Economic Geography

Key research questions
The interesting questions concern the evolving and ever-changing interaction
among labor skills, knowledge and technology, employment, and entrepreneur-
ship. These processes are central to the competitiveness of places, and affect the
range of choices regarding work for local populations.
Technology, broadly conceived as knowledge and its application, continues to
be fundamental to regional change. It dramatically affects which jobs are created
in which locations, and thus it profoundly influences the labor market choices of
young people in specific locations. The pace of change and media attention to
the migration of jobs to China and India only reinforces the importance of these
processes. Our understanding of positive, cumulative development processes has
progressed through various research ‘fads’, including high tech, regional innova-
tion systems, and creative learning regions. These concepts have clarified our
understanding of how regions work and how some places grow and develop
while others do not.
In a setting of relentless competition and creative destruction, it is vital that
we understand better the process of new firm formation – and of entrepreneur-
ial success more generally. New jobs, new firms, and new industries occur most
at the sites of innovation, whether they are based on R&D, new technology
(such as IT), or on management innovations. Resources found in the (local and
nonlocal) geographical environment are central to the variable chances that firms
will be able to start, thrive, and grow.
Let me pose five key questions related to geography and entrepreneurship: 
(1) Is new firm formation equally likely everywhere? The Global Entrepreneurship
Monitor (GEM) suggests that the answer is ‘no’ and that the reasons are related
to cross-national variations in culture, policy, and many other variables.
Technology-based firms and entrepreneurial universities also are part of the vari-
ation. (2) Why are some places entrepreneurial? We know a bit about successful
places and innovative milieus and their wealth of role models, venture and seed
capital, sources of ideas (universities, research), networks of interaction, cultures of
entrepreneurship, and supporting institutions. But we have many more accounts
of successful than of unsuccessful places. (3) Why are some places not so entre-
preneurial? We have hints about unsupportive industrial structure and corporate
organization, low levels of human capital, local cultures of distrust, and regula-
tion, bureaucracy and corruption. (4) How can local environments be improved,
and can governments help? Policies and politicians come and go, resulting
frequently in policies too short-lived to be a basis for long-term development.
The fifth question re-opens the black box of technology in its new guise: 
How have the Internet and the rise of the creative class affected entrepreneurial
environments? Although we know that delivering services is easier than deliver-
ing goods, the death of distance has not occurred. ‘Handshakes’ still require 
face-to-face interaction, even if ‘conversations’ do not (Storper and Venables 2004).

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The creative class and its preferences for some places rather than others may appear
to doom declining regions that cannot re-make and re-brand themselves.
The fact that not all jobs are equal – that some are unstable, have little upward
mobility, do not stimulate one’s creativity, or are otherwise unattractive in the
long run – also needs continual research. Jobs are dumbed down, divided
spatially, restructured, made redundant, replaced by computers, outsourced, and
off-shored. Although we think now that knowledge jobs will withstand
outsourcing, this might not be true.
Finally, knowledge – of all types – has grown to be essential to the character
of good jobs and to the development of regions. Untraded interdependencies,
which are essentially flows of tacit knowledge among firms, are among the most
intriguing (Storper 1997). Data on tacit knowledge flows, like those on all
untraded interdependencies and informal linkages, are impossible to track from
any secondary data sets. Painstaking empirical work is needed simply to answer
the important research questions.