Essays on Pharmaceutical Policies and Markets

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Title: Essays on Pharmaceutical Policies and Markets
Author: Izhak, Olena
Contributor organization: University of Helsinki, Faculty of Social Sciences
Doctoral Programme in Economics
Helsinki Center for Economic Research
Helsingin yliopisto, valtiotieteellinen tiedekunta
Taloustieteen tohtoriohjelma
Helsingfors universitet, statsvetenskapliga fakulteten
Doktorandprogrammet i ekonomi
Publisher: Helsingin yliopisto
Date: 2018-10-02
Language: eng
Belongs to series: URN:ISSN:2323-9794
Thesis level: Doctoral dissertation (article-based)
Abstract: The thesis is a collection of three essays analyzing pharmaceutical markets and regulations. In the first chapter using the Finnish prescription registry I empirically evaluate how the probability of substitution of a prescribed drug in a pharmacy depends on the pharmacists' profits and patients' out of pocket costs. I find that the more pharmacists stand to loose from successful substitution the less likely it is to occur. This effect is driven by branded medicines. In the second chapter we theoretically derive a simple rule for the optimal patent breadth and duration for pharmaceutical patents. Using the exogenous variation in patent duration caused by the Agreement on Trade-Related Aspects of Intellectual Property Rights (TRIPS) and American Investors Protection Act (AIPA) and newly constructed US drug patent data, we find that extending patent length increases incentives to imitate via so-called Paragraph IV certifications, whereas broadening patents reduces these incentives. We conclude that the current policies might render pharmaceutical patents longer than socially optimal and patent term extensions are not efficient from the welfare point of view. The third chapter of the thesis is a stock market event study. I test if a broader, but uninformative of commercial success, news coverage of a medical condition a drug is meant to treat is associated with a stronger stock market reaction to the drug's regulatory approval event. I construct a novel dataset combining stock market performance measures, information on drug approval events of the US publicly traded pharmaceutical firms and the news coverage of medical conditions treatable with approved drugs. I approximated the news coverage by the number of times disease names appeared in the news headlines. I find that stock returns are positively related to the amount of unrelated news coverage before the drug approval date. The findings offer yet another evidence of behavioural biases on the investors' side leading to stock market inefficiencies.-.
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