Predicting Housing Price Trends in Poland: Online Social Engagement - Google Trends

IF 0.6 Q4 BUSINESS, FINANCE

Real Estate Management and Valuation Pub Date : 2023-12-01 DOI:10.2478/remav-2023-0032

M. Bełej

引用次数: 0

Abstract

Abstract Various research methods can be used to collect housing market data and predict housing prices. The online search activity of Internet users is a novel and highly interesting measure of social behavior. In the present study, dwelling prices in Poland were analyzed based on aggregate data from seven Polish cities relative to the number of online searches for the keyword dwelling tracked by Google Trends, as well as several classical macroeconomic indicators. The analysis involved a vector autoregressive (VAR) model and the Granger causality test. The results of the study suggest that the volume of online searches returned by Google Trends is an effective predictor of housing price dynamics, and that unemployment and economic growth are important additional variables.

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预测波兰住房价格趋势：在线社交参与 - 谷歌趋势

摘要:收集住房市场数据，预测房价，可以采用多种研究方法。互联网用户的在线搜索活动是一种新颖而有趣的社会行为测量方法。在本研究中，波兰的住宅价格是基于七个波兰城市的总体数据，相对于谷歌趋势跟踪的关键词住宅的在线搜索数量，以及几个经典的宏观经济指标进行分析的。分析涉及向量自回归(VAR)模型和格兰杰因果检验。研究结果表明，谷歌趋势返回的在线搜索量是房价动态的有效预测指标，失业率和经济增长是重要的附加变量。

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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来源期刊

Real Estate Management and Valuation Economics, Econometrics and Finance-Finance

CiteScore

1.50

自引率

25.00%

发文量

审稿时长

23 weeks

期刊介绍： Real Estate Management and Valuation (REMV) is a journal that publishes new theoretical and practical insights that improve our understanding in the field of real estate valuation, analysis and property management. The aim of the Polish Real Estate Scientific Society (Towarzystwo Naukowe Nieruchomości) is developing and disseminating knowledge about land management and the methods, techniques and principles of real estate valuation and the popularization of scientific achievements in this field, as well as their practical applications in the activities of economic entities.