Knowledge that Transforms

We extract information from earnings call transcripts to develop a comprehensive and reliable measure of labor shortage exposure. After validating the measure at the state, industry, and firm levels, we show that firms with labor shortage exposures experience lower earnings call CARs, future stock returns and operating performance. Firms respond to labor shortages by substituting labor with capital and R&D investments, and by producing more production-process patents. Such responses help mitigate the negative effects on future performance. Our measure has broad applicability, and our findings provide new insight into labor-capital substitution in imperfectly competitive labor markets.

We find that firms are the primary sellers who clear the market for index fund buying, providing shares at a nearly one-for-one rate. Most demand-side institutions trade in the same direction as index funds rather than accommodating passive demand. We use two instruments for index fund demand and show that firms causally respond to exogenous passive demand, with prices serving as the coordinating mechanism. Firms satisfy passive demand mostly through nonprimary market issuance, for example, through employee stock-based compensation. Our results suggest that passive investing has systematically supplied capital to firms by enabling equity issuance over the last two decades.

Government-provided flood insurance contracts have strict coverage limits, leaving some households underinsured against flood risk. This paper exploits these strict coverage limits as well as staggered flood map updates to show that mortgage lenders screen for uninsurable flood risk by requiring lower loan-to-value ratios at origination. This credit rationing leads delinquency rates to equalize inside and outside of flood zones, and shifts the composition of mortgage borrowers in flood zones toward richer and higher credit quality individuals. I conclude that lenders reduce credit supply when they retain residual uninsured exposures to flood risk, which has distributional consequences for flood zones.

Long-dated inflation swap contracts provide widely used estimates of expected inflation. We develop methods to estimate complementary tail probabilities for persistently very high or low inflation using inflation options prices. We show that three new adjustments to conventional methods are crucial: inflation, horizon, and risk. We find that: (a) U.S. deflation risk in 2011–2014 has been overstated, (b) ECB unconventional policies lowered deflation disaster probabilities, (c) inflation expectations deanchored in 2021–2022, (d) reanchored as policy tightened, (e) but the 2021–2024 disaster left scars, and (f) U.S. expectations are less sensitive to inflation realizations than in the eurozone.

This paper estimates willingness to pay (WTP) for carbon mitigation from demand for carbon offsets in a field experiment with an online supermarket. The experiment randomizes whether the firm subsidizes the price of the offset or matches the offset’s impact on carbon mitigation. Consumers are price-elastic but fully impact-inelastic, implying that they buy the offset but their WTP for the carbon it mitigates is zero. If the firm informs consumers that it contributes to the offset costs, WTP increases to 16 EUR/tCO$ _2 $. A complementary survey shows that consumers’ stated WTP is 238 EUR/tCO$ _2 $, far above their revealed preferences.

We introduce a pricing kernel with time-varying volatility risk aversion to explain the observed time variations in the shape of the pricing kernel. When combined with the Heston-Nandi GARCH model, this framework yields a tractable option pricing model in which the variance risk ratio (VRR) emerges as a key variable. We show that the VRR is closely linked to economic fundamentals, as well as sentiment and uncertainty measures. A novel approximation method provides analytical option pricing formulas, and we demonstrate substantial reductions in pricing errors through an empirical application to the S&P 500 index, the CBOE VIX, and option prices.

By aggregating information into stock prices, financial markets help guide the allocation of resources. We show that speculators without information about firms’ fundamentals can exploit this role of prices and profit from inflating firm valuations. Uninformed speculation is profitable because high valuations attract employees, business partners, and investors, creating value at targeted firms at the cost of diverting resources from better firms. Both large and small speculators, without pre-existing stock positions, can profit from uninformed speculation, particularly when targeting firms with moderate Q, operating in “normal” (neither hot nor cold) markets, and using performance pay or equity to attract stakeholders.

We study the interplay between a “one person-one vote” political system and a “one share-one vote” corporate governance regime. If shareholders push firms for more prosocial policies, political backlash may arise, undoing these initiatives. If public policy is frictionless, shareholder democracy becomes irrelevant: the political system fully offsets shareholder influence. With public policy frictions, prosocial corporations can mitigate regulatory shortcomings and enhance corporate public goods provision. Nevertheless, shareholder democracy can hurt citizens due to the representation problem: it favors the preferences of the wealthy. Investor diversification, pass-through voting, and corporate greenwashing have important implications for these trade-offs of shareholder democracy.

How does the increased use of data technologies, like machine learning, by financial intermediaries affect the allocation of capital towards innovation? I study this question in the context of startup financing by venture capitalists (VCs). While VCs adopting data technologies become better at screening startups similar to those in historical data, they tilt their investments towards this pool and become concurrently less likely to finance innovative startups that achieve rare major success. Plausibly exogenous variations in VCs’ screening automation suggest that these effects are causal. These findings highlight how investors’ adoption of data technologies can have real effects through innovation financing.

Research shows that access to high-quality financial services varies with local income and wealth. We study how financial firms’ internal allocation of human capital contributes to these disparities. Using a near-comprehensive panel of over 350,000 U.S. mortgage loan officers, we document large and persistent differences in productivity and performance. We find that firms’ hiring and promotion practices allocate workers with less experience or poor track records to branches serving low-income customers. Further, the consequences of poor performance differ by location: low sales, bad loans, and misconduct are more tolerated in low-income branches, exacerbating income-based disparities in financial services.