Published and Accepted Papers:
1. Can Markets Discipline Government Agencies? Evidence from the Weather Derivatives Market
with Amiyatosh Purnanandam. Journal of Finance, 2016, 71: 303–334.
Published Version
We analyze the role of financial markets in shaping the incentives of government agencies using a unique empirical setting: the weather derivatives market. We show that the introduction of weather derivative contracts on the Chicago Mercantile Exchange (CME) improves the accuracy of temperature measurement by 13% to 20% at the underlying weather stations. We argue that temperature-based financial markets generate additional scrutiny of the temperature data measured by the National Weather Service, which motivates the agency to minimize measurement errors. Our results have broader implications: the visibility and scrutiny generated by financial markets can potentially improve the efficiency of government agencies.
2. Financial Sector Stress and Risk Sharing: Evidence from the Weather Derivatives Market
Review of Financial Studies, 2019, 32(6), 2456-2497.
Internet Appendix
Published Version
I examine the effect of financial sector stress on risk sharing in a novel setting: the CME’s weather derivatives market. The structure of the market allows me to disentangle price movements due to financial sector stress from price movements due to fundamentals. Contracts, which are typically priced near their actuarially fair value, experience significant price declines during periods of financial sector stress. Contracts with greater margin requirements and total risk are the most affected. The results provide causal evidence of the effect of financial sector stress on the pricing of exchange-traded financial contracts and risk sharing in the economy.
3. Are Monthly Market Returns Predictable?
with Jussi Keppo and Tyler Shumway. Forthcoming, Review of Asset Pricing Studies.
Internet Appendix
We document significant persistence in the market timing performance of active individual investors, suggesting some investors are skilled at timing. We also show that the net purchases of skilled versus unskilled active investors predict monthly market returns. Our tests use data on all trades by active Finnish individual investors over 14.5 years. Our evidence suggests that it is possible to use the trading patterns of skilled investors to anticipate market movements, lending credibility to the view that market returns are somewhat predictable.
with Amiyatosh Purnanandam. Journal of Finance, 2016, 71: 303–334.
Published Version
We analyze the role of financial markets in shaping the incentives of government agencies using a unique empirical setting: the weather derivatives market. We show that the introduction of weather derivative contracts on the Chicago Mercantile Exchange (CME) improves the accuracy of temperature measurement by 13% to 20% at the underlying weather stations. We argue that temperature-based financial markets generate additional scrutiny of the temperature data measured by the National Weather Service, which motivates the agency to minimize measurement errors. Our results have broader implications: the visibility and scrutiny generated by financial markets can potentially improve the efficiency of government agencies.
2. Financial Sector Stress and Risk Sharing: Evidence from the Weather Derivatives Market
Review of Financial Studies, 2019, 32(6), 2456-2497.
Internet Appendix
Published Version
I examine the effect of financial sector stress on risk sharing in a novel setting: the CME’s weather derivatives market. The structure of the market allows me to disentangle price movements due to financial sector stress from price movements due to fundamentals. Contracts, which are typically priced near their actuarially fair value, experience significant price declines during periods of financial sector stress. Contracts with greater margin requirements and total risk are the most affected. The results provide causal evidence of the effect of financial sector stress on the pricing of exchange-traded financial contracts and risk sharing in the economy.
3. Are Monthly Market Returns Predictable?
with Jussi Keppo and Tyler Shumway. Forthcoming, Review of Asset Pricing Studies.
Internet Appendix
We document significant persistence in the market timing performance of active individual investors, suggesting some investors are skilled at timing. We also show that the net purchases of skilled versus unskilled active investors predict monthly market returns. Our tests use data on all trades by active Finnish individual investors over 14.5 years. Our evidence suggests that it is possible to use the trading patterns of skilled investors to anticipate market movements, lending credibility to the view that market returns are somewhat predictable.
Revise and Resubmit:
1. Disaster Lending: "Fair" Prices, but "Unfair" Access (Revise & Resubmit, Review of Economics and Statistics)
with Taylor Begley, Umit Gurun, and Amiyatosh Purnanandam
AFA, Red Rock, Univ. of KY, FIRS, Finance Down Under, MoFiR, Front Range, CFIC, EBCN, MFA, MD4SG
We find that under risk-insensitive loan pricing – a feature present in many government programs – marginal credit quality borrowers are less likely to receive credit. By restricting price flexibility, marginal applicants that would likely receive a loan at a higher interest rate are instead denied credit altogether. Our particular setting is the Small Business Administration’s disaster-relief home loan program, where risk-based pricing is absent, but screening on credit quality remains. We find that this program denies more loans in areas with larger shares of minorities, subprime borrowers, and higher income inequality, even relative to private market denial rates. Thus, despite ensuring “fair” prices, risk-insensitive pricing may lead to “unfair” access to credit. As a consequence, the government’s own lending program ends up denying credit to minority and poor borrowers at a higher rate than private markets.
with Taylor Begley, Umit Gurun, and Amiyatosh Purnanandam
AFA, Red Rock, Univ. of KY, FIRS, Finance Down Under, MoFiR, Front Range, CFIC, EBCN, MFA, MD4SG
We find that under risk-insensitive loan pricing – a feature present in many government programs – marginal credit quality borrowers are less likely to receive credit. By restricting price flexibility, marginal applicants that would likely receive a loan at a higher interest rate are instead denied credit altogether. Our particular setting is the Small Business Administration’s disaster-relief home loan program, where risk-based pricing is absent, but screening on credit quality remains. We find that this program denies more loans in areas with larger shares of minorities, subprime borrowers, and higher income inequality, even relative to private market denial rates. Thus, despite ensuring “fair” prices, risk-insensitive pricing may lead to “unfair” access to credit. As a consequence, the government’s own lending program ends up denying credit to minority and poor borrowers at a higher rate than private markets.
Working Papers:
1. Firm Finances and the Spread of COVID-19: Evidence from Nursing Homes
with Taylor Begley
FIRS*, Eastern Finance Association*
We find that firms’ financial resources play an important role in mitigating the spread of COVID-19. We study nursing homes – whose residents account for over one-third of all U.S. COVID-19 deaths – at a time when investment in risk mitigation was costly and critical. We find that facilities with less liquidity and those experiencing more severe cash flow shocks had a higher likelihood of COVID-19 reaching residents. These patterns are strongest for financially constrained facilities. We also find higher rates of transmission between staff and residents within liquidity-constrained facilities, which is consistent with these facilities creating a less-effective barrier between groups.
2. Dream Chasers: The Draw and the Downside of Following House Price Signals
with Taylor Begley and Peter Haslag
Atlanta Fed/GSU Real Estate Conference, Finance Down Under, RCFS/RAPS, Stockholm LFG, EFA, LFG @ Georgia Tech (postponed)
We study individual labor market decisions during the house price run-up of the early 2000s using the career paths of nearly 7 million workers. We find that individuals switch careers to become real estate agents (REAs) at higher rates in areas with stronger house price growth, despite little or no growth in average REA wages. We find that those drawn into real estate come from virtually all parts of the skill, wage, and education spectrums, and respond to both fundamental and non-fundamental house price growth. Examining wages, we find that those drawn into REA near the peak of the run-up experienced substantially lower wage paths than similar non-entrants through the end of our sample in 2017. These effects are particularly severe for entrants in areas with higher non-fundamental growth. Overall, we shed light on some important consequences of house price fluctuations, both fundamental and non-fundamental, on labor market outcomes.
3. Revealed Heuristics: Evidence from Investment Consultants' Search Behavior
with Sudheer Chava and Soohun Kim
WFA, Cavalcade, Oregon SFC, Helsinki, NFA, MARC (Outstanding Paper Award), Cavalcade Asia, Behavioural Finance WG, MFHFFI, APFM
Using proprietary data from a major fund data provider, we analyze the screening activity of investment consultants (ICs) who advise institutional investors with trillions of dollars in assets. We find that ICs frequently shortlist funds using threshold screens clustered at round, base 5 or base 10 numbers: $500MM for AUM, 0% for the return net of a benchmark, and quartiles for return percentile rank screens. A fund’s probability of being eliminated by a screen is significantly negatively related to its future fund attention and flows, with funds just above the $500MM AUM threshold getting 14 to 18% more page views and 5 to 9 pps greater flows over the next year compared to similar funds just below the threshold. Our results are consistent with ICs using a two-stage, consider-then-choose decision making process, and cognitive reference numbers in selecting screening thresholds.
4. Uncovering Financial Constraints
with Matt Linn
MFA, FMA
We classify firms’ financial constraints using a random forest model trained on the Hoberg and Maksimovic (2015) text-based constraint measures. Our model uses only financial variables to predict constraints, allowing us to significantly expand the cross- section and time-series of classified firms compared to the text-based measures. We conduct a number of tests to validate the informativeness of our measures. Using our classifications, we provide evidence that returns of debt (equity) constrained firms are more sensitive to shocks to the cost of equity (debt) financing. The results highlight the importance of financial flexibility in determining a firm’s exposure to financing shocks.
Portions of this paper were "spun-off" an older working paper entitled "Seeing the Forest Through the Trees: Do Investors Under-react to Systemic Events?"
*scheduled
with Taylor Begley
FIRS*, Eastern Finance Association*
We find that firms’ financial resources play an important role in mitigating the spread of COVID-19. We study nursing homes – whose residents account for over one-third of all U.S. COVID-19 deaths – at a time when investment in risk mitigation was costly and critical. We find that facilities with less liquidity and those experiencing more severe cash flow shocks had a higher likelihood of COVID-19 reaching residents. These patterns are strongest for financially constrained facilities. We also find higher rates of transmission between staff and residents within liquidity-constrained facilities, which is consistent with these facilities creating a less-effective barrier between groups.
2. Dream Chasers: The Draw and the Downside of Following House Price Signals
with Taylor Begley and Peter Haslag
Atlanta Fed/GSU Real Estate Conference, Finance Down Under, RCFS/RAPS, Stockholm LFG, EFA, LFG @ Georgia Tech (postponed)
We study individual labor market decisions during the house price run-up of the early 2000s using the career paths of nearly 7 million workers. We find that individuals switch careers to become real estate agents (REAs) at higher rates in areas with stronger house price growth, despite little or no growth in average REA wages. We find that those drawn into real estate come from virtually all parts of the skill, wage, and education spectrums, and respond to both fundamental and non-fundamental house price growth. Examining wages, we find that those drawn into REA near the peak of the run-up experienced substantially lower wage paths than similar non-entrants through the end of our sample in 2017. These effects are particularly severe for entrants in areas with higher non-fundamental growth. Overall, we shed light on some important consequences of house price fluctuations, both fundamental and non-fundamental, on labor market outcomes.
3. Revealed Heuristics: Evidence from Investment Consultants' Search Behavior
with Sudheer Chava and Soohun Kim
WFA, Cavalcade, Oregon SFC, Helsinki, NFA, MARC (Outstanding Paper Award), Cavalcade Asia, Behavioural Finance WG, MFHFFI, APFM
Using proprietary data from a major fund data provider, we analyze the screening activity of investment consultants (ICs) who advise institutional investors with trillions of dollars in assets. We find that ICs frequently shortlist funds using threshold screens clustered at round, base 5 or base 10 numbers: $500MM for AUM, 0% for the return net of a benchmark, and quartiles for return percentile rank screens. A fund’s probability of being eliminated by a screen is significantly negatively related to its future fund attention and flows, with funds just above the $500MM AUM threshold getting 14 to 18% more page views and 5 to 9 pps greater flows over the next year compared to similar funds just below the threshold. Our results are consistent with ICs using a two-stage, consider-then-choose decision making process, and cognitive reference numbers in selecting screening thresholds.
4. Uncovering Financial Constraints
with Matt Linn
MFA, FMA
We classify firms’ financial constraints using a random forest model trained on the Hoberg and Maksimovic (2015) text-based constraint measures. Our model uses only financial variables to predict constraints, allowing us to significantly expand the cross- section and time-series of classified firms compared to the text-based measures. We conduct a number of tests to validate the informativeness of our measures. Using our classifications, we provide evidence that returns of debt (equity) constrained firms are more sensitive to shocks to the cost of equity (debt) financing. The results highlight the importance of financial flexibility in determining a firm’s exposure to financing shocks.
Portions of this paper were "spun-off" an older working paper entitled "Seeing the Forest Through the Trees: Do Investors Under-react to Systemic Events?"
*scheduled