Forecasting private consumption with Google Trends data

doi:10.1002/for.2559

2018-11-22

PRE

Jaemin Woo

Ann L. Owen *

DOI：10.1002/for.2559

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摘要

En 中文

This paper examines the predictive relationship of consumption-related and news-related Google Trends data to changes in private consumption in the USA. The results suggest that (1) Google Trends-augmented models provide additional information about consumption over and above survey-based consumer sentiment indicators, (2) consumption-related Google Trends data provide information about pre-consumption research trends, (3) news-related Google Trends data provide information about changes in durable goods consumption, and (4) the combination of news and consumption-related data significantly improves forecasting models. We demonstrate that applying these insights improves forecasts of private consumption growth over forecasts that do not utilize Google Trends data and over forecasts that use Google Trends data, but do not take into account the specific ways in which it informs forecasts.

Keyword:

consumer sentiment indicators

forecasting

Google Trends

private consumption

期刊

Journal of Forecasting

IF:

2.7

论文数:

2.3K

被引数:

3.0K

机构

Hamilton College

学者数:

409

论文数: 314

被引数: 413

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