Given the recent controversy over deviations of street earnings from GAAP earnings, we show that the nonrecurring items that analysts include in street earnings are more persistent and have higher valuation multiples than those items they exclude from street earnings. In addition, we find no evidence that the pricing differential between the included and excluded items leads to future abnormal returns. If, as analysts claim, the primary use of street earnings is to value a stock, then our results suggest that analysts do have expertise in processing earnings information and that certain items appear justifiably excluded.

This paper investigates whether private information from lending activities improves the forecast accuracy of bank-affiliated analysts. Using a matched sample design, matching by affiliated bank or borrower, we demonstrate that the forecast accuracy of bank-affiliated analysts increases after the followed firm borrows from the affiliated bank. We also find that the increase in forecast accuracy is more pronounced for borrowers with greater information asymmetry and bad news, and for deals with financial covenants. Last, we find that the informational advantage of bank-affiliated analysts exists only when the affiliated banks serve as lead arrangers, not merely as participating lenders. Overall, our evidence suggests that information flows from commercial banking to equity research divisions within financial conglomerates.

This study investigates the role personal connections play in a crucial element of the supply chain—supplier selection. We find that the likelihood that a potential supplier (hereafter, a vendor) is selected to be an actual supplier (hereafter, supplier) increases when personal connections between executives of the vendor and the customer exist. The magnitude of the effect varies predictably across management ranks and positions and is stronger when information asymmetries between a vendor and a customer are high. Conditioning on the existence of a supply-chain partnership, a departure of a personally connected executive prompts the termination of the supply-chain relationship more often than a departure of an unconnected executive. Additional analyses show personal connections are associated with less restrictive procurement contracts and with improved customer performance after the formation of a supply-chain relationship. Overall, our study highlights the role of personal connections in reducing information asymmetry and improving operating efficiency in the supply chain.

Using data on over a million land transactions during 2004–2016 where local governments are the sole seller, we find that firms linked to members of China's supreme political elites—the Politburo—obtained a price discount ranging from 55.4% to 59.9% compared with those without the same connections. These firms also purchased slightly more land. In return, the provincial party secretaries who provided the discount to these “princeling” firms are 23.4% more likely to be promoted to positions of national leadership. To curb corruption, President Xi Jinping stepped up investigations and strengthened personnel control at the province level. Using a spatially matched sample (e.g., within a 500-meter radius), we find a reduction in corruption of between 42.6% and 31.5% in the provinces either targeted by the central inspection teams or whose party secretary was replaced by one appointed by Xi. Accordingly, this crackdown on corruption has also significantly reduced the promotional prospects of those local officials who rely on supplying a discount to get ahead.

In this paper, we propose a new spot-futures hedging method that determines the optimal hedge ratio by minimizing the riskiness of hedged portfolio returns, where the riskiness is measured by the index of Aumann and Serrano (2008). Unlike the risk measurements widely used in the literature, the riskiness index employed in our method satisfies monotonicity with respect to stochastic dominance. We also provide an empirical example to demonstrate how to estimate and test this optimal hedge ratio in equity data by the method-of-moments.

ABSTRACT We investigate whether multiemployer defined-benefit pension plan (MEPP) underfunding is priced by shareholders and creditors. Prior to the FASB's new MEPP standard (effective December 2011), when the disclosures on such plans were sparse, we find evidence (some evidence) that our estimate of a firm's share of MEPP underfunding is credit (value) relevant. We also find some evidence that a proxy for the funded status of a firm's MEPPs is incrementally value relevant over and above the firm's cash contributions, but no evidence that it is credit relevant. Furthermore, an estimate of MEPP underfunding that incorporates the additional disclosures required under the new MEPP standard is value and credit relevant, both individually and incrementally, over and above our old estimate. Overall, our findings suggest that shareholders and creditors view MEPP underfunding as a debt-like obligation and that the additional MEPP disclosures under the new standard are useful to market participants.

ABSTRACT We employ a sharp regression discontinuity design to identify the causal effects of investor-base disclosure (IB DISCLOSE) on funding outcomes and entrepreneurship success. Since February 2016, Kickstarter has disclosed IB information, namely, backer statistics including geographic locations and previous funding experience of the backers, once the number of backers for a project reaches ten. Exploiting this discontinuity, we show the disclosure increases the likelihood of funding success by 10 percent and the amount of funds pledged by 13 percent. The effect is more pronounced when the project quality is high and for projects with less credible creators, high ex ante uncertainty, high information asymmetry between creators and backers, and high financial costs to backers. We also find IB DISCLOSE increases the likelihood of product delivery. Our study highlights the importance of platform-provided disclosure in improving the efficiency of capital allocation. JEL Classifications: M41; G24; L15; O31; D04.