Asset Embeddings
Xavier Gabaix, Ralph S. J. Koijen, Robert Richmond, Motohiro Yogo
Firm characteristics are ubiquitously used in economics. These characteristics are often based on readily-available information such as accounting data, but those reflect only a part of investors’ information set. We show that useful information about firm characteristics is embedded in investors’ holdings data and, via market clearing, in prices, returns, and trading data. Based on insights from the recent artificial intelligence (AI) and machine learning (ML) literature, in which unstructured data (e.g., words or speech) are represented as continuous vectors in a potentially high-dimensional space, we propose to learn asset embeddings from investors’ holdings data. Indeed, just as documents arrange words that can be used to uncover word structures via embeddings, investors organize assets in portfolios that can be used to uncover firm characteristics that investors deem important via asset embeddings. This broad theme provides a natural bridge to connect recent advances in the fields of AI and ML to finance and economics. Specifically, we show how language models, including transformer models that feature prominently in large language models such as BERT and GPT, can handle numerical information, and in particular holdings data to estimate asset embeddings. We provide initial evidence on the value added of asset embeddings through a series of applications in the con- text of firm valuations, return comovement, and uncovering asset substitution patterns. As a by-product, the models generate investor embeddings, which can be used to measure investor similarity. We propose a programmatic list of potential applications of asset and investor em- beddings to finance and economics more generally.
Contract Completeness of Company Bylaws and Entrepreneurial Success
Paul Beaumont, Johan Hombert, and Adrien Matray
Does reducing the cost for entrepreneurs to write more complete contracts with their financiers enhance entrepreneurial success? To shed light on this question, this paper exploits a 2008 French reform that made it less costly for new firms to choose a legal form allowing more complete financial contracts in the company bylaws. Using comprehensive tax-filing data from 2004 to 2015, we find a marked increase in the adoption of that legal form among new firms, leading to higher growth in capital, labor, and revenues in the first three years after creation. The effects are more pronounced for firms with high marginal returns to capital, suggesting that capital misallocation decreases. Our findings highlight the significant role of legal and financial structures in entrepreneurial success, which has policy implications for promoting entrepreneurship.
Entrepreneur Experience and Success: Causal Evidence from Immigration Wait Lines
Abhinav Gupta, Franklin Qian, and Yifan Sun
This paper investigates the causal impact of entrepreneurs' prior experience on startup success. Employing within-country changes in Green Card wait lines to instrument for immigrant first-time entrepreneurs' experience, we uncover that startups led by more experienced founders demonstrate superior funding, patenting, and employee growth. Specifically, each additional year of founder experience leads to a 0.7 p.p. (1 p.p.) increase in the likelihood of a startup undergoing an IPO (growing to over 1000 employees), over the subsequent decade. The larger initial team size, facilitated by the improved ability to recruit former colleagues, explains the observed startup success. Our findings imply that each extra year of experience is worth $200,000, underscoring a critical consideration for policymakers in the design of startup incubators.
Expected EPS x Trailing P/E
Itzhak Ben-David and Alex Chinco
When an analyst includes a price target in their earnings report, they are required to explain exactly how they calculated this one-year-ahead forecast. We read through these explanations to understand how analysts price their own subjective cash-flow expectations. Contrary to what textbooks assume, most do not apply present-value reasoning. Instead, they typically multiply a company’s expected earnings per share (EPS) times its trailing price-to-earnings ratio (P/E). We outline a simple model where this mostly backward-looking approach is correct on average because prices themselves are mostly backward-looking. When we reexamine the data, we find trailing P/E ratios explain both analysts’ price targets and realized future returns exactly as predicted by our model.
When Private Firms Provide Public Goods: The Allocation of CSR Spending
Kim Fe Cramer, Lucie Gadenne, and Noémie Pinardon-Touati
This paper studies how firms allocate their Corporate Social Responsibility (CSR) spending to shed light on the potential social effects of corporate contributions to public goods. We do so using a novel dataset covering the universe of the CSR expenditures of Indian firms over the period 2015-2019, which includes detailed information on the projects and social causes firms invest in. Using textual analysis methods, we construct an index of the technological proximity of firms’ industries to social causes to capture the extent to which firms use their production processes for CSR projects. Preliminary results suggest that firms do spend more on causes they have a comparative advantage in, in line with the theoretical literature on the desirability of CSR (Besley and Ghatak, 2007; Hart and Zingales, 2017). However, firms tend to spend in geographic areas where social returns are relatively low.
Fund Flows and Income Risk of Fund Managers
Xiao Cen, Winston Wei Dou, Leonid Kogan, and Wei Wu
We develop a unique dataset, the first-ever of its kind, by leveraging the US Census Bureau’s LEHD program and various big textual data sources, to examine the factors influencing the compensation and career trajectories of US active equity mutual fund managers. We find that managers’ compensation is primarily determined by assets under management (AUM), with return performance directly influencing bonuses beyond its impact on AUM. Despite not aligning with client interests, fund flows significantly affect manager compensation and career outcomes. Large fund outflows increase a manager’s likelihood of job turnover (with a substantial decline in compensation) by 4 percentage points.
Taxation when markets are not competitive: Evidence from a loan tax
Felipe Brugués and Rebecca De Simone
We study the interaction of market structure and tax-and-subsidy strategies utilizing pass-through estimates from the unexpected introduction of a loan tax in Ecuador, a quantitative model, and a comprehensive commercial-loan dataset. Our model generalizes bank competition theories, including Bertrand-Nash competition, credit rationing, and joint-maximization. While we find the loan tax is distortionary, neglecting the possibility of non-competitive lending inflates estimated tax deadweight loss by 80% because non-competitive banks internalize some of the burden. Conversely, subsidies are less effective in non-competitive settings. If competition were stronger, tax revenue would be 10\% lower. Findings suggest policymakers consider market structure in tax-and-subsidy strategies.
The Economics of Market-Based Deposit Insurance
Edward T. Kim, Shohini Kundu, and Amiyatosh Purnanandam
We examine the financial stability implications of deposit insurance using a recent financial innovation: reciprocal deposits. Banks can significantly increase deposit insurance coverage through the reciprocal deposit network, where they break up large deposits and place them with other banks in an offsetting manner. With close to half a trillion dollars in outstanding contracts under this arrangement, reciprocal deposits have become an important source of funding for the U.S. banking sector. Using network presence as an instrument, we show that enhanced insurance coverage allowed banks to retain deposits following the 2023 banking crisis. Network banks pay lower interest rates on their deposits, indicating depositors’ willingness to accept lower rates for higher insurance access. Enhanced coverage also has implications for competition and bank risk-taking; we find evidence that network banks grow larger and increase their exposure to interest rate risk.
The Subjective Risk and Return Expectations of Institutional Investors
Spencer J. Couts, Andrei S. Goncalves, and Johnathan A. Loudis
We use the long-term Capital Market Assumptions of major asset managers and institutional investor consultants from 1987 to 2022 to provide three stylized facts about their subjective risk and return expectations on 19 asset classes. First, there is a strong and positive subjective risk-return tradeoff, with most of the variability in subjective expected returns due to variability in subjective risk premia (compensation for market beta) as opposed to subjective alphas. Second, belief variation and the positive risk-return tradeoff are both stronger across asset classes than across institutions. And third, the subjective expected returns of these institutions predict subsequent realized returns across asset classes and over time. Taken together, our findings imply that models with subjective beliefs should reflect a risk-return tradeoff. Additionally, accounting for this subjective risk-return tradeoff when modeling multiple asset classes is even more important than incorporating average belief distortions or belief heterogeneity in our setting.
Unlocking Mortgage Lock-In: Evidence From a Spatial Housing Ladder Model
Julia Fonseca, Lu Liu, and Pierre Mabille
U.S. mortgage borrowers are “locked in”: unwilling to sell their house and move, as that would require giving up low fixed-rate mortgage rates for high current rates. This paper studies the general equilibrium effects of mortgage lock-in on house prices, mobility, and homeownership and evaluates policies aimed at unlocking mortgage lock-in. To do so, we design a spatial housing ladder model that captures moving patterns across different housing market segments. Households can move between locations differing in economic opportunity and cost of living, and within the housing ladder by deciding whether to rent, own a starter home, or own a trade-up home. In equilibrium, house prices and rents are endogenously determined by household mobility within and between locations, and are thus impacted by lock-in. We provide new empirical evidence on moving behavior along the housing ladder and over the life cycle and calibrate the model with rich microdata from 2024. Despite also reducing housing demand, we show that the net ef- fect of mortgage lock-in is a negative shock to housing supply, which increases house prices and thus creates inflationary pressure. We further evaluate the equilibrium effects of the proposed 2024 Mortgage Relief Credit, which would provide a $10,000 subsidy to sellers of starter homes. We find that the policy modestly increases first-time home buying and has larger effects on upward mobility at the top of the housing ladder. The upward mobility within the housing ladder comes at the cost of renters and starter homeowners moving from high- to low-opportunity areas, as house prices in higher-priced areas increase.
