Conference Agenda

We quantify racial differences in the total rate of return on owner-occupied housing from 1975-2021. The total rate of return of buying a house equals the price appreciation plus the rental value of its housing services, minus taxes and maintenance. To measure the total return, we develop a new method to estimate the rental value of each owner-occupied house. We use houses that switch between the rental and owner-occupied market to estimate the relationship between purchase prices and rents. We then use this regression to predict the rental value of the entire owner-occupied housing stock and find this prediction out-performs standard hedonic techniques. We document both in raw data and with our new method that minority homeowners earn a 1.5-2 percentage point higher rental yield on housing than

white homeowners, which largely explains their 2-2.5 percentage point higher total return. Black and Hispanic homeowners’ total returns are also more volatile and sensitive to the business cycle. Observable differences in household income largely account for these racial return disparities. Our findings are broadly consistent with a model with a more severe credit constraint for minorities, which bids up rents, lowers house prices, and makes house prices sensitive to credit supply.

We study the transmission of monetary policy through bank securities portfolios for the United States using granular supervisory data on bank securities, hedging positions, and corporate credit. We find that banks that experienced larger market value losses on their securities during the monetary tightening cycle in 2022 extended relatively less credit to firms. Such a spillover effect was stronger for (i) available-for-sale securities, (ii) unhedged securities, and (iii) banks that have to include unrealized gains and losses on their available-for-sale securities in their regulatory capital. A structural model, disciplined by our cross-sectional regression estimates, shows that policy rate transmission is more powerful if banks are required to adjust their regulatory capital for unrealized value changes of securities.

We construct an overlapping generations model of financial advisors, who have ethics, are hired competitively, interact with strategic investment funds, and are regulated. Misconduct is the outcome of the tension between the endogenous career concerns created by a competitive labour market rewarding good advisor behaviour and the strategic investment fund which can frustrate clients' inference by paying commissions to alter advisor incentives. We characterise market conditions leading to high misconduct. We offer a prediction as to the pattern of misconduct as wealth inequality increases. And we establish when, over the course of a career, financial advisors are most trustworthy.

U.S. firms have reduced their investment in scientific research (“R”) compared to product development (“D”), raising questions about the returns to each type of investment, and about the reasons for this shift. We use Census data that disaggregates “R” from “D” to study how US firms adjust their innovation investments in response to an external increase in funding cost. Companies with greater demand for refinancing during the 2008 financial crisis, made larger cuts to R&D investment. This reduction in R&D is achieved almost entirely by reducing investment in research. Development remains essentially unchanged. If other firms patenting similar technologies must refinance, however, then Development investment declines. We interpret the latter result as evidence of technological competition: firms are reluctant to cut Development expenditures when that could place them at a disadvantage compared to potential rivals.

The empirical investment literature studying the determinants of investment relies almost exclusively on truncated samples of publicly listed firms due to the lack of data on private firms. This truncation, however, is not random because listing is a choice for many firms, whereas others cannot list due to their characteristics. The ensuing endogenous truncation entails biased estimates. We develop a methodology that corrects for the bias. The bias-corrected results lend strong support for the q-theory: the investment-cash flow sensitivity disappears and the relation between investment and q nearly quadruples. Our econometric framework is also applicable in many other economic contexts.

To address credit constraints in small-business lending markets, policymakers frequently use loan guarantees, which insure lenders against default. Guarantees affect loan prices by altering the effective marginal cost of lending but may create a moral hazard problem, weakening lenders’ information-acquisition incentives. I quantify these channels using data from the SBA 7(a) Loan Program. Guarantees benefit borrowers, on average, but redistribute surplus from low- to high-risk borrowers. Fixing government spending, an alternative policy with a 50% guarantee and a subsidy leads to an increase in borrower surplus and 0.1 percentage point (1.1%) decline in the program’s default rate.

What explains cross-sectional dispersion in stock valuation ratios? We find that 75% of dispersion in price-earnings ratios is reflected in differences in future returns, while only 25% is reflected in differences in future earnings growth. This holds at both the portfolio-level and the firm-level. We reconcile these conclusions with previous literature which has found a strong relation between prices and future profitability. Our results support models in which the cross-section of price-earnings ratios is driven mainly by discount rates or mispricing rather than future earnings growth. Evaluating six models of the value premium, we find that most models struggle to match our results, however, models with long-lived differences in risk exposure or gradual learning about parameters perform the best. The lack of earnings growth differences at long horizons provides new evidence in favor of long-run return predictability. We also show a similar dominance of predicted returns for explaining the dispersion in return surprises.

We study the implications of model uncertainty in a climate-economics framework with three types of capital: “dirty” capital that produces carbon emissions when used for production, “clean” capital that generates no emissions but is initially less productive than dirty capital, and knowledge capital that increases with R&D investment and leads to technological innovation in green sector productivity. To solve our high-dimensional, non-linear model

framework we implement a neural-network-based global solution method. We show there are first-order impacts of model uncertainty on optimal decisions and social valuations in our integrated climate-economic-innovation framework. Accounting for interconnected uncertainty over climate dynamics, economic damages from climate change, and the arrival of a green technological change leads to substantial adjustments to investment in the different capital types in anticipation of technological change and the revelation of climate damage severity.

We characterise the large number of mortgage offers for which people qualify in the United Kingdom. Very few pick the cheapest option, nonetheless the one selected is not usually noticeably more expensive. A few borrowers make very expensive choices. These are most common when the menu they face has many expensive options, and are most likely for high loan-to-value and loan-to-income borrowers. Young people and first-time buyers are more prone to making expensive choices. The dispersion in the mortgage menu is consistent with banks price discriminating for borrowers who might pick poorly while competing for others who shop more effectively.

This paper studies how tightening monetary policy transmits to the economy through the mortgage market and sheds new light on the distributional consequences at both individual and regional levels. We specifically examine the sharp increase in mortgage interest rates during 2022 and 2023. We find that almost all of the decline in mortgages compared to prior years was concentrated in loans that would have had a debt-to-income (DTI) ratio above underwriting thresholds. These effects are even more pronounced for minority and middle-income borrowers. Additionally, regions more affected by the thresholds exhibited greater reductions in mortgage originations, house prices, and consumption.

We evaluate the effectiveness of portfolio mandates on equilibrium capital allocation. We show that the impact of mandates crucially depends on firms' demand elasticity of capital. In a production economy with constant returns to scale, firms' demand for capital is infinitely elastic, and mandates can significantly impact the allocation of capital across sectors despite having a negligible impact on the cost of capital. This is in sharp contrast to an endowment economy where inelastic demand for capital implies equilibrium price reactions to mandates, which significantly reduce their effectiveness. Within a canonical real-business-cycle model calibrated to match key asset-pricing and macroeconomic moments, we estimate that a significant portion of the mandate remains effective in shaping equilibrium capital allocation, even when there is little disparity in the cost of capital across sectors. Our analysis challenges the common practice of judging the effectiveness of portfolio mandates by their impact on firms' cost of capital.

We provide the first large-sample evidence of substantial anticipatory effects: firms are affected by proposed rules long before those are finalized. We construct a new data set that tracks the timeline of each rule proposal developed by federal agencies since 1995, total of 43,000 proposals. The average proposal spends more than two years in the rulemaking pipeline and only two-thirds convert into a final rule. Training a machine-learning algorithm, we derive a firm-level measure of exposure to the regulatory pipeline: the amount of rule proposals which are relevant to the firm. We find that firms with greater exposure increase overhead costs, reduce capital investments, and report lower profits, independent of their current regulatory burden and political risk. The effects increase with the expected burden of the proposals and when agencies develop rules outside of their core expertise. Calibrating a latent factor model of stock returns with our new firm-specific measure, we identify systematically important regulatory topics such as Securities, Natural Resources, and Environment. Our results are the first to document anticipatory effects based on the entire body of potential federal regulations.

Using micro data on managerial expenditures, we uncover heuristics in capital budgets, such as nominal rigidity, anchoring, and sharp reset deadlines. Such heuristics engender managerial opportunism. Managers with a budget surplus increase investment before budget deadlines, and such projects underperform. Managers who reach a budget constraint early in the fiscal cycle halt spending until their budget is reset, irrespective of investment options. These effects are stronger at firms with more hierarchical layers and a greater subordinates-to-executives ratio. Such firms become targets of private equity funds. After the buyout by strong principals, firms remove budgetary heuristics and switch to continuous capital allocations. Overall, simplifying budgeting rules engender strategic managerial behavior.

Pandemic fraud is geographically concentrated and stimulated local purchases with effects on prices, particularly for housing. Fraudulent PPP loan recipients significantly increased their home purchase rate after receiving a loan compared to non-fraudulent PPP recipients, and house prices in high fraud zip codes increased 5.7 percentage points more than in low fraud zip codes within the same county, with similar effects after controlling for other explanations for house price appreciation during COVID. Zip codes with fraud also experience heightened vehicle purchases and consumer spending in 2020 and 2021, with a return to normal in 2022.

We develop an approach to determine whether a particular predictor represents a proxy for fundamental risk. We build on the assumption that risk-based predictors should be linked to new information about economic conditions. We show that most predictors forecast returns on either days with macroeconomic announcements or the remaining days, indicating that sources of return predictability differ across predictors: few are driven by fundamental risk; most have other origins. We show that Shiller’s excess volatility is confined to non-announcement days, suggesting that the ability to forecast stock market’s noise component underlies much of the predictability documented in the literature.

In Australia’s Murray Darling Basin (MDB), short term (allocation) and long term (entitlement) water rights are separately traded, centrally reported, and disseminated to the public. I utilize this setting to demonstrate three primary findings concerning water rights and climate change risk. First, water rights appear to be a climate change hedge: in periods of diminishing supply, allocation cash flows spike as price increases offset quantity declines. Second, since 2014, entitlement prices in climate exposed areas have increased approximately $1500 per MegaLitre (about 39%) more than prices in non-climate exposed areas while allocation prices have remained similar in both areas. These price differences provide a clear market signal about future scarcity and help to define investment opportunities available today to preserve water resources. Finally, estimating the allocation cash-flow to rainfall elasticity and extrapolating using the 2050 IPCC rainfall scenarios, I attribute about 21% of the price effect to differences in expected cash flow, and the remainder to a lower discount rate. The premium I estimate equates to a 1.2% lower rate of return for climate hedge or mitigation assets, a critical parameter in climate economics.

We study the impact of rising mortgage rates on mobility and labor reallocation. Using individual-level credit record data and variation in the timing of mortgage origination, we show that a 1 p.p. decline in mortgage rate deltas (Δr), measured as the difference between the mortgage rate locked in at origination and the current market rate, reduces moving rates by 0.68 p.p, or 9%. We find that this relationship is nonlinear: once Δr is high enough, households’ alternative of refinancing without moving becomes attractive such that moving probabilities no longer depend on Δr. Lastly, we find that mortgage lock-in attenuates household responsiveness to shocks to nearby employment opportunities that require moving, measured as wage growth in counties within a 50 to 150-mile ring and instrumented with a shift-share instrument. We provide causal estimates of mortgage lock-in effects, highlighting unintended consequences of monetary tightening with long-term fixed-rate mortgages on mobility and labor markets.

Financial technology has reshaped commercial banking. It has the potential to radically alter the transmission of monetary policy by lowering search costs and expanding banking markets. This paper studies the reaction of online banks to changes in federal fund rates. We find that these banks increase rates that they offer on deposits significantly more than traditional banks do. A 100 basis points increase in the federal fund rate leads to a 30 basis points larger in rates of online banks relative to traditional banks. Consistent with the rate movements, online bank deposits experience inflows, while traditional banks experience outflows during monetary tightening in 2022. Results are similar across banking markets of different competitiveness and demographics, but they vary with the stickiness of banking relationships. Our findings shed new light on the role of online banks in interest rate passthrough and the deposit channel of monetary policy.

Person-to-person charity has grown substantially in recent years, yet little is known about who benefits from it. This paper uses micro data on crowdfunding campaigns after a major wildfire to ask whether donors give according to the comparative need of beneficiaries. Linking to personal financial data and holding losses fixed, we find that beneficiaries with incomes above $150,000 receive 28% more support than beneficiaries with income below $75,000 and are more likely to have a campaign in the first place. We document that high-income beneficiaries possess several network advantages when soliciting crowdfunding. However, a networks mechanism does not fully explain why donors who give to multiple campaigns tend to give larger amounts to higher-income beneficiaries. These findings suggest that crowdfunded private charity may exacerbate income inequalities in the recovery process.

Innovation booms are often fueled by easy financing that allows new technology firms to pay high wages that attracts skilled labor. Using the late 1990s Information and Communication Technology (ICT) boom as a laboratory, we show that skilled labor joining this new sector experienced sizeable long-term earnings losses. We show these earnings patterns are explained by faster skill obsolescence rather than either worker selection or the overall bust in the ICT sector. During the boom, financing flowed more to firms whose workers would experience the largest productivity declines, amplifying the negative effect of labor reallocation on aggregate human capital accumulation.

We show how the threat of “uncertainty-induced zombification”—creditors’ willingness to keep their distressed borrowers alive when faced with uncertainty—shapes various industry dynamics. Under a real options framework, we demonstrate that unlevered firms become reluctant to invest and disinvest in anticipation that uncertainty induces creditors to convert defaulting rival firms into zombies. We validate our theory using dynamic, industry-specific estimates of expected uncertainty induced zombification together with loan contract-level data. Empirically, higher uncertainty-led rival zombification expectations prompt healthy firms to reduce their costly-to-reverse capital investment and disinvestment, hiring, and establishment-level openings and closures (intensive and extensive margins are affected). We confirm those dynamics using granular, near-universal data on the asset allocation decisions of global shipping firms. Critically, uncertainty-led zombification expectations depress healthy firms’ sales, profits, and stock returns. Our results reveal nuanced effects on creative destruction—while healthy firms’ asset allocation slows down, their innovation activity accelerates. Our findings highlight a novel channel through which uncertainty shapes firms’ capital accumulation, distorting their real and financial policies and performance.

Do banks accumulate knowledge about corporate technology, and does it matter for

their lending? To answer this question, we combine corporate innovation with syndicated

loan data. We find that loans to firms sharing similar technologies with banks’

prior borrowers obtain lower loan spreads. We can rule out product market competition,

the value of their technology and ability to innovate, and/or numerous other firm

characteristics as alternative explanations. By estimating a structural bank-borrower

matching model and exploiting the consummation of bank mergers and acquisitions,

we can show that shocks to banks’ technology knowledge causally affect loan spreads.

Present-value logic says that aggregate stock prices are driven by discount-rate and cash-flow expectations. Dividends and net repurchases are both cash flows between the firm and household sectors. Aggregate dividend-price ratios do not forecast dividend growth, but do robustly forecast future buybacks and issuance. Long-run variance decompositions say that discount-rate and cash-flow expectations contribute equally to aggregate dividend-price-ratio variation.

We construct novel measures of mutual funds’ environmental, social, and governance (ESG) commitment by analyzing the discretionary investment-strategy descriptions of their prospectuses. We find that fund flows respond strongly to text-based ESG measures. Using discrepancies between text- and fundamentals-based ESG measures, we identify greenwashing funds. We find that greenwashing is more prevalent since 2016 (coinciding with the Paris Agreement) and among funds with lower past flows and higher expense ratios, and isn't associated with superior subsequent performance. Furthermore, greenwashers attract similar flows to genuinely green funds, suggesting that investors cannot distinguish them. Our results could help regulators' efforts to combat ESG-related misconduct.

In this paper, we study the implications of a vacant home tax for housing availability and affordability. We develop a model with owner-occupied homes, tenanted rental units, and empty houses. Housing units are constructed by competitive developers and supplied to local households, but can also be sold to investors as a store of wealth. Empty homes held by investors are classified as speculative vacancies. Frictional vacancies, on the other hand, are the equilibrium result of search-and-matching frictions in the owner-occupied market. A tax on empty homes can improve housing availability and affordability in the rental market by reducing speculative vacancies, but can dis- tort the incentives to supply vacant homes for sale in the owner-occupied market (i.e., frictional vacancies), thereby increasing house prices and lowering home-ownership. Empirical predictions derived from the calibrated model are consistent with the pat- terns we observe for listings, sales, prices and rents in Vancouver following the recent implementation of an empty homes tax.

We propose a theory of payments that highlights a conflict between the roles of medium of exchange and store of value. We posit that payments must involve the reciprocal transfer of a scarce reserve good, which holds value for other non-payment purposes. The theory demonstrates that agents make payments only when reserves are abundant enough and when the conflict is low. Otherwise, history-dependent equilibria arise in which an agent’s payment decision depends on the payment history of other agents within an equilibrium. The theory explains why payments frequently encounter delays and interruptions. Improving payment technologies may not reduce such fragility when reserves remain scarce and valuable for non-payment functions. The theory helps explain the evolution of money and payment systems, encompassing metallic payments before fiat money, modern bank payments, cross-border payments, and contemporary digital payment systems.

Using confidential information on banks’ portfolios, inaccessible to market participants, we show that banks that emphasize the environment in their disclosures extend a higher volume of credit to brown borrowers, without charging higher interest rates or shortening debt maturity. These results cannot be attributed to the financing of borrowers’ transition towards greener technologies and are robust to controlling for banks’ climate risk discussions. Examining the mechanisms behind the strategic disclosure choices, we highlight that banks are hesitant to sever ties with existing brown borrowers, especially if they exhibit financial underperformance.

We open the black box of corporate innovation production by examining its most important input: the employees tasked with creating new inventions. Using a novel within-firm research design involving the universe of U.S. corporate inventors across four decades, we find that inventors’ shared cultural values are a critical driver of inventor team formation. Moreover, using premature co-inventor deaths as exogenous shocks to team composition, we document both positive and negative impacts of inventor team cultural diversity on team patent production. Less culturally diverse teams produce a higher overall quantity of patents that tend to exploit existing technologies, while more culturally diverse teams produce more risky, exploratory patents with a greater potential for high-impact innovations. Exploring the underlying mechanisms, we present evidence that culturally diverse teams tend to seek new knowledge from more heterogeneous and non-traditional input information sources, but they also face greater knowledge integration challenges. Overall, our results present a more nuanced perspective on diversity, revealing that it does not lead to uniformly better or worse outcomes, but instead impacts the type of R&D output.

This paper measures the impact of information quality on the success of firms' investment decisions using the U.S. census as an empirical context. Over the course of a decade, information from the decennial census snapshot likely deviates from the evolving market condition, thereby making the data less relevant. I find that on average, outdated census information increases establishment failure rate by 1.6% per year. The effects are stronger for geographic areas that experience large changes in demographics, for industries that rely on precise information in small trade areas, and for independent retailers that lack alternative sources of demographic information.

We build a Markov model of banks' internal loan ratings to illustrate the relationship between ratings inflation and systematic ratings drift. Using administrative data from the Shared National Credit (SNC) Program, we find evidence of systematic downward drift in ratings, consistent with initial ratings inflation. The drift is predictable based on pre-issuance borrower characteristics, suggesting that screening and pricing information is not being fully incorporated into ratings. We use the conditional random assignment of loan examinations to study the causal impact of loan-level supervision on ratings, and find not only that supervision reduces ratings inflation, but also that these effects spill over within a bank's loan portfolio, consistent with learning. We employ our model to investigate various counterfactual capital ratios and provide new insights about the relationship between bank supervision in bank capital cyclicality.

We show that an increase in passive exchange-traded fund (ETF) ownership leads to stronger and more persistent return reversals. Exploiting exogenous changes due to index reconstitutions, we further show that more passive ownership causes higher bid-ask spreads, more exposure to aggregate liquidity shocks, more idiosyncratic volatility, and higher tail risk. We examine potential drivers of these results and show that higher passive ETF ownership reduces the importance of firm-specific information for returns but increases the importance of transitory noise and a firm's exposure to market-wide sentiment shocks.

We examine whether foreign institutional capital promotes green growth in emerging-market firms, using firm-level and China A-shares’ market-level inclusions in the MSCI Index as shocks to foreign capital. While foreign capital boosts output in emerging-market firms, emissions rise disproportionately, leading to substantial increases in emissions intensity. In contrast, emissions intensities of developed-market firms tend not to increase with foreign capital. These increases in emissions intensity are concentrated in emerging markets with weaker environmental regulations and firms receiving more capital from high-sustainability-score investors. Overall, results suggest that environmental considerations are assigned lower priority when emerging-market firms utilize foreign capital for growth.

This paper studies how language barriers between lenders and borrowers translate into differences in borrower outcomes in the U.S. mortgage market. I use survey data to infer and machine learning techniques to predict borrowers' English proficiency. I document significant descriptive differences in perceptions of mortgages, application experiences, and mortgage rates between limited English proficient (LEP) and non-LEP borrowers. To measure the causal effects of language frictions, I exploit a Federal Housing Finance Agency policy that provided translated mortgage documents in Spanish to mortgage lenders. After the policy change, LEP Hispanic borrowers had a streamlined application process, contacted more lenders, understood mortgage contracts better, and enjoyed lower borrowing costs. Reducing language frictions also led to expanded access to credit, reduced loan risks, and a more competitive mortgage market for LEP borrowers. Overall, my findings highlight a cost-effective way to create a responsible inclusion of well-qualified LEP borrowers in the mortgage market.

We examine the impact of digital payments on the transmission of monetary policy. Leveraging administrative data on Pix, a digital payment system introduced by the Central Bank of Brazil, we find that Pix adoption has diminished banks’ market power, making them more responsive to changes in policy rates. Subsequently, we estimate a dynamic banking model in which digital payment amplifies deposit elasticity through the household sector. Our counterfactual results reveal that digital payments amplify the monetary policy transmission by reducing banks’ market power – banks respond more to policy rate changes after Pix. We find that digital payments impact monetary transmission primarily through the deposit channel.

This paper studies the impact of voluntary climate commitments by banks on their lending activity. We use administrative data on the universe of bank lending from 19 European countries. There is strong selection into commitments, with increased participation by the largest banks and banks with the most pre-existing exposure to high-polluting industries. Setting a commitment leads to a marked boost in a lender’s ESG rating. Lenders reduce credit in sectors they have targeted as high priority for decarbonization. However, climate-aligned banks do not change their lending or loan pricing differentially compared to banks without climate commitments, suggesting they are not actively divesting. We can reject that climate aligned lenders divest from mining firms by more than 0.36% and from firms in targeted sectors by more than 2.6%. Firm borrowers are no more likely to set climate targets after their lender sets a climate target, which casts doubt on active engagement by lenders. These results call into question the efficacy of voluntary commitments.

Analyzing millions of patents granted by the USPTO between 1970 and 2020, we find a pattern where specific patents only rise to prominence after considerable time has passed. Amongst these late-blooming influential patents, we show that there are key players (patent hunters) who consistently identify and develop them. Although initially overlooked, these late-bloomer patents have significantly more influence on average than early-recognized patents and open significantly broader new markets and innovative spaces. For instance, they are associated with a 15.6% (t = 29.1) increase in patenting in the late-bloomer’s technology space. Patent hunters, as early detectors and adopters of these late-blooming patents, are also associated with significant posi- tive rents. Their adoption of these overlooked patents is associated with a 22% rise in sales growth (t = 6.55), a 3% increase in Tobin’s Q (t = 3.77), and a 4.8% increase in new product offerings (t = 2.25). We instrument for patent hunting and find similarly large positive impacts on firm value. Interestingly, these rents associated with patent hunting on average exceed those of the original patent creators themselves. Patents hunted tend to be closer to the core technology of the hunters, more peripheral to the writers, and to be in less competitive spaces. Lastly, patent hunting appears to be a persistent firm characteristic and to have an inventor-level component as well.

We show that production networks amplify the effects of a firm’s financial constraints, generating substantive contagion effects on its partners’ investment. We quantify these effects via a network multiplier whereby a one-dollar drop in the constrained firm’s investment reduces total supply-chain investment by an additional dollar. To facilitate identification, we employ multiple financial-constraint measures, a Network Regression Discontinuity Design that accounts for covenant-violation spillovers, and an instrumented network of long-term partners. Consistent with production-driven spillovers, firms producing specific inputs generate larger investment spillovers and receive more trade credit. Overall, our results suggest that production networks aggregate firm-level financial frictions.

The bank lending channel is heterogeneous across firms. Using matched bank-firm credit data, we develop a framework that estimates the effects of firm-demand and bank-supply credit shocks, allowing for interactions between bank and firm unobserved factors. Bank shocks can have heterogeneous effects across firm types, where firm type is unobserved for the econometrician. We decompose credit growth dynamics into time-varying firm and bank-firm type interaction effects. We uncover significant heterogeneity in the bank lending channel: i) The effect of bank shocks varies considerably across the identified firm types, ii) During the Great Recession, more exposed banks severely contracted their loan supply to some firms but shielded others, iii) We uncover a bank-firm matching channel: the transmission of shocks crucially depends on the bank-firm network, with credit growth dropping by up to 20% in a counterfactual randomly matched network, iii) Accounting for interactions helps to more precisely estimate the impact of bank shocks on firm real outcomes.

This paper addresses a key question in economic forecasting: does pure noise truly lack predictive power? Economists typically conduct variable selection to eliminate noises from predictors. Yet, we prove a compelling result that in most economic forecasts, the inclusion of noises in predictions yields greater benefits than its exclusion. Furthermore, if the total number of predictors is not sufficiently large, intentionally adding more noises yields superior forecast performance, out- performing benchmark predictors relying on dimension reduction. The intuition lies in economic predictive signals being densely distributed among regression coef- ficients, maintaining modest forecast bias while diversifying away overall variance, even when a significant proportion of predictors constitute pure noises. One of our empirical demonstrations shows that intentionally adding 300 ∼ 6, 000 pure noises to the Welch and Goyal (2008) dataset achieves a noteworthy 10% out-of-sample R2 accuracy in forecasting the annual U.S. equity premium. The performance sur- passes the majority of sophisticated machine learning models.

We conduct a field experiment in partnership with the largest job platform in Brazil to study how environmental, social, and governance (ESG) practices of firms affect talent allocation. We find both an average job-seeker’s preference for ESG and a large degree of heterogeneity across socioeconomic groups, with the strongest preference displayed by highly educated, white, and politically liberal individuals. We combine our experimental estimates with administrative matched employer-employee microdata and estimate an equilibrium model of the labor market. Counterfactual analyses suggest ESG practices increase total economic output and worker welfare, while increasing the wage gap between skilled and unskilled workers.

Does emergency credit prevent long-term financial distress? We study the causal effects of government provided recovery loans to small businesses following natural disasters. The rapid financial injection might enable viable firms to survive and grow or might hobble precarious firms with more risk and

interest obligations. We show that the loans reduce exit and bankruptcy, increase employment and revenue, unlock private credit, and reduce delinquency. These effects, especially the crowding-in of private credit, appear to reflect resolving uncertainty about repair. We do not find capital reallocation away from neighboring firms and see some evidence of positive spillovers on local entry.

I study how financial technology reshapes competition among banks. I exploit quasi-random variation in exposure to the introduction of Brazil's Pix, an instant payment system, and show that instant payments increase deposit competition. Small bank deposits rise relative to large banks because Pix allows small banks to offer greater payment convenience to depositors. Since they become more competitive in the provision of payment services, small banks reduce deposit rates relative to large banks. Finally, I estimate a deposit demand model and find that depositors' welfare increases with Pix. These findings suggest that universally available payment systems can foster banking competition.

This paper investigates how competition affects banks’ adaptation to climate change. The analysis matches detailed supervisory data on home equity lines of credit with high resolution flood projections to identify climate risks. Following Hurricane Harvey, banks updated their internal risk models to better reflect flood risk projections, even in areas unaffected by the disaster. These updates are only detected in banks with exposures to the disaster, indicating heterogeneous bank learning. We use this heterogeneity to identify how bank adaptation is affected by competition. Exposed banks reduce lending to areas with higher flood risks but only in less competitive loan markets, suggesting that competition fosters risk-taking over risk mitigation. Additionally, banks are less likely to adapt in markets where competitors are also less likely to do so, suggesting a strategic complementarity in bank adaptation. More broadly, our paper sheds light on the role of competitive forces in how banks manage emerging risks.

We document a form of "excess" commitment to R&D projects and examine the consequences for innovation outcomes and consumer welfare, using detailed data on pharmaceutical firms' clinical trial projects. Plausibly-exogenous delays in the completion of the preceding trial-phase, empirically uncorrelated with various project-quality measures, substantially reduce firms' subsequent project termination propensity. This excess project commitment intensifies when the CEO has higher stock-price-compensation sensitivity and is personally responsible for the project’s initiation. Welfare implications are nuanced: delay-driven commitment induces investment crowd-out, while not predicting increased adverse effects in marginally-launched drugs and predicting continuation of drugs for diseases lacking alternative treatments.

Using large, plausibly exogenous shocks to the maturity structure of U.S. government debt, I find that a higher supply of long-term government bonds increases firms’ discount rates at long horizons leading to a crowding-out of long-duration investment. This crowding out occurs through reallocations of capital away from long-duration investment towards short-duration investment. This happens across industries, within industries across firms and within firms across divisions. Such changes to the average duration of investment explain a significant share of changes to the average maturity of corporate debt. These results identify important real effects of policies which affect the net supply of long-termbonds, such as quantitative easing by central banks.

We document that in the US residential mortgage market, the share of integrated intermediaries acting as both originator and servicer has declined dramatically. Exploiting a regulatory change, we show that borrowers with integrated servicers are more likely to refinance, and conditional on refinance, are more likely to be recaptured by their own servicer. Recaptured borrowers pay lower fees relative to other refinancers. This trend is partially offset by a rise in integrated fintech originator-servicers, who recapture at higher frequency but at worse terms. We build and calibrate a dynamic structural model to interpret these facts and quantify their impact on equilibrium outcomes. Our model suggests that integreated intermediaries enjoy a marginal cost advantage when refinancing recaptured borrowers, and fully disintegrating them would reduce refinancing frequencies and increase fees. Fintechs use technology to reacquire customers and reduce borrower inertia against refinancing. This endogenously creates market power, which fintechs exploit through higher fees. Despite worse terms ex-post, fintechs increase consumer welfare ex-ante by increasing refinancing frequencies. Taken together, our results highlight the importance of intermediaries' scope in consumer financial outcomes and highlight a novel, quantitatively important application of fintech: customer acquisition.

Numerous trading strategies examined in options research exhibit remarkably high mean returns and Sharpe ratios. We show some of these seemingly ``good deals'' are due to look-ahead biases. These biases stem from using information unavailable at the portfolio formation time to filter out observations suspected of being noisy or erroneous. Our results suggest that elevated Sharpe ratios may serve as potential indicators of such look-ahead biases. Furthermore, deviating from previous literature findings, we show that illiquidity is not strongly priced in stock options and that only a small set of stock characteristics are in fact associated with option expected returns.

Women continue to be underrepresented in corporate leadership positions. This paper studies the role of social connections in women's career advancement. We investigate whether access to a larger share of female peers in business school affects the gender gap in senior managerial positions. Merging administrative data from a top-10 US business school with public LinkedIn profiles, we first document that female MBAs are 24 percent less likely than male MBAs to enter senior management within 15 years of graduation. Next, we use the random assignment of students into sections to show that a larger proportion of female MBA section peers increases the likelihood of entering senior management for women but not for men. This effect is driven by female-friendly firms, such as those with more generous maternity leave policies and greater work schedule flexibility. A larger proportion of female MBA peers induces women to transition to these firms where they attain senior management roles. We find suggestive evidence that some of the mechanisms behind these results include job referrals and gender-specific information transmission. These findings highlight the role of social connections in reducing the gender gap in senior management positions.