Research

This paper studies the sorting of firms and directors appointed to their boards. I leverage a novel finite-mixture random-effects model to estimate the contribution of unobserved firm and director heterogeneity while being the first to explicitly allow for an interaction between the two to estimate the quality of the match between board members and firms. Results reveal that positive complementarities drive positive sorting. Using hand-collected data and textual analysis to build a large dataset on directors’ skills and qualifications, I find directors with specialized skill sets to be associated with higher complementarities while, consistent with the idea of knowledge hierarchies in the firm. On the contrary, CEOs or CFOs tend to be generalists relying on directors’ advice. Finally, I exploit unexpected deaths of board members to establish a positive causal effect of boards, where productivity is concentrated to a few highly complementary directors, on firm value and firm performance.

We present causal evidence on the effect of boardroom networks on firm value and compensation policies. We exploit a ban on interlocking directorates of Italian financial and insurance companies as exogenous variation and show that firms that lose centrality in the network experience negative abnormal returns around the announcement date. The key driver of our results is the role of boardroom connections in reducing asymmetric information. The complementarities with the input-output and cross-ownership networks are consistent with this channel. Using hand-collected data, we also show that network centrality has a positive effect on directors’ compensation, providing evidence of rent sharing.

This paper studies the role of social connections in shaping individuals' concerns about climate change. I combine granular climate data, region-level social network data and survey responses for 24 European countries in order to document large information spillovers. Individuals become more concerned about climate change when their geographically distant friends living in socially-connected regions have experienced large increases in temperatures since 1990. Exploring the heterogeneity of the spillover effects, I uncover that the learning via social networks plays a central role. Further, results illustrate the important role of social values and economic preferences for understanding how information spillovers affect individual concerns.

Individual investors reduce their trading activity in financial markets after the release of negatively biased Hollywood movies related to financial markets. These movies regularly depict financial markets and professionals active in them as marked by greed and corruption (Lichter et al. 1997). This decline in trading activity at the extensive margin comes together with depressed investor sentiment marked by higher likelihoods and volumes of selling than of buying transactions by those investors still active. Their avoidance of investing in and tendency to trade out of stocks related to companies in the financial industry, as well as their shift from actively managed mutual funds to passive vehicles (ETFs), provide evidence for the deterioration of investors’ trust in the financial industry and its managers. This channel is in line with existing literature on subjective beliefs in investment decisions and the impact of biased media coverage, such as the negative depiction of financial markets, shareholders, and managers in Hollywood movies.

When banks expand abroad, their riskiness decreases if foreign expansion happens in destination countries that are more competitive than their origin countries. We reach this conclusion in three steps. First, we develop a flexible dynamic model of global banking with endogenous competition and endogenous risk-taking. Second, we calibrate and simulate the model to generate empirically relevant predictions. Third, we validate these predictions by testing them on an original dataset covering the activities of the 15 European global systemically important banks (G-SIBs). Our results hold across alternative measures of individual and systemic bank risk.

We argue that automation may make workers and firms more selective in matching their specialized skills and tasks. We call this phenomenon “core-biased technological change”, and wonder whether something similar could be relevant also for offshoring. Looking for evidence in occupational data for European industries, we find that automation increases workers’ and firms’ selectivity as captured by longer unemployment duration, less skill-task mismatch, and more concentration of specialized knowledge in specific tasks. This does not happen in the case of offshoring, though offshoring reinforces the effects of automation. We show that a labor market model with two-sided heterogeneity and search frictions can rationalize these empirical findings if automation strengthens while offshoring weakens the assortativity between workers’ skills and firms’ tasks in the production process, and automation and offshoring complement each other. Under these conditions, automation decreases employment and increases wage inequality whereas offshoring has opposite effects.