寻找信息:利用谷歌趋势数据缩小低收入发展中国家的信息差距

Futoshi Narita, Rujun Yin
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引用次数: 30

摘要

及时提供数据是低收入发展中国家在决策和分析方面的一个长期挑战。本文探讨了使用谷歌趋势的数据来缩小这种信息差距,并发现关于一个国家的在线搜索频率与宏观经济变量(例如,实际GDP,通货膨胀,资本流动)显着相关,条件是其他协变量。与实际GDP的相关性比夜间灯光的相关性强,而新兴市场经济体的情况正好相反。搜索频率也提高了样本外预测的效果,尽管效果不大,这表明它们有可能促进对低收入发展中国家经济状况的及时评估。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
In Search of Information: Use of Google Trends' Data to Narrow Information Gaps for Low-Income Developing Countries
Timely data availability is a long-standing challenge in policy-making and analysis for low-income developing countries. This paper explores the use of Google Trends’ data to narrow such information gaps and finds that online search frequencies about a country significantly correlate with macroeconomic variables (e.g., real GDP, inflation, capital flows), conditional on other covariates. The correlation with real GDP is stronger than that of nighttime lights, whereas the opposite is found for emerging market economies. The search frequencies also improve out-of-sample forecasting performance albeit slightly, demonstrating their potential to facilitate timely assessments of economic conditions in low-income developing countries.
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