Information Immobility and the Home Bias Puzzle

Many argue that home bias arises because home investors can predict home asset payoffs more accurately than foreigners can. But why does global information access not eliminate this asymmetry? We model investors, endowed with a small home information advantage, who choose what information to learn before they invest. Surprisingly, even when home investors can learn what foreigners know, they choose not to: Investors profit more from knowing information others do not know. Learning amplifies information asymmetry. The model matches patterns of local and industry bias, foreign investments, portfolio outperformance, and asset prices. Finally, we propose new avenues for empirical research.     

Presidential Address: Sustainable Finance and ESG Issues—Value versus Values

In this address, I discuss differences across investor and manager motivations for considering sustainable finance—value versus values motivations—and how these differences contribute to misunderstandings about environmental, social, and governance investment approaches. The finance research community has the ability and responsibility to help clear up these misunderstandings through additional research, which I suggest.     

Macroeconomic Effects of Credit Deepening in Latin America

We augment a standard dynamic general equilibrium model with financial frictions, in order to quantify the macroeconomic effects of the credit deepening process observed in Latin America in the 2000s—most notably in Brazil. In the model, a stylized banking sector intermediates credit from patient households to impatient households and entrepreneurs. Motivated by the Brazilian experience, we allow the credit constraint faced by households to depend on labor income. Our model is designed to isolate the effects of credit deepening through demand-side channels, and abstracts from potential effects of credit supply on total factor productivity. In the calibrated model, credit deepening generates only modest above-trend growth in consumption, investment, and GDP. Since Brazil has experienced one of the most intense credit deepening processes in Latin America, we argue the quantitative effects that hinge on the channels captured by the model are unlikely to be sizable elsewhere in Latin America.     

Talking Over Time - Dynamic Central Bank Communication

This paper studies the optimal dynamic communication strategy of central banks using a Bayesian persuasion game framework. In a dynamic environment, financial market participants and the general public have misaligned interests because the present and future have different relevance in their optimization problems, leading to a novel trade-off for the monetary authority. Compared to the static benchmark, I show that the central bank (CB's) optimal dynamic communication policy should put a higher weight on talking about the present state than the future. In addition, the CB should strategically send more noisy signals than in the static benchmark.     

Does Real-Time Macroeconomic Information Help to Predict Interest Rates?

We analyze the predictive ability of real-time macroeconomic information for the yield curve of interest rates. We specify a mixed-frequency macro-yields model in real time that incorporates interest rate surveys and treats macroeconomic factors as unobservable components. Results indicate that real-time macroeconomic information is helpful to predict interest rates, and that data revisions drive a superior predictive ability of revised macro data over real-time macro data. We also find that interest rate surveys can have significant predictive power over and above real-time macroeconomic variables.