We provide a comprehensive analysis of the timing success for equity risk factors. Our analysis covers over 300 risk factors (factor zoo) and a high dimensional set of predictors. The performance of almost all groups of factors can be improved through timing, with improvements being highest for profitability and value factors. Past factor returns and volatility stand out as the most successful individual predictors of factor returns. However, both are dominated by aggregating many predictors using partial least squares. The median improvement of a timed vs. untimed factor is about 2% p.a. A timed multifactor portfolio leads to a 20% increase in return relative to its untimed counterpart.

We investigate the effect of ETF ownership on stock market anomalies and market efficiency. We find that low ETF ownership stocks exhibit higher returns, greater Sharpe ratios, and highly significant alphas in comparison to high ETF ownership stocks. We show that high ETF ownership stocks demonstrate more pronounced information flows than low ETF ownership stocks which reduces their mispricing as they are more informationally efficient. We find similar results when we match the two groups based on size, volume, book-to-market, and momentum. Our results are robust to different matching methods and to a wide array of controls in Fama-MacBeth regressions. Using Russell index reconstitution, we find causal evidence that ETF ownership attenuates anomaly returns.

We hypothesize that when price correction requires more capital than any one investor can provide, institutions coordinate trading via crowd-sourcing in the media. When the crowd reaches a consensus, synchronized trading occurs, prices are corrected, and anomaly returns result. We use over one million Wall Street Journal articles from 1980 to 2020 to develop a novel textual measure of institutional investors making predictions in the media (InstPred). We show that (i) both value and momentum anomaly returns are 34% to 63% larger when InstPred is higher; (ii) these effects are driven by stocks whose institutional investors are highly cited in WSJ articles; and (iii) institutional investors collectively trade the anomalies more aggressively when InstPred is higher. Our results cannot be explained by existing measures such as document tone.

We use options and return data to show that negative stock market returns are significantly more painful to investors when they occur in periods of low volatility. In contrast, popular asset pricing theories imply that the pricing of stock market risk does not vary with volatility, or that it moves in the opposite direction. Our finding suggests that stock market volatility evolves largely independently from the pricing kernel. We embed this assumption into a consumption-based model with a disappointment averse investor. The model captures the dynamics of the pricing kernel and resolves four recent puzzles about stock market risk premia.

We bring investors with preferences for green assets to a general equilibrium setting in which they also prefer consuming green goods. Their preferences for green goods induce consumption premia on expected returns that 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, and 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 contributes to explaining the limited impact of green investing on polluting firms’ costs of capital.

We propose an equilibrium asset pricing model in which agents learn about the parameters that drive economic fundamentals and differ in their aversion to uncertainty. We first show that, when agents are averse to parameter uncertainty, learning about the volatility of fundamentals has a first-order effect on portfolio flows: uncertainty-averse agents increase their risky asset holdings in periods of high uncertainty, despite holding conservative portfolios. We then show that subjective risk premia increase following both unexpected good and bad news. These predictions are consistent with observed portfolio flows of retail and institutional investors around dividend surprises. Our model highlights that heterogeneity of preferences and learning about volatility of fundamentals are key channels for understanding the equilibrium dynamics of portfolio holdings and risk premia following news about economic outcomes.

Does the availability of monitoring capital influence private firms’ decision to go public? Using a geographic framework, we measure the amount of monitoring capital provided by institutional investors and banks in each U.S. region. When the capital of institutional investors in a region is abundant, young collateral-poor resident firms are more likely to go public. They also do so at a younger age. In contrast, when regional bank capital is abundant, these firms are less likely to go public. To sharpen our empirical analysis, we design a quasi-exogenous experiment using out-of-state pension flows and banking deregulation to show that regional economic factors do not drive our findings. Overall, the evidence is consistent with the theoretical prediction that monitoring capital alleviates collateral constraints and provides firms with the opportunity to obtain financing (Holmstrom and Tirole, 1997).

This paper analyzes cash flow and cost of capital dynamics around share repurchase announcements of publicly traded US firms by decomposing stock returns into news related to cash flows and discount rates. After repurchase announcements, the cost of capital decreases significantly, while cash flows do not change. The decrease in the cost of capital is largest for firms that appear underpriced. These firms also experience the highest long-term returns after repurchase announcements. The volatility of the discount rate and cash flows also decreases but is not systematically related to long-term returns. The findings suggest that market participants learn about a temporary overestimation of the cost of capital when firms announce share repurchases.

We analyze how the adoption of the California Consumer Privacy Act (CCPA), which limits the acquisition, processing, and trade of consumer personal data, heterogeneously affects firms with and without previously gathered customer data. Exploiting a novel and hand-collected data set of 11,436 conversational-AI firms with rich personal information on U.S. consumers, we find that the CCPA gives a strong protection and advantage to firms with previously accumulated (in-house) data. First, products of these firms generate more customer feedback and exhibit higher product ratings after the adoption of the CCPA. Second, publicly traded firms with in-house data exhibit higher valuations, profitability, asset utilization, and they invest more after the adoption of the CCPA. Third, earnings of such firms can be more accurately predicted by analysts. To rationalize these empirical findings, we build a general equilibrium model where firms produce intermediate goods using labor and data in the form of intangible capital. Data can be traded with other firms subject to a cost representing regulatory and technical challenges. Firms differ in their ability to collect data internally, driven by their business models and/or the size of their customer base, and reliance on data. When the introduction of the CCPA increases the cost of trading data, firms with a low ability to collect in-house data and high reliance on data suffer the most as they cannot adequately substitute the previously externally purchased data.

This paper investigates the influence of creditor control rights on the pricing of corporate loans. We construct a novel dataset, which combines hand-collected covenant violations data with individual borrower, creditor, and loan contract information. Our data allows us to distinguish between creditors that receive direct control rights after a covenant violation and creditors that do not receive control rights after a violation. By comparing the loan terms of these two creditor types, we can isolate the impact of creditor control rights on loan pricing from the impact of other factors related to a covenant violation. We find that creditors exploit control rights to overprice new loans, which is a key determinant of the loan premium puzzle. In addition, we uncover novel cross-sectional and time-series loan pricing patterns that can be explained by creditor control rights.

We examine whether banks manage climate transition risk by securitizing corporate loans. We present two novel results. First, banks are more likely to securitize loans when borrowers increase their carbon emission intensity. Second, securitization serves as a vehicle to shift transition risk, especially when banks do not have market power to price transition risk into loan contracts. Exploiting the Trump election as an exogenous shock to transition risk, we establish a causal link between transition risk and loan securitization. Our estimates show stronger effects for banks that do not exhibit preference for sustainable lending and domestic lenders. We discuss how our paper speaks to the debate on the design of bank climate policies.

This paper studies how the California Consumer Privacy Act (CCPA), a comprehensive privacy law that grants users control over their data, affects fintech lending. To develop hypotheses we build a parsimonious screening model. Consumers apply for loans with banks and a fintech that has a superior but data-intensive screening technology. However, consumers dislike sharing their data, and in particular with the fintech. We empirically show that the introduction of the CCPA, by assuaging concerns about data sharing, increases mortgage applications with fintechs relative to banks. Consistent with applicants' greater willingness to share data, fintechs make greater use of non-traditional data to improve screening. In turn, they deny more applications and can offer lower interest rates.

We report on an experiment that shows how the demand for ETF index products affects the prices and trading volume of assets included or excluded from the ETF index. We compare an environment where the ETF index includes all assets against an environment where one asset is excluded from the index. We find that (i) traders place significant value on the ETF asset; (ii) there is evidence of a substantial index premium for included assets; and (iii) the index premium persists even when short-selling is permitted. The price increase of the ETF share and the underlying assets between treatments suggests that ETF products can distort the efficiency of markets.

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 1.1 percentage points that grows to 1.7 percentage points over the following 6 years. I show that the incorporation of personal experiences in mortality beliefs can be explained by the canonical consumption life-cycle model augmented by the experience-based learning model. The saving response to the shock strongly depends on households’ age, emotional involvement, risk aversion, and decays over time. Overall, this paper provides novel insights into whether and how mortality beliefs are incorporated into households’ financial planning.

This paper a develops novel statistical test of whether individual factor risk premia

are identified from return data in multi-factor models. We give a necessary and

sufficient condition for population identification of individual risk premia, which we

call the kernel-orthogonality condition. This condition is weaker than the standard

rank condition commonly assumed for linear factor models. Under misspecification,

our condition ensures point identification of the risk premium with minimal pricing

error. We show how to test this restriction directly in reduced-rank models. Finally,

we apply our test methodology to assess identification of risk premia associated with

consumption growth and intermediary leverage.

We document that the carry of crypto futures, i.e. the difference between futures and spot prices, can become very large (up to 60% p.a.) and varies strongly over time. This behavior is most consistent with the existence of a highly volatile crypto convenience yield that stems from two main forces: (i) trend-chasing and attention by smaller investors seeking leveraged upside exposure to crypto assets in boom periods, and (ii) the relative scarcity of "arbitrage" capital taking the other side through a cash and carry position. Engaging in the latter is risky due to spikes in margins and liquidations amid drawdowns. The interplay between these two forces, and the involved high leverage, may help explain why severe market crashes are a frequent feature of crypto markets.

This paper identifies a new currency risk stemming from time-varying linkages among option-based currency volatilities. The network strategy buying net-receivers and selling net-transmitters of transitory shocks to currency volatilities generates significant excess returns. Intuitively, net-receivers are exposed to volatility spillovers and compensate investors with higher average returns. In turn, net-transmitters are resilient to volatility transmission and offer a lower risk premium because they hedge against volatility interdependencies in the foreign exchange market. When volatility linkages are controlled for contemporaneous correlations, the network portfolio is uncorrelated with popular benchmarks. Also, the volatility network factor is priced in a broad currency cross-section.

In this paper we investigate the price, volatility and micro-level effects of central bank swap lines during the 2020 pandemic. These policies lowered the ceiling on covered interest rate parity violations and reduced volatility following settlement of swap line auctions. We then combine dealer-level dollar repo auctions by the Bank of England with a trade repository that includes the universe of FX forward and swap contracts traded in the UK. We find evidence of a substitution channel: dealers that draw on swap lines reduce their demand for dollars at the forward leg in the FX market. We also find evidence that dealers that draw on swap lines increased their net supply of dollars to non-financial institutions, supporting the rationale for swap lines in providing cross-border liquidity to the real economy.

We examine the strategic production of CSR as a post-shock damage control instrument (responsive CSR). We proxy for the negative shock using securities class action lawsuits (SCAs) and find that net CSR increases 53% after a filing. We create a hand-collected dataset that reveals lawsuit firms strategically place news releases to blunt short-term effects from negative news related to the litigation process. Moreover, firms use responsive CSR synergistically with advertising for short-term effect. We find that responsive CSR mostly represents window dressing – it does not add long-term firm value and is associated with board members who have significant reputational concerns.

We examine the effect of CEO personal reputational capital on financial misconduct. We find that Home CEOs (defined as those who manage firms located within 100 miles of their birthplaces) are associated with significantly less misconduct than firms with non-home CEOs. However, home CEOs also appear to rationally calculate the effect of corporate events on personal reputation. When their firms are financially distressed, home CEOs do not act differently from non-home CEOs in the levels of firm misconduct at their firms, perhaps because the catastrophic reputational damage of bankruptcy is higher than the reputational costs of engaging in financial misconduct.

This paper predicts recessions using the dispersion of deposit rates offered by banks on insured deposits. An increase in the dispersion of deposit rates can accurately predict recessions over long time horizons at the county, state, and national levels. We find that the growth of deposits, particularly uninsured deposits of riskier banks, slows down at the onset of a downturn, regardless of whether the downturn was preceded by a credit boom. In turn, riskier banks increase their deposit rates to attract more funding to support their balance sheet. The resulting increase in the dispersion of deposit rates predicts an impending economic downturn.

I show that the long-term decrease in the nominal short rate since the 1980s contributed to a decline in banks' supply of business loans, firm investment and new firm creation, and an increase in banks' real estate lending. The driving force behind these relationships was the shift in banks’ funding mix from time deposits (CDs) to savings deposits, which was caused by the decrease in the nominal rate. I show that banks finance business lending with time deposits because of their matching interest-rate sensitivity and liquidity. A lower nominal rate reduces the spread on liquid deposits (e.g., savings deposits), leading households to substitute towards them and away from illiquid time deposits. In response to an outflow of time deposits, banks cut the supply of business loans and increase their price. The decrease in business lending leads to reduced investment at bank-dependent firms and a lower entry rate of firms in industries that are highly reliant on external funding. I document these relationships both in the aggregate, and in the cross-section of banks, firms and geographic areas. For identification, I exploit cross-sectional variation in banks' market power and business credit data. I develop a general equilibrium model which captures these relationships and shows that the transmission mechanism I document is quantitatively important.

Using data from the U.S. syndicated loan market, we find women under-represented among senior commercial bankers. This gap persists due to unequal promotion rates for men and women at the same institution in the same year and cannot be explained by different individual or managerial performance. The gap is more influenced by individuals than institutions, with senior bankers showing assortative matching when changing jobs and perpetuating the promotion gap from their previous workplace. Our findings suggest that the gender gap may be partially attributed to women taking on more family care responsibilities. Hard credentials or female leadership at the top of banks do not alleviate the gender gap, but targeted gender discrimination lawsuits have resulted in increased promotion of women.

We show that investors price immediate, short-term stock market outcomes very different from outcomes that occur further into the future. To this end, we introduce the forward pricing kernel to decompose long-term pricing kernels into short-term and forward pricing kernels. Using index options, we find that kernels with maturities up to twelve months are U-shaped, and show that this results from the shape of the one-month pricing kernel. Once we remove the impact of the one-month kernel, we show that forward kernels are in line with standard long-run risk models in terms of their shape, level and time-series variation.

Equity duration is a measure of discount-rate sensitivity that is driven by both, stock-specific cash-flow timing and stock-specific discount-rate levels. Established measures of equity duration using market-price information derive their predictive power for returns from using market-implied discount rates. We introduce new measures of pure cash-flow timing which disentangle discount-rate level from cash-flow timing information. Our results indicate an unconditionally flat relationship between timing and average returns. However, it turns out that in recessions (expansion episodes), there is a negative (positive) relation between cash-flow timing and average stock returns.

We study U.S. house price movements using a variance decomposition based on subjective expectations data from the University of Michigan’s Survey of Consumers. Contrary to previous VAR-based models for rational expectations, we find that households’ subjective cash flow (income) expectations account for the dominant share of the overall variation in house prices, whereas subjective discount rate (return) expectations are insignificant. We also show that households’ ex post forecast errors and ex ante belief distortions, defined as the difference between subjective and rational expectations, are persistent and associated with housing data, macroeconomic views of households, and credit conditions.

Software companies have steadily become key pillars of the digital economy, representing upwards of 12 percent of U.S. market capitalization. A simple buy-and-hold strategy of pure-play software companies over the past three decades produced annual alphas of over 7.1 percent. We document that these firms are growing at 13.9 percent annually and that both management and analysts systematically underestimate over a third of this growth. We show that these expectation errors appear to largely explain the foregoing outperformance of software companies and that management, analysts, short sellers, and other market participants ignore key performance indicators that describe these pure-play software firms and signal future growth. Together, the study underscores the value of software to the economy and how its economic impact has been significantly under-appreciated for the past two decades.

We analyze the size and power of a large number of "robust" asset pricing tests of the hypothesis that the price of risk of a candidate factor is equal to zero. Different from earlier studies, our approach puts all tests on an equal footing and focuses on sample sizes comparable to standard applications in asset pricing research. Thus, our paper guides researchers on which method to use. A simple test based on bootstrapped confidence intervals stands out as it does not over-reject useless factors and is powerful in detecting useful factors.

In statistics, samples are drawn from a population in a data-generating process (DGP). Standard errors measure the uncertainty in estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence-generating process (EGP). We claim that EGP variation across researchers adds uncertainty: Non-standard errors (NSEs). We study NSEs by letting 164 teams test the same hypotheses on the same data. NSEs turn out to be sizable, but smaller for better reproducible or higher rated research. Adding peer-review stages reduces NSEs. We further find that this type of uncertainty is underestimated by participants.

We study how labor rigidities affect firms' responses to credit shocks. Using novel data on the universe of workers, firms, banks and credit in Portugal, we establish three main facts. First, a short-term credit supply shock leads to a decrease in firms' employment and size and to a greater probability of exit, but the effects are concentrated on firms deriving greater value added from labor within their industries. Second, this exposure to liquidity risk stems from exposure to high-skill workers' compensation: the shock disproportionately affects productive firms with a high-skilled specialized labor force that requires greater investment in on-the-job training. Third, given labor costs exposure, productivity does not attenuate the effects of credit shocks. Our findings suggest that labor rigidities are an important driver of the lack of productivity-enhancing reallocation throughout financial crises.

I analyze the effect of non-compete agreements (NCAs) on career trajectories of 600,000 inventors in the US. NCAs constrain the employment choice set of inventors, who are unable to move to competitors. I show that inventors bypass their NCAs by moving to new employers in more distant product markets. I identify causal effects using staggered changes in NCA enforcement across US states. There is significant reallocation as 1.5 in 100 inventors annually move to more distant product markets after higher NCA enforcement. Reallocated inventors are subsequently less productive. Inventors move to new employers who are less reliant on NCAs and they patent in unfamiliar technologies. There is a lower quality match between inventors and their new employers. I highlight regulatory frictions which lead to unintended detrimental reallocation of human capital in the economy.

An established theoretical literature argues that uncertainty shocks are important determinants of firm decisions and aggregate fluctuation. However, few studies estimate the causal effects of these shocks on firm level employment dynamics, usually focusing on samples of public firms, with limited information on the firms' employment decisions. In this paper, we shed light on the interplay between firm-level uncertainty shocks and heterogeneous employment decisions using a matched workers-firms dataset of the population of Swedish firms for 1997-2017, with more than 18 million worker-level observations. Using shrinkage methods on commodity prices, we construct a firm-specific expected profits shock, and the associated second moment uncertainty index. We use them to measure the causal effect of exogenous changes in uncertainty on the employment decisions of firms. We find that negative first moment profitability shocks significantly reduce hiring and increase firing uniformly across different categories of workers. Conversely, uncertainty shocks change little the overall employment levels, but have significant and quantitatively important compositional effects. In particular, when uncertainty increases, firms are less likely to fire younger and short-tenured workers, are more likely to hire workers with previous experience in the same sector, and are more likely to both hire and fire more skilled workers, relative to normal times. The results emphasize the importance of workers heterogeneity, especially along the flexibility dimension, in driving the effects of uncertainty shocks on employment dynamics. Additional robustness checks confirm this interpretation and highlight the role of disruptive high uncertainty episodes as creative destruction periods for the labour force.

We examine the value of skilled foreign labor in finance by leveraging on two natural experiments. We find that hedge funds that secure more H-1B visas in random lotteries deliver higher alphas, Sharpe ratios, and information ratios. Moreover, an unexpected reduction in the H-1B quota undermined the performance of hedge funds that were dependent on H-1B workers. The superior performance of funds with high H-1B allocations can be attributed to highly-educated STEM majors operating systematic strategies. Notwithstanding the valuable skills that foreign workers possess, racial and ethnic homophily induces some fund managers to eschew foreign labor.

We propose a precise definition of greenwashing in asset management that combines ESG self-labels, sustainability scores of portfolio holdings, and funds’ voting behavior. Armed with this definition, we are able to quantify the prevalence of greenwashing in the US mutual fund industry. Although self-labeled ESG funds dominate non-ESG funds in terms of ESG ratings and voting support for ESG proposals, 24% of them are greenwashers according to our definition. Greenwashers are more likely to belong to larger and older fund families and less likely to be offered by signatories of the United Nations Principles for Responsible Investment. Importantly, while retail investors do not distinguish between greenwashers and true ESG funds, institutional investors are not deceived by the former. Our results suggest that accusations of ubiquitous greenwashing in asset management exaggerate the true extent of the problem. However, there is room for regulation aimed at enhanced ESG disclosure, at least for those funds that target retail investors.

I study the causal effect of bond investor demand on the financing and investment decisions of nonfinancial firms using granular data on the bond transactions of U.S. insurance companies. Liquidity inflows from insurance premiums combined with insurers' persistent investment preferences identify bond demand shifts, which raise bond prices and reduce firms' financing costs. In response, firms issue more bonds, especially when they have well-connected bond underwriters. The proceeds are used for investment rather than shareholder payouts, particularly by financially constrained firms. The results emphasize that bond investors significantly affect corporate financing and investment decisions through their price impact.

We study the post-Great Recession market for retail investment products. With an experiment, we show that low interest rates drive investment demand but not product differentiation. Elicited margins go hand in hand with investors’ underestimation of complex risk exposures. We empirically document that (i) rising complexity follows market growth, (ii) issuer margins increase in complexity, and (iii) simpler products first-order dominate more-complex products. Furthermore, biased dependency perceptions predict margins in the cross-section. Consistent with limited buy-side learning and growing sell-side competition, banks employ strategic price complexity to mitigate competitive pressure. Our findings showcase how low interest rates fuel excessive risk-taking.

Using checking account transactions and credit line, term loan, and customer data from a North-American bank, we find that more inattentive customers are at greater risk of future financial distress. Inattention predicts future financial distress similar to internal and external credit risk models, in-sample and out-of-sample, and also for customers excluded from credit by conventional credit score providers. Our results can explain several "fintech facts," identify inattention as an important cause for future financial distress, and suggest checking account transactions as a newly available financial distress measure for banks and non-banks that enables more credit access without increasing borrower risk.

Using a novel database of complex securities, I study how salient attributes of security design distort household investment decisions. I show banks add non-standard (fine-print) conditions to artificially increase advertised headline returns---a phenomenon I term "enhancement." Enhancement increases headline returns by 11 percentage points, on average, but does not increase realized returns. Flexibly controlling for all other product attributes and using high-frequency shocks to structuring costs of enhancement for identification, I find demand is highly elastic to enhancement. Enhancement is costly to investors: a one standard deviation decrease implies savings of more than $1 billion in fees.

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.

Trading at decentralized exchanges (DEXs) requires traders to bid blockchain fees to determine the execution priority of their orders. We employ a structural vector-autoregressive (structural VAR) model to provide evidence that DEX trades with high fees not only reveal more private information, but also respond more to public price innovations on centralized exchanges (CEXs), contributing to price discovery. Using a unique dataset of Ethereum mempool orders, we further demonstrate that high fees do not result from traders competing with each other on private or public information. Rather, our analysis lends support to the hypothesis that they bid high fees to reduce the execution risk of their orders due to blockchain congestion.

This paper studies the interactions between corporate law and venture capital (VC) exits by acquisitions, an increasingly common source of VC-related litigation. We find that transactions by VC funds under liquidity pressure are characterized by (i) a substantially lower sale price; (ii) a greater probability of industry outsiders as acquirers; (iii) a positive abnormal return for acquirers. These features indicate the existence of fire sales, which satisfy VCs' liquidation preferences but hurt common shareholders, leaving board members with conflicting fiduciary duties and litigation risks. Exploiting an important court ruling that establishes the board’s fiduciary duties to common shareholders as a priority, we find that after the ruling maturing VCs become less likely to exit by fire sales and they distribute cash to their investors less timely. However, VCs experience more difficult fundraising ex-ante, highlighting the potential cost of a common-favoring regime. Overall, the evidence has important implications for optimal fiduciary duty design in VC-backed start-ups.

We propose a novel measure of the ex-ante inflation risk premium (IRP) for each commodity based on a term structure model of commodity futures. Our theory-based IRP, capturing forward-looking information in the futures markets, outperforms well-known characteristics in explaining the cross-section of commodity returns. The IRP factor – the low minus high portfolio constructed from sorting IRP – has the highest Sharpe ratio among existing factors, and none of the latter can explain it, implying it has substantial new information. Moreover, various aggregations of individual commodity IRP predict future stock market returns significantly, even after controlling for major economic predictors. The link between commodities and the stock market is stronger than previously thought.

Using a dataset of more than 38 million consumer-bank relationships in 518 districts of Southern Peru, we find that first-time borrowers receive credit and better loan terms from the bank where their families are more central. Our results are explained by informal-oriented banks using family ties as a strategy toward the unbanked. They give first credits to retain the relatives of the recipients as clients, and they also screen first-time borrowers using the credit behavior of their relatives.

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.

We challenge conventional wisdom that retail investors largely consume dividends and rarely reinvest them. Using a German online brokerage dataset, we show that the decision whether to consume or reinvest dividends depends on the structure of an investor’s brokerage account. Brokerage cash serves as a buffer that absorbs dividends, keeps them from being spent and, over the long run, is drawn down when dividends are reinvested. Using independent international survey evidence, we show that an account structure including brokerage cash is the rule, not an exception. Therefore, our results generalize to a large share of the retail investor population.

Little is known about the participation of small individual landlords in the rental market, and about rental income earned by households. Using unique tax filings data from Australia, we show that 20% of middle and retirement age median-income individuals are landlords. This fraction has risen over the last 20 years, increasing by 80% for the retirement age group. We provide evidence linking this change to cuts in interest rates, which have led older individuals to substitute interest income with rental income. Higher participation in the rental market rises individuals’ exposure to local shocks, increases house prices, and lowers rental yields.