ANALYSIS and listened to the lamentations of countless numbers of colleagues concerning the rate at which the literature is expanding, the field of finance seems to cry out for a precious period of time, however brief it may be, to catch its breath. There appears to be little doubt that keeping up with new ideas, infused into the milieu which is finance, and reincarnated old ideas, clothed in a garb more fitting to the contemporary scene, is at best a most difficult task, especially with the increasing degree of specialization of previously neat and identifiable compartments.

The standard F test for linear restrictions in regression is relevant as a criterion but fails to capture the notion of tradeoff between bias and variance. Average squared distance criteria yield operational tests that are more appropriate, depending upon objectives. In the present paper two alternative criteria are developed. The first allows testing of the hypothesis that the average squared distance of a restricted estimator from the parameter point in k space is less than the average squared distance of the unrestricted, ordinary least squares estimator from the same parameter point. The second sets up a test of betterness of the restricted estimator over the unrestricted estimator of E(Y/X), where betterness is again defined in average squared distance.

Merkley et al. (2023) examine how cryptocurrency influencers recommend digital coins on Twitter (X) and the associated price effects. They report that influencers may exploit market investors via potential pump and dump schemes. While plausible, researchers may develop a broader understanding of influencers’ incentives and their influence by considering how investors engage these markets for social identity needs that enhance utility. Social-psychological research indicates that someone’s social identity strongly influences their behavior, even making the behavior maladaptive. This paper discusses how crypto influencers create social identity resonance. It then discusses how influencers can leverage this resonance for potentially lucrative financial opportunities, which might manifest in different expected crypto price patterns. The paper concludes by recommending more research on influencers’ experience, networks, and communication choices; the effects of video relative to text communication; and implications of social identity cohorts that influence prices and undermine regulatory trust in traditional markets.

I use account-level credit card and term loan data to analyze consumers’ responses to anticipated increases in cash on hand following term loan run-offs. Financial constraints are elicited using past credit card payment behavior and can explain the response of credit card but not term loan expenditure: unconstrained consumers are 23% more likely to finance new durable goods with term loans after the run-off. The results provide evidence of consumers engaging in sequential term loan borrowing.

There is now a substantial body of evidence that suggests business cycles are asymmetric. However, the evidence has been accumulated using a wide array of statistical techniques and, consequently, is based on various definitions of asymmetry. This paper examines several parametric models that have been used to study asymmetries in real GNP. Although these models capture asymmetries in very different ways, their dynamic properties are remarkably similar.

We study a model of financial reporting where investors infer the precision of reported earnings. Reporting a larger earnings surprise reduces the inferred earnings precision, dampening the impact on firm value of reporting higher earnings, and providing a natural demand for smoother earnings. We show that for sufficiently “bad” news, the manager under‐reports earnings by the maximum, preferring to take a “big bath” in the current period in order to report higher future earnings. If the news is “good,” the manager smoothes earnings, with the amount of smoothing depending on the level of cashflows observed. He either over‐reports or partially under‐reports for slightly good news, and gradually increases his under‐reporting as the news gets better, until he is under‐reporting the maximum amount for sufficiently good news. This result holds both when investors are “naïve” and ignore management’s ability to manipulate earnings, or “sophisticated” and correctly infer management’s disclosure strategy.

We examine how community banks respond to liquidity shocks created by natural disasters. We address community banks’ responses to liquidity shocks due to their focused geographic and economic presence, which coincide with their communities’ exposure to the disasters and the ability of the local banks to meet their needs. We find that community banks respond to liquidity shocks by managing their balance sheet, rather than any single balance sheet account. In particular, we find that they respond to the liquidity needs of their communities by increasing loans as deposits are withdrawn.

Macro news can affect currency prices directly and indirectly via order flow. Past research shows that the direct effects of scheduled macro news account for less than 10% of daily price variance. This paper shows that the arrival of macro news can account for more than 30% of daily price variance. Two features of our analysis account for this finding: (1) We consider the broad spectrum of macro news items that market participants observe, not just scheduled announcements. (2) We allow the arrival of news to affect prices indirectly via its impact on the volatility of order flow. Our analysis shows that order flow variations contribute more to currency price dynamics following the arrival of public macro news than at other times. This is not consistent with news effects being common knowledge that is impounded in price directly. Roughly two-thirds of the total effect of macro news on the DM/$ exchange rate is transmitted via order flow.