Generic Entry and The Effect on Prices in the Prescription Drug Market
By Sahana Giridharan
Abstract
Drug firms have utilized a variety of strategies that contribute to rising drug prices in the
U.S. for the last few years. Strategic entry timing and number of indications a drug is approved
might be two factors that contribute to this rise in prices. While there have been some studies
uncovering a positive relationship between generic entry and branded prices, there has been little
research done on the effects of generic entry on generic prices thus far. This work can impact
policy aimed at decreasing generic drug prices and increasing competition in the generic drug
market.
Oncology and inflammatory bowel disease (IBD) are two disease areas that have a high
price burden to patients in the U.S. today, hence using Medicare Part B Average Sales Price
(ASP) data, I analyze the effect of entry timing on the price of 24 drugs in these two indication
areas. Using the Drugs@FDA Database, I collect data on the FDA approval date of a drug, and
on the indications a drug is approved for. Utilizing OLS, my results suggest that later entry times
lead to lower drug prices, with a 1 year increase in entry time resulting in a 6.99% increase in
prices. Results also suggest that an increase of 1 in the number of indications a drug is approved
for leads to a 49.79% decrease in drug price. This could suggest that having existing generic
competitors in the pharmaceutical market decreases generic prices, and that number of
indications is a strong indicator of drug price.
If the current work is confirmed by future studies similar to this studying entry time and
price in the generic pharmaceutical market, it is possible that future drug policy should focus on
promoting competition within the pharmaceutical market to lower generic prices.
Professor Frank Sloan, Faculty Advisor
Professor Grace Kim, Faculty Advisor
Professor Kent Kimbrough, Faculty Advisor
JEL Classification: L11; I11; C3
Myocardial Infarction, Health Behavior, and the Grossman Model
by Emma Mehlhop
This paper contributes an empirical test of Michael Grossman’s model of the demand for health and a novel application of the model to myocardial infarction (MI) incidence. Using data from the University of Michigan’s Health and Retirement Study (HRS), I test Grossman’s assumptions regarding the effects of hourly wage, sex, educational attainment, and age on health demand along with the effects of new variables describing health behaviors, whether or not a respondent is insured, and whether or not they are allowed sufficient paid sick leave. I use logistic regression to estimate health demand schedules using five different health demand indicators: exercise, doctor visits, drinking, smoking, and high BMI. I apply the Cox Proportional Hazard model to examine two equations for the marginal product of health investment both in terms of propensity to prevent death and to prevent MI, one of the leading causes of mortality in the United States. This study considers the effects of the aforementioned health demand indicators, among other factors, on the marginal product of health investment for the prevention of death compared to the prevention of MI. Additionally, there is significant evidence of a negative effect of health insurance on likelihood of exercising regularly, implying some effect of moral hazard on the health demand schedule.
Advisors: Professor Charles Becker, Professor Grace Kim, Professor Frank Sloan | JEL Codes: I1, I10, I12
The Impact of Medicare Nonpayment: A Quasi-Experimental Approach
By Audrey Kornkven
In October 2008, a provision of the Deficit Reduction Act of 2005 known as Medicare “Nonpayment” went into effect, eliminating reimbursement for the marginal costs of preventable hospital-acquired conditions in an effort to correct perverse incentives in hospitals and improve patient safety. This paper contributes to the existing debate surrounding Nonpayment’s efficacy by considering varying degrees of fiscal pressure among hospitals; potential impacts on healthcare utilization; and differences between Medicare and non-Medicare patient populations. It combines data on millions of hospital discharges in New York from 2006-2010 with hospital-, hospital referral region-, and county-level data to isolate the policy’s impact. Analysis exploits the quasi-experimental nature of Nonpayment via difference-in-differences with Mahalanobis matching and fuzzy regression discontinuity designs. In line with results from Lee et al. (2012), Schuller et al. (2013), and Vaz et al. (2015), this paper does not find evidence that Nonpayment reduced the likelihood that Medicare patients would develop a hospital-acquired condition, and concludes that the policy is not likely the success claimed by policymakers. Results also suggest that providers may select against unprofitable Medicare patients when possible, and are likely to vary in their responses to financial incentives. Specifically, private non-profit hospitals appear to have been most responsive to the policy. These findings have important implications for pay-for-performance initiatives in American healthcare.
Advisors: Professor Charles Becker, Professor Frank Sloan, Professor Grace Kim| JEL Codes: I1, I13, I18
Security Without Equity? The Effect of Secure Communities on Racial Profiling by Police
By Jack Willoughby
Anecdotal and circumstantial evidence suggest that the implementation of Secure Communities, a federal program that allows police officers to more easily identify illegal immigrants, has increased racial bias by police. The goal of this analysis is to empirically evaluate the effect of Secure Communities on racial bias by police using motor vehicle stop and search data from the North Carolina State Bureau of Investigation. This objective differs from most previous research, which has largely attempted to quantify racial profiling for a moment in time rather than looking at how an event influences racial profiling. I examine the effects of Secure Communities on police treatment of Hispanics vs. whites with an expanded difference-in-difference approach that looks at outcomes in
motor vehicle search success rate, search rate conditional on a police stop, stop rate, and police action conditional on stop. Statistical analyses yield no evidence that the ratification of Secure Communities increased racial profiling against Hispanics by police. This finding is at odds with the anecdotal and circumstantial evidence that has led many to believe that the ratification of Secure Communities led to a widespread increase in racial profiling by police, a discrepancy that should caution policy makers about making decisions driven by stories and summary statistics.
Advisor: Frank Sloan | JEL Codes: J15, K14, K37, K42 | Tagged: Racial Policing, Bias, Immigration Law, Secure Communities
Are the Chinese Altruistic? Explaining Motives behind Chinese Intergenerational Transfers using the Strategic Bequest Motive
By Lucy Yin
Two main competing theories regarding intergenerational transfers from adult children to elderly parents exist: the altruism model and the exchange model. The strategic bequest motive supports the exchange model in claiming parents with bequeathable wealth will incentivize children to devote more resources to parents in order to receive a larger bequest. I use data from the Chinese Longitudinal Healthy Longevity Survey to assess whether children increase monetary or time transfers to elderly parents with bequeathable property ownership. My findings suggest an altruistic model at play, which contradicts most findings in East Asian countries but may be a trend found in other developing countries.
Advisor: Frank Sloan, Michelle Connolly | JEL Codes: D14, D64 | Tagged: Bequests, Altruism, Intergenerational Transfers
Trauma Center Eficacy: Certification Status and its Effect on Traffic Fatalities at Varying Radii
By Robert Van Dusen
The goal of the paper is to better inform policy makers on the optimal placement of trauma center facilities. Below, I examine the effect of Californian trauma centers vs. standard emergency departments on traffic fatalities for 2002 to 2008. Hospital addresses are geocoded and compared to the geographic coordinates of fatal car accidents provided through USDOT in order to create a dependent fatality density variable for every hospital at different radii. Demographic controls for different radii are constructed using ArcGIS
to serve as a model for traffic fatalities.
Advisor: Frank Sloan, Kent Kimbrough | JEL Codes: I1, I10, I18 | Tagged: Healthcare,
Trauma, Trauma Center
Incentives and Characteristics that Explain Generic Prescribing Practices
By Rahul Nayak
This study uses the National Ambulatory Medical Care Survey (2006-2010) and Health Tracking Physician Survey (2008) to study the incentives and characteristics that explain physician generic prescribing habits. The findings can be characterized into four main categories: (1) financial/economic, (2) informational, (3) patient- dependent and (4) drug idiosyncratic effects. Physicians in practices owned by HMOs or practices that had at least one managed care contract are significantly more likely to prescribe generic medicines. Furthermore, physicians who have drug industry influence are less likely to prescribe generic medicines. This study also finds consistent evidence that generic prescribing is reduced for patients with pri- vate insurance compared to self-pay patients. Drug-specific characteristics play an important role for whether a drug is prescribed as a generic or brand-name – in- cluding not only market characteristics, such as monopoly duration length, public familiarity with the generic and the quality of the generic, but also non-clinical drug characteristics, such as the length of the generic name compared the length of the brand-name. In particular, the public’s familiarity with the generic has a large effect on the generic prescribing rate for a given drug. There are few differences between the generic prescribing habits of primary care physicians and specialists after controlling for the drugs prescribed.
Advisor: Frank Sloan | JEL Codes: D82, D83, I11, I13, I18 | Tagged: Drug Market Charac- teristics, Efficient Prescribing, Electronic Prescribing, Generic Prescribing, HTPS, Industry Influence, NAMCS, Patient Preferences, Physician Incentives, Principle- Agent Problem
Debunking the Cost-Shifting Myth: An Analysis of Dnamic Price Discrimination in California Hospitals
By Omar Nazzal
Cost-shifting, a dynamic form of price discrimination, is a phenomenon in which hospitals shift the burden of decreases in government-sponsored healthcare reimbursement rates to private health insurers. In this paper, I construct a data set spanning 2007 – 2011 that matches financial metrics of California hospitals to hospital- and market-specific characteristics with theoretical implications in price discrimination. The subsequent analysis is split into three stages. In the first and second stages, I use a fixed-effects OLS model to derive a point estimate of the inverse correlation between private revenue and government revenue that is consistent with recent empirical work in cost-shifting, a body of literature almost entirely reliant upon fixed-effects and difference-in-difference OLS. These types of models are encumbered by the inherent causality loop connecting public and private payment sources. I address this endogeneity problem in the third stage by specifying a fixed-effects 2SLS model based on an instrument for government revenue constructed with data from the California Department of Health Care Services and the U.S. Census. This instrument performed well in canonical tests for relevance and validity. I find that an increase in government payments causes an increase in private payments, and that the relationship is statistically-significant at all reasonable levels. In addition, I comment on properties of the data set that suggest that the original inverse correlation was due to inadequate measurements of market power. I conclude with policy implications and suggestions for future research.
Advisor: Frank Sloan | JEL Codes: I11, I13, I18, L11, L80 | Tagged: Health Insurance, Market Structure, Medicaid, Medicare, Price Discrimination
Integrating Medicare and Medicaid Healthcare Delivery and Reimbursement Policies for Dual Eligible Beneficiaries: A Cost-Efficiency Analysis of Managed Care
By Kan Zhang
The extreme underpricing of Chinese Initial Public Offerings in the early days of the Chinese equity markets was reduced by several reforms instituted by the Chinese government from around 2000 to 2002. These reforms reduced 1-day returns on IPOs from 295% to 72%. The reforms reduced IPO underpricing by decreasing the inequality between IPO supply and demand. These reforms, while announced between 2000 and 2002, likely took until around 2004 to take full effect. In addition to inequality between supply and demand, other factors such as information asymmetry and government/quality signaling contributed to underpricing both before and after the reforms.
Advisor: Frank Sloan | JEL Codes: D61, I0, I11, I12, I18 | Tagged: Dual Eligibles, Managed Care, Medicare
Health Care Utilization and Health Status of NCMS Elderly Enrollees in China: Evidence from CHARLS Data
By Pengpeng Wang
This study explores the effect of benefit designs and demographic factors on health care utilization and health status of elderly rural enrollees in the New Cooperative Medical Scheme, a rural health insurance program implemented by the Chinese government in 2003. Using the new data from CHARLS pilot study, we find that immediate reimbursement does not have a statistically significant effect on health utilization as suggested in a previous study, but instead on health status. Other policy-related factors neither have a significant effect due to limited data and large standard deviation nor display a consistent effect.
Advisor: Frank Sloan | JEL Codes: I13, I18 | Tagged: Health Care Utilization, Health Insurance, Health Status, New Cooperative Medical Scheme, Reimbusement Method, Rural China
