US money market funds (MMFs) play an important role in short-term markets as large investors of Treasury bills (T-bills) and repurchase agreements (repos). We build a theoretical model in which MMFs strategically interact with banks and each other. These interactions generate interdependencies between repo and T-bill markets, affecting the pricing of these near-money assets. Consistent with the model's predictions, we empirically show that when MMFs allocate more cash to the T-bill market, T-bill rates fall, and the liquidity premium on T-bills rises. To establish causality, we devise instrumental variables guided by our theory. Using a granular holding-level dataset to examine the channels, we show that MMFs internalize their price impact in the T-bill market when they set repo rates and tilt their portfolios towards repos with the Federal Reserve when Treasury market liquidity is low. Our results have implications for the transmission of monetary policy, benchmark rates, and government debt issuance.

We explain variation in the strength of the U.S. dollar with capital flows driven by primitive economic factors. Prior to the global financial crisis, global savings and demand shifts depreciated the dollar, whereas they appreciated it after. Interest rates impacted the dollar’s value over short horizons, but declined in significance over longer horizons as rates converged. Our estimates imply that the dollar’s value is stable even when one foreign country unilaterally sells its U.S. assets. However, a weakening global demand for U.S. assets of the same magnitude as the early 2000s could significantly depreciate the dollar.

The United States (US) seems safe relative to the rest of the world (ROW). Her macro quantities, asset prices and wealth share all rise relative to the ROW during global downturns. These novel US safety facts challenge the traditional view that the US exorbitant privilege, the large average excess returns on the US external portfolio, is a risk premium that compensates the US for her role as the global insurance provider. Furthermore jointly accounting for countercyclical dollar and global risk premium dynamics alongside the US exorbitant privilege requires the US to suffer a worse recession than the ROW during global downturns, an implication also at odds with these facts. To resolve this puzzle, I emphasise a novel source of US specialness: her excess fiscal capacity vis-a-vis the ROW. I study the joint dynamics between the US fiscal condition, global innovation and growth, international risk-sharing, the dollar and global risk premia in a quantitative model with risk-sensitive preferences that takes this excess US fiscal capacity as given. The framework quantitatively resolves the US safety puzzle, as well as other stylised facts in international macro-finance. These results therefore tie the excess US fiscal capacity to key puzzling phenomena within the modern global financial system, a novel insight that has received surprisingly little emphasis thus far and has important implications for policy moving forward

Machine learning methods for big data trade off bias for precision in prediction. To understand the implications for financial markets, I formulate a trading model with a prediction technology where investors optimally choose a biased estimator. The model identifies a novel cost of complexity that arises endogenously. This effect makes it optimal to ignore costless signals and introduces in- and out-of-sample return predictability that is not driven by priced risk or behavioral biases. Empirically, the model can explain patterns of vanishing predictability of the equity risk premium. The model calibration is consistent with a technological shift following the rise of private computers and the invention of the internet. When allowing for heterogeneity in information between agents, complexity drives a wedge between the private and social value of data and lowers price informativeness. Estimation errors generate short-term price reversals similar to liquidity demand.

This paper develops an asset market-based test for preference for the timing of resolution of uncertainty. Our main theorem provides a characterization of preference for early resolution of uncertainty in terms of the risk premium of assets realized during the period when the informativeness of macroeconomic announcements is resolved. Empirically, we find support for preference for early resolution of uncertainty based on evidence on the dynamics of the implied volatility of S&P 500 index options before FOMC announcements.

I examine the implications of time inconsistency, modeled by hyperbolic discounting, for the excessive trading puzzle and asset prices. I show that unlike the case of long-term contracting with naive time-inconsistent agents where the welfare inefficiency of naivete disappears, dynamic trading allows time-consistent agents to exploit naive agents even over long horizons. In addition, partial awareness of the naivete bias induces leading trading motives such as gambling behavior and perceived information advantage, which can serve as a microfoundation for the puzzling excessive trading volume observed empirically. I show that the asymmetric information about the extent of partial naivete creates uncertainty about the optimal trading contract that the time-consistent agent can offer and endogenously generates extra risks in her consumption dynamics. As a result, the presence of naive time-inconsistent investors increases the risk-free rate, volatility, and risk premium in the economy.

Tweet-level data from a social media platform reveals low average accuracy and high dispersion in the quality of advice by financial influencers, or “finfluencers”: 28% of finfluencers are skilled, generating 2.6% monthly abnormal returns, 16% are unskilled, and 56% have negative skill (“antiskill”) generating -2.3% monthly abnormal returns. Consistent with homophily shaping finfluencers’ social networks, antiskilled finfluencers have more followers and more influence on retail trading than skilled finfluencers. The advice by antiskilled finfluencers creates overly optimistic beliefs most times and persistent swings in followers’ beliefs. Consequently, finfluencers cause excessive trading and inefficient prices such that a contrarian strategy yields 1.2% monthly out-of-sample performance.

We identify a new dimension of cross-firm linkages by exploring the social connectedness between firms' geographical locations. Industry peers located in regions with strong social ties tend to adopt similar strategies and exhibit strong co-movements in both fundamentals and returns. However, this information is not immediately reflected in stock prices and can be exploited using information contained in social peer returns (SPFRET). The predictability of SPFRET lasts for up to a year and forecasts future earnings surprises, analysts' forecast errors, and returns around earnings announcements. The effect is particularly strong for low-visibility firms and those located outside of industry clusters.

Expert networks provide investors with in-depth discussions with subject matter experts. Expert call demand is higher for younger, technology-oriented firms and those with greater intangible assets, consistent with demand for information on hard-to-value firms. Expert calls are more (less) likely to emphasize technology and operational (financial) topics relative to earnings calls. We find that expert call volume is associated with hedge fund position changes and greater price efficiency. The relation is asymmetric, with call volume preceding hedge fund sales, greater short interest, and negative firm performance. The evidence suggests that expert networks help investors discern complicated bad news.

We model platform competition with endogenous data generation, collection, and sharing, thereby providing a unifying framework to evaluate data-related regulation and antitrust policies. Data are jointly produced from users' economic activities and platforms' investments in data infrastructure. Data improves service quality, causing a feedback loop that tends to concentrate market power. Dispersed users do not internalize the impact of their data contribution on (i) service quality for other users, (ii) market concentration, and (iii) platforms’ incentives to invest in data infrastructure, causing inefficient over- or under-collection of data. Data sharing proposals, user privacy protections, platform commitments, and markets for data cannot fully address these inefficiencies. We introduce and analyze user union, which represents and coordinates users, as a potential solution for antitrust and consumer protection in the digital era.

Money is debt that circulates with no questions asked. Stablecoins are a new form of private money that circulate with many questions asked. We show how stablecoins can maintain a constant price even though they face run risk and pay no interest. Stablecoin holders are indirectly compensated for stablecoin run risk because they can lend the coins to levered traders. Levered traders are willing to pay a premium to borrow stablecoins when speculative demand is strong. Therefore, the stablecoin can support a $1 peg even with higher levels of run risk.

I study credit market outcomes with different competing lending technologies: A fintech lender that learns from data and is able to seize on-platform sales, and a banking sector that relies on physical collateral. Despite flexible information acquisition technology, the endogenous fintech learning is surprisingly coarse---only sets a single threshold to screen out low-quality borrowers. As the fintech lending technology improves, better enforcement harms, while better information technology benefits traditional banking sector profits. Big data technology enables the fintech to leverage data from its early-stage operations in unbanked markets to develop predictive models for expansion into wealthy markets.

Asset heterogeneity is widely believed to restrict liquidity in many markets involving important fixed-income assets. We model the impact of quasi-consolidated (QC) trading---a design that allows sellers to deliver heterogeneous assets for identical payments---on over-the-counter (OTC) markets involving assets with varying values. We show that allowing for QC trading reduces market fragmentation but introduces a cheapest-to-deliver (CTD) effect. In consequence, although QC trading increases total trading volume and social welfare, it hurts liquidity for sellers who do not switch to QC trading and lowers profits for both these sellers and some other sellers who switch to QC trading. Consolidating multiple QC contracts increases (decreases) total trading volume and social welfare if the contracts cover assets with similar (distinct) values.

Repo markets suffer from funding misallocations and funding runs. We develop a rollover risk model with collateral to show how repo trading and clearing mechanisms can resolve these inefficiencies. In over-the-counter markets, non-anonymous trading prevents asset liquidations but causes runs on low-quality borrowers. In central-counterparty markets, anonymous trading provides insurance against small funding shocks but causes inefficient asset liquidations for large funding shocks. The privately optimal market structure requires central clearing with a two-tiered guarantee fund to insure against both illiquidity and insolvency. Our findings inform the policy debate on funding crises and explain empirical patterns of collateral premia.

We examine how intermediary capitalization affects asset prices in a framework that allows for intermediary market power. We introduce a model in which capital constrained intermediaries buy or trade an asset in an imperfectly competitive market, and show that weaker capital constraints lead to both higher prices and intermediary markups. In exchange markets, this results in reduced market liquidity, while in primary markets, it leads to higher auction revenues at an implicit cost of larger price distortion. Using data from Canadian Treasury auctions, we demonstrate how our framework can quantify these effects by linking asset demand to individual intermediaries' balance sheet information.

Most research on venture capital (VC) focuses on VCs’ value-add to their portfolio companies. We explore VCs’ broader value-add on the companies they do not fund, specifically as a by-product of their due diligence. We use novel data from a seed Fund that assigns applicants to due diligence based on the scores of quasi-randomly assigned reviewers. We find that assignment to due diligence leads to higher growth, but also increased closure, even among applicants rejected for investment. The results suggest that VC due diligence helps entrepreneurs reduce their information frictions, possibly by enabling entrepreneurs to learn about their businesses.

We study the portfolio problem of an investor (LP) that invests in stocks, bonds, and private equity (PE) funds. The LP repeatedly commits capital to PE funds. This capital is only gradually contributed and eventually distributed back to the LP, requiring the LP to hold a liquidity buffer for its uncalled commitments. Despite being riskier, PE investments are not monotonically declining in risk aversion. Instead, there are two qualitatively different investment strategies with intuitive heuristics. We introduce a secondary market for PE partnership interests to study optimal trading in this market and implications for the LP’s optimal investments.

Recently, new firm formations have become more geographically dispersed with greater regional industry diversity. Using detailed early-stage firm information from Crunchbase, we show that such a diminishing industrial agglomeration trend for young firms is driven by angel financing. This trend is tied to angel investors' unique portfolio selection of startups that diverges from venture capital's approach. Specifically, angels who are exceedingly intolerant of geographic distance prefer to invest in more distinctive firms industry-wise, while venture capital investors make industry-concentrated investments with relatively greater geographic flexibility. We also show that angel investors' portfolio selection of disparate startups enhances funded firms' performance and plays an important economic role in forming the regional entrepreneurial ecosystem.

Using granular payroll data on 22 million federal employees, we study how regulators respond to revolving door incentives: the option to obtain a job in the private sector. We document bunching of salaries just below a threshold that triggers post-government employment restrictions, indicating a deliberate effort to preserve private sector opportunities. Individuals just below the threshold are more likely to exit and become lobbyists. Agencies with significant bunching regulate high-paying industries, initiate fewer enforcement actions, and issue less costly rules, suggesting regulatory capture. Estimating a structural model, we show that eliminating the restriction will increase incentive distortion by 1.7%.

We study the effect of government-subsidized childcare on women’s career outcomes and firm performance using linked tax filing data. Exploiting a universal childcare reform in Quebec in 1997 and the variation in its timing relative to childbirth across cohorts of parents, we show that earlier access to childcare increases employment among new mothers, particularly among those previously unemployed. Earlier childcare access increases new mothers’ reallocation of careers across firms, leading to higher earnings and higher productivity. Firms traditionally unattractive to mothers with young children benefited from the reform, drawing more young female workers and experiencing better performance. Our results suggest that childcare frictions hamper women’s career progression and their allocation of human capital in the labor market.

Entrepreneurs with better diversified portfolios provide more insurance to employees against labor income risk: in a sample of over 524,000 Canadian firms and 858,000 owners, firms owned by more diversified entrepreneurs offer more stable jobs and earnings to employees when faced by idiosyncratic shocks. A one standard deviation increase in owner’s diversification reduces the shock’s pass-through rate to labor layoffs by 13% and to workers’ earnings by 41%. The data are consistent with such insurance being partly provided to retain valuable human capital and partly to avoid costly terminations. There is no evidence of insurance being priced in average wages.

This paper investigates the role of rights offerings as a new market-based mechanism in resolving valuation uncertainties in U.S. Chapter 11 reorganizations. Using hand-collected data on these offerings, I document three novel facts: (i) in the last decade, they have been used to finance 45% of bankruptcy filings, (ii) hedge funds or private equity firms generally proposed them, and (iii) their occurrence is highly correlated with the performance of the stock market. In an instrumental variable setting, I find that compared with other sources of financing, rights offerings are associated with higher recovery rates, shorter time spent in Chapter 11, and lower bankruptcy refiling rates. They also allow firms to access new capital without resorting to asset liquidations, which are value reducing. Overall, these findings suggest that by alleviating key bargaining frictions in the bankruptcy process, rights offerings may improve the efficiency of resource allocation in the economy.

We examine whether CEOs use share repurchases to sell their equity grants at inflated stock prices, a widely shared concern. We document that share repurchases, just like equity grants, vesting dates, and insider trades, are largely affected by the corporate calendar—the firm’s schedule of earnings announcements and blackout periods. The corporate calendar can fully explain why share repurchases and equity-based compensation coincide. Our analysis reveals that firms are actually less likely to repurchase shares when CEOs sell equity. Our findings reconcile earlier studies and highlight the first-order importance of the corporate calendar for the timing of share repurchases.

We examine how access to debt markets affects firms' provision of trade credit. Using hand collected data on trade credit between customer-supplier pairs, we show that increased access to debt strengthens firms' bargaining power relative to major customers and reduces the trade credit they provide to those customers. We establish causality using the staggered passage of anti-recharacterization laws that increased firms' debt capacity. Affected firms expand their customer base, reduce customer concentration, and decrease trade credit to powerful customers. The decline in trade credit leads customers to cut investment, increase leverage, and scale back trade credit provision to firms further downstream.

We study how risk management through hedging impacts firms and competition among firms in the life insurance industry - an industry with over 7 Trillion in assets and over 1,000 private and public firms. We examine firms after a staggered state-level reform that reduces the costs of hedging by granting derivatives superpriority in case of insolvency. We show that firms that are likely to face costly external finance increase hedging and reduce risk and the probability of receivership. Firms that are likely to face costly external finance, also lower prices, increase policy sales and increase their market share post reform.

Nonprofit banks in the U.S. are primarily organized as credit unions (CUs) and have grown steadily over the last two decades, increasing their share of total lending to U.S. households. This paper studies the economic effects of banking with CUs using consumer credit report data merged to administrative data on originated mortgages and detailed data on the locations and balance sheets of CUs. To estimate causal effects, I construct a novel instrument for banking with a CU using a distance-weighted density measure of nearby CUs. I find that banking with a CU causes borrowers to have fewer mortgage delinquencies, higher credit scores, and a lower risk of bankruptcy several years later. I find support for several mechanisms behind these results: CUs charge lower interest rates, price in less risk-sensitive ways, are less likely to resell their originated mortgages in the secondary market, and are more likely to accommodate borrowers that become past due. These results suggest that CUs behave differently than for-profit banks, that many consumers experience different outcomes by banking with CUs, and are inconsistent with CUs behaving as ``for-profits in disguise."

Real-world contractual agreements between firms are often incomplete, leading to suboptimal investment and loss of value in supply-chain relationships. To what extent can blockchain technology help alleviate problems arising from contractual incompleteness? We examine this issue by exploiting a quasi-natural experiment based on the staggered adoption of U.S. state laws that increased firms’ in-state ability to develop, adopt, and use blockchain technology. We find that, after exposure to a pro-blockchain law, firms with greater asset specificity exhibit more positive changes to Tobin’s Q, R&D, and blockchain-related innovation. Also, such firms appear to rely less on vertical integration, form more strategic alliances, and shift their emphasis to less geographically proximate customers. Overall, our results suggest that blockchain technology can help firms remedy constraints and inefficiencies arising from contractual incompleteness.

We present a new log-linear identity that relates a firm's market value to future markups, output growth, discount rates, and investment in a present-value framework. Expected markups are a dominant contributor to variation in firm values and to the rise in the aggregate market value of U.S. public firms since the 1980s. The rise in aggregate expected markups is driven by reallocation of market share towards higher-markup firms, echoing results for realized markups. Expressing markups in terms of a forward-looking value component rather than realized markups reveals that this reallocation has recently been accelerated by mergers involving highly-valued, high-markup target firms. Expected markups are closely tied to expected fixed costs and investments, including investments in intangibles. We find a a negative time-series relationship between expected markups and discount rates rates, but a positive cross-sectional link to risk premia after accounting for other risk factors, thus reconciling risk-based arguments with theories tying the rise in market power to the fall in interest rates.

I demonstrate that the preference by asset managers to diversify stocks and follow certain investment mandates result in forecastable contrarian trading on their largest positions. Since large-cap stocks are held in similar positions across most asset managers, few equity portfolios are available to absorb this predictable source of demand. The large stock portfolios during the sample period (Q1 1990 to Q2 2021) exhibit a novel return-reversal pattern that is consistent with this demand channel. A variable that forecasts this source of demand for large stocks can explain return reversals in the momentum portfolios formed from the largest US companies.

This paper explores the asset pricing implications of a granular economy, where a few firms are exceedingly large (the size of ’grains’). We present three new findings that support the idea that a more granular economy may be detrimental to investors, due to reduced diversification across stocks and heightened aggregate risk. First, the slope of the Security Market Line (SML) exhibits a negative relationship with the level of granularity. Second, the betting-against-beta (BAB) strategy performs well only during times of increased granularity, aligning with the SML’s decreasing slope. Third, exposure to granularity is negatively priced, indicating that stocks performing well during increased granularity offer protection against diversification risk, thereby providing lower returns. These results underscore the critical role of granularity in understanding vital aspects of equity markets.

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.

Stock valuation ratios contain expectations of returns, yet, their performance in predicting returns has been rather dismal. This is because of an omitted variable problem: valuation ratios also contain expectations of cash flow growth. Time-variation in cash flow volatility and a structural shift toward repurchases have magnified this omitted variable problem. We show theoretically and empirically that scaling prices by forward measures of cash flows can overcome this problem yielding optimal return predictors. We construct a new measure of the forward price-to-earnings ratio for the S&P index based on earnings forecasts using machine learning techniques. The out-of-sample explanatory power for predicting one-year aggregate returns with our forward price-to-earnings ratio ranges from 7% to 11%, thereby beating all other predictors and helping to resolve the out-of-sample predictability debate (Goyal and Welch, 2008).

We argue that State of the Union (SOTU) addresses by the U.S. President function as announcements about broad government policies related to upcoming legislative activity of the administration. Unlike traditional macroeconomic and monetary policy announcements, SOTU addresses go back to the 1930s, which allows to expand the sample and context for the announcement effects for financial markets. We find that stock market returns on SOTU days are about ten times larger than on other days, are less volatile, and show strong pre-announcement drift prior to the address. SOTU returns increase in adverse economic, political and high volatility times, more so than on other announcement days. The overall evidence supports the risk premium/uncertainty resolution channel for announcement effects.

What are the real costs of reversals in international capital flows? In this paper, I exploit plausibly exogenous variation in firms’ exposure to rollover risk to identify a causal liquidity channel at play during sudden stop episodes. Using a panel of firms across 39 countries, I show that firms with higher exposure (as measured by the share of long-term debt maturing over the next year) reduce investment ten percentage points more than non-exposed firms following sudden stops in capital flows. The impact is persistent: exposed firms experience lower investment, lower employment and lower assets than non-exposed firms even three years after the initial shock. In robustness tests, I show that the results are specific to sudden stop episodes in that they do not hold in periods without sudden stops, and they hold across sudden stop episodes regardless of whether the sudden stop takes place during large economic contractions.

The corporate basis measures the price differences between bonds issued in dollars and foreign currencies by the same corporate entity. In this paper, we propose a novel method to decompose the corporate basis into three components: credit spread differential, convenience yield differential, and deviation from covered interest rate parity. With this decomposition, we document several stylized facts, and in particular, the substitution effect between safe and risky dollar assets. We provide further evidences on the substitution effect using the structural VAR analysis, which shows that a negative shock to financial intermediaries' balance sheets causes a tightening of credit spread differential, a demand shift toward safe assets, and an appreciation of the dollar. We also find consistent holdings-level evidences using foreign investors' aggregated holdings of safe and risky dollar assets. Lastly, we find spillover effects to the equity and commodity markets, as well as to the domestic and international economic activities. Our results highlight the important role of the dollar, which are further amplified by financial intermediaries, in the global financial markets.

This paper elicits subjective risk premia from an international survey dataset on interest rates and exchange rates. Survey implied risk premia are (i) unconditionally negative for bonds, positive for investment currencies and negative for funding currencies, (ii) correlated with (subjective) macro expectations, (iii) correlated with quantities of risk, (iv) mean-reverting, as opposed to extrapolative; and (v) predict future realised returns with a positive sign. Taking beliefs as given, we estimate a subjective asset pricing model with time-variation in economic uncertainty which supports these findings. This demonstrates that subjective risk premia respect a risk-return trade-off regardless of whether they are rational or not, suggesting that behavioural theories of belief formation can co-exist with rational theories of risk pricing.

Central banks can operate with negative equity, and many have done so in history without undermining trust in fiat money. However, there are limits. How negative can central bank equity be before fiat money loses credibility? We address this question using a global games approach motivated by the fall of the Bank of Amsterdam (1609–1820). We solve for the unique break point where negative equity and asset illiquidity renders fiat money worthless. We draw lessons on the role of fiscal support and central bank capital in sustaining trust in fiat money.

We provide a theoretical framework to analyze the market maker of last resort (MMLR) role of central banks. Central bank announcement to purchase assets in case of distress promotes private agents’ willingness to make markets, which immediately restores liquidity to prevent disorderly sales. This, in turn, decreases the future need for the central bank to intervene. Here, the central bank can reduce the expected usage of the facility by announcing a large capacity, that is, it can end up buying less ex-post by committing to do more ex-ante. However, this beneficial feature comes with potential downsides. First, the central bank may not achieve the intended outcome due to the possibility of multiple self-fulfilling equilibria, which may arise if it does not intervene with sufficient aggression or if market participants have doubts about its commitment. Second, public liquidity provision may crowd out private liquidity if the MMLR access becomes permanent and make the intervention ineffective.

Financial regulation has led banks to increase their equity ratios. Yet, several studies find that this has not led to a decrease in bank equity risk. We show theoretically, that keeping less capital in excess of the minimum capital requirement can outweigh the risk-reducing effect on equity of increased total capitalization. Empirically, we find that excess capitalization is a significant determinant of equity risk, and can explain why bank equity risk has not become lower after the Great Financial Crisis. Smaller excess capitalization also leads to decreases in market-to-book ratios. Lower leverage has, however, reduced the cost of bank debt.

We show in a model of over-the-counter trading that customers in equilibrium may choose to contact very few dealers to incentivize maximum liquidity provision—“less is more.” This happens when dealers’ liquidity supply is sufficiently elastic to competition. This mechanism is orthogonal to conventional concerns, such as contacting or search cost, private information, and relationship. A social planner would mandate even fewer contacts than the market outcome, where customers induce excessive dealer competition. The model predicts endogenous market power, yields implications for regulation and design of electronic platforms, and speaks to customers’ search behavior and their execution quality.

This paper rationalizes the LASSO algorithm based on uncertain fat-tail priors and max-min robust optimization. Our rationalization excludes heuristic learning or restrictive prior assumptions in the original interpretation of LASSO (Tibshirani (1996)). In our setting, economic agents (arbitrageurs) face ambiguity about fat-tail shocks and in equilibrium, they ignore a reasonable range of ambiguous signals but respond linearly to almost unambiguous signals. With this LASSO equivalent strategy, arbitrageurs can amass extra market power which induces a “cartel” to protect their aggregate profit from being competed away. This result shows a new mechanism for limited arbitrage.

Information arrives at securities markets through price quotes and trades. Informed traders impose adverse-selection costs on quote suppliers. This creates incentives for the latter to identify relatively uninformed groups and trade with them off-exchange. The marketplace turns hybrid, at the cost of thinner, highly informed (toxic) volume at the center. This pattern has largely eluded econometricians, because the standard approach to measuring information shares is biased against finding it. We show why this is the case, and design a bias-free approach. The novel approach shows that, indeed, the conjectured pattern is strongly present in the data.

Debt moratoria that allow borrowers to postpone loan payments are a frequently used tool intended to soften the impact of economic crises. We conduct a nationwide experiment with a large consumer lender in India to study how debt forbearance offers affect loan repayment and banking relationships. In the experiment, borrowers receive forbearance offers that are presented either as an initiative of their lender or the result of government regulation. We find that delinquent borrowers who are offered a debt moratorium by their lender are 4 percentage points (7 percent) less likely to default on their loan, while forbearance has no effect on repayment if it is granted by the regulator. Borrowers who are offered forbearance by their lender also have causally higher demand for future interactions with the lender: in a follow-up experiment conducted several months after the main intervention demand for a non-credit product offered by the lender is 10 percentage points (27 percent) higher among customers who were offered repayment flexibility by the lender than among customers who received a moratorium offer presented as an initiative of the regulator. Overall, our results suggest that, rather than generating moral hazard, debt forbearance can improve loan repayment and support the formation of longer-term banking relationships.

Long-term fixed-rate mortgage contracts protect households against interest rate risk, yet most countries have relatively short interest rate fixation lengths. Using administrative data from the UK, the paper finds that the choice of fixation length tracks the life-cycle decline of credit risk in the mortgage market: the loan-to-value (LTV) ratio decreases and collateral coverage improves over the life of the loan due to principal repayment and house price appreciation. High-LTV borrowers, who pay large initial credit spreads, trade off their insurance motive with reducing credit spreads over time using shorter-term contracts. To quantify demand for long-term contracts, I develop a life-cycle model of optimal mortgage fixation choice. With baseline house price growth and interest rate risk, households prefer shorter-term contracts at high LTV levels, and longer-term contracts once LTV is sufficiently low, in line with the data. The findings help explain reduced and heterogeneous demand for long-term mortgage contracts.

I use the random assignment of debt relief policies in a large-scale field experiment to test default models emphasizing liquidity and strategic behavior. In contrast to liquidity being the sole trigger, borrowers respond differently to a dollar reduction in current payments when delivered through forbearance or interest rate reduction: forbearance reduces payments twice as much, whereas delinquencies are more responsive to a rate reduction. Compatible with strategic behavior, borrowers default in response to changes in future payments orthogonal to solvency and liquidity. Compatible with the endogeneity of triggers, whether forbearance or interest rates are more effective, and defaults are strategic is tightly linked to borrower balance sheets. I characterize a single strategic default trigger whose location is influenced by distress, precaution, and assets. The findings have implications for targeting loan modifications and modeling the pass-through of interest rates.

Why do so few women become CEOs? We answer the question by estimating a dynamic model of the CEO gender decision that contains three sources of gender-based differences: unobserved productivity, search frictions that reflect limited female labor supply, and employer disutility arising from discrimination against women. We find that the most crucial factor in explaining the apparent glass ceiling is the shortage of suitable candidates. Net of the availability of suitable candidates, boards are in favor of hiring female CEOs.

We find widespread evidence of firms appearing to avoid paying overtime wages by exploiting a federal law that allows them to do so for employees termed as “managers” and paid a salary above a pre-defined dollar threshold. We show that listings for salaried positions with managerial titles exhibit an almost five-fold increase around the federal regulatory threshold, including the listing of managerial positions such as “Directors of First Impression,” whose jobs are otherwise equivalent to non-managerial employees (in this case, a front desk assistant). Overtime avoidance is more pronounced when firms have stronger bargaining power and employees have weaker rights. Moreover, it is more pronounced for firms with financial constraints and when there are weaker labor outside options in the region. We find stronger results for occupations in low-wage industries that are penalized more often for overtime violations. Our results suggest broad usage of overtime avoidance using job titles across locations and over time, persisting through the present day. Moreover, the wages avoided are substantial - we estimate that firms avoid roughly 13.5% in overtime expenses for each strategic “manager” hired during our sample period.

What characterizes the business angels that invest in early stage innovative firms and what determines their investment performance? We use Norwegian population data on equity transactions for the years 2004--2018 and find that angel investors earn higher returns in their public stock investments than other investors. Their angel investment returns in innovative firms are highly skewed and we document a pronounced performance persistence in angel investments among angel investors.

Does pledging movables as collateral alter corporate borrowing? To answer this question, we study the effect of collateral law reforms on syndicated bank loans granted across nine European countries that facilitated pledging movables between 1995 and 2019, comparing them to nineteen countries that did not. We find that although the reforms have enabled firms to issue more secured loans, the average cost of the loans and the number of covenants has also increased. Banks may demand more to compensate for both the potential wealth redistribution induced by newly issued secured credit and the extra monitoring involved to mitigate concerns about using movables as collateral.

We find that debt covenants have an asymmetric effect on capital structure adjustments of over- and underleveraged firms. While the literature suggests that the presence of covenants imposes a financial cost to all firms, we find that their impact is more nuanced. Introducing a novel measure for covenant tightness, we show that overleveraged firms with tight covenants indeed are slowed down in their adjustment towards their target capital structure. However, this effect is negligible for loose covenants. Conversely, underleveraged firms generally appear to slow down their adjustment in the presence of debt covenants. However, if they get sufficiently close to violation, the covenant has a discipling effect and incentivizes the firms towards a faster adjustment towards the target. Our results are robust across time periods and hold for different definitions of leverage ratios.

Banks are widely believed to have an information advantage, but regulation forces them to sell deteriorating loans, potentially hampering renegotiation and amplifying the initial negative shock to the borrower. We study to what extent the secondary market affects loan outcomes after an initial shock to credit quality. We show that banks, together with CLOs, sell downgraded loans to unregulated financial institutions. The reallocation of loan shares favors the syndicate's concentration, increases lenders' incentives to renegotiate and substitutes lenders' specialization. However, during periods of generalized distress, when potential buyers experience financial constraints, the secondary market fails to reallocate loan shares and syndicate ownership remains dispersed. We show that subsequently loans are less likely to be amended and more likely to be downgraded even further.

We exploit regional variations in exposure to heat stress to study if physical climate risk is priced in municipal and corporate bonds as well as in equity markets. We find consistent evidence across asset classes that local exposure to heat stress is associated with higher yield spreads for bonds, especially for lower-quality and longer-maturity bonds, as well as higher conditional expected returns for stocks. These results are observed robustly starting in 2013–15, and are consistent with macroeconomic models where climate change has a direct negative impact on aggregate consumption.

This paper analyzes how climate risks are priced on financial markets. We show that climate tipping thresholds, disagreement about climate risks, and preferences that price in long-run risks are crucial to an understanding of the impact of climate change on asset prices. Our model simultaneously explains several findings that have been established in the empirical literature on climate finance: (i) news about climate change can be hedged in financial markets, (ii) the share of green investors has significantly increased over the past decade, (iii) investors require a positive, although small, climate risk premium for holding "brown'' assets, and (iv) "green'' stocks outperformed "brown'' stocks in the period 2011--2021. The model can also explain why investments to slow down climate change have been small in the past. Finally, the model predicts a strong, non-linear increase in the marginal gain from carbon-reducing investments as well as in the carbon premium if global temperatures continue to rise.

Carbon-intensive firms have been underperforming in the U.S. despite their higher carbon transition risk. The brown-minus-green return spread, or carbon return, is zero on average globally but varies significantly across countries with unexpected cash flow shocks and climate taste shifts. The lower carbon return in developed markets reflects stronger growth in climate concerns instead of a lower expected carbon return. Additionally, countries with civil laws, more renewable energy, and tighter climate policies exhibit higher carbon returns. The inference differs from previous studies because I relate stock returns to lagged carbon measures, avoiding the issue of forward-looking bias.

Using a comprehensive database of corporate news, we examine how bond mutual funds trade on the sentiment of news releases. We find that bond funds trade against the direction of news sentiment (e.g., selling after good news about a firm). The results are more pronounced in bonds that lie within a fund’s investment objective sector, and in bonds with high turnover and low information asymmetry, and in credit-rating news and news with positive sentiment. Funds that most frequently trade against news sentiment produce a higher alpha, and a source of such alpha is bond price reversals post news events. Fixed income mutual funds, dealers, and insurance companies complement each other in news trading, with mutual funds trading against news largely in the absence of dealers. Our study indicates that bond mutual funds represent a significant liquidity provider, upon corporate news events, in the market for corporate bonds.

Using a dataset of over a million local government procurement contracts in China, we study the social and economic costs of local government debt. Firms contracting with local governments with high maturing debt-to-fiscal income see an increase in accounts receivables that do not reverse, a decrease in cash balances, and an increase in the probability of litigation by creditors. These effects (1) are not driven by local economic conditions, endogenous government indebtedness, or self-selection into becoming government suppliers, (2) do not apply for government-linked firms, and (3) are larger for firms in areas with weaker labor and property rights. Affected firms are less likely to be repeat government contractors and more likely to see protests relating to non-payment of wages or pension contributions, suggesting that suppliers bear the costs involuntarily.

We use a model of a limit order book to determine the optimal tick size set by a social planner who maximizes the welfare of market participants. Our results show that when investors arrive sequentially and supply liquidity by undercutting or queuing behind existing orders, the optimal tick size is a positive function of the asset value and a negative function of stock liquidity. Intuitively, the tick size is a strategic tool a social planner uses to optimally affect investors' choice between liquidity demand and supply, thus mitigating the inefficiencies created by excessive undercutting and queuing. The policy implication of such findings is that both the European tick size regime and the 2022 SEC proposal dominate Reg. NMS Rule 612 that formalizes the tick size regime for the U.S. markets. Using data from the U.S. and the European markets we test our model's predictions.

We test for skewness preferences in a large set of observational panel data on online

poker games (n=4,450,585). Each observation refers to a choice between a safe option and

a binary risk of winning or losing the game. Our setting offers a real-world choice situation

with substantial incentives where probability distributions are simple, transparent, and

known to the individuals. Individuals reveal a strong and robust preference for idiosyncratic

skewness, which has important implications for asset pricing. The effect of skewness

is most pronounced among experienced and losing players but remains highly significant

for winning players, in contrast to the variance effect.

We find that active mutual funds owning product market competitors have superior risk-adjusted returns that are not driven by industry concentration, common selection, or stock-picking ability. These funds charge higher fees but also generate persistent net-of-fee returns for investors. Funds with higher common ownership are more active voters who are more likely to vote against executive incentives compensation and for directors with existing directorships in competitors. Our findings suggest some actively- managed mutual funds have an incentive to soften product market competition and that proxy voting could serve as one mechanism for influencing corporate policy.

Using a novel representative sample of digital payment data, we observe a robust U-shaped relationship between individual investors’ monthly entertainment-related consumption and stock market returns in the previous month. Contrary to the prediction of the wealth effect, individuals increase their entertainment-related consumption after experiencing large positive and negative stock market shocks. We show that the latter effect, termed “financial retail therapy,” is consistent with a dynamic model of Prospect Theory, and provide further evidence for it in a controlled laboratory experiment. Finally, we show that our results are not driven by income effects or wealth shock measurement errors.

Households exhibit "return chasing" behavior, so through asset reallocation channel, good stock market performance induces contractions in deposit supply. Using stock market performance as a shock to deposit supply, we trace out banks' deposit demand and identify the relationship between bank market power and the slope of deposit demand. Exploiting a fixed effects identification strategy by comparing branches with the same parent bank located in different cities within the same county, we find that bank market power makes deposit demand curve steeper. Steeper deposit demand curve attenuates the spillover effects on the local deposit market of stock market fluctuations. Counties with more bank market power also experience less contractions in small business lending when stock market performance is good. Overall, our results suggest that bank market power is important in insulating and stabilizing local deposit and lending market from the spillover effects of the stock market.

A beneficial effect of bank regulation may play out through the asset management sector. When asset managers count on a central bank to support market liquidity in a systemic event, they take on fire-sale risk that is excessive from a social perspective. However, the extent of risk-taking today also incorporates the spread that bank dealers would charge for absorbing fire sales tomorrow. If regulation constrains banks' balance-sheet space, the expected spread would be higher, reining in excesses in asset managers' risk-taking and ultimately raising welfare.

This paper investigates the impact of trading on the commodity futures risk premium. We focus on intra-commodity spreading positions and study the asset pricing implications of spreading pressure (SP), that is, spreading positions scaled by open interest, on the cross-section of commodity futures returns. We document that SP negatively predicts futures excess returns. A battery of empirical tests shows that SP helps separate commodities that trade based on economic fundamentals from commodities that are subject to market frictions introduced via commodity index investments. We propose an SP factor, a long-short portfolio based on SP that is priced in the commodity futures market, even after controlling for well-known factors, and is robust to accounting for omitted variable biases and measurement errors.

We uncover a significant relationship between the persistence of marketing employment strategy and fund performance in the U.S. mutual fund industry. Using regulatory filings, we show a large heterogeneity in fund companies' marketing employment share, which refers to the fraction of employees devoted to marketing and sales. Not only does the marketing employment share increase in family size and predict subsequent fund flows, but it is also persistent across fund families. A framework based on Bayesian persuasion and costly learning helps explain the observed strategic marketing decision. Regarding an optimal marketing plan, fund companies with different skill types commit to heterogeneous marketing employment strategies. Conditional on the skill level, fund companies' optimal marketing employment share responds to their past performance differently. Low-skill funds only conduct marketing following good-enough past performance, whereas high-skill funds maintain a high marketing employment share even with very poor past performance. Consistent with the model prediction, we show that the volatility of the marketing ratio is negatively correlated with the long-term performance of fund companies.

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 firm. Board connections have positive profitability spillovers on the closest rivals, and the effects are stronger when the newly connected peers share major corporate customers, have more similar business descriptions, or are located closer to each other. Using retail scanner data, we further provide direct evidence that new board connections are related to higher product prices of consumer goods.

Using a sample of 101,834 cross-border deals announced between 1985 and 2018, we show that merger flows involve acquirers from more democratic countries than their targets. This result is primarily driven by a “pull” factor, that is, firms in countries with weaker democratic institutions attract cross-border deals. Democratic institutions have a fundamental influence on international merger activity because they are conducive to better corporate governance standards. Further decomposing the effect reveals that democratic institutions also play a direct role that is not due to investor protection or economic development. Our findings imply that democracy is an important, omitted determinant of cross-border mergers.

Private Equity (PE) has grown into a substantial asset class, but there remain major problems with measuring PE fund returns. Investors continue to use the internal rate of return (IRR) as a key measure of fund performance. It is well known that early returns of cash can have a substantial impact on fund IRRs, but the magnitude and causes of this effect have not previously been systematically analysed. We demonstrate that the IRR is affected by two biases: a convexity bias, and a “quit-whilst-ahead” bias arising because the returns on PE projects tend to covary with their durations. Both bias the IRRs of PE funds upwards.

Using parametric and non-parametric estimation techniques, we show that these biases boost fund IRRs by an average of around 3% per annum. This represents a substantial proportion of the amount by which the average net PE fund IRR (around 12% per annum) appears to outperform returns on listed equity indices.

Fund cash multiples and PMEs become similarly biased if they are annualized to try to make them comparable with other assets. We further demonstrate that alternative performance measures which have been suggested by practitioners are also biased, which confirms how poorly understood these effects are. Failure to take proper account of these biases is likely to lead investors into badly misinformed investment decisions.

I present a theory of investor selling behavior in which the disposition effect arises because investors are slow to update their beliefs about the values of the assets they hold. I show numerically that the theory generates a disposition effect, propensity to sell functions, and other trading statistics that are in line with empirical estimates. I also show that the theory generates a reversed disposition effect at the end of the tax year, a weaker effect for more sophisticated investors, a stronger effect in more volatile stocks, and a disposition effect in short sales.

We study the impact of investors’ benchmarking concerns on market efficiency and asset pricing. Both separative and integrative learning technologies are examined as investors allocate limited attention across assets. We show that benchmarking can increase the price informativeness of benchmarked asset as investors optimally adopt integrative learning to observe a combined signal about asset payoffs. This is contrary to the result from the existing literature that assumes separative learning. Benchmarking can also increase the overall market efficiency with either type of learning. Yet, the implications for asset prices and comovements can be qualitatively different under different learning technology.

The value factor has no incremental pricing power in the Fama-French (2015) five-factor model. Thereby, its pricing power is primarily subsumed by the investment factor. We show that the strong relationship between the two factors arises because their sorting variables—book-to-market and investment—are both driven by shocks to expected cash flows and discount rates. We document that only stocks driven by shocks to discount rates contain the factors’ cross-sectional pricing information. The value and investment premia based on these stocks are more than 50% higher than the usual value and investment premia. Importantly, adjusted versions of the value and investment factors that use only such discount rate shock-driven stocks cannot subsume each other and improve the five-factor model’s pricing power. Thus, a value factor built from stocks for which book-to-market is actually a good indicator of expected returns captures incremental pricing information and is no longer redundant. Consequently, multifactor models should include such a value factor.

We find that loans to a borrower sharing similar technologies with the bank’s prior borrowers have lower loan spreads, likely due to reduced costs in loan screening and monitoring from bank’s accumulated knowledge. Such effect cannot be explained by product market competition, technology value and innovation ability or other firm characteristics. We show that borrower technology similarity is informative about firm creditworthiness. Despite identification challenges, we use a structural bank-borrower matching model to show that the total economic surplus for banks and borrowers can be enhanced by matching banks to borrowers with a high technology similarity to the bank’s prior borrowers. This technology similarity also plays an important role in the bank’s learning-by-lending process.

Unlike labor income, human capital is inseparable from individuals and does not accrue to creditors 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 individually identifiable data, we provide empirical support for the model.

This paper compares various machine learning models to predict the cross-section of emerging market stock returns. We document that allowing for non-linearities and interactions leads to economically and statistically superior out-of-sample returns compared to traditional linear models. Although we find that both linear and machine learning models show higher predictability for stocks associated with higher limits to arbitrage, we also show that this effect is less pronounced for non-linear models. Furthermore, significant net returns can be achieved when accounting for transaction costs, short-selling constraints, and limiting our investment universe to big stocks only.

We study the extent to which actively managed mutual funds bet on the CEO. Focusing on firms with CEO turnovers in a particular month, we find significantly higher trading activity and exit rates for funds holding this stock in that month compared to all other months and compared to all other firms. The trading activity and exit rates are higher for raided CEOs and serial CEOs, consistent with some funds placing larger bets on CEOs with higher perceived managerial ability. In further tests, we find strong persistency in the tendency for some funds to bet on the CEO, and show that such funds are less likely to be team managed, and have larger portfolio weights on firms in industries where managerial skills are more valuable. They charge higher fees, but despite that, their net returns are similar. Overall, our results uncover that betting on the CEO is an investment strategy of some actively managed mutual funds. We finally show that this strategy is upheld in equilibrium in a model where the motive for trade is differences in opinion about the importance of the CEO.

We develop a machine learning (ML) approach to establish new insights into how memory affects financial market participants’ belief formation processes in the field. Using analyst forecasts as proxies for market beliefs, we extract analysts' mental contexts and recalls that shape forecasts by training an ML memory model. First, we find that long-term memories are salient in analysts’ recalls. However, compared to an ML benchmark trained to fit realized earnings, analysts pay more attention to distant episodes in regular times but less during crisis times, leading to recall distortions and therefore forecast errors. Second, we decompose analysts' mental contexts and show that they are mainly shaped by past earnings and forecasting decisions instead of current firm fundamentals as indicated by the ML benchmark. This difference in contexts further explains the recall distortion. Third, our comprehensive memory model reveals the significance of specific memory features and channels in analysts' belief formation, including the temporal contiguity effect and selective forgetting.

I show that, in a DSGE setting with heterogeneous shareholders, the stock market risk premium and volatility decrease as monitoring increases. Monitoring arises because inside shareholders have an incentive to extract private benefits from firm output, whereas outside shareholders have the incentive to limit this extraction. Monitoring varies positively with the share of outside shareholder ownership, such that monitoring represents a source of cross-sectional and time-series variation in equilibrium asset pricing moments. I present empirical evidence supporting these theoretical results.

The microfinance industry serves over 140 million borrowers worldwide, and has been hailed as a means of fighting poverty and stimulating growth of small businesses in low- and middle-income countries. Yet evidence from several countries suggests a negligible average impact of microcredit on the performance of small businesses. In this paper, I explore the impact of equity-like microfinance contracts with performance-contingent payments, which provide a greater amount of risk-sharing than the standard rigid microcredit contract. I conduct artefactual field experiments with a sample of business owners who were participating in two broader field experiments in Kenya and Pakistan that had provided their businesses with large capital injections. I find that contracts with performance-contingent repayments outperform standard microcredit contracts, by stimulating more profitable investment choices, especially for the most risk-averse individuals. Loss-averse individuals also particularly value equity-like contracts, which provide downside protection in return for upside profit sharing. However, individuals who exhibit non-linear probability weighting prefer debt contracts, especially in the presence of a skewed profits distribution (where there is a low probability of very high outcomes, which such individuals overweight). I structurally estimate these three distinct dimensions of risk preferences using a prospect-theoretic model and show that relatively simple tweaks to contract design (specifically, capping upside profit sharing) can improve the feasibility of equity-like contracts. By utilising financial technology developments that improve screening and monitoring, and by taking into consideration three distinct elements of risk preferences, financial institutions that cater to small firms can unlock new forms of performance-contingent capital to provide better risk-sharing and improve client welfare.

I quantify the costs of realized flood disasters for banks and create a novel measure of bank-level flood risk exposure using expected flood risk estimates and mortgage lending data. I document that banks with large shares of mortgages in affected areas experience lower profits and capital ratios following flood disasters. In the cross-section of stock returns, small banks with high exposure to flood risk underperform other banks, on average, by up to 9.6% per year; this implies that exposure to flood is not fully priced. Underperformance persists when controlling for the negative effects of disasters on realized returns and adjusting for investors’ climate change concerns. The findings support regulatory concerns that bank equity is exposed to physical risk from climate change.

This paper uses proprietary data on self-reported employee reviews from Glassdoor.com to study the relationship between employee satisfaction and mutual funds’ performance. Using the staggered adoption of Anti-SLAPP (Strategic Lawsuits Against Public Participation) laws in the U.S. and variation from mergers between asset management companies to identify exogenous variation in job satisfaction, we find that employee satisfaction is positively linked to fund performance and size but that only performance-critical employees' satisfaction matters. A one-point increase on the 5-point scale of employee satisfaction leads to a 36bps increase in annual abnormal fund performance. Finally, while there is a positive effect of employee satisfaction on risk-taking, we cannot establish a causal relationship.

We evaluate the performance of common stock trade classification algorithms to infer the trade direction of option trades. Using a large sample of matched intraday transactions and Open/Close data, we show that the algorithms’ success to classify option trades is considerably lower than for stocks. The weak performance is due to sophisticated customers who often use limit orders instead of market orders to implement their trading strategies. These traders’ behavior varies over time and across exchanges with different pricing models. We introduce new rules that enhance existing algorithms and improve classification accuracy by 9% to 47%. Applying our new rules to construct a long-short trading strategy for stocks based on option order imbalance increases Sharpe ratios from 2.65 to 4.07.

In this paper, we provide an estimate of the ex-ante risk premia on earnings announcements based on the option market. We find that the risk premia are time-varying and have predictive power on future stock returns. The well-documented positive post-earnings-announcement drift (PEAD) is present only when the risk premia are high. After controlling for the announcement risk premia, the PEAD factor of the literature no longer has any abnormal returns. Moreover, while trading option straddles is not profitable unconditionally, conditional on high ex-ante risk premia, it becomes profitable even net of transaction costs.

ETFs add a new layer of market-making to the corporate bond market that improves the market quality of the underlying bonds. Dealers use the flexibility of the primary corporate bond ETF market as a warehouse to manage inventory. The face value of ETF holdings in investment grade (high yield) bonds is 9.1% (25.9%) greater on the downgrade date than thirty days prior. Bonds eligible for inclusion in ETFs with the most active primary markets overreact less than other downgraded bonds from the same issuer. This new layer of market-making leads to a negative relation between ETF ownership and idiosyncratic volatility.

We examine the causal effect of politicians’ partisan ideologies on firms’ industrial pollution

decisions. Using a regression discontinuity design involving close U.S. congressional elections, we show that plants increase pollution and invest less in abatement following close Republican wins. We also find evidence of reallocation: firms shift emissions away from areas represented by Democrats. However, costs rise and M/B ratios decline for firms whose representation becomes more Democratic, suggesting that politicians’ ideological demands can be privately costly. Pollution-related illnesses spike around plants in Republican districts, suggesting that firms’ passthrough of politicians’ ideologies can have real consequences for local communities.

Using granular auction data on 15 million item purchases in Brazilian public procurements between 2005-2021, we document a widespread pattern that the lowest bidder (``kamikaze'') does not satisfy required formalities after the auction is concluded, which allows the second-lowest bid to win the auction. Such a pattern can be observed in up to 15-20% of procurement auctions and results in 15-17% higher procurement prices as compared to similar auctions procuring the same product or service items, organized by the same government institutions, and even having the same winning firm. Kamikaze firms are smaller, younger, and tend to be co-owned by the same ultimate owner as the winning firm. Using observed kamikaze behaviour as a marker, we aim to measure how higher procured prices contribute to real outcomes by public service providers by reducing the budget available for sourcing other items. Taking the case of hospital mortality data, we see an increased number of deaths in the four quarters after an increased fraction of procurement auctions involving kamikazes.

Our study introduces an experimental framework to examine the role of attention in the decision-making process, with a particular focus on its impact on learning and belief formation. In order to identify attention, we draw upon the Salient Theory developed by Bordalo, Gennaioli, and Shleifer (2012). We conduct a two-stage online experiment and uncover several noteworthy findings. Firstly, slightly more than half of the participants show salient thinking characteristics, indicating a proclivity to overweight the standout option among a set of alternatives. Secondly, our results reveal that participants tend to overreact to salient signals and, more importantly, that overreaction is mainly driven by salient thinkers. Additionally, salient thinkers exhibit a greater degree of optimism than others when they receive positive signals, which is further amplified when these signals are infrequent. Lastly, while the salience anomaly is more pronounced in the short term, it disappears over an extended estimation period.

Using a unique experiment in the credit market, we find that anonymous loan applications mitigate racial disparities. When names are on applications, ethnic minorities are 10.7% less likely to receive online loan offers than otherwise identical majority applicants; anonymizing applications eliminates such disparities. After receiving online loan offers, applicants need to visit lenders in person for identity verification before loan origination. Despite that race is revealed to lenders, racial disparities in loan origination also decrease. We do not find significant racial gaps in loan performance either before or after anonymization. Further tests show that accurate statistical discrimination is unlikely to explain our results.

Using comprehensive issuance-level information for dollar-denominated short-term debt, we show that investments by money market mutual funds (MMFs) significantly reduce issuers’ funding frictions. Issuers without MMF funding pay approximately 10 basis points more for placing their short-term debt, even when comparing issuers with small MMF investments to issuers without MMF investments. Funding costs increased for issuers who lost their MMF investors because of an exogenous regulatory shock to the MMF industry in 2016. Issuers who lose their MMF investors reduce their outstanding short-term debt by more than 50% and issue debt with shorter durations, suggesting that MMF investments reduce an issuers’ funding fragility.

We study the effect of a central bank digital currency (CBDC) on the money market. A CBDC is equivalent to a 100% reserve requirement to fund those transactions that require CBDC, contrary to transactions that require bank deposits that only need partial reserve backing. We find that a higher fraction of transactions conducted with CBDC will drain reserves and tend to increase the interbank rate. The effect of CBDC remuneration is however ambiguous. A higher CBDC rate increases its value as a payment instrument. This leads to lower funding costs and larger investment, decreasing or increasing the demand for reserves and the interbank market rate, depending on which effect dominates. We show that a cap on CBDC will reduce the interbank rate and the deposit rate, as banks need less deposits to buy reserves. A CBDC design with tiered remuneration does not bring additional benefits relative to a single (lower) remuneration rate.

We propose a novel method to impute daily mutual fund trades in individual stocks from data on quarterly fund holdings, monthly total net assets, and daily fund returns – so that the method can be applied to standard CRSP mutual fund data. We set up an (underidentified) system of linear equations and solve the underidentification issue with an iterative method that applies random and adaptive constraints on trade incidence. The method produces daily, stock-level trade estimates with associated confidence levels. Validation and simulation analyses using proprietary daily fund trading data show good accuracy, especially for larger trades.

This paper studies the link between government guarantees for banks and bank asset concentration. We show theoretically that these guarantees, when combined with high leverage, incentivize banks to further invest in asset classes they are already heavily exposed to. We confirm these predictions using U.S. panel data, exploiting exogenous changes in banks' political connections for variation in bailout expectations. At the bank level, we find that higher bailout probabilities are associated with higher portfolio concentration. At the bank-loan class level, we find that banks respond to an increase in their bailout expectations by further loading up on loan classes that already have a high weight in their portfolio.

I study the spillover effects of removing barriers to growth in one product market on entry and growth of firms in the downstream/customer market. Constrained firms produce low quality goods and, in turn, hamper access to high quality inputs for downstream firms. I exploit the repeal of product reservation in India, whereby hundreds of products stop being reserved for exclusive production by small firms. With an increase in production of high quality goods in the input market, entry in the downstream product market increases. Entrants are not worse on observable characteristics. Productive downstream incumbents grow and less productive ones shrink. My results imply that business dynamism has positive spill-over effects along the supply chain.

While various theories stress the importance of technology for cryptocurrency valuation, empirical evidence is limited. In this paper, we study whether technology aspects of cryptocurrencies matter for their valuations, using machine learning methods to construct a technology index from initial coin offering whitepapers. We then track down the performance of cryptocurrencies from their initial offering to long-term valuations. We find that the cryptocurrencies with high technology indexes are more likely to succeed and less likely to be delisted subsequently. Moreover, the technology index strongly and positively predicts the long-run performances of cryptocurrencies. Overall, the results suggest that technological sophistication is an important determinant of cryptocurrency valuations.

In this paper, I define employee morale as employees’ attitudes toward and perceptions of the tasks the employees have in the companies they work for, toward companies’ dynamics and working conditions, and toward their interactions with fellow colleagues. I explore how employee morale affects post-merger integration and performance and post-merger merged firm employee morale using various proxies. The paper makes several novel findings. First, mergers between firms with similar employee morale are more likely to merge and achieve greater short-run and long-run post-merger synergies. Second, firms with high and similar morale achieve better post-merger integration than firms with low and similar morale and complementary morale. Third, companies with similar morale experience a more rapid rate of completion and exhibit a higher likelihood of completion. Fourth, target companies with high employee morale take less time to be integrated into acquiring companies, regardless of the acquiring companies’ employee morale. Fifth, acquiring companies value the employee morale profile of target companies and they tend to go after target companies with high level and low dispersion in dimensions of employee morale. Sixth, distance between acquirer and target employee morale is negatively associated with post-merger employee morale level and positively associated with post-merger employee morale changes. Finally, the observed acquirer price runup reflects takeover rumors generated from acquirer employees.

We study how prepayment penalties influence credit availability and borrowers' post-origination loan performance using a fuzzy regression discontinuity design that exploits exogenous variation due to idiosyncrasies of US state law. Estimates show a prepayment penalty 1) reduces the probability of delinquency by 5.1%, 2) the odds of foreclosure by 4.9%, 3) increases the likelihood of loan origination by 2.5%, and 4) lowers interest rates by 6.4%. The effect sizes are larger among riskier borrowers. The findings are consistent with theoretical models' predictions that prepayment penalties act as a borrower commitment device which acts against adverse selection as refinancing leads to a deterioration of the quality of lenders' mortgage pools.

This paper studies how banking regulators should disclose the models they use to assess banks that have reporting discretion. In my setting, assessments depend on both economic conditions and the fundamental of banks' asset. The regulatory models provide signals about economic conditions and banks report the fundamental of their asset. On the one hand, disclosing the models helps banks to understand how their assets perform under different economic environments. On the other hand, it induces banks with assets that are socially undesirable to manipulate the report and obtain favorable assessments. While the regulator can partially deter manipulation by designing the assessment rule optimally, the disclosure of regulatory models is necessary. The optimal disclosure policy is to disclose the regulatory models when the assessment rule is more likely to induce manipulation and keep them secret otherwise. In this way, disclosure complements the assessment rule by reducing manipulation in cases that harm the regulator more. The analyses speak directly to the supervisory stress test and climate risk stress test.

Why are over-the-counter markets the dominant market structure for many asset classes? We argue that non-anonymous trading and repeated interactions facilitate trading relationships that solve a moral hazard problem. Using data from a large European OTC dealer, we provide show that customers with a strong relationship obtain much more favorable bid-ask spreads, and that this effect is even stronger during market stress. We present evidence that moral hazard, not adverse selection, drive relationships. Customers with strong relationships can credibly commit to a fixed trading size, to not trade with other dealers and to not exploit the dealer when quotes are stale. We also show that the scope of OTC relationships extends across asset classes and that investment banks' organisational structure is designed to ensure that traders offer discounts to highly valued customers.

I develop a real options model to explain average returns and return volatilities of stock portfolios sorted on the book-to-market ratio. While average returns increase monotonically across portfolios, return volatilities are U-shaped. My model combines business cycle variations with countercyclical economic uncertainty. Operating leverage and procyclical growth options make both value stocks and growth stocks risky, generating U-shaped return volatilities. Growth stocks additionally load on the negative variance risk premium which reduces their expected return. Using structural estimation, my model jointly fits average returns and return volatilities, thereby solving a long-standing problem in investment-based asset pricing. Further reduced-form evidence supports the model channels.

We combine high-frequency stock returns with risk-neutralization to extract the daily common component of tail risks perceived by investors in the cross-section of firms. We find that our tail risk measure significantly predicts the equity premium, variance risk premium and realized moments of market returns at short-horizons. Furthermore, a long-short portfolio built by sorting stocks on their recent exposure to tail risk generates abnormal returns with respect to standard factor models and helps explain the momentum anomaly. Incorporating investors’ preferences via risk neutralization is fundamental to our findings.

We show that net demand in the S&P 500 option market is fundamental to explain empirical puzzles related to the pricing kernel. When public investors (non-market makers) are exposed to variance risk by net-selling out-of-the-money (OTM) options, the pricing kernel is U-shaped, expected option returns are low and the variance risk premium is high. Conversely, when public investors are protected against variance risk by net-buying OTM options, the pricing kernel is decreasing in market returns, expected option returns are high and the variance risk premium is low. Our findings support equilibrium models with heterogeneous agents in which options are nonredundant.

Max Pain price is the strike price at which the total payoff of all options (calls and puts) written on a particular stock, and with the same expiration date, is the lowest. We construct a measure of (potential) Max Pain gain/loss, sort stocks according to this measure, and find that a spread portfolio that buys high Max Pain stocks and sells low Max Pain stocks generates large, positive and statistically significant returns and alphas. Our results provide strong evidence of stock return predictability at the expiration of the options. Finally, we find that these returns reverse after the options expiration week. This is all consistent with stock manipulation on the part of market participants with short positions. Our results are especially strong for relatively small and illiquid stocks.

We document that implied volatility (IV) curves extracted from short-term equity options frequently become concave prior to the earnings announcements day (EAD), typically reflecting a bimodal risk-neutral distribution for the underlying stock price. Firms with concave IV curves exhibit significantly higher absolute stock returns on EAD and higher realized volatility after the announcement, as compared to firms with non-concave IV curves. Hence, concavity in the IV curve constitutes an ex-ante option-based signal for event risk in the underlying stock. Returns on delta-neutral straddles, delta-neutral strangles, and delta- and vega-neutral calendar straddles are all negative and significantly lower in the presence of concave IV curves, showing that investors pay a substantial premium to hedge against the gamma risk arising due to this event.

We document a regime change in the U.S. Treasury market post-Global Financial Crisis (GFC): dealers switched from net short to net long Treasury bonds. Consistent with this change, we derive ``net-long'' and ``net-short'' Treasury curves that account for dealers' balance sheet costs, and show that actual Treasury yields moved from the net short curve pre-GFC to the net long curve post-GFC. This regime change helps explain negative swap spreads post-GFC and the co-movement among swap spreads, dealer Treasury positions, yield curve slope, and covered-interest-parity violations, and implies changing effects for a wide range of monetary and regulatory policy interventions.

We examine the opportunity cost of foreign exchange (FX) intervention when both CIP and UIP deviations are present. We consider a small open economy that receives international capital flows through constrained international financial intermediaries. Deviations from CIP come from limited arbitrage or through a convenience yield, while UIP deviations are also affected by risk. We show that the sign of CIP and UIP deviations may differ for safe haven countries. We examine the optimal policy of a constrained central bank planner in this context. We find that there may be a benefit, rather than a cost, of FX reserves if international intermediaries value more the safe haven properties of a currency that domestic households. We show that this has been the case for the Swiss Franc and Japanese Yen.

The rise in net international bond positions of non-US investors over the last decade can account for the long-run surge in net dollar hedging positions in FX derivatives. The latter influence spot exchange rates through CIP arbitrage. Using intermediaries' capital ratio as a supply shifter, we identify a price inelastic derivative demand by institutional investors and document that changes in their net hedging positions can explain approximately 30% of all monthly variation in the seven most important dollar exchange rates from 2012 to 2022.

This study documents how investors extrapolate from recent stock returns of locally headquartered firms when forming beliefs about aggregate stock market outcomes. Consistent with studies on the equity home bias, we find that the responsiveness to local information is a function of proximity. While investors may feel more comfortable interpreting local information, we find no evidence that these effects are sensitive to the informativeness of local returns for the aggregate outcome. Our findings suggest that differences in beliefs about information contained in public signals varies systematically with geography, which has been suggested as an important driver of the local bias in equity markets.

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.

Recent findings on the term structure of equity and bond yields pose severe challenges to existing equilibrium asset pricing models. This paper presents a new equilibrium model of subjective expectations to explain the joint historical dynamics of equity and bond yields (and their yield spreads). Equity/bond yields movements are mainly driven by subjective dividend/GDP growth expectations. Yields on short-term dividend claims are more volatile because short-term dividend growth expectation mean-reverts to its less volatile long-run counterpart. Procyclical slope of equity yields is due to the counter-cyclical slope of dividend growth expectations. The correlation between equity returns/yields and nominal bond returns/yields switched from positive to negative after the late 1990s, mainly owing to a shift in correlation between real GDP growth and real dividend growth expectations from negative to positive, and only partially due to procyclical inflation. Dividend strip returns are predictable and the strength of predictability decreases with maturity due to underreaction to dividend news and hence predictable dividend forecast revisions. The model is also consistent with the data in generating persistent and volatile price-dividend ratios, excess return volatility, and momentum.

How do shocks to banks transmit to loan terms faced by borrowers on different loan markets? In our model of multidimensional contracting between heterogeneous risky borrowers and intermediaries with limited lending capacity, loan terms depend on loan demand elasticities and default elasticities. These two sufficient statistics predict how the cross-section of loan terms and bank risk react to changes in capital and funding costs. Using empirical estimates, they explain the heterogeneous transmission of shocks across loan markets and borrower risk categories. Accounting for non-price loan terms is important for dynamics because their endogenous response can increase the persistence of credit crises.

Does global financial market integration alleviate or exacerbate the transmission of major disruptions in global trade? Using novel data linking regional banking markets with import flows in Brazil, we document that the presence of globally-active banks at the municipal level is associated with a weakened transmission of trade disruptions to imports. For identification, we exploit municipalities’ exposure to pandemic-related lockdowns in their trade partners abroad, controlling for local imports demand. The supply-driven and robust results suggest that global banks compensate for the effect of lockdowns by providing wider access to US dollar funding as well as by reducing cross-border information frictions. This evidence highlights a strong link between global financial integration and the resilience of real-sector integration.

This paper studies how interconnected plants distribute additional liquidity from banks

through the supply chain. Using a spatially segmented bank branch expansion rule in India, we find that direct exposure to additional bank credit allows plants to hold less precautionary cash and increase bank debt. Directly exposed plants pass through liquidity to customer plants as short-term trade credit. This liquidity spillover improves sales, employment, and productivity at customer plants. Structural estimation yields an average credit multiplier of 1.48. Our results underscore the credit multiplier effects of production networks and the importance of financial integration among firms with limited banking services.

Using a comprehensive multi-year U.S. dataset, we show that off-exchange (wholesaler) executions tend to benefit retail investors by separating their flow from the more toxic non-retail flow. Although the wholesale industry is concentrated, three findings suggest that wholesalers may not abuse market power. Firstly, brokers reward wholesalers who offer lower liquidity costs with more order flow. Secondly, the largest wholesalers offer the lowest costs, due to economies of scale. Finally, the entry of a new large wholesaler does not result in a reduction of liquidity costs.

We investigate differences in execution quality and payment-for-order-flow (PFOF) across asset classes. In equities, retail trades receive meaningful price improvement, particularly in tick-constrained stocks, and PFOF is small. In single-name equity options, problematic market structures lead to worse retail price improvement, and PFOF is large. While all option trades execute on-exchange, option exchange rules facilitate internalization. We exploit variation in designated-market-maker (DMM) assignments, minimum tick size, and auction allocation rules, showing that option internalization is imperfectly competitive. Option market structure gives rise to a second potential incentive conflict of brokers: encouraging customers to trade assets offering higher PFOF.

We investigate the effects of market fragmentation on price impact. Using a newly launched exchange as a quasi-natural experiment, we find that an exogenous increase in market fragmentation leads to a higher price impact of equity trading in the primary U.S. equity exchanges. Our IV estimates suggest a 1.6% increase in market fragmentation of a stock will induce approximately 2.9 bps increases in NBBO-based price impact and much more significant increases in exchange-based price impact for trading that stock. We attribute the increases in price impact to both the mechanical channel and the informational channel. Our results are providing supportive evidence to the recent theories such as Chen and Duffie (2021) that the introduction of a new lit exchange changes the landscape of trading in a multi-market setting, therefore leading to an increase in the price impact of trading.

I study the causal effects of life expectancy on households' financial and economic decisions. My sample consists of individuals who undergo genetic testing for a hereditary cancer syndrome. Genetic testing randomizes tested persons into two groups. Those who test positive learn that they face a high risk of cancer and a shorter life expectancy. Those who test negative learn that their cancer risk is not elevated. The differences in outcomes between these two groups identify the effects of life expectancy. I find that life expectancy has a positive effect on wealth accumulation. Lower savings rates, safer portfolios, decreased labor supply, and different preferences for household composition explain lower wealth accumulation under reduced life expectancy.

This paper is the first to non-experimentally establish a causal relationship between households’ mortality beliefs and subsequent saving and consumption decisions. Motivated by prior literature on the effect of personal experiences on individuals’ expectation formation, I exploit the death of a close friend as an exogenous shock to the salience of mortality of a household. Using data from a large household panel, I find that the death of a close friend induces a significant reduction in saving rate of 2.2 percentage points which persist over the following 5 years. I augment the life-cycle model of consumption by the experienced-based learning model and quantify the impact of this personal experience on mortality beliefs. Even though the shock has

no material impact on a household’s situation, I find a quantitatively large initial

reduction in expected survival probability of 7.1 percent.

We exploit a policy reform that exogenously deteriorates mothers’ job prospects. China switched from a one-child policy to two-child in 2016, which increased female workers’ childbearing and caring responsibilities. Using a leading peer-to-peer lending platform targeting college students in China, we find that loan applications from female college students decrease by 15.6\% relative to male students after the reform. The drop suggests that female students can anticipate the poorer future job prospects; they reduce their expenditure and invest less in human capital accordingly. Applications for long-term and large-amount loans and loans for human capital investment purpose experience the largest decline. We also find that loan applications decrease after provincial governments' staggered extension of maternity leaves and that the decrease is more prominent when the expected motherhood penalty is greater. The results are unlikely driven by credit supply channels.

Using both the onset of the US-China trade war in 2018 and the most recent Russia-Ukraine conflict and associated trade tensions, we show that government-linked firms increase their importing activity by roughly 33% (t=4.01) following the shock, while non-government linked firms trading to the same countries do the opposite, decreasing activity. These increases appear targeted, in that we see no increase for government-linked supplier firms generally to other countries (even countries in the same regions) at the same time, nor of these same firms in these regions at other times of no tension. In terms of mechanism, government supplier-linked firms are nearly twice as likely to receive tariff exemptions as equivalent firms doing trade in the region who are not also government suppliers. More broadly, these effects are increasing in level of government connection. For example, firms that are geographically closer to the agencies to which they supply increase their imports more acutely. Using micro-level data, we find that government supplying firms that recruit more employees with past government work experience also increase their importing activity more – particularly when the past employee worked in a contracting role. Lastly, we find evidence that this results in sizable accrued benefits in terms of firm-level profitability, market share gains, and outsized stock returns.

We examine the survival, profitability, and employment profiles of private equity (PE) acquired hospitals. Target hospitals sustain their survival rates and improve in profitability. Although employment and wage expenditures substantially decline, the effect differs across employee types: The decline in core medical workers is short-lived, while the decline in administrative workers and their wages persists. These changes are more pronounced for nonprofit targets, and targets acquired into larger systems, and PEs with healthcare industry expertise. We do not find patient outcomes to worsen at acquired hospitals. Our results suggest that PE acquirers improve hospitals’ operational efficiency without compromising healthcare quality.

We examine why institutional investors vote the way they vote on director elections, using a novel dataset on voting rationales provided by institutional investors. We find that the most important reasons for opposing directors are board independence, board diversity, tenure, firm governance, and busyness; institutional investors are also increasingly voting against directors to hold them accountable for failure to address environmental and social issues. We find that institutional investors' concerns are well-grounded: companies with low board gender diversity receive more rationales on board diversity, similar for companies with long director tenure and busy directors. This is consistent with institutional investors devoting significant effort toward governance research. Finally, companies with high dissent voting related to board diversity, tenure, and busyness improve their board composition in the following year. Our results suggest that directors are willing to address concerns that result in high shareholder dissent, and voting rationales can be an effective tool to communicate the source of dissent.

Workers care deeply about wage and employment stability. Given potentially differing attitudes towards risk, we investigate whether the provision of wage and employment insurance by firms differs for men and women. We find that women are less protected than men against idiosyncratic shocks to their employers—a gender gap in firm insurance. Using detailed administrative data from Sweden, we document that the elasticity of women’s wages with respect to variations in firm’s idiosyncratic performance is 90% higher than that of men. The likelihood of dismissal due to a negative firm shock is 36% higher for female than for male employees. These gender differences in exposure to corporate idiosyncratic shocks are larger for employees with children, in firms with fewer female executives, and in financially constrained firms.

We show that signals of leadership qualification are more important for women's career advancement than for men's. Specifically, signals of higher education, professional experience and access to professional networks increase male directors' probability to enter a leadership position by 5.2%, and their compensation by 5.7% ($246,900). Female directors with these signals are 11.0% more likely to enter a leadership position, and their compensation is 19.7% ($796,800) higher. This result is in line with models of screening discrimination, in which women need to provide more observable skill signals to counterbalance higher uncertainty about their unobservable qualifications for a leadership position. Supporting this channel, we find that our results are stronger if information asymmetries between (mostly) male employers and female candidates are larger: successions after the sudden death of a CEO, successions in firms with all-male nomination committees, and outside hires.

This paper provides novel evidence that female politicians increase the proportion of US government procurement contracts allocated to women-owned firms. The identification strategy uses close elections for the US House of Representatives. The effect concentrates in local contractors and persists after the female politician’s departure. The more gender-balanced representation in government contracting does not seem to be associated with economic costs, as the firm characteristics of the average contractor and contract performances are unchanged. By analyzing congressional requests from legislators to federal agencies, we show that female politicians affect procurement contract allocation through individual oversight.

We introduce investors with preferences for green assets to a general equilibrium setting in which they also prefer consuming green goods. Their preference for green goods induces consumption premia on expected returns, which counterbalance the green premium stemming from their preferences for green assets. Because they provide a hedge when green goods become expensive, brown assets command lower consumption premia, while green investors allocate a larger share of their portfolios towards them. Empirically, the green-minus-brown consumption premia differential reached 30-40 basis points annually, and con- tributes to explaining the limited impact of green investing on the cost of capital of polluting firms.

We study ESG and non-ESG mutual funds managed by overlapping teams. We find that non-ESG mutual funds include more high ESG stocks after the creation of an ESG sibling, and the high ESG stocks they select exhibit superior performance. The low ESG stocks selected by ESG siblings also exhibit superior performance and despite being more constrained, the ESG funds outperform their non-ESG siblings. The latter result is consistent with fund families making choices that favor ESG funds. Specifically, ESG funds tend to trade illiquid stocks prior to their non-ESG siblings and get preferential IPO allocations.

Flooding is the most costly natural disaster in the US. To protect collateral value against flood risk, many mortgage borrowers are thus required by law to maintain flood insurance. However, compliance is loosely enforced and lapsed policies are common. This paper hypothesizes that with a high monitoring cost borne by lenders, credit supply will depend on borrowers' insurance incentives. Exploiting an exogenous premium rise ($266 per year) which disincentivizes some borrowers to buy flood insurance, I show that lenders increase the corresponding mortgage denial rates by 0.8 percentage points (3.54% of the mean). This effect is gigantic, 80 times larger than that of lowering a borrower's annual income by $266. I rule out alternative demand-side explanations and provide evidence to support the mechanism that lenders internalize ex-post monitoring costs into ex-ante restrictions on credit supply.