高盛-中国房地产乐鱼体育- 乐鱼体育官方网站- 世界杯指定平台LEYU SPORTS：高线城市将引领全国房价回升（摘要）

　　乐鱼体育,LEYU乐鱼体育官方网站,乐鱼体育靠谱吗,乐鱼体育app,乐鱼体育官网,leyu乐鱼体育,乐鱼体育入口,乐鱼体育官方,乐鱼leyu官网登录APP,乐鱼后台,乐鱼体育网址,乐鱼体育官方网站,乐鱼体育注册译文：主要城市的房地产数据包括两种：一种是来自统计局的官方数据，另一种是来自中原房产等第三方数据。统计局70城的二手房价指数主要覆盖了大中型城市，数据源于房地产机构、实地调查、当地住房管理局登记处。鉴于统计局数据城市覆盖范围大且包含第三方数据源，我们在下面的分析中重点关注统计局房价指数。但统计局的数据也并非没有缺陷，比如地方政府在经济上行和不景气时都面临稳定房地产价格的压力，这通常会导致数据过于平滑，从而低估了实际价格的波动。

　　原文：First, Cluster 1 includes mostly tier-1 and large tier-2 cities, where house prices have shown larger price appreciation and greater resilience (e.g., limited price decline in the 2014-15 downturn). The majority of the 70 cities – 77% on a population-weighted basis – fall into Clusters 2 and 3, which consist primarily of medium-sized tier-2 and tier-3 cities (see Appendix for more detailed city composition and geographic distribution, 图表 8 and 图表 9). Cluster 4 consists of cities such as Jinzhou, Mudanjiang (both in the northeast and with population outflows), and Wenzhou which had a housing bust in the early 2010s.

　　译文：首先，集群1主要包括一线和强二线城市，这些城市的房价表现出更大的升值空间和更强的弹性（例如在2014到2015年经济低迷期间房价下跌有限）。70城中的大多数（按人口加权计算为77%）属于集群2和集群3，主要由普通二线和普通三线城市组成（更详细的城市构成和地理分布见图8和图9）。集群4由锦州、牡丹江（均位于东北部且人口外流）和温州等城市组成，温州入选的原因是因为在2010年代初经历了房地产泡沫。

　　原文：Second, as shown in 图表 3, most cities reached their peak house prices before December 2022, with cities that have stronger fundamentals peaking later. Around 57% of the 70 cities peaked between January 2020 and December 2022, while only 6% peaked after December 2022. On average, Cluster 1 cities peaked the latest, around mid-2022, likely supported by stronger demand fundamentals and more stringent supply restrictions. This is followed by Clusters 2 and 3, which peaked around late 2020 to mid-2021. Cluster 4 cities peaked the earliest, with their house prices continuing to decline despite a brief pick up during the 2015-18 shantytown redevelopment program.译文：其次，如图3所示，大多数城市在2022年12月之前达到了房价峰值，而基本面较强城市的房价达峰较晚。70城市中约有57%的城市在2020年1月至2022年12月期间房价达到峰值，有6%的城市在2022年12月之后房价达到峰值。平均而言，集群1的城市最晚在2022年年中左右达到峰值，这可能是由于更强劲的需求基本面和更严格的限购措施被放开；集群2和集群3在2020年底至2021年中达到峰值；集群4的城市最早达到峰值，尽管房价在2015到2018年棚改期间短暂回升，但最终继续下跌。

　　原文：Third, while the recent decline in house prices is similar across clusters – ranging from 15% to 20% since their peaks – the cumulative gains since 2011 differ markedly (图表 4 ). Cluster 1 cities have seen house prices appreciate by 75% over the period, Cluster 2 cities have experienced only 20% cumulative increase, and the latest declines have wiped out all prior gains in Cluster 3. Cluster 4 cities stand out as the only group to experience a net price decline over the last decade. These trends highlight that stronger fundamentals not only delay the timing of house price peaks but also preserve some of the earlier price gains during a nationwide housing downturn.

　　原文：图表 5 suggests that population flows4 are important for house prices. The left panel shows that every 10% increase in population growth from 2010 to 2020 corresponds to approximately 3% rise in house prices in the 2010s. For example, cities like Chengdu and Zhengzhou, which experienced population inflows of around 45% over the decade, saw house price increases of around 50%. In contrast, some northeastern cities such as Jilin, which faced a 20% population decline, recorded a 20% rise in house prices. The 65% disparity in population growth between these two groups of cities accounts for roughly 30% variation in house price performance during the period. The right panel suggests that cities with strong population inflows in the 2010s also experienced milder price declines in the recent housing downturn.

　　译文：图表5表明人口流动对房价来说很重要。左图显示，从2010年到2020年，城市人口每增加10%带来的房价涨幅约为3%。例如成都和郑州等城市在过去十年中累积了约45%的人口流入，对应的房价上涨了约50%，作为对照的吉林等一些东北城市人口下降20%，对应的房价上涨了20%，这两组城市之间65%的人口增长差距导致房价表现的差异约为30%。右图表明，在2010年到2020年间人口流入较多的城市在最近的房地产低迷期中房价下跌也比较温和。

　　原文：Another driver for the recent house price declines could be the elevated housing supply. Longer inventory months – measured as the sellable gross floor area divided by the 12-month rolling gross floor area sold – tend to exert downward pressure on prices. As shown in 图表 6 (left chart), inventory months have risen sharply in lower-tier cities since 2021. Among the seven cities classified in Clusters 2 and 3 that also have inventory months data, there is significant variation in average inventory months since 2023, with Dalian the highest (49 months) and Hangzhou the lowest (10 months) (图表 6, right chart).

　　原文：To summarize the two drivers of house price dynamics, we estimate a panel regression model to link annual house price growth with 1) changes in inventory months5 and 2) population growth between 2010 and 2020. We also control for the 1-year lag of house price growth as well as time fixed effects to account for other uncontrolled factors that may drive house prices. The analysis was conducted using two panels, one focusing on cities in Clusters 2 and 3, and another including all available cities in the dataset for increased statistical power. The results are largely consistent across the two panels (图表7）.

　　原文：We find that a one-month increase in housing inventory supply leads to around 20bp decline in house price growth. Meanwhile, a 10% increase in population between 2010 and 2020 results in an average annual house price increase of 0.3%, accumulating to 3% over a decade – consistent with our earlier scatter plot analysis. Combining these estimates, average population increased 23% in our Clusters 2 and 3 sample over the last decade, which accounts for roughly 28% of the total house price appreciation during this period. Moreover, housing inventory has risen by about 17 months since the price peak in 2020-22, contributing to around 18% of the subsequent price decline.Furthermore, we find that the persistence of house price growth, as measured by the one-year lagged house price growth, is less pronounced (0.2%) compared to the US (around 0.4%). This implies that house prices are less sticky in China, potentially reflecting the larger role of government policies in the economy.