This paper examines whether common institutional ownership is associated with CEO connectedness across firms. We document that higher common ownership between two same-industry firms predicts a greater likelihood that a newly appointed CEO has preexisting social ties to the incumbent CEO of the peer firm. To address endogeneity, we use mergers among institutional investors in a stacked difference-in-differences design. In a hiring-firm-peer panel that carries connection status forward from the most recent appointment, exposure to a merger-induced common blockholder approximately doubles the probability that the pair is observed in a connected-CEO state. In a broader firm-pair panel, it increases the probability of CEO connections by 48.7%. We further document that gaining CEO connections through another firm’s CEO appointment is associated with improvements in peer firms’ returns on assets and Tobin’s Q, in both OLS and IV specifications. Peer firms that gain such a connection also experience positive abnormal returns around other firms’ CEO hiring announcements, corresponding to an average increase of $112.5 million in shareholder value. These performance patterns suggest that CEO connections may be valuable from a portfolio-level perspective. Consistent with this interpretation, the association between common ownership and CEO connections is concentrated among product-similar and organizationally complex firms and strengthens after the 2008–2009 financial crisis, when connections appear more valuable. Our findings point to CEO connection as a potential governance channel through which common institutional ownership is linked to firm outcomes, complementing prior work on executive compensation, shareholder voting, and board interlocks.

This study investigates the impact of inaccurate assumptions on economic forecast precision. We construct a new dataset comprising an unbalanced panel of annual German GDP forecasts from various institutions, taking into account their underlying assumptions. We explicitly control for different forecast horizons to reflect the information available at the time of release. Our analysis reveals that approximately 75% of the variation in squared forecast errors can be attributed to the variation in squared errors of the initial assumptions. This finding emphasizes the importance of accurate assumptions in economic forecasting and suggests that forecasters should transparently disclose their assumptions to enhance the usefulness of their forecasts in shaping effective policy recommendations.

This study employs synthetic control methods to estimate the effect of the Iberian exception mechanism on wholesale electricity prices and consumer inflation, for both Spain and Portugal. We find that the intervention led to an average reduction of approximately 40% in the spot price of electricity between July 2022 and June 2023 in both Spain and Portugal. Regarding overall inflation, we observe notable differences between the two countries. In Spain, the intervention has an immediate effect, and results in an average decrease of 3.5 percentage points over the twelve months under consideration. In Portugal, however, the impact is small and generally close to zero. Different electricity market structures in each country are a plausible explanation.

How does immigration affect support for redistribution? While most research focuses on overall tax and spending levels, we investigate how immigration influences preferences conditional on tax structures. Using two original survey experiments in the UK, we find that low- and middle-income respondents are more likely to support redistribution to immigrants under progressive systems shielding them from fiscal costs, but oppose redistribution when immigrants are identified as beneficiaries and the tax structure increases their fiscal burden. In contrast, high-income respondents' preferences are largely unaffected by either tax structure or immigrant inclusion. These findings suggest that progressive taxation (1) is a viable revenue-generating strategy without provoking major political backlash; (2) reduces native resistance to immigrant welfare inclusion; (3) helps explain puzzling variation in immigration's effects on welfare attitudes; and (4) clarifies why low- and middle-income groups sometimes reject generous welfare programs despite standing to benefit. Our results highlight the importance of institutional design in shaping how economic self-interest and immigration concerns interact.

We examine whether combining factual information on inflation levels and forecasts with a narrative can persistently shape consumers’ inflation expectations. In a preregistered randomized controlled trial with a representative sample of 3,000 German consumers, participants received either numerical or textual information about inflation rates, with or without an accompanying narrative. All treatments immediately lower inflation expectations, with numerical information eliciting stronger adjustments. Adding a narrative produces no additional immediate effect, confirming that it conveys no new information. However, only the combination of numerical information with a narrative yields a lasting reduction in inflation expectations and forecast uncertainty still observable after four weeks. Our results suggest that combining precise information with a narrative enhances information retention and can lead to more persistent shifts in consumers’ beliefs. The effects are strongest when respondents perceive the narrative as relatable and emotionally engaging, and among those with low financial literacy and limited knowledge of inflation.

Social preferences facilitate the internalization of health externalities, for example, by reducing mobility during a pandemic. We test this hypothesis using mobility data from 258 cities worldwide alongside experimentally validated measures of social preferences. Controlling for time-varying heterogeneity that could arise at the level at which mitigation policies are implemented, we find that they matter less in regions that are more altruistic, patient, or exhibit less negative reciprocity. In those regions, mobility falls ahead of lockdowns, and remains low after the lifting thereof. Our results elucidate the importance, independent of the cultural context, of social preferences in fostering cooperative behavior.

Externalities and social preferences, such as altruism, play a key role in the choice of social interactions, which in turn affect the diffusion of a pandemic. We build a dynamic epidemiological model with endogenous social interactions in a frictional environment, also in a variant with heterogeneous agents and a network structure. Taking into account agents’ endogenous behavior and altruism generates markedly different predictions relative to a naïve epidemiological model with exogenous contact rates. Congestion and commitment inefficiencies arise, even under full altruism, and call for policy intervention. We derive the efficient allocation, and show how the Ramsey planner can mitigate the respective externalities.