We propose a set of novel non-macro-based uncertainty indicators that rely on the frequency of Google searches (NM-GSIs) for the following health-, environmental-, security-, and politicalrelated topics: "Symptom", "Pollution", "Terrorism", and "Election". By means of VAR investigations, we document that an intensification of people interest in non-macro-based topics harms the US real economic activity. In particular, NM-GSI shocks generate (i) a significant drop in consumer credit and (ii) a mild decrease (increase) in production (unemployment) levels. Noteworthy, rising non-macro-based uncertainty is found to have stronger influence on the outstanding level of consumer credit than rising macro-based uncertainty. Our findings suggest that increasing interest in specific non-macro-based topics might be associated with raising people's anxiety. A battery of robustness checks confirms our main findings.

This paper examines the macroeconomic effects of rising migration uncertainty in four advanced economies (i.e. US, UK, Germany and France). Migration uncertainty is first captured by the Migration Policy Uncertainty (MPUI) and the Migration Fear (MFI) news‐based indexes developed by Baker et al. (Immigration fears and policy uncertainty, 2015), and then by a novel Google Trend Migration Uncertainty Index (GTMU) based on the frequency of Internet searches for the term ‘immigration’. VAR investigations suggest that the macroeconomic implications of rising migration uncertainty differ across countries. Moreover, news‐based and Google search‐based migration fear shocks generate different macroeconomic effects. For instance, in the US (France), MPUI, MFI and GTMU shocks all improve (undermine) production and labour market conditions in the medium run. For Germany and the UK, mixed evidence is found, suggesting that increasing media attention on migration phenomena and rising population's interest in migration‐related issues influence people's mood differently. The observed heterogeneity in the macroeconomic effects of rising migration uncertainty can be explained by cross‐country gaps in (a) the level of labour market rigidity, (b) the degree of people's happiness and life satisfaction and (c) the percentage of graduates.

Why are unemployment expectations of the man in the street markedly dierent from professional forecasts? We present an agent-based model to explain this deep disconnection using boundedly rational agents with dierent levels of education. A good t of empirical data is obtained under the assumptions that there is staggered update of information, agents update episodically their estimate and there is a fraction of households who always and stubbornly forecast that the unemployment is going to raise.The model also sheds light on the role of education and suggests that more educated agents update their information more often and less obstinately xate on the worst possible forecast.

We propose a novel index of global risks awareness (GRAI) based on the most concerning risks—classified in five categories (economic, environmental, geopolitical, societal, and technological)—reported by the World Economic Forum (WEF) according to the potential impact and likelihood occurrence. The degree of public concern toward these risks is captured by Google search volumes on topics having the same or similar wording of that one of the WEF Global Risk Report. The dynamics of our GRAI exhibits several spillover episodes and indicates that concerns on the five different categories of global risks are—on average—highly interconnected. We further examine the interconnection between global risks perceptions and the macroeconomy and find that concerns on economic-, geopolitical-, and societal-related risks are net shock transmitters, whereas the macroeconomic variables are largely net receivers. Finally, we perform standard cross-sectional asset pricing tests and provide evidence that rising interconnection among global risks awareness commands a positive and statistically significant risk premium.