کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
7383455 1480433 2018 8 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
The signaling effects of incremental information: Evidence from stacked US Food and Drug Administration designations
ترجمه فارسی عنوان
اثرات سیگنالینگ اطلاعات افزوده: شواهد از دسته بندی های اداره غذا و دارو ایالات متحده
موضوعات مرتبط
علوم انسانی و اجتماعی اقتصاد، اقتصادسنجی و امور مالی اقتصاد و اقتصادسنجی
چکیده انگلیسی
The US Food and Drug Administration offers multiple designations for drugs under development, such as the fast-track designation (for drugs that treat serious conditions with unmet medical need) and the orphan drug designation (for drugs that treat rare diseases). In this study, we look at whether a stacked designation (a fast-track designation with a prior orphan designation) provides stronger positive signaling effects to investors than an unstacked designation (a fast-track alone). We examine differences in average cumulative abnormal returns (CARs) following “stacked” and “unstacked” announcements using daily stock data for individual firms and the S&P 500 Composite Index for the period of 1998-2015. Results show a substantial decline in average CARs over the study period for both stacked and unstacked designations. We hypothesize that this decline could be caused by the increased availability of information caused by the growth of the internet over the study period: as more information is more readily available, the value of each piece of incremental information may decrease. We also find evidence of substantially larger average CARs for small firms than large firms for both stacked and unstacked designations. We believe that this evidence supports the conclusion that there is a strong “dilution effect” for incremental information, as large pharmaceutical firms make more frequent announcements than smaller firms.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: The Quarterly Review of Economics and Finance - Volume 67, February 2018, Pages 219-226
نویسندگان
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