China’s policymakers are managing the country’s housing challenges diligently, just as they did during the previous housing easing cycle. For several reasons, however, the recovery this time is likely to be shallower, with implications for China’s growth outlook for the rest of 2022.

One way for investors to gauge the prospects of a return to stability in China’s housing market is to compare what’s happening today with the sector’s previous recovery cycle in 2014–2016. The differences are much more apparent than the similarities.

The most obvious difference is the latest COVID outbreak, which, in April and May, further disrupted and distorted supply and demand. In another complication, construction delays have prompted some buyers of new homes to threaten to withhold mortgage repayments until work resumes.

But the biggest difference lies in the policy environment. In previous cycles, the government regarded the housing sector as a cyclical tool: by taking action to stimulate or cool housing sector activity, it could also stimulate or cool the broader economy. Times have changed.

Although the sector remains very important to the economy, its position in the minds of policymakers has changed. They have made clear that they will no longer use housing as a cyclical tool. Instead, they have focused on stabilizing growth in the sector, which has made a structurally lower contribution to overall growth.

Another difference is that local authorities are playing a bigger role in housing sector policy. All these factors need to be considered when weighing the sector’s short-term outlook.

Policy Activity Is High, but Housing Activity Stays Subdued

If anything, policymakers seem to be even more active today than they were in 2014–2016. Several months out from the latest trough in housing sales, policy activity—as measured by the J.P. Morgan China Housing Policy Index —has been more intense than it was during the comparable period in the previous cycle (Display).

The housing policy index started lower and fell faster in 2022 than in the last housing downturn.

The decline in house sales this time had been steeper but, as a result of policy actions, it slowed earlier this year at a roughly similar rate to that of 2014–2016. This year’s COVID outbreak, however, caused sales to fall again in April and remain weak in May. They rebounded in June on pent-up demand, then fell again in July, partly because of the mortgage strike threat (Display).

House sales volume for the 2022 cycle shows a brief recovery followed by a second downturn after April’s Covid shock.

Without the impact of COVID, it’s reasonable to assume that the pace of stabilization in house sales would have continued to parallel 2014–2016. But even accounting for COVID, why hasn’t the pick-up in house sales been more robust, given the notably stronger policy efforts on this occasion?

Local Policy Variations May Be a Factor

One reason may be local authorities’ involvement in housing policy. While the People’s Bank of China (PBOC) manages benchmark rates and the lower bound for mortgage interest rates, local authorities can vary restrictions on sales and purchases and set down-payment ratios.

National-government policy actions tend to be fairly uniform across the country, but there is scope for variation between one local authority and another. This has the potential to affect the efficiency with which policy is transmitted across the housing sector.

For example, local housing policy in theory would be more effective from an overall perspective if jurisdictions with the greatest downward pressure on house prices had correspondingly easier policy settings. But this does not appear to be the case in practice.

When we compared local policy actions in the first six months of this year (using data from Goldman Sachs) with regional home prices in the fourth quarter of 2021, we found the correlation to be close to zero. There appears, in other words, to have been a mismatch to date between local housing policy and downward house-price pressure.

Nonpolicy Variables Are Important

Housing policy is not the only factor driving activity in the sector. Other factors include house-price expectations, income expectations and credit supply (mortgage availability). The decline in mortgage interest rates so far this cycle is similar to 2014–2016, but the trend in credit supply is different.

As rates declined in 2014–2016, mortgage lending increased noticeably, suggesting a plentiful supply of mortgages. Today, mortgage lending has dwindled. Weak demand is one reason, but tight supply may be another (Display).

Line shows a steep decline in mortgage volume in recent months despite a concurrent reduction in the mortgage rate.

The decline in house prices since the third quarter of 2021 has caused a significant increase in the share of households expecting house prices to fall, and the share of people planning to buy houses in the next three months has fallen (Display).

Households expecting lower house prices rose as those expecting to buy fell. Meanwhile, actual house costs fell.

These sentiment indicators are markedly more pessimistic than they were in 2014–2016 and may have offset some of the positive effects of recent policy easing. The same applies to expectations about income and employment, which have fallen sharply since the third quarter of 2021 (Display).

Consumer expectations of future income and employment are down as sharply as the early days of the pandemic.

This analysis, in our view, provides investors with helpful yardsticks for assessing the prospects of a return to stability in the housing sector.

Scope to Ease Policy and Manage Expectations

With regard to policy, there appears to be scope for further easing. Local authorities, for example, could further relax restrictions on purchases and sales, as well as down-payment ratios—particularly in those areas where easing to date has lagged downward pressure on prices.

There is room for mortgage rates to fall, through a lower benchmark rate and/or lower rate premiums. But, given that initial rate levels this cycle were already much lower than in 2014–2016, the size of such reductions is likely to be smaller (so far this cycle, the five-year Loan Prime Rate has fallen 35 b.p. and the mortgage rate has fallen by about 100 b.p., compared with falls of 165 b.p. and more than 200 b.p., respectively, in 2014¬–2016).

The PBOC has recently asked banks to increase the mortgage supply.

Steps can be taken, in our view, to improve house-price expectations and sentiment toward the sector. Price momentum remains weak, particularly in lower-tier cities, and this, combined with construction delays and mortgage repayment strikes, could create a negative feedback loop.

Policymakers can help to avoid this. The central government, for example, has announced a special lending program through policy banks to help fund house-building projects to completion.

Income and employment expectations may improve following the economy’s rebound from its second-quarter trough in 2022. The unemployment rate has also eased. Lower-income earners have been hit hard, and an improvement in their outlook could be material for the sector.

Sales Are Likely to Stabilize at a Lower Level

Light at the end of the tunnel for China’s housing sector depends on there being improvement in all these factors. Even so, the daylight into which the sector will eventually emerge is likely to be dimmer than it was in 2014–2016.

We expect house sales volumes to stabilize in the coming months but, for the structural and cyclical reasons outlined above, they could struggle to exceed, even by year-end, the levels seen before April’s COVID shock.

For 2022, we expect declines in both national house sales volumes and housing investment (excluding land purchases).

1 The index records policy announcements at local and national levels and aggregates them on a quantitative basis.

The views expressed herein do not constitute research, investment advice or trade recommendations and do not necessarily represent the views of all AB portfolio-management teams. Views are subject to change over time.

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