This paper examines the impact of the conglomerate form on the scale and novelty of corporate Research and Development (R&D) activity. I exploit a quasi-experiment involving failed mergers to generate exogenous variation in acquisition outcomes of target firms. A difference-in-differences estimation reveals that, relative to failed targets, firms acquired in diversifying mergers produce both a smaller number of innovations and also less-novel innovations, where innovations are measured using patent-based metrics. The treatment effect is amplified if the acquiring conglomerate operates a more active internal capital market and is largely driven by inventors becoming less productive after the merger rather than inventor exits. Concurrently, acquirers move R&D activity outside the boundary of the firm via the use of strategic alliances and joint ventures. There is complementary evidence that conglomerates with more novel R&D tend to operate with decentralized R&D budgets. These findings suggest that conglomerate organizational form affects the allocation and productivity of resources.

We follow a representative panel of millions of consumers in the United States from 2007 to 2017 and document new facts on the long-term effects of the Great Recession. There were about six million foreclosures over this period. Only a quarter of foreclosed households regained homeownership, taking an average four years to do so. This persistent loss of homeownership accounts for most of the decline in the U.S. homeownership rate. Despite massive stimulus and debt relief policies, house prices, consumption, and unemployment remained below precrisis levels in about half of the zip codes in the United States Regions that recovered to precrisis levels took on average four to five years. Regional variation in the extent and speed of recovery is strongly and persistently associated with frictions affecting the pass-through of lower interest rates and debt relief to households.

We examine whether securitization impacts renegotiation decisions of loan servicers, focusing on their decision to foreclose a delinquent loan. Conditional on a loan becoming seriously delinquent, we find a significantly lower foreclosure rate associated with bank-held loans when compared to similar securitized loans: across various specifications and origination vintages, the foreclosure rate of delinquent bank-held loans is 3% to 7% lower in absolute terms (13% to 32% in relative terms). There is a substantial heterogeneity in these effects with large effects among borrowers with better credit quality and small effects among lower quality borrowers. A quasi-experiment that exploits a plausibly exogenous variation in securitization status of a delinquent loan confirms these results.

This article examines the link between mortgage securitization and lender screening during the boom and bust of the U.S. housing market. Using comprehensive data on both prime and subprime securitized and bank-held loans, we provide evidence that securitization affected lenders' screening decisions in the subprime market for low-documentation loans through two channels: the securitization rate and the time it takes to securitize a loan. The change in decision-making by subprime lenders occurs on dimensions that are unreported to investors. Examining the time-series evolution of the securitization market further reinforces these findings. We exploit heterogeneity across subprime and prime markets to illustrate that the potential for moral hazard may be reduced with greater collection of hard information and increased monitoring of lenders. Our results suggest that the policy debate regarding securitization and lenders' underwriting standards should separately evaluate the agency and non-agency markets, with special attention toward the extent of soft information in assets being securitized.

We document that contractual disclosures by intermediaries during the sale of mortgages contained false information about the borrower's housing equity in 7–14% of loans. The rate of misrepresented loan default was 70% higher than for similar loans. These misrepresentations likely occurred late in the intermediation and exist among securities sold by all reputable intermediaries. Investors—including large institutions—holding securities with misrepresented collateral suffered severe losses due to loan defaults, price declines, and ratings downgrades. Pools with misrepresentations were not issued at a discount. Misrepresentation on another easy‐to‐quantify dimension shows that these effects are a conservative lower bound.

Patents and citations are powerful tools increasingly used in financial economics (and management research more broadly) to understand innovation. Biases may result, however, from the interactions between the truncation of patents and citations and the changing composition of inventors. When aggregated at the firm level, these patent and citation biases can survive popular adjustment methods and are correlated with firm characteristics. These issues can lead to problematic inferences. We provide an actionable checklist to avoid biased inferences and also suggest machine learning as a potential new way to address these problems.

We argue and demonstrate that resource allocation within firms' internal capital markets provides an important force countervailing financial market dislocation. We estimate a structural model of internal capital markets to separately identify and quantify the forces driving the reallocation decision and illustrate how these forces interact with external capital market stress. The weaker (stronger) division obtains too much (little) capital, as though it is 12% (9%) more (less) productive than it really is. Out-of-sample simulated data are consistent with the actual data showing that internal capital markets offset financial market stress during the recent financial crisis by 16%–30%.

A central question surrounding the current subprime crisis is whether the securitization process reduced the incentives of financial intermediaries to carefully screen borrowers. We examine this issue empirically using data on securitized subprime mortgage loan contracts in the United States. We exploit a specific rule of thumb in the lending market to generate exogenous variation in the ease of securitization and compare the composition and performance of lenders' portfolios around the ad hoc threshold. Conditional on being securitized, the portfolio with greater ease of securitization defaults by around 10%–25% more than a similar risk profile group with a lesser ease of securitization. We conduct additional analyses to rule out differential selection by market participants around the threshold and lenders employing an optimal screening cutoff unrelated to securitization as alternative explanations. The results are confined to loans where intermediaries' screening effort may be relevant and soft information about borrowers determines their creditworthiness. Our findings suggest that existing securitization practices did adversely affect the screening incentives of subprime lenders.

We show theoretically that the responsiveness of a fund manager's portfolio allocations to changes in public information decreases in the manager's skill. We go on to estimate this sensitivity ( RPI ) as the R 2 of the regression of changes in a manager's portfolio holdings on changes in public information using a panel of U.S. equity funds. Consistent with RPI containing information related to managerial skills, we find a strong inverse relationship between RPI and various existing measures of performance, and between RPI and fund flows. We also document that both fund‐ and manager‐specific attributes affect RPI .

This article studies the impact of the arbitrator selection process on consumer outcomes. Using data from consumer arbitration cases in the securities industry over the past two decades, where we observe detailed information on case characteristics, the randomly generated list of potential arbitrators presented to both parties, the selected arbitrator, and case outcomes, we establish several motivating facts. These facts suggest that firms hold an informational advantage over consumers in selecting arbitrators, resulting in industry-friendly arbitration outcomes. We then develop and calibrate a quantitative model of arbitrator selection in which firms hold an informational advantage in selecting arbitrators. Arbitrators, who are compensated only if chosen, compete with each other to be selected. The model allows us to decompose the firms’ advantage into two components: the advantage of choosing pro-industry arbitrators from a given pool and the equilibrium pro-industry tilt in the arbitration pool that arises because of arbitrator competition. Selecting arbitrators without the input of firms and consumers would increase consumer awards by $60,000 on average relative to the current system. Forty percent of this effect arises because the pool of arbitrators skews pro-industry due to competition. Even an informed consumer cannot avoid this pro-industry equilibrium effect. Counterfactuals suggest that redesigning the arbitrator selection mechanism for the benefit of consumers hinges on whether consumers are informed. Policies intended to benefit consumers, such as increasing arbitrator compensation or giving parties more choice, would benefit informed consumers but hurt the uninformed.