Hasselback's Faculty Roster

Compiled Data of James R. Hasselback's Faculty lists, combined with Scopus IDs

What is this?

James Hasselback publishes a near-complete list of faculties of Economics, Management, Finance and Accounting departments in the US, Canada and some other places for various years. I have compiled those lists (available at http://www.jrhasselback.com/FacDir.html as pdfs) to make them usable in my research.

The following lists have been parsed:

	Accounting	Economics	Finance	Management
1999-2000		x
2000-2001	x		x	x
2001-2002	x	x
2002-2003			x
2003-2004	x	x
2004-2005
2005-2006
2006-2007		x

However, because of old listings in case an institution did not respond, faculty information goes back to as early as 1992/1993.

I only report faculty members with PHD and who are not decesased, retired or emeritus.

They are augmented with the Scopus IDs of the researchers. Although I've given great attention to the mapping of researchers to their Scopus Author profile IDs, there might be few errors. We used all availble information, including affiliation history and field.

Feel free to use them in your research, too. You can find a variable description on James' website. I am open to data additions and gladly accept Pull Requests. Note that I aggregated information for researchers holding a PhD only.

How do I use this?

...

Usage in your scripts is easy:

• In python (with pandas):

import pandas as pd

FACULTY_FILE = ('https://raw.githubusercontent.com/Michael-E-Rose/Hasselback'
                'FacultyRoster/master/hasselback.csv')
hass = pd.read_csv(FACULTY_FILE, index_col=0)

What's the benefit?

• Central online storage for seamless inclusion in local scripts.
• Longitudinal collection of faculty information for US-based researchers including academic rank, year of PhD and PhD school and more.

Workflow

• ./mapping_files/institutions.csv and ./mapping_files/persons.csv are mapping files to aggregate over differently used university names and to map researchers to their Scopus profile IDs.
• make_hasselback.py.py combines the information.
• hasselback.csv is the resulting file.