fiscal/tax measures:
  - Use taxes on housing transactions and capital gains to dampen speculation.
  - Introduce recurrent property taxes gradually (decisively) by resolving property registration and legislative hurdles; benefits include dampening house price volatility and creating a more sustainable revenue base.

### Fiscal findings and implications (recurrent property taxes)
- Introduction of recurrent property taxes can provide revenue sources for local governments to finance local public services and avoid excessive dependence on (volatile) land sales, which in turn would dampen the adverse effects of boom bust cycles in real estate.
- A (partial) decoupling of the house prices and local government financing is also likely to change households’ expectation that the housing market is “too important to fail”.
- Overall fiscal policy should support ongoing rebalancing efforts while gradually reducing the “augmented” deficit to its debt stabilizing level (IMF 2017).

### Structural policies and macro-financial framework
- More focus on increasing real estate supply at a pace commensurate with that of demand, especially in higher tier cities where incomes and productivity growth is highest, is welcome.
- Increasing land supply and building higher-density housing in major cities can attract migrants and facilitate a smooth transition in the housing market.
- Complementary reforms:
  - Reforms on social security and household registration (hukou) to give migrants from the rural area full access to public services.
  - Reducing China’s very high level of domestic savings and gradually opening up the capital account in a well-sequenced and phased manner appropriately in tandem with other reforms to help reduce the propensity for asset price inflation/boom-bust cycles.
  - Greater exchange rate flexibility and a stronger monetary policy framework are essential.
- Policy stance on growth targets:
  - Move away from the practice of setting annual growth targets that has fostered an undesirable focus on short-term, low-quality stimulus measures.
  - Diminishing the importance of growth targets would align real estate dynamics more closely to fundamental demand and supply conditions and allow prudential policies to play the major role in guarding against macro-financial risks.
- Population density note:
  - The first tier cities have population density varying from 1,000 to 2,000 people per square kilometer in 2010, whereas the top 100 American MSAs (metropolitan statistical area) all have density above 4,000 people per square kilometer (Glaeser et al 2016).

### Empirical results (selected panel regression and diagnostics)
- Selected coefficient estimates from Table 4 (Dependent variable: real residential house prices, change):
  - Affordabilty, lagged: -0.1419**, -0.1568***, -0.1726***, -0.2117***
  - Income per capita, change: 0.0225, 0.0126, 0.0225, 0.1424**
  - Working age population, change: 0.0228, -0.0350, -0.0231, -0.0009
  - Bank credit, change: 0.0938, 0.0905*, 0.0900*, 0.0476
  - Downpayment ratios, change, lagged: -0.0709*, -0.0431, -0.0221, -0.1313
  - Interacted with Tier-1 dummy: -0.3528***, -0.4680***, -0.4369***
  - Interacted with Tier-2 dummy: -0.0252, -0.0283, -0.0503**
  - Land supply per capita, change, lagged: -0.0023, -0.0023, -0.0055*, -0.0020
  - Interacted with Tier-1 dummy: 0.0850***, 0.0621**
  - Local mortgage rate, change: 0.0107, 0.0121**, 0.0116**, -0.0029
  - Local government fiscal balance, change: -0.4279, -0.3997, -0.4450, 0.0065
  - Stock prices, change: 0.0744***, 0.0724***, 0.0706***
  - RMB per USD, change: -2.0645***, -2.1142***, -2.1473***
  - Interbank interest rate, change: -0.0170, -0.0194*, -0.0230***
  - Dummy for housing cycle: -0.0661***, -0.0652***, -0.0635***
  - Constant: -0.7315, -0.8016***, -0.8748***, -1.0282***
- Year dummies (selected coefficients):
  - 2008-0.0701***; 2009-0.0918**; 2010-0.0897***; 2011-0.0916***; 2012-0.1548***; 2013-0.1071***; 2014-0.2207***; 2015-0.2289***
- Model fit and sample:
  - R-sq (overall): 0.2974, 0.3086, 0.3026, 0.3928
  - Number of obs: 418
  - Number of groups: 68
- Significance notation:
  - ***, **, * denote significance at the 1, 5, and 10 percent level, respectively.

### Data sources, limitations, and coverage
- National Bureau of Statistics (NBS):
  - Commodity Building Residential Selling Price index is based on aggregate sales value divided by total floor space sold during a period; index only consists of provincial level data without individual city information and therefore tends to understate the increase in house prices.
  - NBS also released the price indices for 70 major cities for newly-constructed homes, which tend to under-represent smaller tier-3 and 4 cities.
  - Similar limitations exist for aggregate inventory data (unsold floor space) (Chivakul and others 2015).
- Local housing bureaus:
  - Local government divisions in charge of city-level real estate market under the Ministry of Housing and Urban-Rural Development; responsible for registration of real estate sales, leases, mortgages, and transfers.
  - Their data tend to be more accurate based on actual transactions for purchases and sales of newly built residential units and cover a more balanced sample with about 134 cities, grouped into four tiers based on the official definition (4 tier-1 cities, 36 tier-2 cities, and the rest are small tier-3 and 4 cities).

*Source: IMF working paper "2016. As signs of overheating emerged, the government turned to tighten real estate markets" (wp17248)*

### 2016. As signs of overheating emerged, the government turned to tighten real estate markets

### 2016. As signs of overheating emerged, the government turned to tighten real estate markets

### Role and size of real estate in the economy
- Real estate investment rose from about 4 percent of GDP in 1997 to the peak of 15 percent of GDP in 2014; residential investment accounts for over two thirds of total real estate investment.
- Bank lending to the sector makes up 25 percent of total bank loans and about half of all new loans in 2016.
- Real estate–related upstream and downstream linkages account for about a quarter of GDP.
- Land sales accounted for about 30 percent of local government revenue in 2016; general government net spending financed by land sales is about 9 percent of the headline revenue in 2016.
- Government subsidies on social housing totaled nearly 6 million apartment units in 2015-2017.

### Heterogeneity across city tiers and recent cycle dynamics
- Top-tier cities show pronounced price volatility but small share of inventory and investment; smaller cities constitute over half of residential real estate investment with much lower price increases during 2013-16.
- Nationwide 70-city new residential property price: up about 10 percent y/y in nominal terms in June 2017 (8.5 percent in real terms, 13 percent weighted by population, and 16 percent weighted by sales value at city-tier levels).
- Tier-1 cities experienced price surges as high as 55 percent y/y in early 2016; tier-2 cities saw nearly 20 percent y/y at the peak.
- Property sales rose 22.5 percent y/y in 2016 and 16 percent in the first half of 2017.
- Total sales in the easing cycle reached near 1.6 billion square meters since May 2015, versus 1.3 billion in 2012-13.
- Real estate investment trough was 1.2 percent y/y in December 2015; overall real estate investment stands at about 10 percent of GDP (below the 15 percent 2014 peak).
- Nationwide housing inventory ratio declined sharply to about 18-20 months from 30 months at the 2014 peak; inventory ratio fell from a peak of 3½-4 years to about 2½-3 years as of the first half of 2017, with unsold floor space remaining high in absolute terms.
- Land sales volume by local governments to residential developers contracted by half since 2014 (floor space measure), despite a recent recovery in land sales value.

### Credit, leverage, and signs of speculation
- Mortgage share in total new bank loans rose from 20-30 percent in 2013-2015 to nearly 50 percent in 2016.
- Annual growth rate of mortgage loans rose from 17 percent in 2014 to 35 percent y/y.
- Down payment patterns: 40 percent of buyers of a first home have a down payment ratio of 25 percent or higher.
- Average loan-to-value ratio (net new mortgage to property sales ratio) increased from less than 15 percent in 2012 to 48 percent in 2016.
- Household debt rose from less than 20 percent of GDP in 2008 to 46 percent by end-2016; mortgages account for more than half of outstanding household debt.
- Emerging speculation: about 18 percent of residential home sales in 2016 were related to investment demand (second homes), versus 6-10 percent between 2012-2015; implies about 10-15 percent of new mortgage borrowing are from buyers of second homes.
- Effective mortgage rate was 4.49 percent (and 5.4 percent for second-home buyers) in March 2017, about 160 basis points lower than in early 2014.

### Recent policy tightening and observed effects
Key measures (differentiated across cities):
- Tighter down-payment requirements: several tier-1 and 2 cities set minimum down payments at least 30 percent and often 50-70 percent for second homes.
- Home purchase restrictions for non-local residents and for second/third homes in tier-1 and tier-2 markets.
- Financing restrictions: limits on shadow funds and informal lending to developers/down payments; tightened bond issuance for developers; window guidance to banks to limit mortgage lending and enforce down payment and collateral requirements.
- Land supply measures: tightened bidding rules, higher deposits, measures to prevent hoarding; some cities considered targeted land-use flexibility.
- Public messaging to anchor expectations and warn of real estate market bubble.

Observed impacts:
- Moderation in sequential month-on-month price rises, new mortgage loans, and real estate sales.
- Empirical analysis indicates changes to down payment requirements have been effective in dampening price cycles.

### Risks of a housing market correction — magnitudes and channels
- Price deviation: nationwide house prices deviate about 5 percent from long-term trend (HP filter); large tier-1 cities deviate about 10-15 percent.
- Affordability: price-to-income ratios in large cities at over 15-25 times city-level disposable household income; national average price-to-income ratios have been declining since 2010 and are about half of large cities; rental yields in tier-1 cities are low at less than 3 percent.
- Debt servicing: effective mortgage rate 4.49 percent (5.4 percent for second-home buyers) in March 2017; 160 basis points lower than early 2014 — aggregate buffers may mask deterioration for new buyers in top-tier cities.

Scenario of a correction and macro impacts:
- A correction of house prices by 10-15 percent (from currently 5 percent above long-term trend to about 5 to 10 percent below trend) could:
  - Real estate investment: potentially slow fixed asset investment by about 11 percentage points or about 6 percent in growth of real estate gross fixed capital formation in national accounts.
  - GDP: residential real estate contributes roughly 9½ percent of GDP; deceleration of real estate investment growth alone could reduce GDP growth by 0.6 percentage points.
  - Private consumption: price correction of 10-15 percent likely subtract 0.1-0.2 percentage points from growth in 2017-18; combined with investment impact could reduce growth by some 0.9 percentage points.
  - Fiscal: weaken local government finances heavily due to reliance on land sales; tighter local spending would have knock-on effects on growth.
  - Capital flows: weakening property returns could trigger capital outflows as households shift to foreign assets, adding depreciation pressures.

Financial stability channels and vulnerabilities:
- Banking sector exposure: household mortgages and loans to property developers represent a total of 15 percent of bank assets; corporate loans collateralized by property or land make up another 10 percent of bank assets.
  - Mortgage delinquency risk: mortgage credit has increased sharply relative to property sales; mortgage default rate historically low; all household mortgages are recourse loans.
  - Collateral devaluation and concentration risks: top five provinces account for 44 percent of national property sales.
  - Liquidity pressures: capital outflows could strain banks and bank-sponsored WMPs, unravelling maturity transformation.
- Shadow banking: shadow products exposed to property may face redemptions and defaults, cascading liquidity stress through the intermediation ladder; risks from informal channels financing down payments.
- Real estate developers:
  - Smaller developers are particularly leveraged, funding land purchases with borrowed funds from shadow banks; Deutsche Bank sensitivity: a 10 percent decline in housing sales raises debt-to-EBITDA of lowest-quartile developers by 14 percentage points to 74 percent, versus 2 percentage points for top quartile.
  - Large developers face refinancing pressures: onshore and offshore bond maturities rise from $5 billion in 2017 to $10 billion in 2018 and $30 billion by 2020; RMB depreciation would increase refinancing costs.
- Expected outcome: increased impaired loans and deterioration of profitability and capitalization for financial institutions; weakest links likely highly leveraged small developers and small city-level banks exposed to weak developers.

Other impacts and feedback loops
- Social: housing is about 60 percent of household wealth; boom-bust could disproportionately hurt low-income groups, cause job losses in low-skill construction, increase delinquency among marginal young buyers, intensify income inequality and slow rebalancing.
- Feedback loop: rising collateral boosts lending and demand; busts reverse the loop with amplified real economy and asset quality effects. Government retains significant control and likely to stabilize markets if needed.

### Policy implications and recommendations
- General stance: smooth deflation of real estate market while containing risky mortgage lending; macro-prudential measures are broadly appropriate and effective ex-ante.
- Continue differentiated, local-condition–tailored macro-prudential policies (LTV/minimum down payments) as first line of defense; empirical evidence confirms down payment changes (especially for second homes) reduce price cycles.
- Expand macro-prudential toolkit:
  - Active use of DSTI (debt servicing to income) caps to ensure affordability and restrain use of unsecured loans to meet down payments; adjust CBRC 2004 guidelines (previously monthly mortgage payment to income <50 percent and monthly total debt payment to income <55 percent) toward international norm of 30-50 percent and extend caps to loans from non-bank financial institutions.
  - Calibrate DSTI to account for adverse distributional impacts on younger and poorer households; use stress testing of household debt servicing capacity to interest rate and income shocks.
  - Consider sectoral capital requirements (risk weights or LGD floors) on banks’ exposures to real estate, tightened during booms to raise cost of funding for developers and build buffers; note potential for arbitrage to nonbanks and limited effectiveness for large developers reliant less on bank funding.
- Strengthen data collection and monitoring:
  - Collect granular indicators: distribution of mortgage loans by LTV and borrower characteristics, borrowers’ debt servicing capacity, cross-sectional NPL differences, shares of banks’ and nonbanks’ loans to real estate and households, qualitative indicators on financial sector risk-taking.
- Reduce reliance on administrative measures over medium term:
  - Administrative tools (purchase restrictions, funding restrictions) can be effective short-term but risk abrupt distortions and circumvention and can disproportionately harm migrants and urbanization efforts.
- Fiscal/tax measures:
  - Use taxes on housing transactions and capital gains to dampen speculation.
  - Introduce recurrent property taxes gradually (decisively) by resolving property registration and legislative hurdles; benefits include dampening house price volatility and creating a more sustainable revenue base.

_Italic_ Source: IMF working paper "2016. As signs of overheating emerged, the government turned to tighten real estate markets" (wp17248)

### introduction of recurrent property taxes can provide revenue sources for local governments to

### wp17248 - introduction of recurrent property taxes can provide revenue sources for local governments to

### Fiscal findings and implications
- Introduction of recurrent property taxes can provide revenue sources for local governments to finance local public services and avoid excessive dependence on (volatile) land sales, which in turn would dampen the adverse effects of boom bust cycles in real estate.
- A (partial) decoupling of the house prices and local government financing is also likely to change households’ expectation that the housing market is “too important to fail”.
- Overall fiscal policy should support ongoing rebalancing efforts while gradually reducing the “augmented” deficit to its debt stabilizing level (IMF 2017).

### Structural policies and macro-financial framework
- More focus on increasing real estate supply at a pace commensurate with that of demand, especially in higher tier cities where incomes and productivity growth is highest, is welcome.
- Increasing land supply and building higher-density housing in major cities can attract migrants and facilitate a smooth transition in the housing market.
- Complementary reforms:
  - Reforms on social security and household registration (hukou) to give migrants from the rural area full access to public services.
  - Reducing China’s very high level of domestic savings and gradually opening up the capital account in a well-sequenced and phased manner appropriately in tandem with other reforms to help reduce the propensity for asset price inflation/boom-bust cycles.
  - Greater exchange rate flexibility and a stronger monetary policy framework are essential.
- Policy stance on growth targets:
  - Move away from the practice of setting annual growth targets that has fostered an undesirable focus on short-term, low-quality stimulus measures.
  - Diminishing the importance of growth targets would align real estate dynamics more closely to fundamental demand and supply conditions and allow prudential policies to play the major role in guarding against macro-financial risks.
- Population density note:
  - The first tier cities have population density varying from 1,000 to 2,000 people per square kilometer in 2010, whereas the top 100 American MSAs (metropolitan statistical area) all have density above 4,000 people per square kilometer (Glaeser et al 2016).

### Empirical results (selected panel regression and model diagnostics)
- Selected coefficient estimates from Table 4 (Dependent variable: real residential house prices, change):
  - Affordabilty, lagged: -0.1419**, -0.1568***, -0.1726***, -0.2117***
  - Income per capita, change: 0.0225, 0.0126, 0.0225, 0.1424**
  - Working age population, change: 0.0228, -0.0350, -0.0231, -0.0009
  - Bank credit, change: 0.0938, 0.0905*, 0.0900*, 0.0476
  - Downpayment ratios, change, lagged: -0.0709*, -0.0431, -0.0221, -0.1313
  - Interacted with Tier-1 dummy: -0.3528***, -0.4680***, -0.4369***
  - Interacted with Tier-2 dummy: -0.0252, -0.0283, -0.0503**
  - Land supply per capita, change, lagged: -0.0023, -0.0023, -0.0055*, -0.0020
  - Interacted with Tier-1 dummy: 0.0850***, 0.0621**
  - Local mortgage rate, change: 0.0107, 0.0121**, 0.0116**, -0.0029
  - Local government fiscal balance, change: -0.4279, -0.3997, -0.4450, 0.0065
  - Stock prices, change: 0.0744***, 0.0724***, 0.0706***
  - RMB per USD, change: -2.0645***, -2.1142***, -2.1473***
  - Interbank interest rate, change: -0.0170, -0.0194*, -0.0230***
  - Dummy for housing cycle: -0.0661***, -0.0652***, -0.0635***
  - Constant: -0.7315, -0.8016***, -0.8748***, -1.0282***
- Year dummies (selected coefficients): 
  - 2008-0.0701***; 2009-0.0918**; 2010-0.0897***; 2011-0.0916***; 2012-0.1548***; 2013-0.1071***; 2014-0.2207***; 2015-0.2289***
- Model fit and sample:
  - R-sq (overall): 0.2974, 0.3086, 0.3026, 0.3928
  - Number of obs: 418
  - Number of groups: 68
- Significance notation:
  - ***, **, * denote significance at the 1, 5, and 10 percent level, respectively.

### Data sources, limitations, and coverage
- National Bureau of Statistics (NBS):
  - Commodity Building Residential Selling Price index is based on aggregate sales value divided by total floor space sold during a period; index only consists of provincial level data without individual city information and therefore tends to understate the increase in house prices.
  - NBS also released the price indices for 70 major cities for newly-constructed homes, which tend to under-represent smaller tier-3 and 4 cities.
  - Similar limitations exist for aggregate inventory data (unsold floor space) (Chivakul and others 2015).
- Local housing bureaus:
  - Local government divisions in charge of city-level real estate market under the Ministry of Housing and Urban-Rural Development; responsible for registration of real estate sales, leases, mortgages, and transfers.
  - Their data tend to be more accurate based on actual transactions for purchases and sales of newly built residential units and cover a more balanced sample with about 134 cities, grouped into four tiers based on the official definition (4 tier-1 cities, 36 tier-2 cities, and the rest are small tier-3 and 4 cities).

*Source: wp17248 - introduction of recurrent property taxes can provide revenue sources for local governments to (IMF working paper content).*

---


_Source: https://www.imf.org/-/media/files/publications/wp/2017/wp17248.pdf_