Information, which can arrive in multiple forms, is a fundamental component of all financial transactions and markets. We define hard and soft information and describe the relative advantages of each. Hard information is quantitative, is easy to store, and can be transmitted in impersonal ways. Its information content is independent of its collection. As technology changes, the way we collect, process, and communicate information, it changes the structure of markets, the design of financial intermediaries, and the incentives to use or misuse information. We survey the literature to understand how information type influences the continued evolution of financial markets and institutions. Received October 25, 2016; editorial decision September 6, 2018 by Editor Efraim Benmelech.

This paper investigates marriage market equilibrium when bargaining in marriage (BIM) determines allocation within marriage. In contrast, the standard marriage market model assumes that prospective spouses make binding agreements in the marriage market (BAMM) that determine allocation within marriage. When BIM determines allocation within marriage, the appropriate framework for analyzing marriage market equilibrium is the Gale-Shapley matching model, not the Koopmans-Beckmann-Shapley-Shubik assignment model. BIM and BAMM have different implications not only for allocation within marriage but also for who marries, who marries whom, the number of marriages, and the Pareto efficiency of marriage market equilibrium.

We analyzed the loan guarantees that the Japanese government provided for banks’ loans to small and medium-sized enterprises (SMEs). We modeled and estimated how much and under what conditions loan guarantees affected banks’ risk-taking and banks’ non-guaranteed lending. In the presence of controls for bank capital and other factors that might affect supplies of bank credit, our estimates supported our model's implications that loan guarantees increased banks’ risk-taking. Consistent with our model, our estimates imply that, when banks initially had fewer guaranteed loans and then got more guaranteed loans, guaranteed loans were complements to, rather than substitutes for, non-guaranteed loans. As complements, loan guarantees could be “high-powered” in that they generated increases not only in guaranteed loans, but also increases in non-guaranteed loans that were a multiple of the increases in guaranteed loans. In addition, banks’ having more capital was associated with doing more non-guaranteed lending.

This paper investigates whether the institutional affiliation of a collateralized loan obligation (CLO) manager influences the manager's access to information and risk appetite. We find that CLO managers affiliated with banks start to sell off their positions in loans arranged by their bank well before the onset of default. In contrast, CLO managers affiliated with nonbanks do not lower their exposures to distressed loans. These findings are consistent with bank-affiliated CLO managers being more risk averse, but they could also derive from them having access to valuable information. On close inspection, we find that although bank-affiliated CLO managers are averse to holding any distressed loans, they are also more aggressive at divesting distressed loans arranged by their parent bank, suggesting that they benefit from an information wedge. Besides helping us understand CLO managers’ trading activities, our findings highlight a potential limit to banks’ ability to originate loans and distribute them via their affiliated CLOs.

This paper investigates the optimal monetary instrument in a New-Keynesian model with multiple monetary assets. We compare a standard interest rate rule to a k-percent rule for three alternative monetary aggregates determined within our model: the monetary base, the simple sum measure of money, and the Divisia measure. Welfare results are striking. While the interest rate dominates the other two monetary aggregate k-percent rules, the Divisia k-percent rule outperforms the interest rate rule. Next we study the ability of Granger Causality tests – in the context of data generated from our model – to correctly identify welfare improving instruments. We find the interest rate Granger Causes both output and prices at extremely high significance levels. The same result is obtained for monetary base and the simple-sum monetary aggregate. The test results for Divisia are the weakest as Divisia fails to Granger Cause prices. We conclude that if the choice of instrument is based solely on its propensity to Granger Cause macroeconomic targets, a central bank may choose an inferior policy instrument.

This paper derives the user cost of monetary assets and credit card services with interest rate risk under the assumption of intertemporal non-separability. Barnett and Su (2016) derived theory permitting inclusion of credit card transaction services into Divisia monetary aggregates. The risk adjustment in their theory is based on consumption capital asset pricing model (CCAPM) under intertemporal separability. The equity premium puzzle focusses on downward bias in the CCAPM risk adjustment to common stock returns. Despite the high risk of credit card interest rates, the risk adjustment under the CCAPM assumption of intertemporal separability might nevertheless be similarly small. While the known downward bias of CCAPM risk adjustments are of little concern with Divisia monetary aggregates containing only low risk monetary assets, that downward bias cannot be ignored, once high risk credit card services are included. We believe that extending to intertemporal non-separability could provide a non-negligible risk adjustment, as has been emphasized by Barnett and Wu (2015). In this paper, we extend the credit-card-augmented Divisia monetary quantity aggregates to the case of risk aversion and intertemporal non-separability in consumption. Our results are for the “representative consumer” aggregated over all consumers. While credit-card interest-rate risk may be low for some consumers, the volatility of credit card interest rates for the representative consumer is high, as reflected by the high volatility of the Federal Reserve’s data on credit card interest rates aggregated over consumers. One method of introducing intertemporal non-separability is to assume habit formation. We explore that possibility.

We examine the effects on IPO uncertainty of an alternative going-public mechanism – the two-stage IPO, where a firm first gets quoted on the OTC market, and then upgrades to a national exchange where it first issues public equity. We find that a two-stage IPO firm experiences lower underpricing and return volatility than does a similar traditional IPO firm. Our study is the first to analyze the impact of U.S. pre-IPO disclosure and liquidity on levels of uncertainty and pricing at the IPO stage. We find that greater disclosure and liquidity during the first stage leads to greater reduction in IPO uncertainty. We control for the potentially endogenous nature of the two-stage IPOs by using a difference-in-difference analysis that utilizes two exogenous OTC market events.

We propose a distress measure for national banking systems that incorporates not only banks’ CDS spreads, but also how they interact with the rest of the global financial system via multiple linkage types. The measure is based on a tensor decomposition method that extracts an adjacency matrix from a multi-layer network, measured using banks’ foreign exposures obtained from the BIS international banking statistics. Based on this adjacency matrix, we develop a new network centrality measure that can be interpreted in terms of a banking system's credit risk or funding risk.