(Yicai) Sept. 15 -- Prices of previously owned homes rose in Beijing, Mudanjiang, and Dali alone in August from a month earlier, while those in 66 other Chinese cities fell. 

Second-hand house prices climbed the most in Beijing last month, rising by 0.4 percent, while Xining and Jinhua had the biggest declines, falling by 1.1 percent, data from 70 Chinese cities released by the National Bureau of Statistics showed today. Six cities saw prices increase in July.

Prices in first- and second-tier cities fell 1.6 percent and 3 percent, versus 1.4 percent and 2.7 percent in July, respectively. In third-tier cities, they slid by 3.5 percent, the same as in the month before.

House prices were at a low level in August, and there were fewer cities where the cost of a pre-owned home rose, noted Zhang Bo, director of think tank 58 Anjuke Institute. Confidence in the property sector needs a further boost, with looser policy driving the market, he added.

New-build property prices rose in 17 cities last month compared with 20 in July, while those in 52 cities declined, according to the NBS data. In first- and second-tier cities, new home prices fell 0.2 percent, and they dropped 0.4 percent in third-tier cities, versus a 0.3 percent slide in the prior month.

Compared with prices a year ago, 25 cities logged gains for new properties, versus 24 in July. The price of previously owned homes rose in three cities, two less than a month earlier.

New home prices in first-tier cities rose 0.6 percent last month from a year ago, while in July, the figure jumped 1 percent. A gain of 0.3 percent was posted in second-tier cities, and a decline of 1.4 percent in third-tier cities.

Prices of second-hand homes in first-, second-, and third-tier cities fell 0.2 percent, 0.5 percent, and 0.4 percent, respectively.

A number of jurisdictions relaxed their mortgage policies last month, boosting market sentiment, said Yan Yuejin, head of the Shanghai E-House Real Estate Research Institute. Interest in buying property next month has increased, and the feedback on transaction data is also good, said Yan, who predicted a strong rebound.

Editor: Martin Kadiev