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RESEARCH

Shareholder Voting and Voluntary Disclosure in M&As, with Beatriz Garcia Osma, Anna Toldra Simats and Fengzhi Zhu, R&R at CAR

We examine the effect of voting requirements in M&A transactions on managerial disclosure, information asymmetries, and voting outcomes. We find that voting requirements lead firms to provide more disclosure and in a timelier manner, including disclosure of the merger agreement, information on expected synergies, and post-merger earnings forecasts. We document a larger reduction in information asymmetries in deals subject to vote. More disclosure in the presence of voting requirements also triggers more sales from transient institutional investors. Lower information asymmetries and more transient institutional sales are associated with higher voting support and a higher likelihood that the deal is completed. Our results suggest that disclosure induced by voting requirements is informative and affects voting outcomes by changing the market valuation of the deal and the shareholder base. Evidence from falsification tests and a regression discontinuity design supports the causal interpretation of our results. 

Mostly Good Robin Hood: Impact of Financial Transaction Tax on Corporate Investment, forthcoming in Corporate Governance: An International Review

I exploit the 2012 French introduction of a financial transaction tax (FTT) levied on stock purchases to examine its impact on corporate investment. Investment may decrease due to the increased cost of capital. The FTT, however, may encourage investment by reducing short-termism. I find an overall positive effect of the FTT on corporate investments. I also find that the FTT causes a shift from short-term to long-term ownership, an improvement in investment sensitivity to changes in growth opportunities, and an increase in likelihood and quality of acquisitions. These results are in line with the prediction that the FTT encourages investment by inducing long-term ownership and alleviating short-termism.

Identifying Peer Firms Based on Consumer Store Visits, with Pawel Bilinski

We propose a novel method for identifying economically related firms by tracking visits by the same consumer across stores representing different brands. Growth in the foot traffic at the stores that share the most consumer visits with the focal brand – related brand stores – predicts the focal brand’s sales growth. This relation increases almost tenfold in magnitude when we use sales growth at the peer brand to predict the focal brand’s sales growth, and the predictive power lasts for up to six months ahead. The between-brands economic ties we identify vary with (i) the intensity of the foot traffic between the focal brand and the peer, (ii) geographic distance between the focal brand and the potential pool of peers, (iii) consumer income and population density at the focal brand location, (iv) the size of the peer’s parent network across states, and (v) between industries. We also demonstrate that the consumer-based peers we identify predict the focal brand’s financial efficiency, profitability, and valuation. The new method identifies firm pairs that share complementarities in consumer demand, while selecting peers using the North American Industry Classification System codes identifies pairs that share a substitution relation. The study highlights how harnessing big data on consumer foot traffic can identify economically linked firms.

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