Do Google Searches Help in Nowcasting Private Consumption?: A Real-Time Evidence for the US

In this paper, we investigate whether the Google search activity can help in nowcasting the year-on-year growth rates of monthly US private consumption using a real-time data set. The Google-based forecasts are compared to those based on a benchmark AR(1) model and the models including the consumer surveys and financial indicators. According to the Diebold-Mariano test of equal predictive ability, the null hypothesis can be rejected suggesting that Google-based forecasts are significantly more accurate than those of the benchmark model. At the same time, the corresponding null hypothesis cannot be rejected for models with consumer surveys and financial variables. Moreover, when we apply the test of superior predictive ability (Hansen, 2005) that controls for possible data-snooping biases, we are able to reject the null hypothesis that the benchmark model is not inferior to any alternative model forecasts. Furthermore, the results of the model confidence set (MCS) procedure (Hansen et al., 2005) suggest that the autoregressive benchmark is not selected into a set of the best forecasting models. Apart from several Google-based models, the MCS contains also some models including survey-based indicators and financial variables. We conclude that Google searches do help improving the nowcasts of the private consumption in US.Google indicators, real-time nowcasting, principal components, US private consumption

Stock Market Valuation Using Internet Search Volumes: US-China Comparison

Search engine query data, which provide information on individuals’ attention allocation, have been proven by scholars to be useful in interpreting financial market performance. This paper explores the use of search volumes in stock market valuation and seeks to identify underlying stock market differences between the U.S. and China by extracting search volume data from their respective dominant search engines – Google and Baidu. On the overall market level, this paper investigates how search terms about financial markets relate to weekly returns of important market indices in each country; on the individual stock level, search volumes of selected company names in each country’s stock market are used to study fluctuations in stock prices. Finally, a set of trading strategies are recommended after combining research results in this paper with search-based strategies proposed in previous studies

Measuring objective and subjective well-being: dimensions and data sources

AbstractWell-being is an important value for people's lives, and it could be considered as an index of societal progress. Researchers have suggested two main approaches for the overall measurement of well-being, the objective and the subjective well-being. Both approaches, as well as their relevant dimensions, have been traditionally captured with surveys. During the last decades, new data sources have been suggested as an alternative or complement to traditional data. This paper aims to present the theoretical background of well-being, by distinguishing between objective and subjective approaches, their relevant dimensions, the new data sources used for their measurement and relevant studies. We also intend to shed light on still barely unexplored dimensions and data sources that could potentially contribute as a key for public policing and social development