Knowledge that Transforms

A dynamic stochastic general equilibrium model with recursive utility, search frictions, and capital accumulation is a good start to forming a unified theory of asset prices and business cycles. The model reproduces an equity premium of 4.27% per annum, a stock market volatility of 12.42%, and an average interest rate of 1.97%, while retaining plausible business cycle dynamics. The equity premium and stock market volatility are strongly countercyclical, whereas the interest rate and consumption growth are largely unpredictable. Because of wage inertia, dividends are procyclical despite consumption smoothing via investment. The welfare cost of business cycles is huge, 33.6%.

We find that 30-minute changes in bond yields around scheduled Federal Open Market Committee (FOMC) announcements are predictable with the pre-FOMC Blue Chip professionals’ revisions in GDP growth forecasts. A positive pre-FOMC GDP growth revision predicts a contractionary policy news shock (positive change in bond yields), a negative GDP growth revision predicts an expansionary policy news shock (negative change in bond yields). Failing to account for this predictability biases the estimates of monetary policy effects on the economy. First, the Fed’s information effect dissipates as the truly unpredictable policy news shock does not affect professionals’ beliefs about the economy. Second, net policy shock has a more negative impact on actual future GDP than the raw policy shock.

We document that (i) debt-to-equity ratios and levered equity betas negatively covary with the market risk premium in distressed firms; (ii) the negative covariance generates negative alphas among those firms. We build a dynamic credit risk model to understand the negative covariance between equity betas and the market risk premium, via endogenous and dynamic debt financing over the business cycles. Because of endogenous debt financing and distress, our model naturally connects the negative failure probability-return relation to the positive distress risk premium-return relation.

Outside of flood hazard zones, households must decide whether to insure or rely on disaster assistance to manage flood risk. We use the quasi-random flooding generated by Hurricane Harvey, which hit Houston in August 2017, to understand the implications of flood losses for households with differing access to insurance and credit. Outside the floodplain, credit-constrained homeowners experience a 20% increase in bankruptcies and a 13% increase in the share of debt in severe delinquency in flooded blocks relative to non-flooded areas. Treatment effects are universally insignificant inside the floodplain, implying that flood insurance mitigates the financial impact of flooding across the credit distribution. Disaster assistance, on the other hand, does not appear to counteract the role of initial inequalities on post-disaster credit outcomes. We find SBA disaster loans and, more surprisingly, FEMA grants to both be regressive in allocation. Our results highlight that averages mask important heterogeneity after disasters, which challenges existing narratives of how effectively Federal disaster programs mitigate the financial burden of natural disasters.

We find that expected return is related to trading volume positively among underpriced stocks but negatively among overpriced stocks. As such, trading volume amplifies mispricing. Our results are robust to alternative mispricing and trading volume measures, alternative portfolio formation methods, and controlling for variables that are known to have amplification effects on mispricing. By attributing trading volume to investor disagreement, we show that our results are consistent with the recent theoretical model of Atmaz and Basak (2018) in that investor disagreement predicts stock returns conditional on expectation bias.

Financially constrained mortgage servicers destroyed substantial MBS investor value during the financial crisis through their management of delinquent mortgages. Servicers advance to investors monthly payments missed by borrowers. In order to minimize this obligation to extend financing to distressed borrowers, constrained servicers aggressively pursued foreclosures and modifications at the expense of investors, borrowers, and future mortgage performance. When agency frictions between the servicer and the investor are higher, the servicer’s financial constraints matter more. IV regressions suggest that, on average per defaulted loan, servicers’ financial constraints are responsible for 20% of the total investor value reduction during the financial crisis.

The Federal Open Market Committee (FOMC) meetings are among the most important economic events. We propose a novel method to recover the FOMC risk premium and drift sizes. Empirically, we find that for the 192 meetings from 1996 to 2019, the FOMC risk premium varies across meetings, from 1 to 326 basis points (bps) with an average of 45 bps. We obtain an out-of-sample R2 of 7.51% when using the recovered FOMC premium to predict the meeting returns around the announcement. The average predicted upward drift size is 101 bps, and the average predicted downward drift size is 129 bps, matching well with the realized ones.

We measure value creation by activist investors via structural estimation of a model of the choice between passive investment and activism. Our estimates imply that average returns following activist intent announcements consist of 74.8% expected value creation, or treatment, 13.4% stock picking, and 11.8% sample selection effects. Higher treatment values predict improvements in firm performance and lower proxy contest probabilities, whereas abnormal announcements returns do not, suggesting that our estimate identifies more effective activism campaigns. The evidence demonstrates the importance of using the joint distribution of investment strategies and announcement returns to recover the expected returns and costs of activism.

We study how the disclosure of corrupt practices affects the growth of firms involved in illegal interactions with the government using randomized audits of public procurement in Brazil. On average, firms exposed by the anti-corruption program grow larger after the audits, despite experiencing a decrease in procurement contracts. We manually collect new data on the details of thousands of corruption cases, through which we uncover a large heterogeneity in our firm-level effects depending on the degree of involvement in corruption. Using investment-, loan-, and worker- level data, we show that the average exposed firms adapt to the loss of government contracts by changing their investment strategy. They increase capital investment and borrow more to finance such investment, while there is no change in their internal organization. We provide qualitative support to our results by conducting new face-to-face surveys with business owners of government-dependent firms.

This paper estimates the effect of bankruptcy court caseload on access to credit by exploiting firms’ plausibly exogenous exposure to the largest recorded drop in court backlog in the United States following the 2005 consumer bankruptcy reform. I show that a drop in court congestion reduces the time firms spend in bankruptcy and increases recovery values, which is priced into credit spreads and loan maturities. Consistent with a shock to credit supply, less congested courts increase firm leverage but leave default risk unchanged. A back-of-the-envelope calculation suggests that backlog in bankruptcy courts costs corporate borrowers at least $740 million per year in interest payments.