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2022–23 Fama-Miller Center Fast Facts

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Research projects funded

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Data subscriptions renewed

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New data sets acquired


Explore the Fama-Miller Research Projects that Have Been Funded

The Convenience Yield and the Demand for U.S. Treasury Securities 

Filippo Cavaleri, Joint Program in Financial Economics PhD student (2023)

This paper investigates the heterogeneity in investors’ preferences for non-pecuniary attributes of US Treasury securities. My goal is to determine which groups of investors draw benefits from holding Treasuries and the reasons why they are willing to pay a premium over safe and liquid corporate bonds. I first presents a conceptual framework to interpret the implications of heterogeneity in valuations of convenience on yields and price elasticities. Then, using sector-level bond holdings from the Financial Accounts, Cavaleri recovers structural demand curves and rank investors by their valuations of convenience services. Estimates reveal that the convenience of long term Treasuries is valuable for US private depository institutions, and security brokers and dealers, whereas it is less attractive to households, pension funds, and insurance companies.  The ordering suggests that a safety attribute is secondary to liquidity even at longer maturities.  Models of convenience yields should (i) accommodate heterogeneity in the elasticity of substitution between Treasuries and corporate bonds and (ii) incorporate liquidity motives at both long and short maturities.

Leveraging Digital Tools and Technology to Create and Manage Wealth in East Africa

Pradeep Chintagunta, Joseph T. and Bernice S. Lewis Distinguished Service Professor of Marketing (2023)

In  this  RCT,  we  investigate  how  firms  create  and  manage  wealth  in  emerging  markets  by  leveraging digital technologies. Our research team has partnered with one of the largest banks in East Africa, Equity Group Foundation, to measure the impact of an innovative digital skills training on profitability, loan accessibility and business investment. They investigate how access to, and knowledge of digital technology can impact wealth creation and management. While technology   has   great   potential   in   creating   and   managing   wealth,   many   small-scale   entrepreneurs in developing countries lack hands-on knowledge of how to leverage them for growth. This lack of ‘digital capital’ can be a significant constraint in today’s digitized society. Our research aims to shed light on this by examining the effectiveness of an innovative digital skills training, which combines 1) practical in-class training of business digitization, and 2) in-depth follow-up mentoring.  

Polarizing Corporations: Does Talent Flow to "Good" Firms?

Emanuele Colonnelli, Associate Professor of Finance and MV Advisors Faculty Fellow (2023)

We study whether and how environmental, social, and governance (ESG) practices of large corporations affect talent allocation in Brazil’s labor market. In collaboration with Catho, Brazil's largest job platform, we conduct experimental surveys where job-seekers rate synthetic job postings, under the sole incentive of receiving real job postings that match their preferences. We use a 7-point Likert scale to measure the rating, which allows them to observe job-seekers' preferences towards characteristics of inframarginal job postings. We combine their experimental estimates with administrative matched employer-employee micro-data from the Brazilian Ministry of Labor's RAIS database and structurally estimate an equilibrium model of the labor market with two-sided heterogeneity. We use the model to quantify the distributional consequences of ESG and assess its relevance for worker sorting and socioeconomic polarization in the workplace. Funding is requested to collect ESG measures of private firms and to estimate a version of the structural model that incorporates firm ESG investment decisions.

The Effect of Environmental Preferences on Investor Responses to ESG Disclosure

Joanna Harris, Joint Program in Financial Economics PhD student (2023)

We study the effect of environmental preferences on portfolio allocation around the implementation of the European Sustainable Finance Disclosure Regulation (SFDR). In a model of asset allocation with heterogeneous environmental preferences, we show that the introduction of disclosure regulation leads to an increase in flows to ESG funds, and that investors with stronger environmental preferences are more responsive to the regulation. We also show that it can be optimal for some funds to overstate their true greenness and for others to understate it, which appears to be the case empirically.  We then use unique security-level data on the holdings of investment fund shares across 24 European countries to study how environmental preferences affected the response to the SFDR. We find that ESG funds experienced higher flows after the regulation, and that the development of these funds was largest in countries with stronger environmental preferences. Institutional investors appear to be more responsive to the disclosure rules than households.

Strategic Bargaining and Portfolio Choice in Intermediated Markets

Jessica Li, Finance PhD student (2023)

Many assets are traded in decentralized markets intermediated by dealers. In these markets, terms of trade are negotiated between trading parties pursuant to strategic bargaining. Investors’ bargaining positions weaken when they experience liquidity shocks. In this paper, I propose a search-based theory with strategic bargaining to study investors’ dynamic portfolio choice and equilibrium asset prices in intermediated markets. Investors hold less extreme positions in illiquid assets, leading to lower trading volumes in these assets. Interestingly, the relationship between asset liquidity and prices is non-monotonic. More liquid assets may not command positive liquidity premia and trade at higher prices. In the cross-section, there is a liquidity threshold such that assets above the threshold (i.e., relatively liquid assets) exhibit positive liquidity premia, while assets below the threshold (i.e., highly illiquid assets) exhibit negative liquidity premia. Furthermore, negative liquidity premia are more prevalent during crises. The model implications are consistent with empirical evidence using corporate bond transaction data.

Risk-Shifting and Compensation in the Private Equity Industry

Edoardo Marchesi, Finance PhD student (2023)

The aim of this project is to investigate whether the compensation schemes enjoyed by private equity (PE) fund managers induce funds to tilt investments towards riskier acquisitions (risk-shifting).  Given that PE fund  managers  are  compensation  packages  include  a  pay-for-performance  component—which  is  triggered whenever the fund delivers a pre-specified rate of return (hurdle rate) to investors—managers have incentives to  increase  the  volatility  of  the  fund’s  underlying  assets.   At the same time, incentives to risk-shift are exacerbated by the fact that PE funds have a pre-determined fund life, which puts additional pressure on the managers to achieve the pre-specified rate of return.  In this paper I test whether funds which are close to the hurdle rate select relatively riskier assets whenever the fund is approaching the date of dissolution.

Bloated Disclosures: Can ChatGPT Help Investors Process Financial Information?

Maximillian Muhn, Assistant Professor of Accounting (2023)

Valeri Nikolaev, James H. Lorie Professor of Accounting and FMC Faculty Scholar

Alex Kim, Accounting PhD student

Generative  AI  tools  such  as  ChatGPT  could  fundamentally  alter  the  way  financial markets process information. We plan to probe the value of generative AI in extracting useful textual information from a large set of unstructured corporate disclosures. Specifically, we plan to use the GPT model to summarize the information content in MD&A and earnings call transcripts, to create a novel measure for the degree of redundant information and to explore standardized theme-specific summaries.  Using the GPT-3.5 model on a small 20% sample, we found promising early results.  The results suggest that unconstrained summaries are dramatically shorter, whereas their information content is amplified.  For example, summarized sentiment is consider-ably more effective at explaining stock market reactions to the disclosed information than the original.  Motivated by these findings, we propose a novel measure of the degree of redundant disclosure (“Bloat”).   Our early findings suggest that bloated disclosures are associated with adverse capital market consequences (e.g., higher in-formation asymmetry).

Get the working paper (

Consumer Bankruptcy Audits

Fabian Nagel, Accounting PhD student (2023)

Consumer bankruptcy is the largest social insurance program in the US. Approximately 800,000 individuals file for bankruptcy every year.  However, with large debt forgiveness also comes the opportunity for abuse of this generosity. Debtor audits – audits of consumer bankruptcy filings – were introduced to determine the truthfulness of bankruptcy filings. This project investigates the economic consequences of audits and material misstatements in bankruptcy filings. Audited individuals in Chapter 7 cases are less likely to have their debt forgiven. Material misstatements and non-compliance with the auditor lead to more frequent case dismissals, while a ‘clean sheet’ during the audit increases the likelihood of debt forgiveness. This project strives to merge individual bankruptcy records with credit bureau data to examine the longer-term consequences of audits and their findings for credit access, interest rates, and mobility.

Migration Responses to Moving Costs: Evidence from the US Mortgage Market

Michael Varley, Joint Program in Financial Economics PhD student (2023)

I  exploit  variation  in  moving  costs  induced  by  mortgage  contracts  to  study  how a  fall  in  moving  costs  effects  the  likelihood  a  household  will  move  and  how  these responses vary with financial constraints.  To do so, I study mortgages with prepayment penalties in their contract, a fee that is only charged in the event a borrower terminates their mortgage in a specified period of time.  Leveraging the variation in the length of  time  these  penalties  are  enforced,  I  implement  a  difference-in-differences  research design using linked administrative loan, credit,  and payroll data to establish that in the year after a prepayment penalty expires, the probability a borrower moves rises by2 percentage points, an economically meaningful increase in migration.  To understand what  drives  the  large  treatment  effect,  I  find  that  this  effect  varies  by  a  borrower’s LTV  ratio  prior  to  moving  and  credit  score  at  mortgage  origination,  suggesting  a mixture  of  down  payment  and  liquidity  constraints  play  a  role  in  one’s  decision  to move.   Using  a  sufficient  statistics  approach,  I  map  these  estimates  into  a  dynamic location choice model to understand what these measures can tell us about the extent of spatial misallocation in the U.S.

Inflation Expectations, Wage Bargaining, and Labor Supply Budget

Michael Weber, Associate Professor of Finance and Fama Faculty Fellow (2023)

This project aims to understand how individuals causally adjust their wage bargaining to their inflation perceptions and expectations, how these expectations shape individuals’ labor supply decisions both at the extensive and intensive margin, and whether increases in monetary policy rate have the power to directly tame possible wage-price spirals.  To do so, we plan to run information-provision experiments on the Nielsen homescan panel to generate exogenous variation in inflation expectations to study how individuals update their wage bargaining expectations, their labor supply, and how they react to the provision of information about policy rate increases of different sizes.  The study will guide the appropriate monetary policy response to the hike in inflation but also allows us to better understand how labor market tightness might change to changes in inflation expectations and the induced adjustment in labor supply.

Corporate Transparency Practices around the World: Measurement and Effects

Emanuele Colonnelli, Associate Professor of Finance and MV Advisors Faculty Fellow

Thomas Rauter, Assistant Professor of Accounting; Asness Junior Faculty Fellow and IBM Corporation Faculty Scholar (2022)

We are working on an international survey of corporate transparency practices across 12 developed and developing countries. Corporate transparency (CT) is a considered to be crucial for firm productivity and growth. Policymakers and investors around the world argue that a lack of CT is the number one reason why firms are unable to access the capital needed for growth. Yet, a lack of data means there is little empirical evidence on these issues. In this project, we aim to comprehensively measure CT practices at a large international scale and examine the effects of these practices on firm productivity and growth. The goal of the survey is to comprehensively measure CT practices and associated adoption frictions using highly detailed face-to-face and phone interviews with owners, CFOs, and finance/accounting managers of medium-sized firms (between 20 and 1000 employees). The survey instrument is inspired by the World Management Survey (WMS) methodology (Bloom and Van Reenen 2007), but fundamentally distinct given the different topic of focus, upon which we enriched various aspects based on recent methodological advancements in the survey design, economics, and accounting/finance literatures. So far, the academic literature has almost exclusively focused on revealed preference measures of what publicly listed firms disclose to outsiders. This project will allow us to open the black box of how firms produce transparency, with a focus on private firms, which will be of relevance to several bodies of literature at the intersection of finance, economics, and accounting. For more details on the survey contents and methodology of the project, please see Thomas’s proposals from 2021.

Over-reaction in Foreigners' Expectations

Zhiyu Fu, Joint Program in Financial Economics PhD Student (2022)

In my ongoing project, I show that foreign flows are more sensitive to financial situation in recipient countries than domestic flows.1During financial distress, foreigners withdraw more capital from the destination countries than domestic investors.  This pattern cannot be explained by currency risks, regulations, or different risk exposures.  Furthermore, higher sensitivity costs foreigners: following foreigners’ trading strategy, they receive lower alpha and Sharpe ratio. These results suggest that foreigners over-react to the economic and financial news. In this project, I plan to use cross-country economic forecast data to directly test this hypothesis. Consensus Economics provides individual-level forecasts for each country. Using this dataset, I can test whether foreign forecasters are indeed more sensitive to economic news than domestic forecasters.

Assessing Gender Gaps in Stock Market Participation

Emma Zhang, Economics PhD student (2022)

We are interested in studying the determinants of the gender gap in financial investments. Our focus is on the extensive margin of investing in the stock market, which has been difficult to study due to the lack of large-scale exogenous variation in income and information, and access to retail bank data. This extensive margin investing gap can lead to large differences in medium and long-run consumption. We aim to study whether the gender investment gap is better explained by rational preferences or behavioral biases by randomizing both positive income shocks as well as information. We aim to observe outcomes in spending and investment behavior through retail bank data. We conduct our study in two very different countries, Australia and India, as existing literature suggests that cross-country differences in gender norms may either exacerbate or explain away the underlying causes of the gender investment gap.

Retail Trading and Asset Prices: The Role of Changing Social Dynamics

Fulin Li, Joint Program in Financial Economics PhD student (2022)

Social-media-fueled retail trading poses new risk to institutional investors.  This paper examines the origin and pricing of this new risk. Using data on meme stocks, I first establish that aggregate fluctuations in retail sentiment originated from a growing and concentrated social network.  I then document that retail sentiment fluctuations induced changes in investor base composition. As sentiment increased through-out 2020 and 2021, retail investors built up long positions, while price-elastic long institutions started to exit the market since early 2020. Short interest stayed high in 2020, then dropped sharply following the price surge in January 2021, and remained low throughout 2021. I develop a model to show that retail sentiment shocks shift investor composition, which in turn determines the price of retail sentiment risk. In particular, following an increase in aggregate retail sentiment, price-elastic long institutions first hit their short-sale constraints.  Then short institutions hit the margin constraints, leading to a short squeeze. As a consequence, the market for an individual stock becomes price-inelastic, and a moderate retail sentiment shock can have a large price impact. The model reconciles the price, quantity and retail sentiment dynamics during this period. Finally, I conduct counterfactuals, which show that social network dynamics shape the distribution of sentiment shocks and have economically large impact on asset prices.

Household Demand for Private Equity and Social Inflation

Sangmin (Simon) Oh, Joint Program in Financial Economics PhD student (2022)

I  study  the  risk  and  economic  consequences  of social  inflation–  shifts  in  the  insurer’s  loss distribution due to factors such as large jury awards and broader definitions of liability – which poses a novel source of aggregate risk to the insurance sector.  Using a dataset spanning jury awards, financial statements, and insurance rate filings, I show that the price impact of social inflation is greater in regions with higher legal exposure, greater for insurers that are more financially constrained, and is economically significant even for insurers not directly affected by verdicts and settlements. Consistent with empirical patterns, a theoretical model of social inflation shows that a shock to the insurer’s loss distribution has a “double kick” effect on insurance supply through higher effective marginal cost and interaction of increased uncertainty with the capital requirement.  I discuss factors that affect the future dynamics of social inflation and implications for the role of insurers.

The Economic Consequences of Common Ownership Along the Supply Chain

Christopher Stewart, Assistant Professor of Accounting

Our  study  aims  to  be  the  first  to  document  the  extent  of vertical common  ownership  along  the supply  chain.  Prior  work  focuses  on  the  consequences  of  horizontal  common  ownership –i.e. ownership  of  industry  rivals  by  the  same  institutional  investor –and  largely  concludes  that common ownership is costly in terms of reducing competition. The impact of common ownership of vertically, rather than horizontally, linked firms may provide novel insights relative to this prior work. In particular, vertical common ownership may allow firms to realize the benefits of vertical integration due to aligned incentives and a reduction in hold-up costs. Alternatively, it is possible that the costs of vertical common ownership are similar to the costs of horizontal ownership –i.e., increasing anticompetitive effects. The goal of our paper is twofold. First, we will document the extent  of  common  vertical  ownership  along  the  supply  chain using  a proprietary  dataset  of  the buyer-supplier network of firms in the U.S. Our plan is to investigate the common ownership by both institutional investors and private equity (PE) firms, since much of the buyer-supplier network includes private companies. Second, we will examine the impact of vertical common ownership on supply chain outcomes. Our data allow us to explore trade volume and trade credit, and we have applied to the BLS to obtain access to producer pricing. Thus, we will provide evidence on the costs and benefits of vertical common ownership. Another output of our study will be to provide data on vertical ownership for use by other researchers.

Safety Nets, Credit, and Investment: Evidence from a Guaranteed Income Program

Nishant Vats, Finance PhD Student (2022)

Do safety nets affect investment? If so, how? Combining a natural experiment that gave guaranteed income to landowning farmers in India with transaction-level bank account data and loan-level credit bureau data, we evaluate the impact of unconditional and perpetual guaranteed income on small farmer entrepreneurs. We find that $1 guaranteed income each year generates an additional $1.7 of income from farming. We then study the mechanisms behind this effect. We find that instead of reducing ambition and initiative, guaranteed income allows recipients to work differently. Specifically, guaranteed income provides protection against downside risk, which increases demand for credit and allows farmers to invest in a more capital-intensive mode of production. Survey evidence suggests guaranteed income increases credit demand by increasing the probability of loan repayment and reducing the cost of default. Our results suggest that uninsured risk inherent in an entrepreneurial venture may be a binding demand-side constraint inhibiting growth. The availability of basic income support increases entrepreneurs' risk-bearing ability and significantly improves their production activity.

Forward-Looking Loan Loss Provisioning Under Imperfect Forecasts

Hristiana Vidinova, Accounting PhD student (2022)

The  new  accounting  standards CECL  and  IFRS  9  stipulate  that  loan  loss  provisions  should  be  forward-looking. Expected results from the new accounting standard simplicitly rest on the assumption that banks’ economic expectations are rational, but the macroeconomic and behavior finance literature finds strong empirical evidence against this hypothesis.I develop a model where banks’ macroeconomic expectations are subject to Kahneman and Tversky’s (1972) representativeness heuristic to study the implications for bank provisions, lending,  and  bank  stability. The  representativeness  heuristic  results  in  overreaction  to news: specifically, excessive lending and risk-taking in good times, and overly precautionary lending in the case  of  negative  macroeconomic  shocks.  The  minimum  capital  adequacy  requirement  constrains the effect  of excessive  optimism, but has  no  bite  on  overreaction  to  news  in case  of  downturns. I test the predictions   of   the   model   during   the   COVID-19   recession by studying the link between banks’ macroeconomic forecasts and provisions of CECL-adopting and non-adopting banks.

An Empirical Demand-and-Supply Framework of the Asset Management Industry

Marco Loseto, Econ PhD student (2022)

This project has two goals. The first one is to propose an empirical demand-and-supply framework of the asset management industry. The second one is to use the framework to study the welfare implications of the rise of the passive investing. The demand side features mean-variance heterogeneous investors that allocate their wealth across the investment options available in their investment plan. The supply side instead features an oligopoly of multi-product investment advisors with heterogeneous costs and differentiated productsthatset fees simultaneously. I show that mutual funds market shares, scaled by their idiosyncratic risk, are linear in fees and factor exposures and thus the model can be estimated through a simple IV strategy. I then plan to use the model estimates to recover advisors’ markups, investors’ welfare, and study their evolution overtime. How those have changed is a priori not obvious because while industry concentration increased, passive options offer high diversification at low costs.

Policy Opacity

William Cassidy, Finance PhD student (2022)

This project studies the impact of political constraints on climate policies and asset prices.  I develop a model where governments implement policies that can lower emissions, but at the cost of lower output. In general, governments and voters disagree over the optimal trade-off between output and emissions.  Voters discipline the policy choice of the government through elections. In equilibrium, voter demand for relatively green or brown policies will affect the actions of the government. Voter preferences are directly linked to the expected cashflows and valuations of firms. Further, when voters and households disagree over the optimal policy, governments misreport the policy they implement. Misreporting relaxes electoral discipline but concurrently increases investor uncertainty over future cashflows.  Political uncertainty endogenously arises because of strategic interaction between voters and the government through elections.

In Search of the Origins of Fickle Capital

Zhiyu Fu, Joint Program in Financial Economics PhD student (2022)

It is well-known in the literature that international capital flows are fickle: During contractions, investors reduce their investment in foreign countries and retrench toward home markets.1This observation motivates numerous theories and policy discussions.2However, as this pattern is mostly observed using aggregate capital flow data, it is unclear who exactly are the fickle investors, how they behave, and why they are fickle. Answers to these questions help to understand the welfare implication of fickle capital flows and inform a better policy design. This project seeks to take a step in this direction. By exploiting detailed portfolio-level data of global institutional investors from various sources, I plan to broadly explore two sets of questions:

  1. Who are the fickle investors? What characteristics of the institutions are associated with fickle capital flows?

  1. When fickle investors retrench, where do they go? Do they invest more in their home countries, home currencies, or safe-haven currencies such as the US dollar?

Distressed Debt Renegotiation: New Evidence from Private Debt and Private Equity

Young Soo Jang, Finance PhD student (2022)

Banks have long known to monitor borrowers using contract terms and realign incentives through renegotiation. A new class of lenders, private debt funds, increasingly have replaced banks as corporate lenders, particularly in transactions led by private equity sponsors. In this paper, I study how these lenders differ from banks in their role of monitoring. Preliminary analysis with hand-collected data on distressed debt renegotiation led by private debt lenders during COVID suggests the following. Like banks, private debt lenders use covenants to monitor distress. Yet, they appear to be more reasonable in renegotiation while demanding more from private equity sponsors in highly distressed situations. Anecdotal evidence suggests that banks no longer efficiently monitor these small, risky firms served now by private debt lenders because the post-crisis banking regulations and influx of institutional capital into the bond and syndicated loan markets have altered banks’ economies of scale to primarily serve larger firms’ financial needs. Hence, private debt lenders likely have eased financing constraints for bank-shunned borrowers with high monitoring costs.

Social Networks and Retail Trading

Fulin Li, Joint Program in Financial Economics PhD student (2022)

This paper develops an empirical model of opinion dynamics on social networks, and estimates the model using data from Reddit wallstreetbets (WSB). This framework allows me to quantify the effect of social network communications on asset prices and retail trading. The model is a high-dimensional VAR. To achieve identification, I exploit the observed network connections between users, and impose parameter restrictions that capture the network effect.  I also address the issue that users infrequently disclose their opinions on the  social  network,  by  assuming  that  a  user’s  decision  to  disclose  his  opinion  is  an  in-dependent Bernoulli process.  I derive an OLS-type estimator under further identifying assumptions.

Mortgage Prepayment Penalties: A Market Solution to Adverse Selection or a Shrouded Attribute?

Michael Varley, Joint Program in Financial Economics PhD student (2022)

Mortgage prepayment penalties protect lenders from the risk of a premature full payment of a loan where they would lose out on the stream of interest payments initially expected throughout the entire amortization schedule. While a benefit to lenders, are any benefits passed through to borrowers? If lenders are worried their loan portfolio will deteriorate in credit quality as their best customers prepay their loans, then we should expect prepayment penalties to improve credit outcomes either by increasing credit supply or lowering the price of credit.  However, if prepayment penalties are shrouded in the loan contract, borrowers may not benefit. This proposal seeks to answer this question by looking at three states that have banned prepayment penalties on certain mortgages with loan balances at or below state-mandated thresholds. These thresholds varied across states and time, providing valuable quasi-experimental variation in the provision of prepayment penalties on a loan contract.

Expectations and Household Leverage

Michael Weber, Associate Professor of Finance and Fama Faculty Fellow

Constantine Yannelis, Assistant Professor of Finance and FMC Faculty Scholar (2022)

We aim to study how expectations and beliefs affect household borrowing decisions. Specifically, we want to explore expectations regarding possible events, such as student loan forgiveness and higher future inflation. Expectations about future loan forgiveness, or wage and price increases, may affect loan repayment, leverage decisions, investment, and asset accumulation today. We aim to build new data, linking survey evidence to credit panel data and write several papers using this new data.

Missing Data in Asset Pricing Panels

Michael Weber, Associate Professor of Finance and Fama Faculty Fellow (2022)

Missing data for return predictors is a common problem in cross sectional asset pricing studies.  Most papers do not explicitly discuss how they treat missing data but conventional treatments focus on complete cases for all predictors or impute the unconditional mean for the missing predictor.  Both methods have undesirable properties - they are either inefficient or lead to biased estimators and incorrect inference.  We propose a simple and computation-ally attractive alternative approach using conditional mean imputations and weighted least squares.  This method allows us to use all sample points with observed returns, it results invalid inference, and it can be applied in non-linear and high-dimensional settings.  We map our estimator into a GMM framework to study its relative efficiency and find that it performs almost as well as the efficient but computationally costly GMM estimator in many cases.  We apply our procedure to a large panel of return predictors and find that it leads to improved out-of-sample predictability.

Investor Behavior in Markets for Crypto-Assets

Anthony Zhang, Assistant Professor of Finance (2022)

This project aims to analyze data on investor behavior in markets for crypto-assets. In the past decade, crypto markets have experienced a large boom in activity, drawing large numbers of inexperienced retail investors in the hopes of outsized returns. Yet crypto markets are unregulated, and the nature of crypto-assets is very different from that of traditional assets, such as fund, equity and debt. Therefore, the key objective of this project is to understand the individual investors’ trading dynamics in crypto markets, and, in particular, how different they are from their behaviors in the traditional markets

Arrested Development in China

Eric Zwick, Associate Professor of Finance and Fama Faculty Fellow

Bianca He, Finance PhD student (2022)

What is the effect on the real estate market of “speculators”—investors who receive no direct utility flows from real estate? We seek to answer this question in the context of the Chinese real estate market, which is currently experiencing one of the largest real estate booms in world history. A literature in finance has argued that speculators amplify booms in asset prices in the presence of short-sales constraints. Our goal is to test this prediction in the Chinese real estate market. Our broad strategy is to exploit cross-sectional variation in the ease of speculating, with a focus on the role of developers.  Specifically, we will use differences across municipalities in land use policy and local government connectedness and preexisting builder footprints as potential sources of exogenous variation in land available for development and speculation.   We will use detailed micro data on house and land transactions from official Chinese records maintained by central and municipal authorities.

Factset Corporate Bond Mutual Funds

Anil K Kashyap, Stevens Distinguished Service Professor of Economics and Finance (2021)

We document new evidence suggesting that bond mutual fund prices are stale and consequently investors have an incentive to withdraw in times of stress to get out before prices fully adjust to reflect market conditions. In particular, we show that during stress periods movements in exchange traded funds predict subsequent movements in bond mutual funds. We develop a model of how mutual fund prices would be set when the underlying securities trade infrequently so that their prices must be estimated. We show that introducing swing pricing can remove the incentive to withdraw. We also show that a social planner would choose a more aggressive degree of swing pricing than would an individual fund, because the planner recognizes that effect of deterring withdrawals on equilibrium prices. 

The Effect of Minority Bank Ownership on Minority Credit (formerly Minority Mortgage: Lending and the Wealth Gap)

Agustin Hurtado, Finance PhD student (2021)

The US economy exhibits a substantial and persistent racial wealth gap. According to the 2019 SCF, the median white household owned about $184,000 in family wealth, which compares to $23,000and $38,000 for the median Black and Hispanic family, respectively.  Housing is the principal asset held by most households, and despite their returns being higher than those of other assets, recent research shows that minorities face a gap in housing returns (relative to whites) that resembles the wealth gap.  This return gap is explained by differential access to mortgage credit and foreclosures. This project has two parts. First, I explore the role of lenders in closing or widening the racial wealth gap through the channels mentioned earlier: Mortgage access and foreclosures. In preliminary work, I show that the minority character of lenders is critical in closing the mortgage access gap.  Second, I aim to understand what mechanisms mediate these (and new) results:  Ownership, governance, or loan officers’ information and biases.

A Machine Learning Classification of VC Contract Terms

Jessica Jeffers, Assistant Professor of Finance and David G. Booth Faculty Fellow (2021)

We seek to create new data on VC contracting, especially around the emerging area of impact investing. We plan to create a public facing website where VCs and   entrepreneurs can assess the relative strengths of their contracts, across multiple dimensions, by uploading legal documents.  Building off pilot data and a process we have already developed, we will leverage natural language processing and machine learning algorithms   to evaluate   the   contract   terms   supplied.   Participants   will   receive   a   contract   score   benchmarked  against  comparable  documents  and  an  opportunity  to  provide  feedback  on  the  scoring  application.  Researchers  will  receive  three  benefits  from the  process:  (1)  access  to  otherwise  hard  to  obtain  data  about  private  market  investments,  (2)  improvement  of  the  research  process  through  automation  and  incorporating feedback,  and  (3)  an audience  for  market  research  from  a  growing repository of VC investors and entrepreneurs.

Does Political Partisanship Cross Borders? Evidence from International Capital Flows

Elisabeth Kempf, Associate Professor of Finance  (2021)

Does partisan perception shape the flow of international capital?  We provide evidence from two settings, syndicated corporate loans and equity mutual funds, to show that ideological alignment with foreign governments affects the cross-border capital allocation by U.S. institutional investors. Moreover, we find that ideological alignment with foreign countries also affects investments of non-U.S. investors and can explain patterns in bilateral FDI flows. Our empirical strategy ensures that direct economic effects of foreign elections or bilateral ties between countries are not driving the result. Combined, our findings imply that partisan perception is a global phenomenon and its economic effects transcend national borders.

View published paper 

“Political ideology and international capital allocation,”

Journal of Financial Economics,

Volume 148, Issue 2, May 2023, Pages 150-173


A Demand-Based Approach for Short-Selling

Federico Mainardi, Joint Program in Financial Economics PhD student (2021)

I propose a model where the optimal portfolio allocation of a representative short-seller that faces margin requirements, collateral requirements and has to pay asset specific lending fees to access short trades obeys a characteristic-based representation a la Koijen and Yogo (2019).  Despite omitting lending fees, structural estimation suggests that short-selling demand is naturally upward sloping and that elasticity of short-selling demand to market prices has steadily increased during the run-up to the financial crisis. Using the demand expression from the structural model, I propose a novel decomposition of short-interest that is suitable to disentangle a component explained by fundamentals and a residual component that reflects (at least) speculative motives.  I use this novel decomposition to show that while betting against short-sellers is not profitable if one isolates crowded short trades based on standard or fundamental short-interest, it is indeed profitable if one isolates crowded short trades with significant speculative component.

View Working Paper (

The Impact of Layoff Notices on Household Debt and Reemployment

Christopher Stewart, Assistant Professor of Accounting

Anna Costello, Professor of Accounting (2021)

Are workers with credit constraints better off when they are warned of a layoff? Over one million U.S. workers are involuntarily displaced from their jobs each year. To assist these workers, U.S. lawmakers enacted the WARN Act, which requires employers to provide employees at least 60 days of layoff notice. Advance notice allows workers to seek alternative employment or to enter skill training programs.  But  such  notice  also  gives  workers  time  to  borrow  in  preparation  for unemployment, which could be vital for credit-constrained workers who, without forewarning of a layoff, might be excluded from access to credit at the time of a redundancy event. Thus, layoff notices  could  benefit  disadvantaged  households,  by  allowing  them  to  supplement  temporary decreases in earnings through a credit channel. Alternatively, by giving workers time to borrow, layoff notices could unintendedly exacerbate debt problems for disadvantaged households, which has  important  consequences  for  households,  lenders,  and  the  overall  labor  market. Using employee-level data on borrowing, spending, saving, and credit we examine our question in the context of “mass” layoff events in the U.S. from 2000 to 2019.

Treasury Debt and the Pricing of Short-Term Assets

Quentin Vandeweyer, Assistant Professor of Finance (2021)

Since the 2008 financial crisis, the supply of short-term debt from the Treasury has been increasingly associated with changes in the yields of short-term money market assets.  This puzzling pattern contrasts with the pre-crisis experience and raises questions about the ability of the Fed to fulfill its mandate.  In this paper, I document and rationalize these developments in an intermediary asset pricing model with heterogeneous banks subject to a liquidity management problem and regulation.  The combination of large amounts of excess reserves and a more stringent capital regulation prevents traditional banks from intermediating liquidity to shadow banks.  As a consequence, the pricing of reserves disconnects from the pricing of other short-term assets.  The liquidity premium of these assets is then free to react to variations in the supply of Treasury bills.  The quantitative model accurately predicts post-crisis variations in Treasury bill and repo yields as well as in reverse repo volumes from the Fed.

Memory and Beliefs: Evidence from the Field

Michael Weber, Associate Professor of Finance and Fama Faculty Fellow  (2021)

This project aims to understand how ordinary people form expectations and the role of memory in the expectations formation process.  We will focus especially on inflation expectations  of  households  which  are  crucial  determinants  of  consumption,  savings,  and  wage-bargaining decisions and hence ultimately determine the effectiveness of fiscal and monetary policy interventions. While central banks typically assume that inflation expectations are well anchored and academic research often postulates the paradigm of a representative agent who forms expectations rationally, mounting evidence documents large heterogeneity in expectations and substantial deviations from the full-information rational benchmark.  Recently, the recovery from the Covid-19 pandemic produced a sharp increase in realized inflation which has swiftly translated in a jump of households’ inflation expectations to unprecedented levels.  At the same time, the last decade has underscored the role of unconventional monetary policy tools such as forward guidance that operate through decision-makers’ expectations in times of low policy rates.  Inspired by all this evidence, this proposal aims to understand how households form their macroeconomic expectations and if and how central banks can manage such expectations.   To  this  aim,  we  plan  to  merge  unique  micro  data  on  households’  consumption spending with customized surveys to elicit their inflation expectations and assess their recall of past price changes.  This unique setting allows us to study how memory of past prices is formed and varies across agents and whether it helps explain their inflation expectations.  This inquiry connects recent advances in the application of insights from cognitive psychology to economics with the recent strand of macroeconomics that studies the sources of heterogeneity in macroeconomic expectations.

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