Publications:
1. Can Markets Discipline Government Agencies? Evidence from the Weather Derivatives Market
with Amiyatosh Purnanandam. The 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 impact of financial sector stress on risk sharing in a novel setting: the Chicago Mercantile Exchange’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. In normal times, contracts are priced near their actuarially fair value. During the recent financial crisis, contract prices one-month before maturity fall by 2.2%. This discount is equivalent to an annualized weather risk premium of 26%. Contract prices decline with increases in the TED spread and the VIX and the declines are greatest for high margin and high total risk contracts. Examining end users, I find the risk-sharing benefits of the weather derivatives market decrease during the crisis. The results provide causal evidence of the importance of financial sector stress in the pricing of financial contracts and its effect on risk sharing in the economy.
with Amiyatosh Purnanandam. The 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 impact of financial sector stress on risk sharing in a novel setting: the Chicago Mercantile Exchange’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. In normal times, contracts are priced near their actuarially fair value. During the recent financial crisis, contract prices one-month before maturity fall by 2.2%. This discount is equivalent to an annualized weather risk premium of 26%. Contract prices decline with increases in the TED spread and the VIX and the declines are greatest for high margin and high total risk contracts. Examining end users, I find the risk-sharing benefits of the weather derivatives market decrease during the crisis. The results provide causal evidence of the importance of financial sector stress in the pricing of financial contracts and its effect on risk sharing in the economy.
Working Papers:
1. Firm Finances and the Spread of COVID-19: Evidence from Nursing Homes
with Taylor Begley
Residents of senior-care facilities account for over 40% of COVID-19-related deaths in the United States despite making up less than 1% of the population. We show that differences in nursing homes’ finances help explain cross-sectional variation in the incidence of COVID-19. In addition to large drops in revenues, nursing homes were forced to make difficult risk mitigation investment decisions in the face of staggering increases in equipment, testing, and labor costs. We find that nursing homes with less liquidity (pre-pandemic days-cash-on-hand) had a higher likelihood of COVID-19 in their facility. Those with larger negative shocks to cash flow – thus lowering firm value and moving them closer to financial distress – also had a higher likelihood of COVID-19. These results have implications for the role finances can play in the welfare of customers, employees, and for broader public health.
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, LFG Meeting @ Georgia Tech*, LFG European conference @ IFN*, EFA*
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. Disaster Lending: "Fair" Prices, but "Unfair" Access
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.
5. 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?"
6. Are Monthly Market Returns Predictable? (R&R Review of Asset Pricing Studies)
with Jussi Keppo and Tyler Shumway
Appendix
Helsinki Finance Summit, Fed HH Econ. and Decision-Making, AEA
We document significant persistence in the market timing performance of active indi- vidual 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.
*scheduled
with Taylor Begley
Residents of senior-care facilities account for over 40% of COVID-19-related deaths in the United States despite making up less than 1% of the population. We show that differences in nursing homes’ finances help explain cross-sectional variation in the incidence of COVID-19. In addition to large drops in revenues, nursing homes were forced to make difficult risk mitigation investment decisions in the face of staggering increases in equipment, testing, and labor costs. We find that nursing homes with less liquidity (pre-pandemic days-cash-on-hand) had a higher likelihood of COVID-19 in their facility. Those with larger negative shocks to cash flow – thus lowering firm value and moving them closer to financial distress – also had a higher likelihood of COVID-19. These results have implications for the role finances can play in the welfare of customers, employees, and for broader public health.
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, LFG Meeting @ Georgia Tech*, LFG European conference @ IFN*, EFA*
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. Disaster Lending: "Fair" Prices, but "Unfair" Access
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.
5. 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?"
6. Are Monthly Market Returns Predictable? (R&R Review of Asset Pricing Studies)
with Jussi Keppo and Tyler Shumway
Appendix
Helsinki Finance Summit, Fed HH Econ. and Decision-Making, AEA
We document significant persistence in the market timing performance of active indi- vidual 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.
*scheduled