Now-Casting Building Permits with Google Trends

David Coble, Pablo M. Pincheira
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引用次数: 12

Abstract

We propose a useful way to predict building permits in the US, exploiting rich real-time data from web search queries. The time series on building permits is usually considered as a leading indicator of economic activity in the construction sector. Nevertheless, new data on building permits are released with a lag close to two months. Therefore, an accurate now-cast of this leading indicator is desirable. We show that models including Google search queries nowcast and forecast better than our good, not naive, univariate benchmarks both in-sample and out-of-sample. We also show that our results are robust to different specifications, the use of rolling or recursive windows and, in some cases, to the forecasting horizon. Since Google queries information is free, our approach is a simple and inexpensive way to predict building permits in the United States.
现在用谷歌趋势铸造建筑许可
我们提出了一种有用的方法来预测美国的建筑许可,利用来自网络搜索查询的丰富实时数据。建筑许可的时间序列通常被认为是建筑业经济活动的领先指标。然而,新的建筑许可数据的发布滞后了近两个月。因此,需要对这一领先指标进行准确的预测。我们表明,包括谷歌搜索查询在内的模型比我们的样本内和样本外的单变量基准更好地预测和预测。我们还表明,我们的结果对不同规格,滚动或递归窗口的使用以及在某些情况下对预测范围的鲁棒性。由于Google查询信息是免费的,我们的方法是一种简单而廉价的方法来预测美国的建筑许可。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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