We estimate and trace a credit demand curve for households that recently experienced damage to their homes from a natural disaster. Our administrative data include over one million applicants to a federal recovery loan program for households. We estimate extensive‐margin demand over a large range of interest rates. Our identification strategy exploits 24 natural experiments, leveraging exogenous, time‐based variation in the program's offered interest rate. Interest rates meaningfully affect consumer demand throughout the distribution of rates. On average, a 1 percentage point increase in the interest rate reduces loan take‐up by 26%. We find a large impact of applicants' credit quality on demand and evidence of monthly payment targeting. Using our estimated demand curve and information on program costs, we find that the program generates an average social surplus of $2900 per borrower.

Katrina Ellis, Roni Michaely, Maureen O'Hara, The Accuracy of Trade Classification Rules: Evidence from Nasdaq, The Journal of Financial and Quantitative Analysis, Vol. 35, No. 4 (Dec., 2000), pp. 529-551

A model of a single-commodity, closed economy is constructed in which the commodity price is fixed and its market clears by quantity adjustment. The distinctive feature is that the real wage and employment are determined by bargaining between unions, representing workers and firms. There are several possible regimes, some with labor hoarding. The effects of changes in autonomous spending and the reservation wage on the endogenous variables of the model, including employment and the real wage are discussed. Some interesting possibilities emerge for the cyclical movement of productivity and the real wage.

The dynamics of house prices, sales, construction, and population growth in response to city-specific income shocks are characterized for 106 US cities. A dynamic model of search in the housing market in which construction, the entry of buyers, house prices, and sales are determined in equilibrium is then developed. The theory generates dynamics qualitatively consistent with the observations and a version calibrated to match key features of the US housing market offers a substantial quantitative improvement over models without search. In particular, variation in the time it takes to sell induces transaction prices to exhibit serially correlated growth. (JEL D83, R21, R23, R31)

We provide the first examination of hedge fund boards and their directors. The majority of directorships are held by extremely busy independent directors. These directors are sought by funds because they have more reputational capital at stake, making them independent and credible monitors whose presence can certify fund quality to investors. Busy independent directors are more likely to be hired by high-quality funds, and their departure from the board is associated with investor withdrawals. Moreover, funds with busy independent directors are less likely to commit fraud, abuse discretionary liquidity restrictions, or engage in performance-based risk shifting.

We examine the potential for selection bias in voluntarily reported hedge fund performance data. We construct a set of hedge fund returns that have never been reported to a commercial hedge fund database. These returns allow a direct comparison of performance between funds that choose to report to commercial databases and funds that do not. We find that funds that report their performance to commercial databases significantly outperform nonreporting funds. Our results suggest that the voluntarily reported performance in commercial databases suffers from a selection bias that may exaggerate the average skill of the universe of hedge fund managers.