Decision Making & Negotiations

This paper estimates a structural model of unconventional monetary policy transmission through bank balance sheets using cross-sectional instruments for loan and deposit demand. We estimate the demand for banking at a branch-specific level from the response of a bank's quantities at one branch to interest rate changes caused by demand shocks at other branches. Depositors are considerably less sensitive to interest rates than corporate or mortgage borrowers.

Using a novel dataset of over 3,500 public and private firms, we construct the network of firm connections through executives and directors on the eve of the 1929 financial market crash. We find that more connected firms have 17% higher 10-year survival rates on average. Consistent with a role in facilitating access to working capital, the results are particularly strong for small firms, private firms, cash-poor firms, and firms located in counties with high bank suspension rates during the crisis.

"Big data" financial technology raises concerns about market inefficiency. A common concern is that the technology might induce traders to extract others' information, rather than to produce information themselves. We allow agents to choose how much they learn about future asset values or about others' demands, and we explore how improvements in data processing shape these information choices, trading strategies and market outcomes. Our main insight is that unbiased technological change can explain a market-wide shift in data collection and trading strategies.

The Great Recession was a deep downturn with long-lasting effects on credit, employment and output. While narratives about its causes abound, the persistence of GDP below pre-crisis trends remains puzzling. We propose a simple persistence mechanism that can be quantified and combined with existing models. Our key premise is that agents don't know the true distribution of shocks, but use data to estimate it non-parametrically. Then, transitory events, especially extreme ones, generate persistent changes in beliefs and macro outcomes.

The Centers for Medicare & Medicaid Services (CMS) and the National Quality Forum have endorsed the 30-day mortality rate as an important indicator of hospital quality. Concerns have been raised, however, as to whether post-discharge mortality rates are reasonable measures of hospital quality as they consider the frequency of an event that occurs after a patient is discharged and no longer under the watch and care of hospital staff. Estimating the causal effect of length-of-stay (LOS) on post-discharge mortality from retrospective data introduces a number of econometric challenges.

This paper shows that when the bankruptcy code protects the creditors' rights with no impairments to secured creditors, issuance of debt such as repo with exemption from automatic stay adds no value. When the bankruptcy process admits violations of absolute priority rules or results in collateral impairments to secured creditors, the liability structure includes short-term debt, with safe harbor protection when the pledged collateral satisfies a minimum liquidity threshold.

How does access to public equity markets affect real outcomes? We examine the human capital of IPO-filing firms and how going public affects their labor force. While IPO-filing ?rms have high average wages and limited industrial diversification, a successful IPO increases departures of high-wage employees to startups and triggers industrial diversification through employment growth in non-core industries. Surprisingly, IPOs do not significantly affect earnings growth of pre-IPO workers. Instead, post-IPO hires receive larger earnings increases upon joining.

A key distinction between over-the-counter markets and centralized exchanges is the non-anonymity of the transactions. In this paper, we develop a model of non-anonymous trading and compare its prices, liquidity, and efficiency of asset allocations against a baseline with anonymous transactions. The non-anonymity improves the market liquidity by reducing the concerns for adverse selection. More specifically, it allows the market participants to learn valuable information about their counterparties through repeated interactions and consequently enables them to form trading relationships.

Salary history bans forbid employers from asking job candidates to disclose their salaries. However, applicants can still volunteer this information. Our theoretical model predicts the effect of these laws varies by how workers comply. Our survey of Americans in the labor force finds candidates fall into three compliance types: 25% always disclose their salary whether asked or not, 17% never disclose, and 58% comply with the ban (disclosing only when asked). Importantly, compliance type varies by demographics (e.g.