People’s Republic of China: Selected Issues
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The Chinese authorities have taken resolute actions to address the risks from the property sector since the start of the pandemic. The key chaiienge now is to smooth the transition of the sector to a smaller, more sustainable size amid unresolved financial distress among developers, weakened homebuyer confidence, and a backdrop of large inventories and structurally declining demand. Key policy priorities should be to expedite the resolution of underlying supply-side imbalances, most importantly by restructuring nonviable developers; support and de-risk surviving developers; and take steps to contain the buildup of risks in the property market.

Abstract

The Chinese authorities have taken resolute actions to address the risks from the property sector since the start of the pandemic. The key chaiienge now is to smooth the transition of the sector to a smaller, more sustainable size amid unresolved financial distress among developers, weakened homebuyer confidence, and a backdrop of large inventories and structurally declining demand. Key policy priorities should be to expedite the resolution of underlying supply-side imbalances, most importantly by restructuring nonviable developers; support and de-risk surviving developers; and take steps to contain the buildup of risks in the property market.

Smoothing the Path to a New Normal: China’s Property Sector Transition1

The Chinese authorities have taken resolute actions to address the risks from the property sector since the start of the pandemic. The key chaiienge now is to smooth the transition of the sector to a smaller, more sustainable size amid unresolved financial distress among developers, weakened homebuyer confidence, and a backdrop of large inventories and structurally declining demand. Key policy priorities should be to expedite the resolution of underlying supply-side imbalances, most importantly by restructuring nonviable developers; support and de-risk surviving developers; and take steps to contain the buildup of risks in the property market.

A. Introduction: China’s Real Estate Markets at a Turning Point

China’s Real Estate Markets: An Overview

1. Real estate activity has been important for China’s rapid growth but has come with significant risks. Property-related activities accounted for an estimated 20 percent of GDP through China’s decades of rapid growth, with real estate ubiquitous as a form of collateral and household wealth. While the authorities proactively limited risks from household leverage, average sales prices still rose almost 350 percent in the 15 years through 2021 and remain at significantly stretched levels relative to incomes. This price growth partly reflected strong investment-driven demand from households, driven by massive savings, a mortgage lending boom, and limited investment alternatives. At the same time, the country’s large developer sector leveraged up heavily to expand construction at a rapid pace, often working closely with local governments who relied on property activity for revenues.

2. The authorities have taken resolute action to address property sector risks since the start of the pandemic. New rules were put in place to rein in developers’ growing leverage and liquidity risks in 2020, including phased-in limitations on debt growth and other business operations for firms exceeding specified threshold for key balance sheet indicators.2 These exposed vulnerabilities among many developers operating with risky, high-turnover business models. After the default of the second largest developer by sales in late 2021 imperiled the completion of millions of presold homes, severe liquidity stress spread through large segments of the developer sector as new presales—relied on as a key form of working capital—slowed sharply. The authorities eased demand-side policies, including relaxing downpayment requirements, easing mortgage restrictions and lowering rates for existing mortgages, but avoided large-scale bailouts to defaulting developers.

uA001fig01

Real Estate Sales, Prices and Developer Bond Prices

(Index: December 2018=100)

Citation: IMF Staff Country Reports 2024, 050; 10.5089/9798400266966.002.A001

Source: Haver Analytics, CEIC Data Company LImited, Bloomberg LLP, and IMF staff calculations.Note: SA=Seasonally adjusted. Sales in gross floor area terms. Developer bond price is the Markit iBoxx USD China Real Estate bond price index.

3. The resulting adjustment of property market imbalances has, however, been uneven, driven largely by sharp declines in sales as opposed to prices. Real estate activity—particularly forward-looking indicators such as starts and developer land purchases—have been contracting quite sharply relative to recent real estate downturns in many other countries. Home prices have declined only modestly, however, in large part reflecting local government efforts to maintain price stability.3 Developers’ balance sheet restructuring has also been largely delayed via forbearance, to allow defaulted developers time to finish their large quantities of unfinished presold homes and limit the immediate effects on the financial system.

4. The authorities are rightly focused on helping the industry transition to a smaller and sustainable size. Over the next decade, demand for new housing is likely to shrink as gains from urbanization diminish, the population declines, and significantly fewer households live in dwellings without modern amenities. At the same time, the returns to real estate investment are likely to shrink as new rules curb risk-taking from leverage and misuse of presale proceeds. The authorities have recently signaled intensified support for construction of public and rental housing, most notably at the Central Financial Work Conference in late 2023. They have also extended policy support only to developers with more conservative business models and better governance.

5. This Selected Issues Paper (SIP) projects the path of real estate investment in China over the medium term and considers policies that will help ease the transition. New housing construction is set to fall significantly in the coming decade. This reflects a likely slowdown in urban household formation and urban redevelopment activities, amid an expected gradual contraction in the overall population. Construction will also face a significant drag from excess developer inventories and rising secondary market supply of previously vacant homes. While there is significant uncertainty around the likely path of sustainable demand for new housing, real property investment is likely to fall by 30 to 60 percent from end-2022 levels and rebound only modestly thereafter, with wide spillovers to other sectors via real estate construction’s large share of domestic value-added. The prospect of delayed price declines and uncertainty related to distressed developers threatens to suppress demand, potentially deepening and prolonging the adjustment. The authorities should expedite the resolution of underlying supply-side imbalances, most importantly by restructuring nonviable developers. Measures are also needed to support and de-risk surviving developers and reform the pre-sales system, to contain the buildup of risks in the property market.

6. The remainder of this SIP is organized as follows. The next section explains key factors affecting supply and demand for new housing in the coming decade and establishes a framework for projecting these variables into the medium term. The following section explores how the medium-term real estate transition could play out at the province-level. The penultimate section considers how certain factors outside the supply and demand framework could shape the real estate projections and then a final section concludes with policy advice.

B. New Housing Investment over the Medium Term

Overview

7. China’s demographic transition is set to reduce the fundamental demand for new housing in the coming decade. The long-run sustainable demand for new housing investment is primarily a function of the additional units needed to: (i) accommodate projected growth in the overall number of households and (ii) replace existing units lost on net from the stock of housing.4 Growth in China’s urban population is set to decelerate significantly from the rapid pace of the last two decades, as net migration to urban areas slows and China’s total population declines. This slowdown could be somewhat offset by declining average household size, reflecting growth in the share of adults in the population due to aging and declining fertility, which could increase demand for housing relative to the population. In cross-country experience, average household sizes decline as societies age but are also influenced by changes in the business cycle and behavioral or cultural factors.5

8. Publicly funded redevelopment played a key role in boosting new housing demand in the last decade. Shantytown redevelopment policies accelerated the demolition of millions of units of older housing, particularly in the 2013–2018 period, much of it lacking in modern amenities. Census data showed the share of the population living in housing built before 2000 dropped from 66 percent in 2010 to 35 percent in 2020, implying the net destruction of 66 million pre-2000 housing units, while the share of housing units without modern amenities fell from 28 to 12 percent. Targets for urban redevelopment programs were scaled down almost 75 percent for the 14th Five Year Plan (2021–25) from the 13th Five Year Plan (2016–2020).

9. This source of demand may rebound in the near term but is likely to remain lower than in the last decade. While the authorities have recently called for stepping up publicly supported urban redevelopment programs to ease the property sector adjustment, several factors will likely limit their scale relative to past programs. The significant taxpayer cost associated with such programs—in particular, compensating and relocating displaced households—will have to be largely borne by local governments facing significant fiscal and financial challenges. These programs are also likely to be constrained by the now much smaller stock of pre-modern housing in need of redevelopment and increased challenges in securing developer participation given widespread financial distress within the sector.

10. Supply-side factors are likely to add to the adjustment for new construction. The rapid pace of developer building before mid-2021 and the sharp decline in property sales since then has left developers with large inventories of finished and unfinished housing inventory, which will have to be absorbed by future demand. Some portion of the large share of unoccupied investment properties is also likely to enter the secondary market or be taken over by investors’ grown children, further reducing the new construction required to satisfy fundamental housing demand. Finally, the extensive and protracted liquidity stress for much of the developer sector is likely to weigh on new housing construction, as the authorities ensure that the troubled developers’ limited resources are used to complete the large backlog of unfinished presale homes.

11. Prices play a critical role in determining supply and demand, but the evolution of prices in China’s current situation is subject to significant uncertainty. In the academic literature, decreases in house prices (relative to construction costs) generally lower developers’ profit margins and reduce supply, independent of demographic or other housing stock factors. Rising prices also shape homebuyer expectations for future price increases, similarly bolstering demand (Muellbauer, 2022). These relationships generally assume flexible, market-clearing prices, but these conditions do not hold in China’s current situation, where interventions to limit house price declines appear to have exacerbated declines in sales and created uncertainty about the level of the true market-clearing price. Use of these price floors is also likely to come with significant trade-offs for economic activity, as discussed in Section D, creating uncertainty about authorities’ commitment to maintain them over time.6

12. Even in the absence of price controls, the future path of house prices remains unclear. Long-run house prices are typically modeled on changes in mortgage credit conditions, household incomes relative to the housing stock, as well as house price expectations, the effects of demography, and other factors (Chauvin and Muellbauer, 2018).7 Mortgage credit availability and the continued trend growth in household income since the property crisis broke out in mid-2021 would be generally expected to provide continued support to house prices, as has the prospect of slower growth in the housing stock due to the collapsing activity in starts. Other factors are however likely generating increased downside risks to house prices, potentially skewing price expectations lower:

  • The ongoing financial turmoil in the developer sector and the ubiquity of pre-sales has introduced completion risk, or counterparty risk, into most homebuying transactions, reducing the marketable value of unfinished properties. The possible eventual liquidation of large stocks of distressed developer inventories at a discount could affect broader house prices.

  • A structural reduction in speculative demand could impact prices through various channels. Structural decline in the vacancy rate due to sales of previously unoccupied investor-owned properties could effectively boost housing supply relative to household income, reducing prices over time in a standard model like the one noted above. More generally, declining investment-or collateral-motivated housing demand may reduce the market-clearing price of housing, particularly given how high home prices are relative to household incomes and rental yields.

  • Expectations for lower growth of household incomes and weaker activity would similarly create expectations for softening house price growth. Developers’ financial distress may also worsen already-stretched local government finances, raising the likelihood of tighter regional financial conditions and future fiscal consolidation (see Section D and the SIP on LGFVs).

Projecting Future Demand and Supply

13. This analysis projects residential real estate investment into the medium term based on the path of expected fundamental demand and the unwinding of supply-side distortions. Using the approach developed in Chivakul et al (2015), this analysis assumes that the developer sector supplies new homes based on the expected demand for housing, i.e., fundamental demand. This baseline production decision is then modified due to various supply-side distortions, which prompt developers to reduce supply in the short run. For the sake of simplicity, the potential impact of prices is not factored in but discussed qualitatively in Section D. In subsequent sections, the estimated path of supply over the medium-term—measured in housing starts in floor space terms— is then used to project the path of real estate investment in GDP.

14. The path of fundamental demand is estimated as a range between two scenarios. For simplicity, both scenarios use United Nations projections for total population growth, under the medium fertility assumption, and assume urbanization slows in line with World Bank projections, but use different assumptions on the size of the average household.

  • In a scenario with lower average household size: the average persons per household falls from 2.77 in 2021 to 2.4 in 2034, approaching levels similar to Japan or Korea, more than offsetting the drag from aggregate decline in the population.8 Net demand from replacement of older units is derived by extending the 2010 to 2020 pace of decline in the pre-2000 housing stock, but starting from a significantly lower base of housing, roughly equivalent to 2.8 million units per year. The average new-build apartment size also grows, from 114 square meters in 2020 to 121 square meters. This reflects both strengthened policies to redevelop remaining substandard housing and robust demand for larger, more modern housing driven by ongoing income growth.9

  • In a scenario with higher average household size: the average household size falls to only 2.6, reflecting greater drag on net household formation from persistent youth unemployment, weak consumer confidence, and continued cohabitation of older adults with working children. Replacement demand occurs at two-thirds the annual pace of the upside scenario, generating demand for only 2.1 million units of housing per year over a decade. The average apartment size remains unchanged.

15. These estimates project fundamental demand in the coming years will decline roughly in the range of around 35–55 percent relative to the past decade, to an average of about 950 million square meters per year. The largest overall compression comes from estimated replacement demand, given the rapid pace of demolition in the 2013–2018. The decline in average household size accounts for the largest difference between the upside and downside scenario, reflecting both the importance of this variable in determining net household formation and the significant uncertainty in projecting its path going forward. These fundamental demand estimates are broadly in line with recent estimates by private analysts in China.10

uA001fig02

Estimated Annual Average Fundamental Housing Demand

(Millions of square meters)

Citation: IMF Staff Country Reports 2024, 050; 10.5089/9798400266966.002.A001

Sources: CEIC Data Company Limited; and IMF staff calculations.Note: HH=Household.

16. Housing supply is assumed to equal future fundamental demand, adjusted for drag from supply-side factors. Developers’ supply function in any given year is expressed in starts in floor space terms and is assumed to equal expected fundamental demand 1.5 years in the future. This reflects an assumption of a three-year production cycle, with pre-sales (the dominant form of new home sales) only allowed one year into the production process, with developers aiming to complete pre-sales before the end of year two. Several other supply-side modules are then layered on to the baseline supply function to derive the expected path of new supply.

  • Excess housing inventories. Developers are assumed to reduce new starts when realized sales fall below projected demand, resulting in excess inventories.11 These inventories are cleared over time by the assumed reduction in starts, with their sales in future years assumed to meet the gap between new supply and fundamental demand.

  • New supply from investor sales. Declining prices and uncertainty related to the prolonged market adjustment lead households to reduce their holdings of unoccupied investment properties. Increased secondary market supply from these investors leads to an equivalent decline in expected fundamental demand. A conservative estimate of 5 percent of cumulative 2017–2021 sales is used.12

  • Presale completion backlogs. Developers facing liquidity stress reduce new starts to redirect available funds to completing overdue presold housing owed to homebuyers, in line with the authorities’ policy priorities and observed practice. To account for significant uncertainty in estimating the magnitude of this channel, the developer sector only faces a trade-off for one quarter the estimated presale completion backlog attributed to liquidity-constrained developers, or ten percent of the total.13

17. The combined drag from supply-side factors is equivalent to about 17 percent of projected fundamental demand in the 2024–2033 period. Excess inventories as of end-2023 are estimated to be just over 1 billion square meters in floor space terms, slightly below the levels reached during China’s property market downturn in 2014–2015 (text chart). New supply from investor sales would amount to 377 million square meters, while the reduction in new starts related to distressed developer backlogs amounts to 535 million square meters.

uA001fig03

Estimated Developer Excess Inventories

(Floor area: Millions of square meters)

Citation: IMF Staff Country Reports 2024, 050; 10.5089/9798400266966.002.A001

Sources: CEIC Data Company Limited; and IMF staff calculations.Note: Data for 2023 is estimated based on year-to-date data.

18. Converting fundamental demand to point-in-time levels requires simplifying assumptions but is needed to generate a time path for new supply. Changes in demographic and housing stock factors are expected to have a slow-moving impact on demand and in any given year may be dominated by short-term cyclical variations in household formation or economic activity. To facilitate more granular forecasting of housing supply from the near term into the medium term, fundamental demand is converted to point-in-time levels. The drag from supply-side disruptions is assumed to be concentrated in the first three years, and then gradually dissipate over the following four years. This is somewhat longer than the average duration of past housing market downturns in many OECD countries but extrapolates forward the slow pace of adjustment seen in the first two years of the crisis.14 Fundamental demand is expressed in floor space terms and converted to annual data.

uA001fig04

Residential Real Estate Sales and Projected Fundamental Demand

(Floor area: Millions of square meters)

Citation: IMF Staff Country Reports 2024, 050; 10.5089/9798400266966.002.A001

Sources: CEIC Data Company Limited; and IMF staff calculations.Notes: Sales for 2023 estimated. FD=Fundamental Demand. HH=Household.
uA001fig05

Real Estate Starts: Actual and Projected

(Floor area: Millions of square meters)

Citation: IMF Staff Country Reports 2024, 050; 10.5089/9798400266966.002.A001

Sources: CEIC Data Company Limited; and IMF staff calculations. Notes: Starts for 2023 estimated. HH=Household.

19. Once supply-side drags are incorporated, the projected medium-term path of new housing starts is subdued for an extended period, with the bulk of the decline stemming from lower fundamental demand. New starts in the ten years of the period starting in 2024 average about 715 million square meters in the central scenario, about 45 percent of the 2019–2021 average level (1.6 billion square meters). The drag from supply-side factors generates about one-quarter of this decline, while declines in fundamental demand and other factors contribute the remainder. As estimated supply factors fade out but fundamental decline falls further in the first five years of the 2030s, the average level of new starts would rebound to only about 52 percent of the 2019–2021 peak pace before starting to decline (text chart).

uA001fig06

Selected Countries: Decline in Real Estate Starts During Downturns

(Housing units: Index t=100)

Citation: IMF Staff Country Reports 2024, 050; 10.5089/9798400266966.002.A001

Source: Haver Analytics, CEIC Data Company Limited, and IMF staff calculations Note: For China, t=2019. Countries include US (t=2005); Spain (2006); Sweden (1990); Denmark (2006); Ireland (2005). For China, starts are measured in square meters of floor space.

20. The magnitude and persistence of the projected decline would not be an outlier based on cross-country experience. Among thirteen advanced economies with relevant data, just five have experienced declines in housing starts of over 50 percent in three years, roughly matching the 60 percent three-year decline in China from 2021-2023. Among these five countries, housing starts remained subdued for an extended period, averaging 26 percent of peak levels over the subsequent five-year window (text chart). The circumstances of these comparator cases differ from China’s current conjuncture in important ways, notably the presence of banking crises, sizable declines in housing prices, and shocks to household balance sheets and employment. In China’s case, the severity of the shocks to the housing activity may nonetheless be comparable, as supply is likely to be affected for years by severe and persistent financial distress in the developer sector, while declines in demand are likely to be exacerbated by only modest price adjustments.

Estimating the Impact on Real Estate Gross Fixed Capital Formation

21. The impact of the projected path of new starts on real estate investment in GDP is then estimated. For this, the analysis uses an estimate of real estate gross fixed capital formation (GFCF), which is compatible with national account (GDP) data.15 Following Chivakul et al (2015), the growth in real estate GFCF is estimated with its own lag terms and the growth in floor space starts, with the results described in Table 1. Both coefficients are constrained to sum to one, which ensures that the average growth rates of the two series are the same over time. The resulting coefficients are then used to convert the path of floor space starts from the previous section into real estate GFCF.

Growth of Real Estate GFCFt = β1 x Growth of Floor Space Statist + β2 x Growth of Real Estate GFCFt-1

Text Table 1.

China: Regression Results

article image

22. The resulting path of real estate GFCF projects declines of roughly 30–60 percent from the end-2022 level by the middle of the 2020s. Real estate GFCF is expected to fall to about 50 percent of its 2021 peak level in the mid-2020s in the central scenario, which is consistent with the lagged impact of the decline in starts. Real estate investment begins to rebound in 2028, eventually reaching 60 percent of its 2021 peak level in the mid-2030s.

23. This decline would also be consistent with comparable cross-country experience. Of the five countries that experienced a three-year decline in starts exceeding 50 percent, most experienced a substantial and prolonged decline in real estate gross fixed capital formation. Real estate investment in these countries averaged 57 percent of peak levels in the ten years after peak investment was reached, compared to 58 percent estimated over the same period in China in the average of the two household size scenarios.

uA001fig07

Projected Real Estate Gross Fixed Capital Formation

(Index: 2021=100)

Citation: IMF Staff Country Reports 2024, 050; 10.5089/9798400266966.002.A001

Source: CEIC Data Company Limited and IMF staff calculations Note: HH= Household

24. The overall impact of declining real estate investment on GDP would be amplified through demand linkages to other sectors. Final demand from real estate-related activity accounted for roughly 20 percent of the economy’s total value-added as of 2020, the latest year for which data are available, and has been roughly consistent over the prior decade. About two thirds of this comes from real estate’s imputed portion of construction activity, and its upstream linkages to producers of metal, glass, cement, and the other goods and service inputs that are used to build housing. Another third comes from real estate services, a sizeable portion of which comes from services connected to the stock of existing housing, for instance leasing and property management. The impact on GDP could be larger due to declining demand for housing-related goods (furniture, appliances) as well as due to wealth effects.

uA001fig08

Selected Countries: Decline in Real Estate GFCF During Downturns

Index (t=100)

Citation: IMF Staff Country Reports 2024, 050; 10.5089/9798400266966.002.A001

Source: Haver Analytics, CEIC Data Company Limited, and IMF staff calculationsNote: For China, t=2021. Countries include US (t=2005); Spain (2007); Sweden (1990); Denmark (2006); Ireland (2006).

C. Medium-Term Adjustment at the Province Level

The urban population for each province is assumed to grow in line with the national projection scaled by the contribution of that province to urbanization growth in the 2017- 2021 period. The change in average household size is likewise assumed to grow in line with the national projection, but scaled by the 2017-2021 province-level change in average household size. Replacement demand is calculated again for each province based on the share of pre-2000 housing in the housing stock in 2020 and the pace of reduction of such housing in the 2010-2020 period. 16

uA001fig09

Estimated Average Annual Province-Level Fundamental Housing Demand, by 10-Year Period

(Millions of square meters)

Citation: IMF Staff Country Reports 2024, 050; 10.5089/9798400266966.002.A001

Sources: CEIC Data Company Limited; National Bureau of Statistics China; and IMF staff calculations.Note: Each dot is a province.

26. For most provinces, the decline in estimated fundamental demand and supply broadly match the aggregate decline. Fundamental demand for the 2024–2033 period, capturing only demand from urban household formation and replacement, falls by 46 from the 2012–2021 period for the median province, with most seeing declines of 30–55 percent. Factoring in the estimated drag on supply from factors such as excess inventories and investor housing sales, average annual projected housing starts in this period are likely to fall 52 percent from their 2019–2021 average pace in the median province, broadly in line with the projected decline in starts nationwide.

uA001fig10

Projected Province-Level Fundamental Housing Demand and Supply Drag in 2024–2033

(Percentage of 2019–2021 Annual Average Housing Starts)

Citation: IMF Staff Country Reports 2024, 050; 10.5089/9798400266966.002.A001

Sources: CEIC Data Company Limited; National Bureau of Statistics China; and IMF staff calculations. Notes: Each dot is a province. The value for fundamental demand for Beijing is not shown but is 155 percent.

27. The estimated drag on starts from supply-side factors is unevenly distributed across provinces, with some concentration in provinces with well-known debt issues. In the 2024–2033 period, the median province faces an average supply-side overhang effect equivalent to roughly 10 percent of the average pace of starts in the 2019–2021 period. For one quarter of provinces this effect is equivalent to 35 percent or more of the recent pace of building activity, which brings their decline in projected average supply to 30 percent or less of the 2019–2021 pace. This segment of provinces is relatively small in aggregate—accounting for only 13 percent of nationwide starts in the 2019–2021 period—but are already among the more fiscally vulnerable provinces based on their official LG debt to GDP ratio (see chart).

uA001fig11

Projected Change in Province-Level Supply vs Local Government Debt Burden

Citation: IMF Staff Country Reports 2024, 050; 10.5089/9798400266966.002.A001

Sources: CEIC Data Company Limited; National Bureau of Statistics China; and IMF staff calculations.Note: Each dot is a province.

28. Housing market policies—including responses to the recent downturn—should be tailored to localized supply and demand projections. For provinces with relatively limited net fundamental demand in the 2024–2033 period, large-scale stimulus to support new housing construction should be avoided in favor of policies that make better use of the existing housing stock. Local supply and demand considerations should also be important considerations in the resolution of unfinished presold projects of financially distressed developers. For projects with significant unsold housing located in markets with weaker demand, partial monetary compensation to homebuyers may be more effective than completing the project.

D. Implications for the Chinese Economy

29. The housing market adjustment could be deeper and more protracted if actual sales fall below projected fundamental demand. The supply model underlying this paper assumes that the total absorption of housing supply in each period is equal to projected fundamental demand. As discussed in section B, actual demand is not solely determined by demographic and housing stock factors, and for instance could fall due to expectations for house price declines or weakening household income. In this situation, developers’ stock of excess inventories—or the extra secondary market supply from investor sales—will be run down more slowly than projected or could even rise.17 If housing demand was weaker than expected, developers would respond by cutting back housing starts further, creating negative spillovers to demand for construction and other upstream industries.

30. The controlled and slow pace of house price adjustment is one factor likely to suppress sales relative to fundamental demand, prolonging the property market contraction. As noted, the relatively limited price adjustment appears to partially reflect efforts by LGs to limit the pace of price declines. 18 While these have likely played an important role in limiting spillovers to household and lender balance sheets, preventing more immediate macro-financial spillovers, price declines generally play an important role in clearing the housing market and restoring equilibrium between supply and demand.

31. Drawn-out price adjustments could reinforce supply pressures and entrench expectations for persistent house price declines. Current house price levels are high relative to both household incomes and rental yields, reflecting the prevalence of investment-motivated demand and the importance of expectations of future price appreciation for homebuyers prior to the property crisis. Going forward, particularly insofar as the decline in home sales is seen as long-lasting, homebuyers’ expectations that property prices will gradually adjust lower to converge with market-clearing levels could further weaken actual sales relative to fundamental demand, prolonging the needed adjustment, and undermining the restructuring of developers’ balance sheets.

uA001fig12

Home Price to Income Ratio, by City Tier (2020)

(Multiples of per capita household disposable income)

Citation: IMF Staff Country Reports 2024, 050; 10.5089/9798400266966.002.A001

Sources: WIND; CEIC Data Company Limited; and IMF staff calculations.Notes: Figures shown are weighted averages. Tier 1 cities include Beijing, Shanghai, Shenzhen, and Guangzhou. Eastern Provinces in Tier 2 include Anhui, Fujian, Jiangsu, Jiangxi, Shandong, and Zhejiang. Price-to-income-ratio is based on the average 2020 sale price for a 90 square meter flat divided by the 2020 per capita household disposable income.

32. Another procyclical factor likely to continue weigh on sales is the unresolved and widening distress of much of the developer sector. The share of defaulted or distressed private developers continued to grow through mid-2023, surpassing 40 percent of the sector in 2020 market share terms. Restructuring of these developers has largely been delayed amid widespread use of forbearance to encourage completion of these firms’ large backlog of unfinished presold housing, resulting in continuing deterioration of their financial positions.19 The unresolved distress among some of these developers—and the slow pace of their delivery of presold housing, proxied by the decline in their presale liabilities in 2022 (text chart)—is likely to reinforce homebuyers’ caution in purchasing unfinished homes from all but the strongest developers, for instance those with strong central government backstops. Uncertainty over the ultimate resolution of troubled developers’ large stock of unfinished properties, residential land, and arrears to suppliers may reinforce homebuyer concerns about the market more generally and further depress sales relative to fundamental levels.

33. Interlinkages between the property sector and local government finances could amplify fiscal vulnerabilities. Local governments have long relied on land sales to property developers and real estate-related taxes to cover their significant structural fiscal deficits, and many smaller cities saw a surge in land sale revenues in the years before COVID. In many cases these land revenues, and the use of land for collateral, helped secure these provinces’ heavy off-budget borrowing. The widespread liquidity distress in the developer sector has however resulted in a sharp decline in land revenues (and likely in land valuations). This has exacerbated on- and off-budget financial difficulties for many local governments, reflected in reports of rising local government and LGFV arrears, and raises the risk of significant fiscal consolidation in the future. Cross-province evidence suggests land sales declines in 2022 were most acute in provinces with pre-existing fiscal weaknesses, proxied by provincial government debt-to-GDP ratios at end-2021 (text chart), suggesting a potential negative feedback loop between declining property activity and fiscal vulnerabilities.

uA001fig13

Selected Balance Sheet Items of Distressed Developers

(Billions of renminbi)

Citation: IMF Staff Country Reports 2024, 050; 10.5089/9798400266966.002.A001

Sources: Capital IQ, and IMF staff calculations.Notes: Includes 24 distressed developers with available financial statements for 2022. Distressed developers have either defaulted within last two years or have average bond prices below 40.
uA001fig14

Province-Level Land Sales Growth in 2022 and Local Government Debt to GDP in 2021

(In percent)

Citation: IMF Staff Country Reports 2024, 050; 10.5089/9798400266966.002.A001

Sources: Capital IQ, and IMF staff calculations. Notes: Each province is a dot. Hainan is excluded.

34. The authorities’ plan to increase production of public housing would be broadly beneficial to construction activity but could also increase the required adjustment in the private housing market. Significantly increased public housing production could help offset the decline in construction sector activity, limiting the projected declines in overall real estate investment. More public housing would also provide more affordable alternatives to the private market, particularly for relatively lower-income household segments. But increased supply of public housing will also absorb fundamental demand for new housing units, shrinking the equilibrium supply growth needed in the private market, potentially delaying the resolution of oversupply in some regions. The impact could be partially mitigated if developers received new revenue streams from overseeing the production of public housing.

E. Policies for Smoothing the Transition

35. The authorities should prioritize the expedited resolution of supply-side imbalances in the property market. The looming and potentially sharp slowdown in fundamental demand for new housing increases the urgency of reducing excess inventories and restructuring the property developer sector. The multiple potential procyclical feedback loops involving prolonged demand weakness—with house prices, developer balance sheets, local government fiscal vulnerabilities— increase the risk of spreading this market adjustment out over time. To facilitate such supply-side transition, the following policies are needed.

  • Accelerating exit of nonviable property developers. Forbearance policies for property lending should be phased out. Supervisors should guide lenders to adopt a conservative approach in assessing developer viability and collateral values and require banks to recognize losses and initiate insolvency proceedings as necessary. The existing corporate restructuring and insolvency regime should be used more, with strengthened liquidation proceedings and out-of-court settlements (Araujo et al, 2022).

  • Supporting housing completion. In cases of commercial nonviability, projects with unfinished presold housing units should be taken over by a central-government-backed support scheme for homebuyers awaiting delivery (as described in Box 1, IMF 2022). The scheme would either complete taken-over projects or provide partial compensation to affected homebuyers, whichever is less costly.

  • Allowing market-based adjustments in house and land prices. Macroprudential and other housing and development policies should not be used to impede market-based price adjustments, which are needed to restore stability and confidence in the regions with excess supply. Some crosscountry evidence shows that faster home price depreciation episodes are associated with stronger growth in GDP and productivity compared to modest but prolonged home price declines, by improving capital allocation efficiency and labor mobility (Jinjarak et al, 2016).

36. Another set of policies is needed to help right-size and de-risk viable property developers.

  • Reforming the presale model. Developers’ use of presale funding as general source of liquidity should be strictly prohibited. Such funding should be backstopped by stronger financial and legal protections for presale homebuyers, for instance by introducing stricter escrow rules and third-party completion insurance. Government-backstopped completion guarantees, backed by conservative underwriting, could also help restore homebuyer and creditor confidence as developers gradually unwind their business model reliance on presales as a source of liquidity (Box 1, IMF 2022).

  • Expanding housing access. Further boosting policy support for public and rental housing construction programs would help meet fundamental demand for lower-income segments and reduce the need for household savings to purchase private housing at elevated valuations. Public housing programs could also be designed to help alleviate the transition for the developer sector by re-purposing private inventories—easing the supply-side adjustment—and by providing alternative revenue streams for developers for new construction.

  • Assisting surviving developers repair balance sheets to adapt to a smaller property market. Surviving firms should be guided to speed up their use of mergers, asset disposals, equity raising, and other tools (including debt restructuring) to boost capital and liquidity buffers.

37. A third set of policies is needed to address the fundamental pressures that incentivized the original build-up of risks in the property sector.

  • Households should be guided towards alternative investment options. To reduce investment-driven demand for housing, medium-term policy measures should include a new nationwide property tax and introduce alternative saving options such as “third pillar” pensions and a voluntary supplementary medical insurance plan.

  • Fiscal reforms are needed to help reduce local governments’ reliance on land sales and property activity. Tax reforms laid out in the accompanying SIP on revenue measures would generate a significant amount of new revenue for local governments. In addition, the share of revenue allocated from the central to the local government should be increased, where needed, to be commensurate with local governments’ spending mandates and thus reduce existing vertical fiscal imbalances. Moreover, transfers to local governments could automatically respond to local economic conditions, attenuating the need for local governments to resort to off-budget financing (IMF 2020). Finally, provinces’ growth targets, which encourage excessive investment financing by growing indebtedness at the local level, should be phased out.

References

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1

Prepared by Henry Hoyle (APD).

2

Known as the “Three Red Lines’, these rules imposed regulatory limitations on developers with liability-to-asset ratios above 70 percent; net debt higher than 100 percent of equity; and cash less than 100 percent of short-term debt. The rules were introduced in August 2020 and were set to take effect in mid-2023.

3

Under the authorities’ Long-Term Mechanism for Real Estate, introduced in 2018, local government are officially mandated with maintaining real estate price stability, and in practice often use listing approvals and other formal and informal tools to discourage transactions above or below a narrow range around desired prices. Local governments do have discretion to ease these policies, but media reports suggest they often face intense lobbying from homeowners and rival developers to avoid doing so.

4

Belsky et al. 2007. In the literature, an additional source of demand for new housing construction comes from the estimated demand for second homes, investment homes, and vacant homes that accommodate the normal turnover of the housing stock. Given evidence of high rates of vacant housing held by owner-investors (see footnote 8), this analysis assumes that the stock of vacant housing will go down over the projection period as owner-investors reduce their portfolios of unused housing. This is treated as a supply-side channel, discussed in paragraph 13.

5

For more see, Lee and Painter, 2013, and Paciorek, 2016.

6

These trade-offs would have to be measured against the economic growth costs of a sharp, destabilizing adjustment in house prices, with potentially wide-ranging spillovers to household and financial sector balance sheets and ultimately activity.

7

Controlling for demographic factors, income relative to housing stock is a proxy for demand relative to supply.

8

Japan’s average household size was 2.52 persons when it reached a similar stage of aging (in 2007) that China is projected to reach in 2034 (approximated by the old-age dependency ratio). Korea has not yet reached China’s projected 2034 old-age dependency ratio but average household size (estimated by total population divided by total households) has been below that of China or Japan at comparable periods of aging.

9

In both scenarios, projected replacement demand is assumed to be frontloaded as authorities seek to offset downside pressures from the current downturn. In both cases, 60 percent of the 10-year total occurs in the first five years.

10

Wu and Xu (2021) project demand for new housing in the 2021–2030 period will decline by an average of 43 percent compared to 2011–2015. Xia and Xu (2022) predict 996 million square meters of new demand through 2035; Song and Zhang (2022) see 960 million square meters in the 2026–2030 period. These are slightly above the central scenario but well within upside and downside scenarios.

11

Excess inventories are calculated as the cumulative sum of lagged 1.5 year starts less sales.

12

Data gaps are particularly significant in estimating potential new supply from investor sales, but survey data consistently point to elevated vacancy rates. Bloomberg cited China Real Estate Information Service data from March 2022 indicating that for 26 cities over a three-year period, roughly 42 percent of newly purchased homes remained vacant. A 2017 survey by Southwestern University of Finance and Business put the total vacancy rate at 22 percent. A PBC survey on household wealth (PBC 2019) found that a sample of 30,000 urban households owned roughly 45,000 homes, implying a vacancy rate as high as one-third (rental markets are relatively underdeveloped outside of the largest cities).

13

Their presale completion backlogs are calculated as the cumulative gap between two years’ lagged presales and estimated presale completions. The presale completion backlog layer may somewhat overstate the scale of overdue presold housing due to biases in the starts and completion data noted earlier, as starts and sales appear to be somewhat over- and under-reported respectively, due to different statistical survey techniques and other factors. Reliable data on stressed developers’ actual project-level liquidity are also not available to ensure the realism of the assumed liquidity budget trade-off between starts and completions.

14

Bracke (2013) finds that the average duration of 19 OECD housing downturns—as measured by home prices—is five years but notes the duration of downturns tends to be positively correlated to that of the upturn, which also favors assuming a longer adjustment period. Kolscheen et al (2018) find that the median downturn in real estate investment across 15 advanced economies is about 11 quarters.

15

Real estate GFCF is estimated by using the share of real estate investment (ex-land purchases) in NBS total fixed asset investment, and then using that share in real GFCF in the national accounts data.

16

The sum of province-level fundamental demand projections differs only negligibly from the national level projections. For urban household formation- and replacement-driven fundamental demand, provincial vs national projections differ by 1.3 and 0.2 percent, respectively, reflecting minor inconsistencies between national and provincial demographic data.

17

Assuming that existing inventories are sold first, the undershooting of sales in a given period means that some newly built supply enters the stock of excess inventories, slowing the projected decline in excess inventories. If sales decline by more than the amount of excess supply projected to be sold in the period, then the excess inventories rise on net.

18

Some downside rigidity in home prices is common in cross-country experience but is typically associated with a lack of “forced sellers”, which is not applicable in China’s current real estate market. In some cases, developers appear to be reluctant to cut prices, or limits on price cuts appear to be driven by political pressure from existing homeowners.

19

Limits on price adjustments could also interfere with the restructuring of developer balance sheets by limiting discounts on saleable assets.

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People’s Republic of China: Selected Issues
Author:
International Monetary Fund. Asia and Pacific Dept
  • Real Estate Sales, Prices and Developer Bond Prices

    (Index: December 2018=100)

  • Estimated Annual Average Fundamental Housing Demand

    (Millions of square meters)

  • Estimated Developer Excess Inventories

    (Floor area: Millions of square meters)

  • Residential Real Estate Sales and Projected Fundamental Demand

    (Floor area: Millions of square meters)

  • Real Estate Starts: Actual and Projected

    (Floor area: Millions of square meters)

  • Selected Countries: Decline in Real Estate Starts During Downturns

    (Housing units: Index t=100)

  • Projected Real Estate Gross Fixed Capital Formation

    (Index: 2021=100)

  • Selected Countries: Decline in Real Estate GFCF During Downturns

    Index (t=100)

  • Estimated Average Annual Province-Level Fundamental Housing Demand, by 10-Year Period

    (Millions of square meters)

  • Projected Province-Level Fundamental Housing Demand and Supply Drag in 2024–2033

    (Percentage of 2019–2021 Annual Average Housing Starts)

  • Projected Change in Province-Level Supply vs Local Government Debt Burden

  • Home Price to Income Ratio, by City Tier (2020)

    (Multiples of per capita household disposable income)

  • Selected Balance Sheet Items of Distressed Developers

    (Billions of renminbi)

  • Province-Level Land Sales Growth in 2022 and Local Government Debt to GDP in 2021

    (In percent)