apidays New York 2022 - Beyond API Regulations for Finance, Insurance, and Healthcare
July 27 & 28, 2022
How have publicly traded firms benefited from APIs?
Jonathan Hersh, Economist and Researcher at Chapman University
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apidays New York 2022 - How have publicly traded firms benefited from APIs?, Jonathan Hersh, Chapman University
1. How APIs Create Growth for Firms
Jonathan Hersh
Argyros School of Business
Chapman University
WorkHelix â Weâre hiring!
@DogmaticPrior
Marshall Van Alstyne
Boston University
Questrom School of Business
MIT Initiative on the Digital Economy
@InfoEcon
A Primer on Convincing Your CEO to
Adopt APIs for Fun and Profit
Seth Benzell
Argyros School of Business
Chapman University
Stanford HAI Digital Economy Lab
@SBenzell
âHow APIs Create Growth by Inverting the Firmâ
R&R Management Science
https://tinyurl.com/economyAPI
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3. How does an economist
think about APIs?
⢠Improve internal communication +
programming efficiency
⢠Traditional âpipelineâ firm productivity
⢠Recruit outsiders to create
complementary products
⢠The âInverted Firmâ (Parker et al.,
2016)
⢠The third parties that develop
complementary products using the
apps also benefit
4. In the process we will answer these questions
⢠How do we know APIs add value?
⢠Causal identification problem: would the firm have grown
without them?
⢠If they work, how do they add value to a firm?
⢠Improve communica�on and ⏠programmer efficiency? OR do
they invert the firm?
⢠What risks do APIs pose for firms?
⢠⏠Hack risk? If so how? How do firms respond?
5. Outline
1. Introduction
2. Mapping the Digital Economy with APIs
3. Measuring How Much Firms Benefit from APIs
4. How do APIs add value? Invert the firm or make programmers more
efficient?
5. Estimated Hack Risks of APIs
6. Conclusion
6. Data Sources
⢠Public API data: ProgrammableWeb â
Wikipedia for APIs
⢠Crowdsourced data on all APIs in use
⢠Data on firms: Compustat.
⢠80k publicly traded firms
⢠Private API data
⢠Data on only internal API firm use
⢠Privacy Rights Clearinghouse
⢠Disclosed data breaches
7. ProgrammableWeb API Network
⢠Programmable web tracks ~25k APIs
⢠Lists date of API opening, developers for each
API, technical specs and âfollowersâ or fans of an
API
⢠We can match these APIs back to firms and see
the evolution of which firms have APIs
⢠Each dot is a firm, each connection is an app that
connects two APIs
⢠âMap of the digital economyâ
8. API Network in 2005
⢠Dot: Firmâs API
⢠Connection: App
connecting APIs
9. API Network in 2006
⢠Dot: Firmâs API
⢠Connection: App
connecting APIs
10. API Network in 2007
⢠Dot: Firmâs API
⢠Connection: App
connecting APIs
11. API Network in 2008
⢠Dot: Firmâs API
⢠Connection: App
connecting APIs
12. API Network in 2009
⢠Dot: Firmâs API
⢠Connection: App
connecting APIs
13. API Network in 2010
⢠Dot: Firmâs API
⢠Connection: App
connecting APIs
14. API Network in 2011
⢠Dot: Firmâs API
⢠Connection: App
connecting APIs
15. API Network in 2012
⢠Dot: Firmâs API
⢠Connection: App
connecting APIs
16. API Network in 2013
⢠Dot: Firmâs API
⢠Connection: App
connecting APIs
17. API Network in 2017
⢠Dot: Firmâs API
⢠Connection: App
connecting APIs
18. API Network By Industry
⢠Dot: Firmâs API
⢠Connection: App
connecting APIs
20. API Network in 2015
⢠Dot: Firmâs API
⢠Connection: App
connecting APIs
21. Average API Use by Industry, Publicly Traded Companies Q3 2020
⢠Growing but low public API
use across publicly traded
firms.
22. Average API Use by Industry, Publicly Traded Companies Q3 2020
⢠Many industries have < 2%
public API use
23. Measuring Impact of Opening APIs on Firm Stock Price
⢠Merge APIs (from ProgrammableWeb) with
COMPUSTAT record of all publicly traded firms.
⢠Estimate two-way fixed effect models:
đđđđđđ đđđđđđđđ đđđđđđđđđđđđ đŁđŁđŁđŁđŁđŁđŁđŁđđ đđ,đĄđĄ = ďż˝
đđ
đ˝đ˝đđđ´đ´đ´đ´đźđź đđ,,đđ,đĄđĄ + đźđźđđ + đžđžđĄđĄ + đđ đđ,đĄđĄ
đźđźđđ = control for firm characteristics
đžđžđđ control for time shocks
đ˝đ˝đđ impact of API opening k periods
before/after API opening
24. ⢠Firms that open APIs
have a 38.7% larger
stock value, compared
to firms that do not
⢠This is true even for
smaller firms or non
computer services firms
Impact of API Opening On Firm Stock Price
25. Synthetic Control
⢠Okay, but firms that open APIs are
different from those that donât.
⢠(They have super smart that attend
this conference.)
⢠Synthetic Control analysis builds
statistical counterfactuals for each
API firm, comparing it to a set of
hypothetical non-API firms
⢠Still impact of APIs is large and
positive.
⢠Cumulative average difference in
stock price is $8.4B after 20
quarters
26. Does having a more popular API matter?
⢠Yes!
⢠Firms with more API
connections grew
faster than those
with fewer
⢠Supported by causal
instrumental variable
analysis â
instrument for API
centrality using
deprecated APIs
27. How do APIs Increase Firm Value
⢠Okay, you win, firms that use APIs have higher
stock prices
⢠How do they do that?
Two hypotheses
1. Improve internal communication + programming efficiency
â Traditional âpipelineâ firm productivity
2. Recruit outsiders to create complementary products
â The âInverted Firmâ (Parker et al., 2016)
â The third parties that develop complementary products using the
apps also benefit
28. No impact on market value from internal only APIs
29. Outside-firm engagement drives all market value increases
⢠More outside partners
â more value
generated
⢠APIs make it easy for
smart people outside
your firm to add value
⢠Takeaway: Make it
seamless for them to
do so!
30. API Firms grow in excess of capital/asset deployed
⢠If we control for
amount of assets a
firm deploys, APIs
still have a large
impact.
⢠APIs donât just help
a firm scale
⢠Takeaway: APIs
are a great use of
capital for firms!
32. Increased hack risk 2 years post API opening
⢠Firms 6-7 times
more likely to be
hacked in the
two years after
opening an API!
⢠Path of attack
via âmalicious
insiderâ
35. In the months after a hack, firms increase testing and login
authorization APIs
36. Conclusions
⢠Public firms adopting public APIs grew much faster than similar
counterparts from 2007-2020
⢠Correlational and IV evidence shows that public firms with more
central APIs in the API network grew faster than those with less
central APIs
⢠Much less evidence of an internal productivity effect, suggesting
most benefits are due to âfirm inversionâ
⢠Some evidence of increased vulnerability to hacks
37. People
⢠Jonathan Hersh, Argyros School of Business and Economics, Chapman
University â hersh@chapman.edu
⢠Marshall Van Alstyne, Boston University Questrom School of Business
â mva@bu.edu
⢠Seth Benzell, Argyros School of Business and Economics, Chapman
University â benzell@chapman.edu
⢠https://tinyurl.com/economyAPI
Comments, Questions or Suggestions
38. Instructor
Jonathan Hersh, PhD - hersh@chapman.edu
Teaching Assistants:
Joshua Anderson
Cady Stringer
Sam Webster
37
⢠Assistant Professor, Chapman University
Argyros School of Business
⢠Education: PhD in economics, Boston
University, M.Sc. Wharton, BA U Chicago
⢠Work experience: Principal Machine Learning
Scientist at Workhelix, Data Scientist for the
World Bank, economic consultant, and
developer
⢠Research: Economics of information systems,
computer vision and applied machine
learning
39. 38
Research Overview
⢠Satellite Imagery + Computer
Vision + Machine Learning
Count cars in
parking lots!
Damaged
buildings in
Syria!
https://www.pnas.org/content/118/23/e2025400118