Do economic incentives govern information diffusion in markets? Using international banks’ advisory activities in corporate takeovers as their source of private information, we show in supervisory data that banks with closer ties to the target, but not the acquirer, advisor trade profitably in the target’s stock prior to the deal announcement. This trading behavior is associated with a higher premium paid by the acquirer without compromising the deal success. As the incentives of informed traders are aligned only with those of the target shareholders, which are represented by the target advisor, our evidence suggests strategic information transmission among these banks.

We study the interaction of expansionary rate-based monetary policy and quantitative easing, despite their concurrent implementation, by exploiting heterogeneous banks and the introduction of negative monetary-policy rates in a fragmented euro area. Quantitative easing increases credit supply less, translating into weaker employment growth, when banks’ funding costs do not decrease. Using administrative data from Germany, we uncover that among banks selling their securities, central-bank reserves remain disproportionately with high-deposit banks that are constrained due to sticky customer deposits at the zero lower bound. Affected German banks lend relatively less to firms while increasing their interbank exposure in the euro area.

This paper examines how political networks influence insider trading in China. Using biographical data to construct chairman–politician social networks, we find that firms with stronger political networks engage in significantly less insider trading. The effect is stronger for non-state-owned enterprises (non-SOEs) and for long-standing or high-ranking connections. The muted trading persists during periods when insiders possess valuable private information, including prior to M&A announcements and major policy events. The evidence suggests that personal political networks function as informal governance mechanisms that discipline managerial opportunism when formal governance through state ownership is absent.

Get access Abstract This study examines how changes in state corporate tax rates affect corporate social responsibility (CSR) performance among U.S. firms. Using staggered state-level tax reforms and a difference-in-differences (DiD) design, we identify an asymmetric causal effect: tax cuts significantly enhance CSR performance by reducing concerns, whereas tax increases only marginally weaken CSR strengths. Drawing primarily on signaling theory, complemented by slack resource and stakeholder perspectives, we argue that tax cuts expand financial slack, enabling firms to use CSR as a positive signal of financial strength, long-term orientation, and responsible use of tax savings. In contrast, firms avoid cutting CSR significantly after tax hikes to prevent negative signaling. In support of the theories, our heterogeneity analyses show that these effects are stronger among financially constrained firms and are concentrated in material CSR issues that are financially relevant to investors. A domain-level analysis further reveals that tax increases reduce environmental strengths, while tax cuts lower concerns related to employee relations, diversity, and environmental practices. These findings highlight how tax policy shapes CSR through its impact on financial flexibility and stakeholder expectation, offering implications for corporate strategy and public policy.

Using the adoption of Zombie Property Laws (ZL) across several US states, we show that requiring lenders to maintain properties in the foreclosure process affects mortgage lending decisions and standards. Difference-in-differences estimations using a state border design show that ZL incentivizes lenders to screen mortgage applications more carefully: they deny more applications and impose higher interest rates on originated loans, especially risky loans. In turn, these loans exhibit higher ex post performance. ZL also affects lender behavior after borrowers become distressed, causing them to strategically keep delinquent mortgages alive. Our findings inform the debate on policy responses to foreclosure crises.

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.

Firms increasingly rely on markets for technology to acquire innovations developed outside their boundaries, yet acquiring intellectual property rights alone often does not guarantee successful implementation. Many technologies depend on tacit know-how that must be supplied by the provider after the transaction is completed. This paper examines whether common ownership between a technology provider and a potential adopter mitigates this implementation problem. I develop a model in which overlapping institutional investors cause the provider to partially internalize the adopter’s gains from successful implementation, strengthening incentives to transfer tacit know-how. This mechanism operates only when know-how is unverifiable – absent this friction, common ownership leaves matching and outcomes unchanged. Under moral hazard, the model predicts that common ownership increases the likelihood of technology transfer to a given adopter, that this effect is stronger when tacit know-how is more important, and that common ownership improves post-transfer outcomes conditional on adoption. I test these predictions using U.S. patent reassignments between publicly traded firms. Using within-deal variation across competing potential adopters and plausibly exogenous variation from passive index-fund holdings, I show that common ownership increases the likelihood that a firm acquires a technology, particularly when the transferred bundle is more tacit. Common ownership predicts stronger subsequent innovation and higher future firm value, especially when ownership overlap is concentrated among investors with stronger incentives to monitor the provider. These findings show how ownership structure shapes interfirm technology transfer by affecting not only who acquires a technology, but also how much value is created.

We study how and why local biodiversity affects residential property values. Leveraging remotely sensed greenness indicators and a novel dataset of granular property listings, we examine how changes in vegetation load on real estate prices. Hikes in greenness are associated with higher listing prices, fewer properties listed, and reduced liquidity in housing markets. These results suggest that price hikes in housing markets are driven by supply-side constraints instead of a “greenium” that buyers might be willing to pay due to innate preferences. Exogenous zoning shocks to foster biodiversity corroborate the presence of supply side constraints as price drivers in residential housing markets. Our findings emphasize the need to calibrate biodiversity and (social) housing policy objectives more explicitly.

This paper examines how firms adjust the number and types of workers they hire in response to increased biodiversity transition risk. Using the adoption of the Key Biodiversity Areas Standard of 2016 as a source of variation that increases the risk of future land-use restrictions, we find that firms reduce job postings in affected areas and reallocate labor to less exposed regions. This effect is concentrated among firms that make negative impacts on biodiversity. Cuts are stronger among production roles, while hiring in green and adaptive occupations increases. The effect is not driven by changes in capital investment or workers’ labor supply decisions. Our findings contribute to the ongoing debate on the costs and benefits of biodiversity conservation policies and their implications for labor market outcomes.

This paper examines the impact of complex yet precise language, particularly financial jargon, on information dissemination and ultimately market efficiency. As a natural laboratory, we analyze the information exchanged during earnings conference calls, where we instrument jargon with the Plain Writing Act of 2010. Our findings suggest that the Act‘s promotion of plain language usage results in a reduction in complex financial jargon for US firms. However, in contrast to the presumed benefits of accessible language, this reduction in jargon is associated with a decrease in market efficiency, implying that the Act may inadvertently hinder information flow. This finding is particularly important at the juncture where human-generated information is received by machines, which are known to be vunerable to ambiguous inputs.