Knowledge that Transforms

We estimate the effect of carbon pricing policy on bank credit to greenhouse-gas-emitting firms. Our analyses exploit the geographic restrictions inherent in California’s cap-and-trade bill and a discontinuity in the embedded free permit threshold of the federal Waxman-Markey cap-and-trade bill. Affected high emission firms face shorter loan maturities, lower access to permanent forms of bank financing, higher interest rates, and higher participation of shadow banks in their lending syndicates. These effects are concentrated among private firms, while credit terms of public firms are largely unaffected. Overall, we show that banks respond quickly to realizations of transition risk.

Analyst forecasts outperform econometric forecasts in the short run but underperform in the long run. We decompose these differences in forecasting accuracy into analysts’ information advantage, forecast bias, and forecast noise. We find that noise and bias strongly increase with forecast horizon, while analysts’ information advantage decays rapidly. A noise increase with horizon generates a mechanical reversal in the sign of the error-revision (Coibion-Gorodnichenko) regression coefficient at longer horizons, independently of over-/underreaction. A parsimonious model with bounded rationality and a noisy cognitive default matches the term structures of noise and bias jointly.

We use a high-frequency identification approach to document that individual politicians affect asset prices. We exploit the regular flow of viewpoints contained in Congress members’ tweets. Supportive (critical) tweets increase (decrease) the stock prices of the targeted firm and the corresponding industry in minutes around the tweet. The bulk of the stock price effects is concentrated in the tweets revealing news about future legislative action. The effects are amplified around committee meeting days, especially when the tweet originates from committee members and influential politicians. Overall, we show that Congress members’ social media accounts are an important source of political news.

This paper studies the real effects of foreign real estate capital inflows. Using transaction-level data, we document (i) a “China shock” in the U.S. housing market characterized by surging foreign Chinese housing purchases after 2008, and (ii) “home bias” in these purchases, as they concentrate in neighborhoods historically populated by ethnic Chinese. Exploiting their temporal and spatial variation, we find that these capital inflows raise local employment, with the effect transmitted through a housing net worth channel. However, they displace local lower-income residents. Our results show that real estate capital inflows can both stimulate the real economy and induce gentrification.

Funds investing in illiquid assets report returns with spurious autocorrelation. Consequently, investors need to unsmooth these funds’ returns when evaluating their risk exposures. We show that funds with similar investments share a common source of spurious autocorrelation not fully resolved by traditional unsmoothing methods and thereby leading to underestimation of systematic risk. Thus, we propose a generalized unsmoothing technique and apply it to hedge funds and private commercial real estate funds. Our method significantly improves the measurement of funds’ risk exposures and risk-adjusted performance, especially for highly illiquid funds. Overall, the average illiquid fund alpha is lower than previously thought. (JEL G11, G12, G23)

We use close gubernatorial elections as a quasi-natural experiment to document a positive effect of political uncertainty on firm-level R&D. This finding is in contrast to the existing literature documenting a negative impact of political uncertainty on capital investment. We examine potential mechanisms and find that our results are consistent with the growth option view of R&D investment. The effect is stronger for politically sensitive and high-tech industries.The results are robust to different proxies for political uncertainty shocks. As predicted by models of investment under uncertainty, the real effects of political uncertainty critically depend on the type of the investment. JEL G18, G38, O31, O32

We show that lender of last resort (LOLR) policy exacerbates bank interconnectedness. Using novel micro-level data, we analyze LOLR’s haircut gaps: the differences between the private market and central bank haircuts. LOLR policy incentivizes banks to increase pledging and holdings of higher haircut-gap bonds, especially those issued by domestic and systemically important banks. Effects only apply to banks, not to nonbanks without LOLR access. LOLR funding revives bank bond issuance associated with higher haircut gaps and increases the subsequent correlation between pledging and issuing banks’ bond prices, in particular during periods of low-market returns and for domestic, systemically important banks.

Chapter 7 is the most popular bankruptcy system for U.S. firms and individuals. Chapter 7 professional fees are substantial. Theoretically, high fees might be an unavoidable cost of incentivizing professionals. I test this empirically. I study trustees, the most important professionals in chapter 7, who liquidate assets in exchange for legally mandated commissions. Exploiting kinks in the commission function, I estimate a structural model of moral hazard by trustees. I show that a policy change lowering trustee fees would harm trustee incentives, reducing liquidation values. Nonetheless, such a policy would dramatically improve creditor recovery, increasing small-business-lender recovery by 15.7%.

Following the Global Settlement, analysts extensively use a top pick designation allowing for greater granularity of information among buy recommended stocks, but conflicts of interest can potentially influence this designation. Examining a novel sample of top picks, we find that a calendar-time portfolio of top picks generates an abnormal performance of 17.6% per year. Top picks have greater investment value than do buy recommendations and alternative analyst investment strategies. Both institutional and retail investors trade in response to top picks. However, only institutional investors appear to identify top picks that have greater investment value when they are announced.

We find that disclosing bank-specific information reallocates systemic risk, but whether it mitigates systemic bank runs depends on the nature of information disclosed. Disclosure reveals banks’ resilience to adverse shocks and shifts systemic risk from weak to strong banks. Yet, only disclosure of banks’ exposure to systemic risk can mitigate systemic bank runs because it shifts systemic risk from more vulnerable banks to those less vulnerable. Disclosure of banks’ idiosyncratic shortfalls of funds does not differentiate such exposure, rendering the resultant reallocation of systemic risk ineffective in mitigating systemic runs.