CHINA: UNDERSTANDING THE RESIDENTIAL REAL ESTATE MARKET

Transcription

1 CHINA: UNDERSTANDING THE RESIDENTIAL REAL ESTATE MARKET August 2016 M. Chivakul, R. Lam, X. Liu, W. Maliszewski, A. Schipke The views expressed in this presentation are those of the speaker and do not necessarily represent those of the IMF policy. 0

2 Agenda Motivation - real estate a key growth engine for China but data are scattered Recent Development in Residential Real Estate Moderate pickup in property sales and prices after slowdown. Will the recovery continue? Fragmented markets: Signs of overheating and oversupply across cities Policy measures to stabilize real estate markets? Empirical analysis Assess how the oversupply comes about and how it may get back to an equilibrium level (an update of earlier version WP with recent data) Gauge the severity and pace of adjustments 1

3 China: Why Looking at Real Estate? 2

4 1. Real estate sector a key engine for China s growth and it is slowing. Real Estate Investment (in percent of GDP) Real estate investment Residential real estate investment 14 percent of GDP 15 percent of fixed assets investment 15 percent of total urban employment XX percent of local public finances XX percent of total bank loans June Sources: CEIC, NBS 3

5 2. Data on China s real estate markets are scattered Sources National Bureau of Statistics Local Housing Bureaus (FangGuanJu 地方房管局 ) National Development and Reform Commission (NDRC) Private proprietary data: Soufun and Vanke Data - Average selling prices for commodity building residential units - transaction data: floor space sold, starts, and completed - don t cover secondary markets and only at provincial levels. - covers 134 cities across the country, including price indices, transaction data on sales and completed. - covers the prices of small set of cities (36 main cities) - price indices and sales including secondary market transactions in selected cities. - proprietary data and not directly comparable 4

6 3. Real estate cycles closely related to other sectors 5

7 What are Floor Space Data Measuring? 6

8 China: Residential Real Estate Development 7

9 1. Residential real estate prices have recovered after some softening but with disparate price trends China Residential House Price Index (Jan-2012=100, 3mma) 155 NDRC: 36 cities NBS: selling price 130 NBS: 70 cities Fangguanju CREIS: 100 Cities Booming Tier 1 House Prices (In percent, year-on-year growth, 3mma) Tier I Tier II Tier III or IV NBS: Floor space selling price Sources: CEIC; Local Housing Administrative Bureau (Fangguanju); and IMF staff calculations May Sources: Fangguanju; and IMF staff estimates

10 2. Sales also recovered across the board after a contraction, partly driven by policy support 9

11 3. Excess inventory is unwinding Residential Real Estate Inventory Ratio by Tiers (In years) All Tier I Tier II Tier III or IV June Sources: Local Housing Administrative Bureau (Fangguanju), Wigram Capital Advisors, IMF staff calculations. 1/Inventory is measured as floor space unsold; inventory ratio is measured as floor space unsold/sold. Residential Real Estate Inventory Ratio by Areas (In years) Less Developed Coastal Industrial Northeast Metropolitan June Sources: Local Housing Administrative Bureau (Fangguanju), Wigram Capital Advisors, IMF staff calculations. 1/Inventory is measured as floor space unsold; inventory ratio is measured as floor space unsold/sold. 10

12 4. But stabilizing sales and prices do not imply a strong pickup of real estate investment Residential Real Estate Inventory: A Lower Bound Estimation (In millions of square meters) Tier I Tier II Tier III All June Sources: Local Housing Administrative Bureau (FangGuanJu), Wigram Capital Advisors, IMF staff calculations. 11

13 5. Increasing share of new credit channeled to household mortgages High and rising leverage, high by international standards. Household credits (mainly mortgages) contribute about 30 percent of the new bank credit. Share of New Mortgage loan in total loan (in percent) Jun-2016 Mar-2016 Dec-2015 Sep-2015 Jun-2015 Mar-2015 Dec-2014 Sep-2014 Jun-2014 Mar-2014 Dec-2013 Sep-2013 Jun-2013 Mar-2013 Dec-2012 Sep-2012 Jun-2012 Mar-2012 Sources: CEIC 12

14 China: Outlook on Real Estate Markets Factors to consider Empirical assessment 13

15 1. Fragmented markets in real estate in affordability, price trends, and inventory ratios House price to income Ratio (100 Sqm house price of annual disposable income per capita) Beijing Shanghai Hainan Tianjin Sources: CEIC Guangdong Fujian Zhejiang Hebei Jilin Hubei Heilongjiang Gansu Jiangsu Jiangxi Shaanxi Sichuan Anhui Chongqing Shanxi Yunnan Liaoning Guangxi Qinghai Henan Shandong Ningxia Xinjiang Guizhou Tibet Hunan Inner Mongolia Nation House price to income ratio (in years) Nation Beijing Shenzhen New York London Tokyo Delhi China Sources: NUMBEO, and staff estimates Other country 14

16 Provinces with more severe overbuilding tends to have lower real estate investment and GDP growth 15

17 2. Policy Measures to Support Real Estate and Contain Financial Risks Measures Introduction and relaxation of purchase restrictions Down payment restrictions Taxation Social housing policy and urbanization Land sale auctions Remarks - Some cities have maintained purchase restrictions; often used as macroprudential measures to contain pricing pressures. - down payment ratio was reduced to about percent for first home purchases; higher for second homes and vary across cities - Effective taxes were reduced in property transactions (e.g., tax exemption if holding for more than 2 years (previously 5 years). - Government provides subsidies to households / rural residents or directly purchases unsold properties from developers for social housing purposes. - The local government has incentives to control land sales to stabilize real estate markets. 16

18 3. Supply side factors (e.g., land sales) also play a role in real estate cycles Real Estate Inventory Development Across Cycles (Build-up of inventory from starts to peaks, index with Jan2007=100) Peak inventory At about 185 (223) as of end- June Peak inventory (135) Peak inventory (145) Trough (140) (84) Trough (84) Cycle Cycle (15 months) (23 months) Sources: Fangguanju, and IMF staff calculations Cycle (24 months) 17

19 Empirical Assessment on Real Estate Adjustments 18

20 Real Estate Adjustment: How Severe and How Long? Assess how the oversupply comes about and how it may get back to an equilibrium level. Scenario analysis Baseline scenario Stronger demand scenario More gradual adjustment Impact on real estate investment and growth 19

21 Real Estate Adjustment: How Severe and How Long? Estimates real estate demand conditions based on fundamentals (i = cities; t = year). Floor space per capita (i,t) = f(household income, residential property prices, urbanization rate, demography, city tiers) Floor space stock (i,t) = floor space per capita (i,t) x urban population growth (i,t) Floor space sold (i,t) = g(floor space sold (i,t-1), D floor space stock (i,t), demolition rate (i,t)) 20

22 A. Assessing Real Estate Demand 21

23 B. Measuring oversupply in real estate Severity: Cumulative stock of real estate floor space built vs sold nationwide and across cities Adjustment duration: Based on assumptions on fundamentals, project mediumterm real estate adjustment and assess how the inventory cycle changes. 22

24 C. Scenario analysis: Baseline 23

25 Scenario analysis: More Gradual Adjustment scenario and Stronger Demand scenario 24

26 Growth impact across scenarios 25

27 Growth impact 26

28 Summary Recent stabilization in real estate prices and sales does not appear to come with strong investment Diverse developments across the country implications for adjustment and policy measures Real estate adjustment to address oversupply Severity: Overbuilding appears to be common in many cities, particularly the tier3/4 cities and in the northeast regions Duration: Multi-year adjustment likely to be structural (even with stronger demand) and may be prolonged given growth concerns. Growth impact: Real estate activity may continue to face a slowdown on investment and pose pressures to growth. 27

29 THANK YOU 28