We model competition between banks and a bigtech platform that lend to a merchant with private information and subject to moral hazard. By controlling access to a valuable marketplace for the merchant, the platform enforces partial loan repayments, thus alleviating financing frictions, reducing the risk of strategic default, and contributing to welfare positively. Credit markets become partially segmented, with the platform targeting merchants of low and medium perceived credit quality. However, conditional on observables, the platform lends to better borrowers than banks because bad borrowers self-select into bank loans to avoid the platform's enforcement, causing negative welfare effects in equilibrium.

Using a large representative sample of individual credit bureau records, we document that personal financial distress increases a married couple’s probability of divorce by 4%-8%. Foreclosures strongly affect marital dissolution, whereas Chapter 13 bankruptcies, which protect debtors from foreclosure, have the opposite effect. These effects of foreclosure and bankruptcy protection on household stability are distinct from health- or employment-related shocks. We isolate plausibly exogenous variation in the probability of foreclosure by exploiting financial assistance programs that protect homeowners after natural disasters. Our findings highlight the role of financial stability and housing security as determinants of family structures and suggest that household finances have broad social consequences.

By investigating dealer banks and high-frequency traders (HFTs) in foreign exchange markets, this study sheds light on the distinct yet complementary roles of ``traditional’’ and ``new’’ market makers in over-the-counter markets. Using message-level data, our findings reveal that these two types coexist by carrying out complementary roles. HFTs excel in processing public information, while dealers are skilled in managing private information. Specifically, HFTs provide resilient liquidity during market-wide volatility spikes, whereas dealer liquidity is robust in informational events such as scheduled macroeconomic announcements or policy regime changes. HFTs contribute to the majority of the information share through frequent quote updates, which incorporate public information. In contrast, dealers contribute to price discovery through trades that impound private information.

In this paper, we establish that universal banks reduce the efficacy of the monetary policy pass-through to the economy. Universal banks have access to a variety of funding sources, beyond retail deposits, which enable them to maintain a higher credit supply when the monetary policy tightens. We show that this has positive real effects on the economy as the higher credit supply by universal banks leads to lower unemployment rates in areas where they lend more. This channel is distinct from existing theories of monetary policy transmission, and we validate that the findings hold beyond a variety of alternative explanations. The results shed new light on the Fed’s execution of monetary policy, as well as how it should regulate the banking system.

We test whether differences in ownership structure influence race and gender diversity in corporate boards. We find that privately-owned, venture-backed companies appoint a lower proportion of minorities and women to their boards compared to publicly traded firms. After the George Floyd Social Justice Movements of 2020, the racial diversity gap in appointments widened significantly from 7 to 30 percentage points, as private firms responded less to social and media pressure to diversify. The lack of diversity in venture-capital (VC) backed private firms is persistent and remains following firms' IPO, leading to a diversity gap between VC- and non-VC-backed public firms. We show real effects of board diversity, as companies with Black directors are more likely to hire Black employees, an effect absent for Hispanic and female directors. Our study, which uses image recognition techniques combined with extensive manual review to build the first large database of board diversity in VC-backed private firms, highlights the influence of both venture capitalists and public shareholders on board composition and its implications on employee composition.

We study equilibrium asset prices in a model where investors favor ``green'' over ``brown'' goods. We show that demand elasticity of goods crucially affects \emph{assets}' riskiness. When demand elasticity is high, brown assets are safer than green, because they hedge against consumption risk. The opposite holds when goods' demand elasticity is low. Our model therefore predicts that the ``green minus brown'' stock return spread (green premium) varies in the cross section and increases in the price elasticity of demand. We test this novel prediction on US stocks and find that over the 2012--2022 period the annual green premium is 11.7\% for firms with high demand elasticity, while it is much smaller and insignificant for firms with low demand elasticity. The high green premium for high-demand elasticity firms is robust to standard risk adjustments and to alternative measures of demand elasticity; it cannot be explained by unanticipated shocks to investors' environmental concerns, and remains strong after using option-implied measures of expected returns. These findings underscore the critical role of goods' demand elasticity for understanding the impact of responsible consumption on asset prices.

Analyzing 563 trillion possible models, we find that the majority of tradable factors designed to price bond markets are unlikely sources of priced risk, and only one novel tradable bond factor, capturing the bond post-earnings announcement drift, should be included in the stochastic discount factor (SDF) with very high probability. Nevertheless, the SDF is dense in the space of observable factors, with both nontradable and equity-based ones being salient for pricing corporate bonds. A Bayesian model averaging–SDF explains corporate risk premia better than all existing models, both in- and out-of-sample, and captures business cycle and market crash risks.

Using valuation models of financial analysts, we identify the drivers of disagreement

in stock valuation. Disagreement in the discount rate is as important in explaining

the variation in a stock’s intrinsic value as the disagreement in expected cash flows.

Analysts derive the discount rate by estimating the same return-generating model

(CAPM) but over different trailing horizons and under different assumptions about the

market risk premium. This approach produces large variation in betas and the discount

rate. These methodological choices are specific to the analyst rather than their firm.

Overall, we offer micro evidence on the inner workings of securities valuation.

Using hand-collected data on robo-advisors, I study the impact of robo-advisors on the corresponding high-skilled (financial advisors) labor market. I find that robo-advisors and financial advisors are complements. This complementarity can be explained by the expansion in market for financial services through (1) an increase in financial advisors at firms that directly compete with robo-advisors in terms of services provided (relative to the rest of the firms) and (2) an increase in investor-level demand for financial advisors. I also find that the observed increase in the number of financial advisors is due to a reduction in separations and an increase in hirings. This is associated with an increase in the average experience of a financial advisor with no e

I study how bankruptcy law firm advertisements affect credit recovery of households

in financial distress. Exploiting the border discontinuity strategy associated with the

geographic unit in which local TV advertisements are sold, I empirically uncover

bankruptcy filings and credit recovery related to exogenous variations in bankruptcy

law firm advertisements. I first document a significant advertising effect on filing

rates and show that advertising-induced filers are similar to existing filers. I then find

a positive effect of advertisements on credit outcomes including credit score, new

homeownership, and foreclosure. I interpret these findings as evidence that lawyers

address information frictions in households’ assessment of the bankruptcy option.

We study the extent of interest rate risk sharing across the financial system using granular positions and transactions data in interest rate swaps. We show that pension and insurance (PF\&I) sector emerges as a natural counterparty to banks and corporations: overall, and in response to decline in rates, PF\&I buy duration, whereas banks and corporations sell duration. This cross-sector netting reduces the aggregate demand that is supplied by dealers. However, two factors impede cross-sector netting and add to substantial dealer imbalances across maturities: (i) PF\&I, bank and corporations' demand is segmented across maturities, and (ii) hedge funds trade large volumes with time-varying exposure. We test the implications of demand imbalances on asset prices by calibrating a preferred-habitat investors model with risk-averse arbitrageurs, who face both funding cost shocks and demand side fluctuations. We find that demand imbalances play a bigger role than arbitrageurs’ funding cost in determining the equilibrium swap spreads at all maturities. In counterfactual analyses, we demonstrate how demand shocks, e.g., regulation leading banks to hedge more, affect the hedging behavior of PF\&I. Our paper provides a quantity-based explanation for empirically observed asset prices in the interest rate derivatives market.

Governments regulate household leverage at a national level, even when credit and housing market conditions vary across locations. We document that loan-to-value limits targeting specific neighborhoods can curb local house price growth. We combine administrative data from Taiwan covering the universe of mortgages, personal income tax returns, geocoded housing transactions, and bank balance sheets. Applying matched difference-in-differences and border difference-in-discontinuity designs, we find leverage limits are effective at persistently reducing local house prices in expensive, high-income neighborhoods, without reducing delinquency or inducing mortgage credit rationing. Consumers avoid place-based mortgage restrictions by obtaining inflated appraisals and moving to less regulated areas.

This paper examines the influence of private equity firm (GP) political contributions on public pension funds' investment decisions using micro-data on investments in private equity (PE) funds. Employing a regression discontinuity design comparing GPs donating to winning versus losing candidates in close U.S. state elections, I find that post-election pensions' tendency to invest are 10 times higher in GPs donating to winner assigned as or appoint their board member. Effects are pronounced for candidates seeking elections afterwards and weakest in states with high public corruption oversight. Connection-based PE funds underperform non-connected ones, partly attributed to abnormal management fees and lower subscription rates.

Are investors’ preferences for responsible investing affected by their idiosyncratic personal experiences? Using a comprehensive dataset for hospital visits and the information on portfolio holdings by retail investors in Denmark, we show that when an investor’s child is diagnosed with a respiratory disease, the investor decreases (increases) portfolio weights of “brown” (“green”) stocks but does not alter their holdings of ESG funds. Consistent with parents attributing respiratory diseases to air pollution, we find no effects for non-respiratory diseases. The results are stronger for more severe diseases and are entirely driven by parents who live with their children.

Are there risk factors that are pervasive across all major classes of corporate securities, including stocks, bonds, and options? We employ a novel procedure that builds

on the ability of asset characteristics to capture the dynamics of asset returns to estimate a conditional latent factor model. A common risk factor structure prominently

emerges across asset classes. The first factor that corresponds to the dominant principal component of the joint cross section significantly explains a substantial component

of time-series variation of individual asset returns across all three asset classes, has a

Sharpe ratio over twice that of the stock market. Other common factors that are less

pervasive, i.e. describe a smaller portion of common variation in returns over time.

Some of the common factors highly correlated with some of asset-class-specific factors

as well as several macroeconomic and financial variables. However, we also document

that the factor structure does not fully capture the cross-section of average returns.

Portfolios that have zero loadings on the top latent risk factors can earn substantial

Sharpe ratios, with different asset classes hedging each other’s exposures to the common

factors.

The financial press is a conduit for popular narratives that reflect collective memory about historical events. Some collective memories relate to major stock market crashes, and investors may rely on associated narratives, or “crash narratives,” to inform current beliefs and choices. Using recent advances in computational linguistics, we develop a higher-order measure of narrativity based on newspaper articles that appear following major crashes. We provide evidence that crash narratives propagate broadly once they appear in news articles, and significantly explain predictive variation in market volatility. We exploit investor heterogeneity using survey data to distinguish the effects of narrativity and fundamental conditions and find consistent evidence. Finally, we develop a measure of pure narrativity to examine when financial press is more likely to employ narratives.

We propose a new framework for understanding non-fungible tokens (NFTs), crypto-assets that typically represent digital artwork. We posit that NFTs are digital Veblen goods: consumers demand them partly because other consumers do. Demand for NFT collections is thus fragile; issuers respond by underpricing their NFTs in primary markets, creating profit opportunities for "scalpers." We construct a simple model of NFT markets emphasizing social forces on demand and verify its predictions empirically. Our results have implications for redesigning NFT primary markets and for interpreting NFT returns.

In the United States, student debt currently represents the second largest component of consumer debt, just after mortgage loans. Repayment of those loans reduces disposable income early in the borrower's lifecycle, when marginal utility is particularly high, and limits their ability to build a buffer stock of wealth to insure against background risks. In this paper, we study alternative student debt contracts that offer a 10-year deferral period. Borrowers defer either principal payments only ("Principal Payment Deferral", PPD) or all payments ("Full Payment Deferral", FPD) with the missed interest payments added to the value of the debt outstanding. We first calibrate an equilibrium with the current contracts, and then solve for counterfactual equilibria with the PPD or FPD contracts. We find that both alternatives generate economically large welfare gains, which are robust to different assumptions about the behavior of the lenders and borrower preferences. We decompose the gains into the percentages resulting from loan repricing and from the deferral of debt repayments. We compare these alternative contracts with the changes to Income Driven Repayment Plans being proposed by the current U.S. administration and show that they dominate such proposals. Crucially, the PPD and FPD contracts deliver similar welfare gains to the debt relief program considered by the administration, with no impact on the government budget constraint.

Using granular data on the entire Brazilian securities lending market merged with all trades in the centralized stock exchange, we identify information leakage from short sellers. Our identification strategy explores trading execution mismatches between short sellers’ selling activity in the centralized exchange and borrowing activity in the over-the-counter securities lending market. We document that brokers learn about informed directional bets by intermediating securities lending agreements and leak that information to their clients. We find evidence that the information leakage is intentional and that brokers benefit from it. We also study leakage effects on stock prices.

We document the emergence of two distinct types of banks over the past decade: high rate banks which provide deposit rates in line with market interest rates, and low rate banks whose deposits are now even less sensitive to market rates. While the aggregate sensitivity of deposit rates to market interest rates has remained similar, the distribution in deposit rates among large banks is now bimodal. High rate banks operate primarily online with very few physical branches, hold short maturity assets, and earn a lending spread by taking credit risk. In contrast, low rate banks operate far more physical branches, offer deposit rates that are even less sensitive to interest rates than before, and they primarily engage in maturity transformation in that they hold longer duration interest rate sensitive assets, but take less credit risk. Deposits shift substantially towards high rate banks when interest rates rise and reduce the ability of the banking sector to engage in maturity transformation. Tracking aggregate deposit flows from the banking sector thus misses a substantial amount of flows within the banking sector. We argue that the distribution of deposits across high and low rate banks is important to understand the transmission of monetary policy, beyond tracking aggregate deposits in the banking sector. Our evidence is consistent with technological changes in banking that lead to the emergence of high rate banks. In response, traditional banks lower rates through the retention of “stickier” depositors.

This paper examines the relation between firm performance and turnover for the directors of public companies over the last two decades. In the mid-2000s, firms with stock price performance in the lowest quartile of the sample exhibit a 15% greater likelihood of director turnover. By the late-2010s, this figure nearly doubles to 28%, a probability that is equivalent to the turnover-performance sensitivity (TPS) for CEOs. We document several factors that contribute to the increase in director TPS over time including trends towards independent board chairs and nominating committees. In addition, the increase in director TPS is most pronounced for firms with a lower local supply of prospective replacement directors and for firms with attentive institutional investors.

Exploiting the unique “twin” structure of German government green and conventional securities, we use a dynamic term structure model to estimate a frictionless

sovereign risk-free greenium, distinct from the yield spread between the green security

and its conventional twin (the green spread). The model purifies the green spread from

confounding and idiosyncratic factors unrelated to environmental concerns. While the

model-implied greenium exhibits a significant relation with proxies of shocks to climate concerns—and the green spread does not—the green spread correlates with stock

market prices and measures of flight-to-quality. We also estimate the greenium term

structure and expected green returns.

I show that non-linear pricing of market risk can explain many prominent cross-sectional stock return anomalies, such as momentum, betting-against-beta, idiosyncratic volatility, and liquidity. The non-linear pricing model is inferred from options data without assumptions on the pricing relationship. I further document that many anomalies have a strong tail risk exposure, which is successfully priced by the model. A key feature of the model is a sizable upside risk premium of approximately 4% per annum. Finally, the pricing results can be explained with a compensation for exposure to systematic variance risk.

I show that the decline in interest rates and corporate tax rates over the past three decades accounts for the majority of the period’s exceptional stock market performance. Lower interest expenses and corporate tax rates mechanically explain over 40 percent of the real growth in corporate profits from 1989 to 2019. In addition, the decline in risk-free rates alone accounts for all of the expansion in price-to-earnings multiples. I argue, however, that the boost to profits and valuations from ever-declining interest and corporate tax rates is unlikely to continue, indicating significantly lower profit growth and stock returns in the future.

This study evaluates the impact of BigTech credit on consumer spending, utilizing a unique dataset from a prominent BigTech ecosystem. In a nearly randomized context, we observe a 19% monthly increase in online spending among credit recipients. This increase is more pronounced for individuals with limited access to traditional financial credit, highlighting the role of BigTech credit in supporting financial inclusion. Moreover, the impact of credit is more notable in areas with more advanced logistics, illustrating the synergy between the financial and non-financial sectors of BigTech firms. Our analysis indicates that the uptick in consumption can be attributed to an increased frequency of purchases rather than to higher order values. Examining order-item level data, we find that credit recipients diversify their buying to include a wider variety of products and brands. Importantly, the provision of credit does not lead to a corresponding increase in discretionary spending or item pricing, and the heightened spending is not associated with increased delinquency, suggesting no overspending associated with BigTech credit.

We document substantial racial disparities in consumer bankruptcy outcomes and investigate the role of racial bias in contributing to these disparities. Using data on the near universe of US bankruptcy cases and a deep-learning imputed measures of race, we show that Black filers are 16 and 3 percentage points (pp) more likely to have their bankruptcy cases dismissed without any debt relief in Chapters 13 and 7, respectively. We uncover strong evidence of racial homophily in Chapter 13: Black filers are 7 pp more likely to be dismissed when randomly assigned to a White bankruptcy trustee. To interpret our findings, we develop a general decision model and new identification results relating homophily to bias. Our homophily approach is particularly useful in settings where traditional outcomes tests for bias are not feasible because the decision-maker’s objective is not well defined or the decision-relevant outcome is unobserved. Using this framework and our homophily estimate, we conclude that at least 37% of the 16 pp dismissal gap is due to either taste-based or inaccurate statistical racial discrimination.

Taking advantage of a novel dataset on individual mutual funds' securities lending activities, we provide the first systematic evidence that mutual funds, especially ESG funds, recall loaned shares prior to voting record dates. Funds' recall-voting sensitivities differ based on their stated lending policies, ownership stakes in portfolio firms, and holding horizons, indicating heterogeneity in funds' perceived values of voting rights. Recalled shares are more likely to be voted against management proposals, and in favor of shareholder proposals and dissident slates in proxy contests. Recall-sensitive funds attract higher fund flows and do not suffer poor performance because of foregone lending revenues.

We investigate how unconventional monetary policy, via central banks’ purchases of corporate bonds, unfolds in credit-saturated markets. While this policy results in a loosening of credit market conditions as intended by policymakers, we report two unintended side effects. First, the policy impacts the allocation of credit among industries. Affected banks reallocate loans from investment-grade firms active on bond markets almost entirely to real estate asset managers. Other industries do not obtain more loans, particularly real estate developers and construction firms. We document an increase in real estate prices due to this policy, which fuels real estate overvaluation. Second, more loan write-offs arise from lending to these firms, and banks are not compensated for this risk by higher interest rates. We document a drop in bank profitability and, at the same time, a higher reliance on real estate collateral. Our findings suggest that central banks’ quantitative easing has substantial adverse effects in credit-saturated economies.

After a new direct board connection is formed to a product market peer, a firm's gross margin increases by 0.8 p.p. Gross margin also rises by 0.4 p.p. after a new connection is formed to a peer indirectly through a third intermediate rm. Using barcode-level data, we further show that new board connections are related to higher prices of consumer goods and a greater tendency to dodge head-on competition. Board connections have positive profitability spillovers on the closest rivals, and the effects are stronger when the newly connected peers have more similar businesses or are located closer to each other.

We analyze jointly optimal carbon pricing and financial policies under financial constraints and endogenous climate-related transition and physical risks. The socially optimal emissions tax may be above or below a Pigouvian benchmark, depending on the impact of physical climate risk on collateral values. We derive necessary conditions for emissions taxes alone to implement a constrained-efficient allocation, and compare the welfare consequences of introducing a cap-and-trade system, green subsidies, or leverage regulation. Our analysis also shows that efficient carbon pricing can be supported by carbon price hedging markets but may be hindered by socially responsible investors in equilibrium.

Contrary to existing literature, we establish that two factors, dollar and carry, suffice to explain a large cross-section of currency returns with R2s exceeding 80%. Our paper highlights the importance of accounting for time-variation in conditional moments. Unconditional estimations that ignore this time-variation mistakenly reject the two-factor model. We propose a parsimonious framework to estimate conditional currency factor models and provide testable restrictions. Our findings imply that currency markets are well described by a model in which (i) each country-specific SDF loads on one country-specific—dollar—and one global—carry shock, and (ii) risk loadings are time-varying. Other risk factors proposed in the literature are useful to describe the time variation in dollar and carry factor risk premia.

I develop a framework to quantify which features of investors’ dynamic trading strategies lead to momentum in equilibrium. I distinguish persistent demand shocks, capturing underreaction, and the term structure of demand elasticities, representing arbitrage intensities decreasing with investor horizon. I introduce both channels into an asset demand system that I estimate from institutional investors’ portfolio holdings and prices. Investors respond more to short-term than longer-term price changes: the term structure of elasticities is downward-sloping, creating momentum, whereas demand shocks mean-revert, contributing toward reversal. Stocks with more investors with downward-sloping term structures exhibit stronger momentum returns by 7% per year.

The integration of algorithmic trading and reinforcement learning, known as AI-powered trading, has significantly impacted capital markets. This study utilizes a model of imperfect competition among informed speculators with asymmetric information to explore the implications of AI-powered trading strategies on speculators' market power, information rents, price informativeness, market liquidity, and mispricing. Our results demonstrate that informed AI speculators, even though they are ``unaware'' of collusion, can autonomously learn to employ collusive trading strategies. These collusive strategies allow them to achieve supra-competitive trading profits by strategically under-reacting to information, even without any form of agreement or communication, let alone interactions that might violate traditional antitrust regulations. Algorithmic collusion emerges from two distinct mechanisms. The first mechanism is through the adoption of price-trigger strategies (``artificial intelligence''), while the second stems from homogenized learning biases (``artificial stupidity''). The former mechanism is evident only in scenarios with limited price efficiency and noise trading risk. In contrast, the latter persists even under conditions of high price efficiency or large noise trading risk. As a result, in a market with prevalent AI-powered trading, both price informativeness and market liquidity can suffer, reflecting the influence of both artificial intelligence and stupidity.

Unlike labor income, human capital is inseparable from individuals and does not completely accrue to creditors, even at default. As a consequence, human capital investment should be more resilient to “debt overhang” than labor supply. We develop a dynamic model displaying this important difference. We find that while both labor supply and human capital investment are hump-shaped in leverage, human capital investment tails off less aggressively as leverage builds up. This is especially the case when human capital depreciation rates are lower. Importantly, because skills acquisition is only valuable when households expect to supply labor in the future, the anticipated greater reduction in labor supply due to debt overhang back-propagates into a reduction in skills acquisition ex ante. Using longitudinal data, we provide empirical support for the model.

Passive investors participate in the corporate bond primary market, despite the bonds not yet being included in their benchmark index. Passive funds have higher holdings in bonds with lower underpricing, which is driven by allocations rather than secondary market purchases or ETF creation baskets. Higher passive holdings are related to deals with less demand (downsized, lower spread compression, and cold offerings) and bonds of lower quality (more likely to be downgraded). The underperformance continues over one month and one year. The main findings are driven by overallocations by underwriters to passive families and by fund families to their passive funds. Our results suggest passive funds serve as a backstop for deals, benefiting underwriters, issuers, and active funds.

We investigate how effective was bank supervision before, during, and after the monetary

tightening of 2022. We find that bank supervisors were aware of the interest rate risks that were emerging in the banking system and began downgrading the ratings of banks with significant exposures to such risks as early as the second quarter of 2022. We do not find that bank supervisors were more likely to downgrade banks whose excessive reliance on uninsured deposits posed liquidity risks. Rating downgrades were associated with subsequent declines in exposures to interest rate risks and with increases in bank liquidity. Overall, our evidence supports the idea that regulators made the banking system safer by limiting the interest rate risk exposures and propping up bank liquidity of many banks as the Federal Reserve began raising interest rates in the second quarter of 2022.

This paper measures diversity, equity, and inclusion (DEI) using proprietary data on survey responses used to compile the Best Companies to Work For list. We identify 13 of the 58 questions as being related to DEI, and aggregate the responses to form our DEI measure. This variable has low correlation with gender and ethnic diversity in the boardroom, in senior management, and within the workforce, suggesting that DEI captures additional dimensions missing from traditional measures of demographic diversity. DEI is also unrelated to general workplace policies and practices, suggesting that DEI cannot be improved by generic initiatives. However, DEI is higher in small growth firms and firms with high financial strength. DEI is associated with higher future accounting performance across a range of measures, higher future earnings surprises, and higher valuation ratios, but demographic diversity is not. DEI perceptions among professional workers, such as R&D employees, are significantly correlated with the number and quality of patents. However, DEI exhibits no link with future stock returns.

In this paper, I study how the political environment impacts the availability of ESG options to individuals. I establish the following judicial channel: because the respect of fiduciary duty is adjudicated by politically-oriented judges, some retirement plans are reluctant to offer ESG options due to litigation risk. I document that there is a significant gap in ESG offerings in retirement plans between conservative and liberal judicial circuits, that is only partially explained by demographic characteristics, firm characteristics, and local political preferences. With a decrease in judicial discretion, which reduces the influence of judges' political orientations, retirement plans face more uniform treatment between judicial circuits. This closes a substantial share of the gap in the ESG market between jurisdictions, and employees in conservative areas increase their ESG investments more than employees in liberal areas. I find that this effect is mostly driven by green firms, small firms, and firms located in the liberal counties of conservative circuits. Additionally, adding ESG options to the menu leads employees to contribute more overall to their retirement plans.

We show that country risk premia include compensation for global political risk. Political risk premia drive international returns within and across asset classes, including equities, bonds, and currencies. A strong factor structure in politically sorted portfolios uncovers systematic variations in global political risk (P-factor). The P-factor commands a significant risk premium of 4.44% per annum with a Sharpe ratio of 0.70, and together with the global market portfolio, it explains up to three-quarters of cross-sectional variation in a large panel of asset returns. The P-factor is unspanned by the existing asset pricing factors, manifests in all asset classes, and is related to systematic variations in expected global growth and aggregate volatility.

This paper studies the distributional effects of earning extrapolation bias on monetary transmission. Empirically, over-pessimistic firms with lower earning forecasts have higher investment elasticity to monetary shocks, which is more pronounced in the advertising-intensive industries. I develop a dynamic model to quantify the effects of extrapolation bias in a frictional product market, where firms extrapolate over idiosyncratic productivity news when making decisions on physical investment and customer acquisition. The model implies that firm-level overreaction amplifies the allocative efficiency of monetary easing: it raises aggregate productivity as capital flows to high markup firms. Moreover, the rise in aggregate output is underestimated by 57% if we assume rational expectation.

Oracles are software components that enable data exchange between siloed blockchains and external environments, enhancing smart contract capabilities and platform interoperability. Using both hand-collected data from hundreds of DeFi protocols and market data for oracle networks, we find that oracle integration is positively associated with total value locked and platform/protocol valuation, triggered by positive network effects in adoption and usage. Our study reveals symbiotic gains from enhanced interoperability across protocols on a given chain and, depending on the mass of integrated protocols, among integrated chains. We also show that oracle integration improves risk-sharing and mitigates contagion; integrated protocols are more resilient than nonintegrated protocols during turbulent periods in crypto markets. We draw parallels between oracle integration and international economics, offering initial insights for regulators, entrepreneurs, and practitioners in the emerging space of decentralized finance.

Constrained, “hand-to-mouth,” households with zero liquid wealth are a central building block of modern heterogeneous-agent consumption models. We document empirically that many of these seemingly borrowing-constrained households actually revolve intermediate levels of high-interest credit card debt, meaning that they are not constrained at either the zero-liquid-wealth kink nor at their credit card borrowing limit. This finding presents a challenge: how can heterogeneous-agent models generate empirically realistic marginal propensities to consume without relying on borrowing-constrained households? We show that present bias induces households to revolve modest levels of credit card debt, but their indebted saving behavior still generates elevated MPCs. We then apply this insight to highlight key channels through which credit card borrowing reshapes households’ responses to fiscal and monetary policy.

Banks finance their lending to risky firms by selling these loans to nonbank financial institutions. Among these nonbanks, collateralized loan obligations (CLOs) provide the bulk of funds. I show that CLO managers have significant market power during loan origination, which increases firms' cost of borrowing in the leveraged loan market. Akin to bank market power in classic lending relationships which are the result of a bank's "information monopoly," nonbank market power is the result of asymmetrically informed nonbanks. Information asymmetries across nonbanks arise from differential information flows during loan underwriting. Contrary to the underwriting of public securities, banks in general disseminate private information about the borrower when marketing a loan. However, some nonbanks self-restrict their information access to publicly available information. To identify my results, I construct a new instrument using novel data on mergers in the CLO industry. I provide the first analysis of these mergers and their determinants. Overall, this research highlights a key distinction between public and private debt markets and its economic consequences for borrowing firms. My findings have important implications for the ongoing legal debate on the applicability of securities law to leveraged loans.

We examine the impact of monetary policy transmission on households’ and firms’ long-duration liabilities using high-frequency variation in 10-year swap rates around FOMC announcements. We find that mortgage rates respond about three weeks after monetary policy announcements at which point they move one-for-one with 10-year swap rates, leaving little explanatory power for credit risk, mortgage concentration, or bank market power. Changes in credit risk do materially affect monetary policy transmission into corporate bonds. We show that expected future short rates and movements in convenience yields play a significant role in explaining both mortgage rates and corporate bond yields. Finally, we assess the implications of our findings for banks’ net worth. Outside of unconventional monetary policy interventions, the banking industry is highly exposed to shocks in long-term rates, with bank stocks increasing by 7.91% for every 1% positive surprise to the 10-year swap rate.

For digital assets, is traditional corporate governance still ideal? We explore the governance of hundreds of prominent Decentralized Autonomous Organizations (DAOs), classifying 28 distinct characteristics related to aspects of governance such as token holder's privileges to bring improvement proposals, the voting process, consensus mechanisms, and security features. Our findings reveal that governance practices fostering broad participation or heightened security are linked with positive abnormal returns, while barriers to improvement proposal adoption correspond to negative returns. This outperformance is also evident in non-financial metrics like user growth and lack of security breaches. Further, evidence from a regression discontinuity design using close-call votes on governance proposals suggests these innovative governance features significantly change value. Overall, our research suggests the benefits of decentralized governance models surpass those that solely concentrate on traditional corporate concerns, such as reducing agency costs, in digital markets.

We study the uncertain transition to a carbon-neutral economy. The requisite technological innovation is made more probable through research and development (R&D). We explore multiple channels of economic and geoscientific uncertainties that impact this transition, and we show how to assess the relative importance of their varied contributions. We represent the social benefit of R&D and cost of global warming as expected discounted values of social payoffs using a probability measure adjusted for concerns about model misspecification and prior ambiguity. Our quantitative results show the value of R&D investment even when the timing of its technological success is highly uncertain.

We provide a unified explanation for two important trends during the last few decades: the decline of the value premium and the rise of the markup. We show that the decline of the value premium and the rise of the markup are primarily driven by firms with high markups, whereas the value premium and the markup remain stable in firms with low markups. We develop a dynamic model with stochastic technology frontier and heterogeneity in firms' technology adoption decisions to explain this finding. In the

model, by adopting the latest technology firms on the technology frontier reduce the operating costs in production, which in turn increases the markup and decreases the dispersion in their exposures to the aggregate technology frontier shocks. This leads to the rise of the markup and the decline of the value premium among the high markup firms. For firms that cannot catch up with the technology frontier due to adoption costs, they keep operating the old technology, thus the markup stays low and the value premium remains sizable.

We study a macro-finance model with entrepreneurs who have diverse views about the likelihood that their ideas will lead to successful innovations. These views and the resulting experimentation stimulate economic growth and overcome market failures that would otherwise occur in an equilibrium without this diversity. The resulting benefits for future generations come at the cost of higher wealth and consumption inequality because a few entrepreneurs will ex-post be successful while most entrepreneurs will fail. Hence, our model provides a potential explanation for the “entrepreneurial puzzle” in which entrepreneurs choose to innovate despite taking on substantial idiosyncratic risk accompanied by low expected returns. Venture capital funds and taxes enhance risk sharing among entrepreneurs, stimulating innovation and growth unless high taxes deplete entrepreneurial capital. Redistribution via taxes reduces inequality and can raise interest rates. Nevertheless, a tradeoff exists between risk-sharing and the exertion of costly effort, giving rise to a hump-shaped economic growth curve when plotted against tax rates.

We use data on stock portfolios of Norwegian households to show that stock market wealth increases entrepreneurship by relaxing financial constraints. Our research design isolates idiosyncratic variation in household-level stock market returns. An increase in stock market wealth increases the propensity to start a firm, with the response concentrated in households with moderate levels of financial wealth, for whom a 20 percent increase in stock wealth increases the likelihood to start a firm by about 20\%, and in years when the aggregate stock market return in Norway is high. We develop a method to study the effect of wealth on firm outcomes that corrects for the bias introduced by selection into entrepreneurship. Higher wealth causally increases firm profitability, an indication that it relaxes would-be entrepreneurs' financial constraints. Consistent with this interpretation, the pass-through from stock wealth into equity in the new firm is one-for-one.

Off-exchange trades are often executed by referencing on-exchange prices. In equilibrium, such price referencing softens market makers' on-exchange competition and makes liquidity expensive for investors. Additionally, by equalizing on- and off-exchange prices, price referencing guarantees “best-execution” and makes investors indifferent where to trade. Market makers effectively obtain a license to fragment orders off exchange, raising their profits but reinforcing market-wide illiquidity. This inefficiency remains tenacious even if more market makers enter and if they are forced to compete off exchange, as in the SEC's proposed order-by-order auction. The model yields important implications for regulating various forms of off-exchange trading.

Traditionally, fund managers cast votes on behalf of investors whose capital they manage. Recently, this system has come under intense debate given the growing concentration of voting power among a few asset managers and disagreements over environmental and social issues. Major fund managers now offer their investors a choice: delegate their votes to the fund or cast votes themselves ("voting choice"). This paper develops a theory of delegation of voting rights and studies the implications of voting choice for investor welfare. If voting choice is offered because investors have heterogeneous preferences, then investors may retain their voting rights excessively, inefficiently prioritizing their private preferences over information. As a result, investors on aggregate are not always better off if voting choice is offered to them. In contrast, if voting choice is offered to aggregate investors' heterogeneous information, then voting choice is generally efficient, increasing investor welfare. However, if information collection is costly, voting choice may lead to coordination failure, resulting in less informed voting outcomes.

This paper investigates how shocks to expected cash flows influence CEO incentive compensation. Exploiting changes in compliance with environmental regulations as shocks to expected future cash flows, we find that adverse shocks typically prompt corporate boards to recalibrate CEO compensation to reduce risk-taking incentives. However, this pattern is not uniform. Financially distressed firms exhibit milder reductions in compensation convexity, with some even increasing it, suggesting a "gambling for resurrection" strategy. Moreover, the strength of corporate governance influences shareholders' capacity to align executive incentives with shareholder risk preferences following unanticipated changes in the stringency of environmental regulations.

Nondiscrimination regulations, administrative costs, and fairness considerations can constrain the within-firm distribution of benefits. Using novel job-level data on nonwage benefits, we find a larger firm component of the variation in benefits than wages. We show that the presence of high-wage colleagues (or high-wage peers in other local firms) positively predicts workers’ benefits, controlling for job characteristics including own wages. Firms with more generous benefits attract and retain more high-wage workers, but also reduce their reliance on low-wage workers more than low-benefit peers. Our results suggest that benefits disproportionately matter for worker-firm matching and, hence, compensation

inequality.

We propose a new framework to explain the factor structure in the full cross section of Treasury bond returns. Our method unifies non-parametric curve estimation with cross-sectional factor modeling. We identify smoothness as a fundamental principle of the term structure of returns. Our approach implies investable factors, which correspond to the optimal spanning basis functions in decreasing order of smoothness. Our factors explain the slope and curvature shapes frequently encountered in PCA. In a comprehensive empirical study, we show that the first four factors explain the time-series variation and risk premia of the term structure of excess returns. Cash flows are covariances as the exposure of bonds to factors is fully explained by cash flow information. We identify a state-dependent complexity premium. The fourth factor, which captures complex shapes of the term structure premium, substantially reduces pricing errors and pays off during recessions.

We study the welfare implications of the rise of common ownership in the United States from 1994 to 2018. We build a general equilibrium model with a hedonic demand system in which firms compete in a network game of oligopoly. Firms are connected through two large networks: the first reflects ownership overlap, the second product market rivalry. In our model, common ownership of competing firms induces unilateral incentives to soften competition. The magnitude of the common ownership effect depends on how much the two networks overlap. We estimate our model for the universe of U.S. public corporations using a combination of firm financials, investor holdings, and text-based product similarity data. We perform counterfactual calculations to evaluate how the efficiency and the distributional impact of common ownership have evolved over time. According to our baseline estimates the welfare cost of common ownership, measured as the ratio of deadweight loss to total surplus, has increased nearly tenfold (from 0.3% to over 4%) between 1994 and 2018. Under alternative assumptions about governance, the deadweight loss ranges between 1.9% and 4.4% of total surplus in 2018. The rise of common ownership has also resulted in a significant reallocation of surplus from consumers to producers.

Combining transaction-level data with survey-based information from a large consumer panel, we show that on average consumers form excessively high expectations about future income relative to ex-post realizations after unexpected positive income shocks. This systematic bias in expectations leads to higher current consumption and debt accumulation as well as a higher likelihood of subsequent default on consumer debt. A consumption-saving model with defaultable unsecured debt and diagnostic Kalman filtering with consumers who over-extrapolate income shocks rationalizes these findings. The model predicts excessive leverage and higher subsequent default rates compared to a rational expectations benchmark. Over-extrapolation of income expectations can contribute to explaining state-dependent household debt cycles.

Women are less likely than men to start firms and female entrepreneurs are less

likely to succeed. This paper studies the effect of childbirth on women’s entrepreneurial activity. Drawing on rich administrative data from Canada and an

event study and instrumental variable design, I show that children have substantial

negative effects on both founding rates and start-up performance, accounting for

a large portion of the gender gap in entrepreneurship. The effects are permanent:

entrepreneurial outcomes never recover to their pre-birth levels. These results are

not fully explained by household specialization based on labor market advantage.

Childcare availability and belonging to a culture with progressive gender norms

reduce the adverse effect of childbirth on the entrepreneurship gap.

We show a significant loss in US Treasury market functionality when intensive use of dealer balance sheets is needed to intermediate bond markets, as in March 2020. Although yield volatility explains most of the variation in Treasury market liquidity over time, when dealer balance sheet utilization reaches sufficiently high levels, liquidity is much worse than predicted by yield volatility alone. This is consistent with the existence of occasionally binding constraints on the intermediation capacity of bond markets.

An asset owner designs an asset-backed security and a signal about its value. After experiencing a liquidity shock and privately observing the signal, he sells the security to a monopolistic buyer. Within double-monotone securites, asset sale is uniquely optimal, which corresponds to the most informationally sensitive security. Debt is a constrained optimum under external regulatory liquidity requirements on securities. Thus, the “folk intuition” behind optimality of debt due to its low informational sensitivity holds only under additional restrictions on security or information design. Within monotone securities, a live-or-die security is optimal, whereas additional-tier-1 debt is optimal under the regulatory liquidity requirements.

We show that firms increase their pollution intensity as they become more financially distressed, particularly in locations with high environmental liability risks. We rationalize these facts using a dynamic model featuring endogenous default and clean and dirty assets. We assume that polluting practices can reduce short-term costs at the expense of exposing firms to persistent liability and regulatory risks. Thus, as firms become more financially distressed, they shift the composition of their assets toward the more polluting ones, akin to a risk-taking motive. Our counterfactuals highlight the limited environmental impact of heightened financing costs as firms intensify their pollution while scaling down.

I find noticeable bunching in venture capital (VC)-backed company valuations at $1 billion, the minimum threshold to be so-called unicorn companies. Exploiting the practice that reported valuations include authorized but unissued shares, VC-backed companies strategically authorize more shares for future employee compensation (e.g., stock options) to achieve unicorn status. Various stakeholders of VC-backed companies, especially employees who face uncertainties and information asymmetry, interpret unicorn status as a positive signal. Contrary to employees’ interpretation, however, inflating valuations to achieve unicorn status lowers the expected value of their stock options. Providing simple stock option payoff diagrams to employees can reduce information frictions.

We study the long-term effects of inflation surges on inflation expectations. German households living in areas with higher local inflation during the hyperinflation of the 1920s expect higher inflation today, after partialling out determinants of historical inflation and current inflation expectations. Our evidence points towards transmission of inflation experiences from parents to children and through collective memory. Differential historical inflation also modulates the updating of expectations to current inflation, the response to economic policies affecting inflation, and financial decisions. We obtain similar results for Polish households residing in formerly German areas. Overall, our findings are consistent with inflationary shocks having a long-lasting impact on attitudes towards inflation.

We study the inflation implications for firms across the market power distribution

from an asset pricing perspective. Inflationary surprises are associated with

persistent declines in stock returns. We propose a new decomposition of the present

value identity of stock prices and show that investors expect nominal cashflows to

remain stagnant during periods of higher-than-expected inflation, a stagflationary

view of the world, on average, while a rising equity risk premium reduces stock

prices. Real yields do not increase in response to inflationary news, inconsistent

with a Taylor-rule type monetary policy-driven stock price response. Firms with a

large degree of market power are shielded from the negative returns following inflation

surprises, as market power firms are expected to generate a relative increase

in their nominal cashflows in response to inflation shocks. Changes in analysts’

firm-level earnings expectations around inflationary surprises confirm these results.

We study the performance of IRA pension plans from 2004 through 2018. We document novel evidence of large return heterogeneity across income groups in the US, and provide estimates of its impact on wealth inequality. High-income individuals substantially outperform low-income ones, and this return differential is almost three times as large in “tax-free” Roth IRAs. These returns cannot be matched by equity market returns, but are consistent with high-income individuals having exposure to private assets.

We examine an emerging phenomenon that talented employees leave successful entrepreneurial firms to join less mature start-ups. Using proprietary person-level data and private firm data, we find that the presence of these “serial venture employees” positively predicts their new employers’ future success in terms of exit likelihoods, size growth, venture capital financing, and innovation productivity. Such predictive power is more likely driven by a screening/matching channel rather than venture labor’s nurturing role. Our paper sheds light on an underexplored pattern of inter-firm labor flow, which provides a nonfinancial yet value-relevant signal about private firms for investors and stakeholders.

U.S. retail brokers route order flow to wholesalers based on their past performance. Brokers

face a strategic choice over how often to reallocate order flow, how aggressively to reward or

punish performance, and what history, across time or securities, to consider. This paper analyzes

how broker choices for allocating order flow shape competition among wholesalers. Our empirical

results are consistent with the theory that prospects for future order flow provide wholesalers

with strong incentives to offer price improvement and allow brokers to discipline the provision

of liquidity.

How efficient is the U.S. patent litigation system? We quantify the extent to which the litigation system shapes innovation using a novel dynamic model, in which heterogeneous firms innovate and face potential patent lawsuits. We show that the impact of a litigation reform depends on how heterogeneous firms endogenously select into lawsuits. Calibrating the model, we find that weakening plaintiff rights through fewer defendant injunctions increases firm innovation and output growth, improving social welfare by 3.32%. Raising plaintiff pleading requirements, which heightens barriers to filing lawsuits, likewise promotes innovation, boosts output growth, and enhances social welfare.

We study production responses to emission capping regulation on manufacturing firms. We find that firms lowered their pollution as they transitioned from self-generated to externally sourced electricity, shifted towards producing less coal-intensive products, and increased their abatement expenditures. Firms preserved profitability by increasing their production towards higher-margin products. However, firms in highly polluting industries produced fewer products, and in the aggregate, leading to lower product variety, higher markups, an altered firm-size distribution, and lower business formation. Our findings highlight both the mechanisms behind how mandated pollution reduction can be effective and its costs, suggesting a loss in agglomeration externalities.

This paper presents new evidence on the impact of bank branch expansion and credit access on human capital outcomes for children. Using a regression discontinuity design, we study a branch authorization policy by the Reserve Bank of India that encouraged banks to open branches in underbanked districts, where the population-to-branch ratio exceeded the national average. Bank presence, bank lending, and household borrowing increased. We find significant improvements in test scores: children in underbanked districts scored 0.16–0.22 SD higher on reading and math. We document three mechanisms. First, we find evidence for a demand-side channel where parents spent more on their children’s education and children spent more time on homework. Second, we document supply-side impacts in improvements in the quantity and quality of schools and teachers. Third, we find support for a labor market channel, with shifts away from agricultural employment and towards employment in manufacturing, while self-employed individuals expanded their businesses.

In March 2020, safe asset markets experienced surprising and unprecedented price crashes. We explain how strategic investor behavior can create such market fragility in a model with investors valuing safety, investors valuing liquidity, and constrained dealers. While safety investors and liquidity investors can interact symbiotically with offsetting trades in times of stress, liquidity investors’ strategic interaction harbors the potential for self-fulfilling fragility. When the market is fragile, standard flight-to-safety can have a destabilizing effect and trigger a dash-for-cash by liquidity investors. Well-designed policy interventions can reduce market fragility ex ante and restore orderly functioning ex post.

We explore the asset pricing implications of shocks that allow firms to extract more rents from consumers. These markup shocks directly impact the representative household's marginal utility and the firms' cash flow. Using firm-level data, we construct a measure of aggregate markup shocks and show that the price of markup risk is negative, that is, a positive markup shock is associated with high marginal utility states. Markup shocks generate differences in risk premia due to their heterogeneous impact on firms. Firms with larger exposures to markup shocks are less risky and have lower expected returns. We rationalize these findings in a general equilibrium model with markup shocks.

We challenge two central tenets of lifecycle investing: (i) investors should diversify across stocks and bonds and (ii) the young should hold more stocks than the old. An even mix of 50% domestic stocks and 50% international stocks held throughout one’s lifetime vastly outperforms age-based, stock-bond strategies in building wealth, supporting retirement consumption, preserving capital, and generating bequests. These findings are based on a lifecycle model that features dynamic processes for labor earnings, Social Security benefits, and mortality and captures the salient time-series and cross-sectional properties of long-horizon asset class returns. Given the sheer magnitude of US retirement savings, we estimate that Americans could realize trillions of dollars in welfare gains by adopting the all-equity strategy.

Price discovery in financial markets guides the efficient allocation

of resources. Yet we argue that speculators uninformed about firms'

fundamentals can profit from distorting the allocative function of prices

by inflating stock prices. Such speculation can be profitable because high

valuations attract employees, business partners, and investors who create

value at targeted firms at the cost of diverting resources away from better

firms. The resulting resource misallocation is worst in "normal" (neither hot nor cold)

markets and when firms o¤er stakeholders performance compensation or equity.

Investors, such as VCs, can also profit from inflating firm valuations in private markets.

Using 150,000 actual trades, we examine competition among wholesalers, to which brokers route orders from their retail investors. We find that each broker's wholesaler execution prices have substantial dispersion and are persistent. However, most brokers do not adjust their routing even when they are sending more orders to higher-cost wholesalers. We also observe that the entry of a new wholesaler improves other wholesalers' execution quality. Finally, we present a stylized model that illustrates how brokers’ limited response to execution allows wholesalers to exercise their market power. Overall, our findings are inconsistent with perfect competition.

How to incentivize a manager to create value and be socially responsible? A manager can predict how his decisions will affect measures of social performance, and will therefore game an incentive system that relies on these measures. Still, we show that the compensation contract uses measures of social performance when the level of corporate social responsibility preferred by the board exceeds the one that maximizes the stock price. Thus, explicit social incentives and socially responsible investors are substitutes. Relying on multiple measures based on different methodologies will generally mitigate inefficiencies due to gaming, i.e. harmonization of social performance measurement can backfire. This has normative implications for the regulation and harmonization of ESG measurement.

The rising frequency and severity of abnormally high temperatures pose significant threats to the health and productivity of exposed workers. This paper identifies a labor channel of corporate exposure to climate risk, measured using firms’ reliance on workers exposed to high temperatures while performing job duties. Consistent with the physical risk mechanism, unexpected extreme heat significantly reduces firm-level and plant-level labor productivity, making labor less efficient than capital as a production input. Firms adapt to these disruptions by shifting toward more capital-intensive production functions, i.e., higher capital-labor ratios. Firms further respond by investing more in robotics-related human capital and developing more automation-related technology. At the macro level, climate change impedes the growth of high-exposure industries in hot areas. My findings highlight that climate change accelerates automation in occupations and firms exposed to rising temperatures.

Using plant-level data from the Census Bureau, we show that unionized plants have lower and less effective incentives in addition to paying higher wages and benefits. Unionized plants do not exhibit the same positive associations between incentives and investment and growth found in non-unionized plants. This effect holds among both non-managerial and managerial employees, although it has a more pronounced influence on the former group. Consequently, unionized plants experience higher closure rates, reduced investment, and slower employment growth. We also find significant spillover effects within the firm: partially unionized firms also offer higher wages and maintain weaker incentives in their non-unionized plants than their industry peers. These effects are economically significant and are half of our estimated reduction in incentives in unionized plants. This pattern aligns with the hypothesis that incentives in nonunionized plants create disutility for the median worker. Spillovers reduce employment and efficiency and make firms less attractive as potential targets, thus reducing the market’s effectiveness in allocating corporate assets. By leveraging recent changes in state-level right-to-work laws, we provide causal evidence that states that adopt such laws experience a boost in employment and investment.

We document low-frequency shifts in the relationship between inflation and the convenience yield on US Treasury bonds. Treasury convenience comoves positively with inflation during the inflationary 1970s and 1980s, but negatively in the pre-WWII period and the pre-pandemic 2000s. We explain these changes with an interplay of the "money channel" and the "New Keynesian demand channel" by introducing Treasury convenience yield into a standard New Keynesian model. Exogenous shocks to inflation (such as cost-push shocks) raise nominal interest rates and, by extension, the opportunity cost of holding money and money-like assets, inducing a positive inflation-convenience relationship as observed in the 1970s and 1980s. In contrast, exogenous shocks to liquidity preferences (such as those originating from financial crises and panics) raise the perceived value of Treasuries, lowering consumption demand and inflation, and result in a negative inflation-convenience relationship as seen pre-WWII and post-2000. We argue that the experience of the past century is inconsistent with a direct effect of inflation depressing Treasury convenience.

We document that 20% of Compustat firms have above-median investment rates despite having below-median marginal product of capital (MPK), seemingly "misallocating" productive resources. These firms are typically younger and significantly more likely to experience a substantial upward jump in their sales and MPK in the following years. They account for a significant share of innovative activity and their investments predict future aggregate productivity in the economy, creating value in ways not captured by their MPK. We propose and estimate a simple endogenous firm growth model that captures the key features of the cross-section of firms and allows for counterfactual analysis. Hypothetical firm investment policies that ignore the potential for future jumps reduce MPK and investment dispersion but also lower aggregate productivity.

Partial Ownership (PO), which allows households to buy a fraction of a home and rent the remainder, is increasing in many countries with housing affordability challenges. We incorporate an existing for-profit PO contract into a life-cycle model to quantify its impact on homeownership, households’ welfare, and its implications for financial stability. We have the following results: 1) PO increases homeownership rates. 2) Willingness to pay increases with housing unaffordability and is highest among low-income and renting households. 3) PO increases aggregate debt as renters become partial owners but also reduces the average leverage ratios as indebted homeowners become partial owners.

This paper studies the economic importance of mobile applications (apps) as intangible assets. Using novel data, we construct a market-based app-value measure and show that it corresponds positively with apps' utility value, measured by future downloads. Firms' app values are associated with a significant reduction in firm-specific risk, especially when the apps collect user data. Following the California Consumer Privacy Act—a plausible exogenous shock to data-collecting ability—the relationship between app value and firm risk diminishes. Moreover, firms' app values predict substantial future growth and increased market power, and the growth is more pronounced when apps collect data.

The canonical mechanism for financial asset exchange is the limit-order book. In decentralized blockchain ledgers (DeFi), costs and delays in appending new blocks to the ledger render a limit-order book impractical. Instead, a “pricing curve” is specified (e.g., the "constant product pricing function") and implemented using smart contracts deployed to the ledger. We develop a framework to study the equilibrium properties of such markets. Our framework provides new insights into how informational frictions distort liquidity provision in DeFi markets.

The classic Q theory of investment is commonly interpreted to assert that marginal Q, synonymous to the marginal value of capital, is the sufficient statistic for investment. That is because Q-theory is purely demand-based in the sense that variations in investment are fully driven by those in the demand for investment.

This paper provides an exposition of how shocks to the supply of investment drive the joint dynamics of investment and Q. In absence of shocks to the marginal cost of invest- ment (i.e., the supply of investment), shocks to the marginal value of investment (i.e., the demand for investment) determine both equilibrium investment and Q, resulting in a con- ventionally expected monotonic relation along the constant upward-sloping investment supply curve. In presence of non-trivial shocks to the marginal cost of investment, how- ever, there is no longer a one-to-one relation between investment and Q. In essence, Q is to investment as price to quantity in any demand-supply system. This paper theoretically demonstrates that, in a general dynamic model of investment, shocks to the investment demand induce a positive comovement between investment and Q when the marginal cost of investment is monotonically increasing, while shocks to the investment supply induce a negative comovement of investment and Q when investment is sufficiently inelastic to supply shocks. The elasticity of investment to demand and supply shocks critically de- pends on their respective persistence. This paper shows with numerical simulations that the correlation between investment and marginal/average Q critically depends on the rela- tive volatility of and the persistence of supply shocks. A modest level of volatility of supply shocks is able to generate low or even negative correlations between investment and Q.

In summary, one should rethink from an equilibrium view the relation between invest- ment and Q, both of which are simultaneously determined by shocks to both investment demand and supply.

This paper studies how homeowners insurance markets respond to growing climate losses and how this impacts mortgage market dynamics. Using Florida as a case study, we show that traditional insurers are exiting high risk areas, and new lower quality insurers are entering and filling the gap. These new insurers service the riskiest areas, are less diversified, hold less capital, and 20 percent of them become insolvent. We trace their growth to a lax insurance regulatory environment. Yet, despite their low quality, these insurers secure high financial stability ratings, not from traditional rating agencies, but from emerging rating agencies. Importantly, these ratings are high enough to meet the minimum rating requirements set by government-sponsored enterprises (GSEs). We find that these new insurers would not meet GSE eligibility thresholds if subjected to traditional rating agencies’ methodologies. We then examine the implications of these dynamics for mortgage markets. We show that lenders respond to the decline in insurance quality by selling a large portion of exposed loans to the GSEs. We quantify the counterparty risk by examining the surge in serious delinquencies and foreclosure around the landfall of Hurricane Irma. Our results show that the GSEs bear a large share of insurance counterparty risk, which is driven by their mis-calibrated insurer eligibility requirements and lax insurance regulation.

Using IQ data from Danish military draft sessions, we document three results: First, employees in family firms have, on average, lower IQs than employees in nonfamily firms. This gap is higher for CEOs and for employees in high-skill job occupations. Second, the IQ gap is correlated with other well-established measures of talent. Third, a firm's average employee IQ is positively correlated with the quality of its management practices, which is significantly lower in family firms. We also document that family members at all levels have higher IQs than non-family members, but family leaders tend to hire employees with lower IQ relatively to non-family leaders. Our findings are consistent with the fact that the talent gap is rooted in family firms’ lower ability to identify and provide incentives for talented individuals.

As a result of the BoJ’s large-scale asset purchases, the consolidated Japanese government borrows mostly at the floating rate from households and invests in longer-duration risky assets to earn an extra 3% of GDP.We quantify the impact of Japan’s low-rate policies on its government and households. Because of the duration mismatch on the government balance sheet, the government’s fiscal space expands when real rates decline, allowing the government to keep its promises to older Japanese households. A typical younger Japanese household does not have enough duration in its portfolio to continue to finance its spending plan and will be worse off. Low-rate policies tax younger, poorer and less financially sophisticated households.

U.S. stocks' response to inflation surprises is, on average, robustly negative and shows pronounced time-series variability. Consistent with a view that stock prices respond to inflation surprises that affect the monetary policy stance, we document the largest stock market sensitivity during periods when inflation expectations and the output gap are running high. During these periods, firms with low net leverage, large market capitalization, high market beta, low book-to-market, and low markups are especially susceptible to inflation surprises.

We propose a structural model of constant gain learning about future earnings growth that incorporates preferences for the timing of cash flows. As implied by the model, a cross-sectional decomposition using survey forecasts shows that high price-earnings ratios are accounted for by both low expected returns and overly high expected earnings growth. The model quantitatively matches a number of asset pricing moments, as learning about growth interacts strongly with the preference for the timing of cash flows, and provides insights on the roles of risk premia and mispricing in the cross-section of stocks. The magnitudes and timing of the comovement between prices, earnings growth surprises, and anomaly returns are all consistent with a gradual learning process rather than expectations being highly sensitive to the most recent realization. Large earnings growth surprises do not immediately translate into large one-period returns, but instead are gradually reflected in future returns over time.

We use data from a major South African payment processor to study how digital payments mitigate asymmetric information challenges in small business "revenue-based financing" contracts, which tie repayment schedules to future revenue. Eight months post-financing, digital payments through the processor are 15% lower for takers than observably similar non-takers. We show this "gap" can be decomposed into three components: moral hazard from revenue hiding, adverse selection, and the causal effect of financing for takers. Two natural experiments suggest that takers shift more revenue off the platform when competition increases (moral hazard), and that financiers can increase repayment by waiting longer before extending offers (adverse selection). With estimates from both experiments, we bound the gap components, finding substantial adverse selection, but also positive short-run causal effects. Our results suggest digital payment platforms with "sticky" features can alleviate classic risk-sharing frictions by imposing hiding costs and limiting hidden information.

Financial data vendors intermediate the flow of information from firms to investors. I study frictions that arise in the context of this intermediation by focusing on one of the most prominent data vendors in the finance industry: Standard & Poor's ('S&P') Compustat database. Compustat provides subscribers with decades of 10-K and 10-Q data; however, it does not cover every public firm in every period. I show that a significant fraction of institutional investors do not invest in firms with missing data -- institutional ownership is over 40% below its unconditional mean for firms not covered in Compustat. A policy change instituted at S&P in the early 1990s provides a quasi-natural experiment to confirm a causal association between Compustat data coverage and institutional investor demand. In a battery of empirical tests, I then show that limited access to financial data is associated with lower informational efficiency of equity prices. This highlights the role that data vendors play in facilitating the flow of information within financial markets.

Textbook theory assumes that firm managers maximize the net present value of future cash flows. But when you ask them, the people running large public corporations say that they are maximizing something else entirely: earnings per share (EPS). Perhaps this is a mistake. No matter. We take managers at their word and show that EPS maximization provides a single unified explanation for a wide range of corporate policies involving leverage, share repurchases, cash holdings, and capital budgeting.

This paper investigates whether green investors can influence corporate greenhouse gas emissions through capital markets, and if so, whether they have a larger effect by the stock of polluting companies in order to limit their access to capital, or by acquiring polluters’ stock and engaging with management as owners. We focus on public pension funds, classifying them as green or nongreen based on which political party controlled the fund. To isolate the causal effects of green ownership, we use exogenous variation caused by state-level politics that shifted control of the funds, and portfolio rebalancing in response to returns from non-equity investment. Our main finding is that companies reduced their greenhouse gas emissions when stock ownership by green funds increased and did not alter their emissions when ownership by nongreen funds changed. Other evidence based on voting, shareholder proposals, and activist pension funds suggests that ownership mattered because of active engagement by green investors, and more through attempts to persuade than voting pressure. We do not find that companies with green investors were more likely to sell off their high-emission facilities (greenwashing). Overall, our findings suggest that (a) corporate managers respond to the environmental preferences of their investors; (b) divestment of polluting companies may lead to greater emissions; and (c) private markets may be able to partially address environmental challenges independent of government regulation.

I examine how population aging affects voter support for and the efficiency of public education provision. Analyzing a decade of school bond referendum data, I find that school districts with older populations are less likely to approve bond proposals to finance school investments. I leverage variations in historical birth rates to show that aging-in-place, rather than endogenous sorting, drives this effect. Comparing narrowly passed and failed referenda, I find that house prices do not appreciate after bond approvals in older-population districts, despite increased spending. These results align with generational divisions over education investment but do not indicate inefficiency.

We study the valuation of state-issued tax-exempt municipal bonds and find that there are significant convenience premia in their prices. These premia parallel those identified in Treasury markets. We find evidence that these premia are tax related. Specifically, the premia are related to measures of tax and fiscal uncertainty, forecast flows into state municipal bond funds, and are directly linked to outmigration from high-tax to low-tax states and to other measures of tax aversion such as IRA and retirement plan contributions. These results suggest that investors are willing to pay a substantial premium to avoid

taxes.

We introduce a novel log-linear identity linking a company's market value to expected future markups, output growth, discount rates, and investments within a present-value framework. By distinguishing between realized and expected markups, we unveil five new empirical facts. (i) Expected markups account for one-third of the rise in aggregate firm values of U.S. public firms since 1980. (ii) The rise in aggregate expected markups is driven by a reallocation of market share towards high-expected-markup firms. Mergers have accelerated this trend with expected (but not realized) markups rising post merger. (iii) Expected markups are closely tied to fixed costs and investments, particularly in intangibles. (iv) There is a negative time-series relationship between expected markups and discount rates, but (v) there is a positive cross-sectional link to risk premia after accounting for other risk factors. These five facts can guide the development of macro-finance models.

Student loans with income-contingent repayment insure borrowers against income risk but can reduce their incentives to earn more. Using a change in Australia's income-contingent repayment schedule, I show that borrowers reduce their labor supply to lower their repayments. These responses are larger among borrowers with more hourly flexibility, a lower probability of repayment, and tighter liquidity constraints. I use these responses to estimate a dynamic model of labor supply with frictions that generate imperfect adjustment. My estimates imply that the labor supply responses to income-contingent repayment decrease the optimal amount of insurance but are too small to justify fixed repayment contracts. Moving from a fixed repayment contract to a constrained-optimal income-contingent loan increases welfare by the equivalent of a 1.3% increase in lifetime consumption at no additional fiscal cost.

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 are 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–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 1.3% 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.

Crowdfunding is an increasingly popular way to raise emergency funding after disasters. However, for victims of a major Colorado wildfire, we find that crowdfunding raised more support for wealthier beneficiaries rather than helping the most vulnerable. Specifically, beneficiaries with income above $150,000 receive 28% more support on GoFundMe than beneficiaries with income below $75,000. High-income households are also 14 percentage points more likely to have a crowdfunding campaign at all. These findings hold conditional on the amount of property value destroyed by the fire. The regressive allocation of disaster crowdfunding relates to several network advantages possessed by high-income households, including more connections outside the disaster area. Our findings highlight substantial disparities in social network insurance, which, as we show, likely 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 healthy 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 uncertainty induced zombification together with loan contract-level data. Empirically, higher uncertainty-led rival zombification prompts unlevered firms to reduce their investment, disinvestment, and employment; as well as establishment-level openings and closures (intensive and extensive margins are affected). These hard-to-reverse decisions are modulated by the anticipation of the extent to which distressed rivals will be subsidized by their creditors. Critically, they depress healthy firms’ long-run sales revenues, profits, and market values. Our findings highlight a novel channel through which uncertainty influences firms’ capital accumulation, performance, and outcomes.

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.

Shocks to the supply of long-term bonds affect the duration of corporate investment. Using large and plausibly exogenous shocks to the maturity structure of US government debt, I find that a higher supply of long-term bonds increases firms’ financing costs at long horizons leading to a crowding-out of long-duration investment. I show that this crowding out occurs through reallocations of capital away from long-duration investment towards short-duration investment, not only across industries but also within industries across firms and within firms across divisions. I show that these changes to the average duration of investment map into changes to the average maturity of corporate debt. These results identify important real effects of policies which affect the net supply of long-term bonds, 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.