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.”

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.

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.

We examine the impact of employee-related Corporate Social Responsibility (ER-CSR) on pay disparity between top management and the average worker. Firms with higher ER-CSR ratings have a lower pay disparity and the effect is greatest when executives are paid the most. ER-CSR is associated with a lower ratio of top management's cash and long-term incentive compensation, relative to the average employee's pay. We find that the negative relation is driven by socially responsible firms paying their average employees more. Finally, we document that CSR activities related to employee relations and diversity are those leading to a significant pay disparity reduction.

In this study, we examine whether the use of artificial intelligence (AI) can reduce the effect of independence conflicts on audit firm liability. In two experiments, we manipulate (1) whether procedures are performed by a human auditor or with AI and (2) whether the audit firm was careful in maintaining the appearance of independence from the audit client. Results of both experiments indicate that the use of AI significantly reduces the impact of the appearance of independence conflicts on jurors' judgments of audit firm liability. When concerns relating to the appearance of independence conflicts are present, the use of AI helps maintain the perceived objectivity of the auditor, which results in jurors maintaining higher overall trust in the audit process. Our study contributes to literature on determinants of auditor litigation risk and how technological change that is likely to grow in prominence might affect audit firm liability.

We study how a market uses temporary workers to accommodate extraordinary demand shocks. When COVID-19 surges, hospitals need additional nurses—especially in specialties central to COVID-19 care. By comparing markets for COVID-relevant and other specialties, we show that the market for travel nurses expands dramatically and estimate travel nurse labor supply across space. Supply is quite elastic, as workers can choose to travel where they are needed. Workers travel longer distances to temporary jobs when payment increases, suggesting that an integrated national market facilitates reallocation when demand spikes. But when national cases peak, travel distance is less responsive to local demand.

We assemble a property-level panel of appraiser-reported attributes associated with 4.6 million loan applications from 2013 to 2017 to test whether attributes were consistently reported. Appraisers have an incentive to misreport property attributes to justify higher appraised values to ensure that associated mortgage loans are approved. We focus on property transactions with multiple sets of attributes reported by the same appraiser within four quarters and find evidence consistent with an intent to inflate valuations through attribute misreporting. We find that strategic misreporting of attributes is prevalent across markets, and that highly leveraged borrowers whose appraisals had inconsistently reported attributes were 9.8 percent more likely to become seriously delinquent in their loan payments.