Fist generic advantage in generic competition - selection bias problem
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The aim of this paper is to estimate the advantage of first generic drugs in pharmaceutical industry taking into account the selection bias problem in unobservable variables. I use the non-parametric method to identify the parameter of interest and it is shown that heterogeneity among firms is not a substantial problem with our data. Three alternative approaches are studied to evaluate the first mover advantage: linear regression, matching methods, and instrumental variables (IV). Under the necessary assumptions and the data requirements for each method, linear regression estimate 26.3% increased in market share for the first generics (matching method is 26.2%, IV is 32.58%). If we compare it to the second generic, the first mover advantage amounts to 21.5%.
Abstract
The aim of this paper is to estimate the advantage of first generic drugs in pharmaceutical industry taking into account the selection bias problem in unobservable variables. I use the non-parametric method to identify the parameter of interest and it is shown that heterogeneity among firms is not a substantial problem with our data. Three alternative approaches are studied to evaluate the first mover advantage: linear regression, matching methods, and instrumental variables (IV). Under the necessary assumptions and the data requirements for each method, linear regression estimate 26.3% increased in market share for the first generics (matching method is 26.2%, IV is 32.58%). If we compare it to the second generic, the first mover advantage amounts to 21.5%.
참고문헌 (12)
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