In Los Angeles, all-cash home purchases quintupled during the last decade. Compared with an else-equal mortgage offer, a cash offer is associated with 29 percent shorter time-to-close and a 2–3.9 percent price discount, indicating a substantial amount of financing risk—the risk to a seller that a transaction may not close on time and may fail to occur again because a mortgage contingency fails. The estimated cash discount aligns well with a canonical model calibrated to the sample market. Our findings reveal that closing risk alone is insufficient to explain the cash discount. Rather, it turns on the possibility that a property back on the market may fail to sell, requiring a substantial risk compensation. The estimated cash discount is smaller during booms and in larger markets, highlighting the inseparability of financial frictions in the mortgage market and search frictions in the housing market.

This study introduces a novel mood metric—blockbuster movie releases—and investigates its correlation with stock market dynamics. We document a significant positive correlation between blockbuster movie releases and US stock market returns in the subsequent week. This pattern remains robust across various robustness tests both in-sample and out-of-sample. The changes in weekly box office revenue and increased Internet searches for movie-related terms further affirm this relationship. Moreover, releases of blockbuster movies predict lower expected market volatility and risk aversion. The positive predictive effect on market returns is also evident in international markets.

This paper examines the role of local politicians’ patronage connections to top political leaders (i.e., the Central Committee of the Communist Party of China) in privatization outcomes. We find that connected local politicians are more likely to sell state-owned enterprises (SOEs) to corrupt buyers at substantially discounted prices. The SOEs purchased by corrupt buyers engage in significantly more fraudulent and corrupt activities following privatization and thus perform worse. For identification, we use the mandatory retirement ages of Central Committee members in a fuzzy regression discontinuity design. When local politicians lose their connections because Central Committee members step down after reaching mandatory retirement ages, we find a 14.4 percentage point drop in the likelihood of choosing corrupt buyers and a 90.13% drop in price discounts for privatization sales. Consequently, the privatized SOEs experience jumps in efficiency gains after the age cut-offs for mandatory retirement.

Using a panel of Dutch listed firms this paper provides empirical evidence for the hypothesis that more risky firms are confronted with more severe capital market constraints than relatively less risky firms. The paper also contributes to the discussion on the usefulness of cash flow as a measure of financial constraints. We present a stochastic version of the Kaplan-Zingales (1997) model. We show that cash flow sensitivity can be used as a meaningful indicator of financing constraints if firms are classified by the degree of uncertainty they face and if the uncertainty originates from cost uncertainty.

This paper proposes a simple back testing procedure that is shown to dramatically improve a panel data model's ability to produce out of sample forecasts. Here the procedure is used to forecast mutual fund alphas. Using monthly data with an OLS model it has been difficult to consistently predict which portfolio managers will produce above market returns for their investors. This paper provides empirical evidence that sorting on the estimated alphas populates the top and bottom deciles not with the best and worst funds, but with those having the greatest estimation error. This problem can be attenuated by back testing the statistical model fund by fund. The back test used here requires a statistical model to exhibit some past predictive success for a particular fund before it is allowed to make predictions about that fund in the current period. Another estimation problem concerns the use of a single statistical model for all available mutual funds. Since no one statistical model is likely to fit every fund, the result is a great deal of misspecification error. This paper shows that the combined use of an OLS and Kalman filter model increases the number of funds with predictable out of sample alphas by about 60%. Overall, a strategy that uses very modest ex-ante filters to eliminate funds whose parameters likely derive primarily from estimation error produces an out of sample risk-adjusted return of over 4% per annum.

We suggest that forward guidance, via publicly committing the central bank to future actions and creating associated expectations, fundamentally affects bank lending decisions independently of other forms of monetary policy. To test this hypothesis, we build a forward guidance measure based on the language used in the Federal Open Market Committee meetings and match this measure with syndicated loans. Our results show that expansionary forward guidance decreases corporate loan spreads and that this effect is stronger for well-capitalized banks lending to riskier firms. Forward guidance also affects nonprice lending terms, such as covenants, performance pricing provisions, and the loan syndicate structure. Additionally, banks tend to initiate new lending relationships with lower spreads after forward guidance issuance.

While credit default swaps (CDSs) can be used to hedge credit risk exposures or to speculate, we examine another use of them: banks buy CDS referencing their borrowers to obtain regulatory capital relief. Such capital relief activities have unintended consequences, as banks extend riskier loans when they buy CDS to boost capital ratios. While capital-induced CDS-user banks achieve higher profitability during normal times, they perform worse and request more government support in crisis periods than other banks that use CDS for trading or speculation. Our findings suggest that banks’ CDS trading for capital relief purposes may make these banks riskier.