Austin Bean

I am an assistant professor of economics at Temple University. My research interests are industrial organization and health economics. I teach Prinicples of Microeconomics (Regular and Honors) and an undergraduate industrial organization class called Economics of American Industry . I have also taught IO at the graduate level. [CV]

Current Working Papers:

Inefficient Technology Investment: Competition, Mortality and Neonatal Intensive Care.

I estimate a dynamic model of hospital investments in neonatal intensive care in Texas. Since the early 1990's, investment in this service has been quite robust. Urban areas have multiple hospitals offering high level facilities but operating below their capacity. Quality in neonatal intensive care is increasing in the number of patients treated: higher volumes lead to lower mortality rates. The entry of additional intensive care units imposes a negative production externality on existing units by reducing patient volumes. I estimate a static model of patient demand to determine how patient choices respond to investment and through the dynamic model recover the hospitals' costs for treating different types of patients. I estimate a model of volume-outcome effects to predict how patient flows affect aggregate mortality. I simulate counterfactual outcomes under several restricted-entry regimes and find that up to 20% of the deaths of very low birth weight infants would be prevented in Texas by restricting entry.

Volume-Outcome Relationships and Organizational Forgetting in Neonatal Intensive Care.

I study an economy of scale in the production of quality and the consequences for consumer welfare in the context of neonatal intensive care in Texas. Using detailed birth-certificate-level data including ID of the hospital of birth covering all NICU patients over eight years, I identify the causal effect of prior patient volume on the probability of mortality for new patients. I also empirically estimate a forgetting rate, capturing the rate at which the stock of accumulated experience declines in importance to the production of lower mortality. I find a very high rate of forgetting in this setting, suggesting that entry into this market may be quite harmful. I find that moving patients from low to high volume NICU's within each county in the state would lead to substantial savings in lives: on the order of 145 infants annually. Valuing these lives at $7,000,000 each results in a welfare improvement of $1,000,000,000. I propose some policy options for the regulator in light of my results, including direct regulation of hospital prices to minimize the welfare loss from monopoly pricing.

“Physician Learning and Forgetting: Evidence from Military Doctors” (w/ Atul Gupta (UPenn) and Stephen Schwab (US Army – Baylor)

“Welfare-enhancing Monopoly in a Competitive Market” (w/ Liisa Laine (UPenn))

“Productivity and Productivity Dispersion in Health Care Markets” (w/ Alexandra Charbi (Charles River Associates))

“A Neural Architecture for Numerical Information Extraction”

“ICD-9 Embeddings for Neural-Network-based Patient Classification”

“Is Predicting Real Estate Prices with Machine Learning Hard? The Failure of Zillow’s iBuyer Program”