• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文会议>Proceedings of the 10th International Conference on e-Business >A comparative prediction study of housing price index based on web search data: Evidence from Beijing and Lanzhou in China
【24h】

A comparative prediction study of housing price index based on web search data: Evidence from Beijing and Lanzhou in China

机译：基于网络搜索数据的房价指数比较预测研究：来自中国北京和兰州的证据

获取原文
获取原文并翻译 | 示例
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Recently, using web search data to predict public health trends and economical indicators, like consumption, unemployment, tourism is arising more and more researchers interest. Based on the thought that web search data could reflect searchers' attention and concern, we study the correlation between housing price index and web search data, then make a comparative analysis of two regions with different economic levels. One the one hand, a theoretical framework illustrating the relationship between web search data and housing price index has been established. One the other hand, empirical studies of Beijing and Lanzhou has been conducted to verify the predict ability of web search data. Comparing with models not including web search data, the mean absolute percentage error decreased and the goodness-of-fit improved in models with web search data. In addition, based on the comparison of Beijing and Lanzhou, we find the predict ability of web search data has a certain relationship with economic development level of the region, and web search data has a better explanation ability for the fluctuation of housing price in developed region, like Beijing. Importantly, using web data to predict is able to achieve true real-time monitoring, and provide as references for government sector to make macro-control policy.
机译：最近，使用网络搜索数据来预测公共卫生趋势和经济指标，例如消费，失业，旅游等，引起了越来越多研究人员的兴趣。基于网络搜索数据可以反映搜索者关注和关注的思想，我们研究了房价指数与网络搜索数据之间的相关性，然后对两个经济水平不同的地区进行了比较分析。一方面，建立了说明网络搜索数据与房价指数之间关系的理论框架。另一方面，对北京和兰州进行了实证研究，以验证网页搜索数据的预测能力。与不包含网络搜索数据的模型相比，具有网络搜索数据的模型的平均绝对百分比误差降低，拟合优度提高。此外，通过对北京和兰州的比较，我们发现网络搜索数据的预测能力与该地区的经济发展水平有一定关系，而网络搜索数据对于发达地区房价波动具有更好的解释能力。北京这样的地区。重要的是，使用网络数据进行预测能够实现真正的实时监控，并为政府部门制定宏观调控政策提供参考。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号