Amanda Kowalski, Assistant Professor of Economics at Yale University and Faculty Research Fellow at the National Bureau of Economic Research (NBER), is a health economist who specializes in applying econometric techniques to answer questions that inform current debates in health policy.
Professor Kowalski's recent research explores the impact of the 2006 Massachusetts health reform with an eye toward the likely impact of the 2010 national health reform, focusing specifically on hospital care, labor market outcomes, and adverse selection in the individual health insurance market. She has also researched the price elasticity of expenditure on medical care and the marginal returns to medical spending on at-risk newborns using new estimation techniques. Her research has received the Zellner Thesis Award, the HCUP Outstanding Article of the Year Award, and the Garfield Economic Impact Award.
The National Institutes of Health, the Robert Wood Johnson Foundation, and the W.E. Upjohn Institute have supported her research, which has been published in peer-reviewed journals, including the Quarterly Journal of Economics and the Journal of Public Economics. Her research has also been featured in the popular press, including The Wall Street Journal and Newsweek.
Professor Kowalski holds a PhD in economics from MIT and an AB in economics from Harvard. Before joining Yale, she held a post-doctoral fellowship in Health and Aging at the NBER in Cambridge, MA. Her interest in health policy has led her to spend two years in Washington, DC, one as a research assistant in health and labor at the White House Council of Economic Advisers, and another as the Okun Model Fellow at the Brookings Institution.
"The Impact of Health Care Reform on Hospital and Preventive Care: Evidence from Massachusetts" (with Jonathan T. Kolstad). Journal of Public Economics. December 2012. Vol. 96. 909-929. (Older Version: NBER Working Paper 16012.) [PDF][Slides]
Video Presentations of Massachusetts Research:
In April 2006, Massachusetts passed legislation aimed at achieving near-universal health insurance coverage.
The key features of this legislation were a model for national health reform, passed in March 2010. The
reform gives us a novel opportunity to examine the impact of expansion to near-universal coverage state-wide.
Among hospital discharges in Massachusetts, we find that the reform decreased uninsurance by 36%
relative to its initial level and to other states. Reform affected utilization by decreasing length of stay and the
number of inpatient admissions originating from the emergency room. When we control for patient severity, we find evidence that preventable admissions decreased. At the
same time, hospital cost growth did not increase.
"Health Reform, Health Insurance, and Selection: Estimating
Selection into Health Insurance Using the Massachusetts Health
Reform" (with Martin B. Hackmann and Jonathan T. Kolstad). American Economic Review: Papers & Proceedings. May 2012. Vol. 102, No. 3: 498-501. (Older Version: NBER Working Paper 17748. Cowles Foundation Discussion Paper 1841.) [PDF]
We implement an empirical test for selection into
health insurance using changes in coverage induced by the
introduction of mandated health insurance in Massachusetts. Our test
examines changes in the cost of the newly insured relative to those
who were insured prior to the reform. We find that counties with
larger increases in insurance coverage over the reform period face
the smallest increase in average hospital costs for the insured
population, consistent with adverse selection into insurance before
the reform. Additional results, incorporating cross-state variation
and data on health measures, provide further evidence for adverse
"The Role of Hospital Heterogeneity in Measuring Marginal Returns to Medical Care: A Reply to Barreca, Guldi, Lindo, and Waddell" (with Douglas Almond, Joseph J. Doyle, and Heidi Williams). Quarterly Journal of Economics. November 2011. Vol. 126, No. 4: 2125-2131. [PDF]
Response to comment on "Estimating Marginal Returns to Medical Care: Evidence from At-Risk Newborns"
In Almond, Doyle, Kowalski and Williams (2010), we describe how marginal returns to medical care
can be estimated by comparing patients on either side of diagnostic thresholds. Our application
examines at-risk newborns near the very low birth weight threshold at 1500 grams. We estimate large
discontinuities in medical care and mortality at this threshold, with effects concentrated at low-quality
hospitals. While our preferred estimates retain newborns near the threshold, when they are
excluded the estimated marginal returns decline, although they remain large. In low-quality hospitals,
our estimates are similar in magnitude regardless of whether these newborns are included or excluded.
We estimate marginal returns to medical care for at-risk newborns by comparing health outcomes and medical treatment provision on either side of common risk classifications, most notably the "very low birth weight" threshold at 1500 grams. First, using data on the census of US births in available years from 1983-2002, we find evidence that newborns with birth weights just below 1500 grams have lower one-year mortality rates than do newborns with birth weights just above this cutoff, even though mortality risk tends to decrease with birth weight. One-year mortality falls by approximately one percentage point as birth weight crosses 1500 grams from above, which is large relative to mean one-year mortality of 5.5% just above 1500 grams. Second, using hospital discharge records for births in five states in available years from 1991-2006, we find evidence that newborns with birth weights just below 1500 grams have discontinuously higher costs and frequencies of specific medical inputs. We estimate a $4,000 increase in hospital costs as birth weight approaches 1500 grams from above, relative to mean hospital costs of $40,000 just above 1500 grams. Taken together, these estimates suggest that the cost of saving a statistical life of a newborn with birth weight near 1500 grams is on the order of $550,000 in 2006 dollars.
"State Health Insurance Regulations and the Price of High-Deductible Policies" (with William J. Congdon and Mark H. Showalter). Forum for Health Economics & Policy. 2008. Vol. 11: Iss. 2 (Health Care Reform), Article 8. [PDF] http://www.bepress.com/fhep/11/2/8/
This study examines the impact of state health insurance regulations on the price of high-deductible family and individual polices in the nongroup market. We use a unique and rich data set on actual insurance policies sold through a large Internet health insurance distributor to examine the impact of various regulations on policy prices, controlling for policy characteristics, demographic characteristics of the purchasers, and state-level demographics. We also use data from a single major insurance firm that provided offer prices for a family policy from a set of randomly selected zip codes. Both datasets suggest a strong statistical relationship between regulation and insurance prices.
Completed Working Papers
"Adverse Selection and an Individual Mandate: When Theory Meets Practice" (with Martin Hackmann and Jonathan T. Kolstad). NBER Working Paper 19149. Latest Version: June 2013. Revise & Resubmit, American Economic Review. [PDF] [Slides]
We develop a model of selection that incorporates a key element of recent health reforms: an individual
mandate. We identify a set of key parameters for welfare analysis, allowing us to model the welfare
impact of the actual policy as well as to estimate the socially optimal penalty level. Using data from
Massachusetts, we estimate the key parameters of the model. We compare health insurance coverage,
premiums, and insurer average health claim expenditures between Massachusetts and other states in
the periods before and after the passage of Massachusetts health reform. In the individual market for
health insurance, we find that premiums and average costs decreased significantly in response to the
individual mandate; consistent with an initially adversely selected insurance market. We are also able
to recover an estimated willingness-to-pay for health insurance. Combining demand and cost estimates
as sufficient statistics for welfare analysis, we find an annual welfare gain of $335 dollars per person
or $71 million annually in Massachusetts as a result of the reduction in adverse selection. We also
find evidence for smaller post-reform markups in the individual market, which increased welfare by
another $107 dollars per person per year and about $23 million per year overall. To put this in perspective, the total welfare gains were 8.4% of medical expenditures paid by insurers. Our model and empirical estimates suggest an optimal mandate penalty of $2,190. A penalty of this magnitude would increase health insurance to near universal levels. Our estimated optimal penalty is higher than the individual mandate penalty adopted in Massachusetts but close to the penalty implemented under the ACA.
"Mandate-Based Health Reform and the Labor Market: Evidence from the Massachusetts Reform" (with Jonathan T. Kolstad). NBER Working Paper 17933. Latest Version: January 2014. Under review. [PDF][Slides][Download Problem Set on This Paper Below]
Video Presentation on Health Reform and the Labor Market:
We model the labor market impact of the key provisions of the national and Massachusetts "mandate-based" health reforms: individual mandates, employer mandates, and subsidies. We characterize the compensating differential for employer-sponsored health insurance (ESHI) and the welfare impact of reform in terms of "sufficient statistics." We compare welfare under mandate-based reform to welfare in a counterfactual world where individuals do not value ESHI. Relying on the Massachusetts reform, we find that jobs with ESHI pay $5,350 less annually, approximately the cost of ESHI to employers. Accordingly, the deadweight loss of mandate-based health reform was approximately 2% of its potential size.
"Estimating the Tradeoff Between Risk Protection and
Moral Hazard with a Nonlinear Budget Set Model of
Health Insurance." NBER Working Paper 18108. Latest Version: December 2013. Under review. [PDF][Slides][Data Appendix]
Insurance induces a tradeoff between the welfare gains from risk protection and the welfare
losses from moral hazard. Empirical work traditionally estimates each side of the tradeoff
separately, potentially yielding mutually inconsistent results. I develop a nonlinear budget set
model of health insurance that allows for both simultaneously. Nonlinearities in the budget
set arise from deductibles, coinsurance rates, and stoplosses that alter moral hazard as well
as risk protection. I illustrate the properties of my model by estimating it using data on
employer sponsored health insurance from a large firm. Within my empirical context, the
average deadweight losses from moral hazard substantially outweigh the average welfare gains
from risk protection. However, the welfare impact of moral hazard and risk protection are
both small relative to transfers from the government through the tax preference for employer
sponsored health insurance and transfers from some agents to other agents through a common
"Censored Quantile Instrumental Variable Estimates of the Price Elasticity of Expenditure on Medical Care" (Job Market Paper) NBER Working Paper 15085. Latest Version: November 2013. Under review. [PDF][Data Appendix][Download Stata Command to Implement CQIV Below]
Efforts to control medical care costs depend critically on how individuals respond to prices. I estimate
the price elasticity of expenditure on medical care using a new censored quantile instrumental variable
(CQIV) estimator. CQIV allows estimates to vary across the conditional expenditure distribution, relaxes
traditional censored model assumptions, and addresses endogeneity with an instrumental variable. My
instrumental variable strategy uses a family member's injury to induce variation in an individual's own
price. Across the conditional deciles of the expenditure distribution, I find elasticities that vary from -1.26
to -1.50, which are an order of magnitude larger than previous estimates.
"Censored Quantile Instrumental Variable Estimation via Control Functions" (with Victor Chernozhukov and Ivan Fernandez-Val). NBER Working Paper 16997. Cowles Foundation Discussion Paper 1797. arXiv identifier 1104.4580. (Older Version: Boston University Department of Economics Working Paper 2009-012.) Latest Version: April 2011. Revise & Resubmit, The Journal of Econometrics. [PDF][Download Stata Command to Implement CQIV Below]
In this paper, we develop a new censored quantile instrumental variable (CQIV) estimator and describe its properties and computation. The CQIV estimator handles censoring semi-parametrically in the tradition of Powell (1986), and it generalizes standard censored quantile regression (CQR) methods to incorporate endogenous regressors in a manner that is computationally tractable. Our computational algorithm combines a control function approach with the CQR estimator developed by Chernozhukov and Hong (2002). Through Monte-Carlo simulation, we show that CQIV performs well relative to Tobit IV in terms of median bias and interquartile range in a model that satisfies the parametric assumptions required for Tobit IV to be efficient. Given the strong parametric assumptions required by Tobit IV, the gains to CQIV relative to Tobit IV are likely to be large in empirical applications. We present results from an empirical application of CQIV to the estimation of Engel curves for alcohol. This empirical application demonstrates the importance of accounting for censoring and endogeneity with CQIV.
Selected Work in Progress
"The Long Term Impact of Health Insurance Expansions on Eligible Children" (with David Brown and Ithai Lurie).
"How do Individual Medical Expenditures Evolve over Time? Evidence from Nonelderly Individuals in New York."
"CQIV: Stata Module to Perform Censored Quantile Instrumental Variable Regression." First Version: December 2010. Latest Version: June 2012. (with Victor Chernozhukov, Ivan Fernandez-Val, and Sukjin Han). [Link to CQIV at RePEc]
The simplest way to install this command is to type the following at the Stata command prompt:
ssc install cqiv
You can also download the .ado and .sthlp files [Download CQIV Stata ado file][Download CQIV Stata help file], and then copy them into your personal ado directory [How to find your personal ado directory].
If you are updating from a previous version, type "net uninstall cqiv" at the Stata prompt before installing.
Problem Set on "Mandate-Based Health Reform and the Labor Market: Evidence from the Massachusetts Reform." First Version: May 2012. Latest Version: October 2012. (Developed with Toby Chaiken and Jonathan Kolstad).
This problem set is designed for graduate students and advanced undergraduates. It requires Stata and Excel.
Download Stata, Excel, and Word Files as a zip file. The Word file contains instructions.
Answer key available, instructors only please. Email Amanda Kowalski.
Problem Set on "Estimating Marginal Returns to Medical Care: Evidence from At-risk Newborns" First Version: February 2012. Latest Version: February 2012. (Developed with Tiffany Fan and Michael Cunetta).
This problem set is designed for undergraduates. It requires Stata.
Download Stata and Word Files as a zip file. The Word file contains instructions.
Answer key available, instructors only please. Email Amanda Kowalski.
Summer 2013 Research Team (from left): William Bishop, Martin Hackmann, Kate Archibald, Tiffany Fan, Amanda Kowalski, Gerardo Ruiz Sanchez.