Gary D. Libecap of University of California, Santa Barbara reviews “Liquid Asset: How Business and Government Can Partner to Solve the Freshwater Crisis” by Barton H. Thompson Jr. The Econlit abstract of this book begins: “Examines the growing freshwater challenges facing the United States and the world, focusing on the growing role of private organizations in the US water sector.”

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.

Assume data on Nj stock (asset) returns are available for p stocks, allowing us to construct approximate density functions f(xj) for (j=1, 2, …, p) from p empirical cumulative distribution functions (ECDFs). Our portfolio choice is designed to rank ECDF-induced, ill-behaved f(xj) densities subject to multiple modes, asymmetric fat tails, dips, turns, and numerous overlaps. Older portfolio theory assumes that parameters like the mean, variance, and percentiles fully describe f(xj). All six of our algorithms avoid (expected) utility theory. The only available algorithm by Anderson for order-k Stochastic Dominance (SDk) needs a trapezoidal approximation. Our new exact algorithm for SDk is based on ECDFs and overcomes pairwise comparisons. We include algorithms for statistical inference using the bootstrap and one for “pandemic proof” out-of-sample portfolio performance comparisons from our R package ‘generalCorr’. We suggest a test for “zero cost profitable arbitrage” and illustrate our algorithms in action by using two sets of recent 169-month stock returns. We do not claim to suggest new optimal portfolios.

How does lending-market competitiveness shape new firms’ financing? Using a unique U.S. representative panel of new firms, we document that in more concentrated local lending markets: (a) new firms are less likely to access credit; (b) new firms have lower leverage; and (c) the best-performing firms are more severely affected by reduced debt financing. We develop a contingent-claims model with monopolistically competitive banks that rationalizes these facts and shows how credit-market conditions determine loan fees and concentration. Our findings highlight banks’ market power as a channel through which the financial sector influences firms’ development and, hence, economic growth.

We examine the effect of the composition of the board of directors on the firm’s chief executive officer (CEO) hiring decision. Using a novel measure of managerial talent, characterized by an individual’s ascent in the corporate hierarchy, we show that firms with non-CEO inside directors tend to hire CEOs with greater managerial skills. This effect obtains for both internal and external CEO hires; moreover, the effect is pronounced when inside directors have stronger reputational incentives and limited access to soft information about the candidate. Our findings demonstrate that boards with inside directors more effectively screen for managerial talent, thereby improving the CEO hiring process.

This paper studies accounting and silence. Building on studies of accounting talk and introducing theories of “silencing,” we highlight the role of accounting silences in the production of engaging organizational conversations. Through a qualitative case study, we identify three forms of silence—the unspeakable, the unsaid, and the inaudible—and their links to accounting. Silences create motivations to engage in further accounting talk, but they also deny certain groups a voice in those conversations. An impression of participation, openness, and transparency emerges despite unequal access and the silencing of certain groups. Accounting itself can be silenced to avoid uncomfortable topics, potential problems, and anxiety‐inducing uncertainties. This silencing may serve to preserve a useful ignorance, avoid being in the know, and build alluring narratives and engaging conversations. Accounting silences sustain such conversations by protecting them from alternative voices, unsettling knowledge, and narratives that are incompatible with the organization's preferred story.

Research suggests that the standard model used to detect opportunistic shifting of core expenses to special items is potentially biased. Such bias has been attributed to the use of accruals, including special item related accruals, as a control for the impact of performance on core earnings in this model. This paper provides an improved classification shifting model which both tests for such accruals-related bias and controls for other sources of error in the measurement of shifting. The paper also modifies conventional market rationality tests in accounting research to examine new dimensions of rationality in relation to measurement and valuation of shifting. The main empirical findings are as follows. First, the improved classification shifting model provides strong evidence of shifting and rejects the hypothesis that inclusion of accruals in the model causes bias. Second, estimates of shifted core expenses generated by the improved model exhibit forecasting properties of shifted earnings. Third, rationality test results are broadly consistent with rationality in relation to shifted core expenses but indicate possible partial (ir)rationality in relation to adjusted special items (i.e., special items excluding shifted core expenses). Further analysis of the latter findings, however, suggests they are more likely related to risk than irrationality. Overall, the paper contributes to improved measurement of shifting and highlights the importance of considering rational expectations when examining stock returns associated with shifting.

Traders may run on financial markets merely out of fear of future liquidity shocks. We present a model that shows that adequately calibrated circuit breakers can prevent such coordination failures by curbing excessive trading. It suggests a novel, forward-looking circuit breaker that becomes most restrictive in cases when expected welfare losses of inefficient market runs are largest. The probabilities of current and future liquidity shortages are important determinants for such welfare-optimized circuit breakers. We empirically illustrate how to calibrate these parameters. We also determine under which economic conditions circuit breakers damage welfare and should not be implemented.

This paper compares three methods for assessing the contagion of risk among ten Globally Significant International Banks, known as GSIBs, listed on the New York Stock Exchange with daily and weekly data sets from 2007 to 2020, based on Machine Learning and Network Analysis. In particular we identify the banks which are the largest net sources or transmitters of risk, and net receptors of risk. We also examine the response of regulatory actions, in the form of fines and BIS Bin Classification for capital adequacy. Under alternative risk measures, of Range Volatility (RV) of share prices, Credit Default Swap (CDS) premia, and Conditional Value at Risk (ΔCoVar), there is a stronger and significant connection between Contagion and the BIS Bin classifications relative to the connections between Contagion and banking fines, either in the amount or frequency of the fines. These results show that BIS bin classifications respond positively to underlying signals of increased contagion in the form of Range Volatility (RV) and ΔCoVar measures but not to CDS risk premia.

Central banks wish to avoid self‐fulfilling fluctuations. Interest rate rules with a unit response to real rates achieve this under the weakest possible assumptions about the behavior of households and firms. They are robust to household heterogeneity, hand‐to‐mouth consumers, non‐rational household or firm expectations, active fiscal policy, and to any form of intertemporal or nominal‐real links. They are easy to employ in practice, using inflation‐protected bonds to infer real rates. With a time‐varying short‐term inflation target, they can implement an arbitrary inflation path, including optimal policy. This provides a way to translate policy makers' desired path for inflation into one for nominal rates. U.S. Federal Reserve behavior is remarkably close to that predicted by a real rate rule, given the desired inflation path of U.S. monetary policy makers. Real rate rules work thanks to the key role played by the Fisher equation in monetary transmission.