Forest through the Trees: Building Cross-Sections of Stock Returns

We build cross-sections of asset returns for a given set of characteristics, that is, managed portfolios serving as test assets, as well as building blocks for tradable risk factors. We use decision trees to endogenously group similar stocks together by selecting optimal portfolio splits to span the stochastic discount factor, projected on individual stocks. Our portfolios are interpretable and well diversified, reflecting many characteristics and their interactions. Compared to combinations of dozens (even hundreds) of single/double sorts, as well as machine-learning prediction-based portfolios, our cross-sections are low-dimensional yet have up to three times higher out-of-sample Sharpe ratios and alphas

Mortgage Pricing and Monetary Policy

This paper examines how central bank policies influence mortgage pricing in the United Kingdom. It shows that lenders price discriminate by offering two-part tariffs of interest rates and origination fees, and during unconventional monetary policies like the Funding for Lending Scheme, lenders reduced interest rates while increasing fees. Using a model of mortgage demand and lender competition, we find that central bank policies increased mortgage lending. Additionally, banning origination fees would reduce lending, as fees help lenders capture surplus while allowing them to price discriminate across borrowers with different sensitivities to rates and fees

A growth mindset frame increases opting in to reading information about bias

We explore the conditions under which people will opt in to reading information about bias and stereotypes, a key precursor to the types of self-directed learning that diversity and anti-bias advocates increasingly endorse. Across 1 meta-analysis (total N = 1,122; 7 studies, 5 pre-registered) and 2 pre-registered experiments (total N = 1,717), we identify a condition under which people opt in to reading more about implicit bias and stereotypes. People randomly assigned to read a growth, rather than fixed, mindset frame about bias opted in to read more information about stereotypes and implicit bias (Study 1, Study 3). The mechanism that drove these effects was individuals’ construal of the task as a challenge (Studies 2-3). Our findings offer insight into how to promote voluntary engagement with information about stereotypes and biases. We discuss how this work advances the study of mindsets and diversity science

Missing Financial Data

We document the widespread nature and structure of missing observations of firm fundamentals and show how to systematically handle them. Missing financial data affects more than 70% of firms that represent about half of the total market cap. Firm fundamentals have complex systematic missing patterns, invalidating traditional approaches to imputation. We propose a novel imputation method to obtain a fully observed panel of firm fundamentals that exploits both time-series and cross-sectional dependency of data to impute missing values and allows for general systematic patterns of missingness. We document important implications for risk premiums estimates, cross-sectional anomalies, and portfolio construction

A simple statistical model and physical device to estimate a woman-specific probability of skilled birth assistance and associated benefit of maternity waiting home stay

This paper presents a simple mathematical model and an associated physical device to predict (i) the risk that a woman’s active labour will begin without a skilled birth attendant based on her parity and anticipated time to access skilled care; and (ii) the extent to which that risk may be reduced by moving to a maternity waiting home some time before her expected due date. This tool is designed to facilitate more systematic discussions and better-informed decisions about labour care access arrangements during antenatal consultations

A Theory of Fair CEO Pay

This paper studies executive pay with fairness concerns: if the CEO’s wage falls below a perceived fair share of output, he suffers disutility that is increasing in the discrepancy. Fairness concerns do not always lead to fair wages; instead, the firm threatens the CEO with unfair wages for low output to induce effort. The contract sometimes involves performance-vesting equity: the CEO is paid a constant share of output if it is sufficiently high, and zero otherwise. Even without moral hazard, the contract features pay-for-performance, to address fairness concerns and ensure participation. This rationalizes pay-for-performance even if effort incentives are unnecessary

Optimizing the Path Towards Plastic-Free Oceans

Increasing ocean plastic pollution is irreversibly harming ecosystems and human economic activities. We partner with a non-profit organization and use optimization to help clean up oceans from plastic faster. Specifically, we optimize the route of their plastic collection system in the ocean to maximize the quantity of plastic collected over time. We formulate the problem as a longest path problem in a well-structured graph. However, since collection directly impacts future plastic density, the corresponding edge lengths are non-linear polynomials. After analyzing the structural properties of the edge lengths, we propose a search-and bound method, which leverages a relaxation of the problem solvable via dynamic programming and clustering, to efficiently find high-quality solutions (within 6%-optimal in practice), and develop a tailored branch-and-bound strategy to solve it to provable optimality. On one-year of ocean data, our optimization-based routing approach increases the quantity of plastic collected by over 60% compared with their current routing strategy, hence speeding up the progress towards plastic-free oceans. Supplemental Material: All supplemental materials, including the code, data, and files required to reproduce the results were reviewed and are available at [https://doi.org/10.1287/opre.2023.0515](https://doi.org/10.1287/opre.2023.0515

Girls’ Night In? Effects of the Kenyan COVID-19 Lockdown on Web Browsing

We present the first objective evidence on how COVID-19 lockdowns affected internet browser usage in Africa: We use detailed digital trace data on PC-based and mobile-based browsing patterns of 316 Kenyans who had access to a PC. Our data cover the period before and during Kenya’s first national COVID-19 curfew, which was declared on March 25, 2020. We find that total daily browser usage increased by 41 minutes, or 15 percent of average browsing time, after the curfew started. We find no significant differences in total browsing time during the curfew by gender or by residence in high-speed versus low-speed broadband access areas. However, we do find gender differences in the content of browsing. Women’s time on YouTube and Netflix exceeded men’s from the start of our sample period, and the gender gap in Netflix browsing increased by 36 minutes daily, which corresponds to almost twice the average daily Netflix time in the sample. Men’s browsing became less concentrated during the curfew, across both domains and topics– but women’s did not. The degree of overlap in browsing between men and women also increased: This was likely due to men visiting sites that were previously exclusively visited by women. Across the entire sample, browsing of Kenyan domains dropped significantly relative to that of non-Kenyan domains, which indicates greater reliance on international content during this period of economic and social upheaval

The Long-Run Effects of Government Spending

Military spending has large and persistent effects on output because it shifts the composition of public spending toward R&D. This boosts innovation and private investment in the medium term and increases productivity and GDP at longer horizons. Public R&D expenditure stimulates economic activities beyond the business cycle even when it is not associated with war spending. In contrast, the effects of public investment are shorter-lived, while public consumption has a modest impact at most horizons. We reach these conclusions using BVAR with long lags and 125 years of US data, including newly reconstructed series of government spending by main categories since 1890. (JEL E21, E22, E23, E62, H50, H56, O30

Can competition increase profits in factor investing?

The increasing number of institutions exploiting factor-investing strategies raises concerns that competition may erode profits. We use a game-theoretic model to show that, while competition among investors exploiting a particular factor erodes profits because of the negative externality of their price impact on each other, competition to exploit other factors can increase profits from the first factor because of the positive externality from trading diversification (netting of trades across factors). We calibrate our model using the investment and profitability factors and find that competition to exploit the profitability factor leads to a 68% increase in the capacity and a 143% increase in the profit from the investment factor. Supplemental Material: The online appendix and data files are available at [https://doi.org/10.1287/mnsc.2022.02684](https://doi.org/10.1287/mnsc.2022.02684