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.

A firm's gross margin increases by 0.8 p.p. after forming a new direct board connection to a product market peer. Gross margin also rises by 0.4 p.p. after a connection is formed to a peer indirectly through a third intermediate firm. Further, using barcode-level data of 2.7 million products, we show that new board connections are related to higher consumer good prices and a greater tendency for market allocation. The effects are stronger when the newly connected peers share corporate customers or have similar business descriptions and hold when controlling for other inter-firm relationships.

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.

In recent years, assets of non-bank financial intermediaries (NBFIs) have grown significantly relative to those of banks. These two sectors are commonly viewed either as operating in parallel, performing different activities, or as substitutes, performing substantially similar activities, with banks inside and NBFIs outside the perimeter of banking regulation. We argue instead that NBFI and bank businesses and risks are so interwoven that they are better described as having transformed over time rather than as having migrated from banks to NBFIs. These transformations are at least in part a response to regulation and are such that banks remain special as both routine and emergency liquidity providers to NBFIs. We support this perspective as follows: (i) The new and enhanced financial accounts data for the United States (“From Whom to Whom”) show that banks and NBFIs finance each other, with NBFIs especially dependent on banks; (ii) Case studies and regulatory data show that banks remain exposed to credit and funding risks, which at first glance seem to have moved to NBFIs, and also to contingent liquidity risk from the provision of credit lines to NBFIs; and (iii) Empirical work confirms bank-NBFI linkages through the correlation of their abnormal equity returns and market-based measures of systemic risk. We conclude that regulation should adapt to this landscape by treating the two sectors holistically; by recognizing the implications for risk propagation and amplification; and by exploring new ways to internalize the costs of systemic risk.