Daily news sentiment and monthly surveys: A mixed-frequency dynamic factor model for nowcasting consumer confidence

Policymakers, firms, and investors closely monitor traditional survey-based consumer confidence indicators and treat them as an important piece of economic information. To obtain a daily nowcast of monthly consumer confidence, we introduce a latent factor model for the vector of monthly survey-based consumer confidence and daily sentiment embedded in economic media news articles. The proposed mixed-frequency dynamic factor model uses a Toeplitz correlation matrix to account for the serial correlation in the high-frequency sentiment measurement errors. We find significant accuracy gains in nowcasting survey-based Belgian consumer confidence with economic media news sentiment.     

Growth in stress

We propose a new global risk index, Growth-in-Stress (GiS), that measures the expected fall in a country’s GDP as the global factors, which drive world growth, are subject to stressful conditions. Using the GDP growth rates of 87 countries, we find that, since the 2008 financial crisis, though mainly from 2011 on, the world overall has fallen in a state of complacency, with the cross-sectional average GiS falling quite dramatically; in 2015, the average worst outcome seems to be no growth at the 95% probability factor stress. However, the cross-sectional dispersion within groups is quite variable: it is the smallest among industrialized countries and the largest among emerging and developing countries. We also measure the factor stress on different quantiles of the GDP growth distribution of each country. We calculate an Armageddon-type event as we seek to find the GiS on the 5% quantile of growth under the extreme 95% probability events of the factors, and find that it can be as large as an annual 20% fall in GDP.