Research

Informational economic transmission is crucial even after accounting for countries' fundamental real and financial connections. Informational connections emerge from anomalous interdependence in agents' beliefs about countries' economic activity. We propose measuring this interdependence through the correlation (between countries) of analysts' one-year forecast errors about countries' economic performance. Our measure is based on a learning model in which informational transmission occurs when agents incorrectly assess the quality of new information regarding common factors that affect multiple countries simultaneously, due to learning frictions. Informational interdependence remains substantial under various validity analyses and robustness checks, and after addressing endogeneity concerns in several dimensions. Additionally, we demonstrate considerable higher-order spillovers of economic shocks.

We empirically study how excess comovement in stock returns can be explained by stock-to-stock interdependence through informational links. Informational linkages emerge from anomalous interdependence in agents' beliefs about stocks' economic performance. We propose a novel measure for informational linkages based on agents' learning process, which is biased towards common information due to learning frictions, generating correlated beliefs across stocks. We empirically measure these correlated beliefs based on analysts' forecast errors. Our results show that informational connections explain stock returns after cleaning for fundamental connections and controlling for various explanations already studied in the literature. We use our estimated informational linkages to study the propagation of a climate event and simulated shocks through the stock market, finding quantitatively important indirect effects.