policymakers demonstrate

Developments in Data for Economic Research 601
variables one would ideally want. Their format may not be optimized for
research use, and in fact can rapidly change over time as internal IT systems
are upgraded. The data may not be kept for a long time, reducing the potential
time-span that one can study. Documentation is occasionally poor. Last but not
least, they can be highly sensitive for the firm.
This means that access to these data tends to be more effort intensive, and
involve a longer and riskier process than other sources of data. 19 Relationships
are crucial here. Successful projects have often had a cheer-leader inside the
firm. Relationships are crucial at the beginning of the project because a minimum
level of trust needs to be established between the researchers and the
firm giving them access to its data. They are crucial during the project because
the firm will often need to continue to devote time and internal resources to
provide access to the data, explain the data, and/or extract additional data, and
because preliminary results may force the researchers and the firm to reorient
the research question. Finally, they are crucial at the end of the project because
the firm will often request to first clear the paper before it is circulated publicly.
Data-driven firms are special in the context of private-sector collaborations
with researchers. Data form the core of their business and they already make
heavy use of data scientists to put them to good use. However, they are often
interested in research that can help better harness the power of their data and
inform the design of their products. To foster research on questions of relevance
for them, many of these firms – including Microsoft, Yahoo! and eBay – have
experimented over time with different forms of engagement with researchers.
This has gone from sponsoring papers and conferences on selected themes to
establishing their own research labs that recruit economists on the academic
job market and have a visitor programme to encourage academic economists
to work on issues of relevance to them. Athey and Mobius (2012), Celis et al.
(2014), and Blake et al. (2015) are examples of empirical research papers that
have grown out of these collaborations.
An interesting aspect of these data-intensive firms is their ability to experiment
with different product designs or prices easily and at a low cost. In fact,
many online platforms already routinely carry out experiments on a small share
of their operations and then implement the successful ones. It is a small step
to the development of carefully crafted field experiments for research purposes
(in the spirit of RCTs discussed in Section 13.5). Blake et al. (2015) designed
such an experiment to measure the returns on paid keyword search in search
engines and found them to be much lower than previously understood.
13.6.2 New Public-Sector Collaborations in Economic Research
New forms of collaborations are also developing between academics and
policy-makers. The drivers there are different: this is not just about greater data