Date of Award

August 2020

Degree Type


Degree Name

Doctor of Philosophy (PhD)


Business Administration


Amiya Basu

Subject Categories



The purpose of this dissertation is to investigate how regulation and deregulation impacts hospital performance, its persistence effect and the different impact on drug markets. The authorities designed programs and policies to regulate hospitals and pharmaceutical markets, aiming at improving hospital performance and control drug prices, while in reality, the programs and policies generate consequences, the effect varies across different types of the hospitals and drugs.

The dissertation consists of three essays. The first essay proposes a propensity score matching-difference in difference framework of program evaluation of Value Based Purchasing program. This framework first applies the propensity score matching method to find a treated group whose characteristics are comparable to our control group (hospitals in Maryland). Next, I used the difference in difference method to evaluate whether and how the VBP program impacts hospitals performance in terms of quality, satisfaction, safety and efficiency. Our empirical analysis using 5 years of hospital performance data from various sources. The results showed that, under the program of VBP, hospitals that are impacted did show improvements in patient experience, but in terms of experience dimensions, only pain control scores were improved significantly. Regarding safety, cost efficiency and conformance quality, the impacted hospitals did not show significant improvements. The sensitivity check supports our conclusion.

The second essay studies the state dependence effect of payment adjustments on hospitals to see whether the effect exist and how it varies across hospitals of different characteristics, socio-economic factors and geo-locations. The program adjusts the payment as follows: First, the program reduces a portion of the hospital`s Medicare payments in a specific fiscal year and then by the end of the same fiscal year, the amount of the payment reductions will be awarded to the hospitals based on the total performance score, thus the hospitals that do not receive the reward will lose the portion of money reduced by Medicare. In this essay, I apply the theory of state dependence and use the dynamic random effect probit model to estimate this effect. The results show that the hospital payment adjustment dynamics have a very significant state dependence effect (0.341), that means, hospitals that received a reward in previous year are 34.1% more probably to receive a reward this year than the ones that received a penalty in previous year. Meanwhile, I also find that the state dependence effect varies significantly across hospitals with different ownership (proprietary/government owned/voluntary nonprofit), the results show that voluntary nonprofit hospitals exhibit largest effect of state dependence (0.370), while government owned hospitals exhibit lowest effect of state dependence (0.293) and proprietary hospitals are in the middle. Among the factors that influence the likelihood a hospital receive a reward, I find that teaching hospitals with large number of beds (>400), are less likely be rewarded; in terms of ownership, I find that voluntary nonprofit hospitals are more likely be rewarded; in terms of demographic factors, hospitals where the average household income are higher within the region are more likely be rewarded.

The third essay studies the effect of deregulation of price cap in pharmaceutical market. Price regulation (either through price cap or reference price) is common practice in pharmaceutical market but recently there are increasing voices calling for deregulation claiming that deregulation could help with lowering drug price and increase revenue of pharmaceutical firms. Upon those callings, Chinese government removed the price cap regulation in June 2015. In this essay, I applied the interrupted time series analysis (ITSA) on the sales revenue data of nine categories of both generic and branded drugs in China from March 2011 to August 2016 (the time frame includes both before and after of the initialization of the deregulation) and analyzed the effect of deregulation. The results showed that, whether the revenue of drugs will increase or decrease after the deregulation of price cap depends on the level of competition and the change of patterns of the branded and generic drugs are different. When HHI is sufficiently low (competition is high), revenue does not change as a result of deregulation, when HHI is moderately low (moderate competition), revenue from generic drugs will decrease significantly and revenue from branded drugs will increase significantly, when HHI is high (low competition), revenue from generic drugs will increase significantly and revenue from branded drugs will decrease significantly.


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