Computing and Data Resources
PhD students are equipped with state-of-the-art computing and data resources. Each student receives his or her own new computer, personal workstation in the department, and necessary computing and statistical software upon request. Stern’s high-end servers facilitate large volume data processing and analysis, and Stern’s own dedicated research computing staff supports PhD students with advanced computing needs.
The Stern School subscribes to major company, financial, economic and marketing databases, such as CRSP and Compustat.
Stern’s newly-renovated Behavioral Laboratory includes over 25 computer work stations, and a variety of break-out rooms for conducting research on individuals and groups. In addition, the behavioral lab offers services related to all aspects of carrying out behavioral research, including assistance with participant recruitment, study design, implementation, and human subjects approval.
Additionally, the NYU Bobst Library’s Business Center houses a general and international business reference collection that includes material on US and international business, investment services, periodical indexes and numerous electronic services that keep the literature at the students’ fingertips. More than 70 business and social sciences databases, such as ABI-Inform, Dow Jones, Ebsco, Econ Lit, Global Access, Lexis-Nexis, The Wall Street Journal, Stat-USA and EIU Viewswire are available through the Web-based Virtual Business Library. Other Business Center resources include Datastream and Bloomberg terminals and depository collections of both US government and UN documents containing a wealth of business information.
Research Centers and Institutes
Stern’s research centers and research institutes also enhance students’ academic experience through hosting frequent conferences that attract international scholars and practitioners, providing research grants, fostering collaboration with other schools at NYU, and providing access to unique data.
Students receive necessary funding for data collection expenses by submitting a formal research funding proposal that is reviewed by a faculty committee.