The gig economy is shaped by technological, economic and political forces. It promises tremendous opportunities to create new jobs and innovative work arrangements. At the same time, it risks undermining aspects of social goals tied to traditional employment.

1. The Gig Economy
and Income Inequality
Presented by: Johannes M. Bauer
Department of Media and Information
IBEI–cetic.br/nic.br/cbi.br Summer School
Barcelona, July 3, 2018

2. The Gig Economy
and Income Inequality
Johannes M. Bauer
Department of Media and Information
IBEI–cetic.br/nic.br/cbi.br Summer School
Barcelona, July 3, 2018

3. Main points
• The gig economy is shaped by technological, economic, and political
forces
• It promises tremendous opportunities to create new jobs and
innovative work arrangements
• At the same time, it risks undermining aspects of social goals tied to
traditional employment
• Emerging technologies (autonomous vehicles, Internet of Things, AI)
will further change the nature of work and the gig economy

4. Plan for today
• Emergence and structure of the gig economy
• Basic economics of the gig economy
• The digital economy and income inequality

5. Emergence and structure of the gig economy

6. Changing modes of production and work
• Gig, sharing, and freelance economy refer to new forms of production
based on economic transactions among decentralized agents enabled by
new forms of digital intermediation (e.g. Uber, Airbnb)
• Related to other types of transactions enabled in the digital economy
• Gift economy (direct or indirect reciprocity, e.g. Couchsurfing) (Sundararajan 2016)
• Commons-based peer production (e.g. Wikipedia, Linux) (Benkler 2016)
• Crowd capitalism (e.g. AngelList for VC funding) and large-scale outsourcing
• Recently, NextGen Work is used to describe a new way of working that
helps people earn more, upskill, and achieve One Life that blends work and
home (ManpowerGroup, 2017)
• Include part-time, contingent, contract, temporary, freelance, permalance,
independent contractor, on-demand online, and online platform working

7. Technological, economic, political forces
• Enabling technologies and services
• Significant performance gains in ICTs, increasing broadband connectivity and
ubiquitous computing
• Building of digitally mediated trust among participants in a transaction
(recommender systems, provider and customer ratings, algorithms)
• Flexible and easy-to-use (mobile) payment systems
• Emerging technologies (AI, IoT, robotics) will cause additional change
• Economic transformation from pipeline to platform markets
• Platform businesses generate value by enabling transactions among other market
participants (e.g. Airbnb links owners of property with people seeking
accommodation)
• Flexibilization of labor markets, weakening of labor relations and
traditional worker protections

8. Labor and capital platforms
Source: Farrrell & Greig, 2016
“Sharing” of an
asset
“Sharing” of labor
and skills

9. Sharing economy
• Many examples of sharing throughout the history of humankind
• 1970s highlighted “collaborative consumption” (Felson & Spaeth,
1978; Botsman & Rogers, 2010)
• Vibrant range of activities have emerged, emphasizing
• Underused assets (e.g. apartments, cars, computing power)
• Monetization by sharing with others (users pay for fractional use)
• New market organization in which digital intermediaries (platforms) facilitate
efficient peer-to-peer exchanges (e.g. Uber, Lyft, Airbnb, BlaBlaCar, Luxe)
• Transactions benefit from direct and indirect network effects: the
value of the platform grows as the number of participants increases

10. Gig (on demand) economy
• Provision of services such as
• Assembling furniture (e.g.
TaskRabbit)
• Buying groceries (e.g. Shipt)
• Wrapping presents (e.g. Gift Six)
• Simple household repairs (e.g.
Handy)
• Laundry (e.g. Cleanly)
• Filling out surveys or solve other
“human intelligence tasks” (e.g.
Amazon Mechanical Turk)
• Data entry, clerical
• Translation services
• Creative and multimedia
• Initially low-skill activities but
increasingly services that require
higher skills
• Intensely competitive, with a high
(but poorly documented) failure
rate of start-ups
Source: The Economist, January 3, 2015.

11. Freelance economy
• Services or products, produced by independent contractors, that
require a higher level of skill
• Wide range of services, new intermediaries
• Software development, programming (e.g. Upwork)
• Accounting services (e.g. Gigcountant)
• Legal work (e.g. Axiom)
• Consulting (e.g. Eden McCallum)
• Medical services (e.g. Medicast, in 2016 bought by a large U.S. health service
provider, Providence St. Joseph Health)
• Individuals freelance to have greater flexibility, work from home, build
a business, exert more control over creative projects

12. Adoption across many
sectors
• Collaborative Economy Honeycomb
developed by Jeremiah Owyang, Crowd
Companies Council
• Research on 460 start-ups, 260 of which
were included
• Details and method at
http://www.web-
strategist.com/blog/2016/03/10/honey
comb-3-0-the-collaborative-economy-
market-expansion-sxsw/

13. NextGen Work and the vision of One Life
• One Life: flexible
integration of work
and home in NextGen
Work
• Widely embraced
among the young
• India, Mexico: 99%
• U.S., Spain, Australia,
Italy, UK: 90-94%
• Sweden: 85-89%
• France: 80-84%
• Germany,
Netherlands: 75-79%
• Japan 70-74%
ManpowerGroup, 2017, p. 7

14. The U.S. gig economy (narrowly interpreted)
Self-employment rate (% employed workers)
Self-employed
Employed
Paid U.S. workforce
2018 U.S. Bureau of
Labor Statistics data
• In 2017, 5.8 million
workers held
contingent jobs
(~3.8% of all workers)
• In 2017, 10.6 million
workers had
alternative work
arrangements (6.9%
of total employment)
• On-call (1.7%)
• Temporary help
agency workers
(0.9%)
• Contract agency
workers (0.6%)
Source: BLS (2018)~21% of workforce, slight decline

15. The U.S. gig economy (broadly interpreted)
Reasons for participation
Gig work by educational attainment
Source: Federal Reserve System, 2018
31% of workforce, slight increase

16. Global freelancing: Online Labor Index (OLI)
• Project by the Oxford Internet
Institute led by Vili
Lehdonwirta, focusing on
freelancing, crowdwork)
• Suggests 26% growth in
projects between July 2016
and July 2017.
• Largest employer country is
the U.S., largest labor
supplier country India.
• http://ilabour.oii.ox.ac.uk/the
-online-gig-economy-grew-
26-over-the-past-year/ for
more details
Fast growth in projects

17. Common characteristics, pros and cons
• Decentral provision of
services
• Coordinated by new digital
intermediaries
• Online mechanisms to build
trust (ratings, reputation
systems)
• Online payment systems
• High flexibility and variability
• New organization of work or
new form of outsourcing?

18. Basic economics of the gig economy

19. Frameworks
• Digital intermediation and coordination
• Reduced transaction and coordination cost shift the boundaries between
(hierarchical) firms and (decentralized) markets (Coase, 1937), expanding
market transactions
• Emergence of platform markets
• In platform markets, value is generated by facilitating transactions between
participants that would otherwise not have been able to engage in a business
relationship (Parker et al., 2016)
• Digital capitalism as a new mode of production
• Significant wealth accumulation and inequality (Piketty 2014)
• Wealth creation and extraction (Mazzucato, 2013, 2018)

20. Digital intermediation and transaction cost
Price (P)
Quantity (Q)
S
S–TC
Supply
Supply after reduction
transaction costs (cost of
negotiating, enforcing
contracts)
Reduction in
transaction costs
Demand (consumer
willingness to pay)
D
P1
P2
Q2
Q1

21. Creation of new markets
Price (P)
Quantity (Q)
S0
S0–TC
Supply (S0). In this situation transaction and other
costs are prohibitively high. The willingness to pay of
consumers is below the level needed to recover costs
Supply based on significantly
reduced transaction costs (S0-TC).
Now a market price P exists that
allows recovering costs of supply
and quantity Q is transacted
Significant reduction
in transaction costs
Demand (consumer
willingness to pay)
D
P
Q

22. Platform business models
22
Cross-side network effectsSame-side
network
effects
Platform 1
Side 1 Side 2 Side n
Platform 2
• Same-sided network effects
imply that the value of the
platform increases with the
growth of participants on one
market side
• Cross-side network effects imply
that the value of the platform
increases with the number of
complementary participants
• Combined with reduced
transaction costs this creates a
virtuous cycle of growth

23. La Ruche Qui Dit Oui! (“The Beehive that Says
Yes”) platform business model

24. Uber platform business model
Source: Henten &
Windekilde, 2016.
70-80% to
drivers
20-30% to
Uber
Pays 100%
to Uber

25. Management challenges
• Recruiting participants to the platform
• Producer side (drivers, hosts, tool owners, farmers, freelancers, artists)
• Customers (individuals needing transportation, seeking accommodations, needing
help)
• Establishing trust between participants
• Recommender systems covering all participants
• Secure payment arrangements
• Protection of privacy
• Finding a sustainable revenue model
• Low barriers to entry in many segments of the sharing economy imply
intense competition unless first-mover advantages can be secured
• Concerns about social impacts

26. Efficiency and innovation
• The gig economy has spurred many improvements in the quality and
diversity of services offered
• Ride-sharing services have put pressure on existing taxi services to improve
quality and reduce prices
• Platforms like Airbnb have diversified the supply of accommodation and
created new networks of personal relations
• Better utilization of asset capacity and time increases productivity
• Unused housing space, cars, computing power
• Flexibilization of work generates benefits for those who face other time
constraints
• Tweaking efficiency at the margin (eliminating waste) or structural gains?
• Overall effects on productivity and growth subject to further
examination

27. A virtuous cycle
• Innovation and network
effects reduce the cost of
supply S0S1S2
• Innovation and network
effects increase
willingness to pay
(demand) D0D1D2
• The market exhibits long-
run declining prices and
expanding volumes
Price (P)
Quantity (Q)
D0
D1
D2
S0
S1
S2P0
P2
Q2Q1Q0
Long-run market
development

28. Critiques of digital capitalism
• Offers a perspective critical of the digital transformation frame
advanced by the tech industry (and many policy-makers)
• Piketty and colleagues point to renewed dynamic of capitalist system
in which return on capital (r) is higher than growth in the economy
(g). With r>g, the importance of wealth will increase and inequality
will rise (Piketty & Saez, 2003; Piketty, 2014)
• Digital capitalism leads to enormous generation of wealth for firms
organizing platform markets, often based on intangible capital (e.g.
knowledge, know how) (Srnicek, 2014; Haskel & Westlake, 2017)
• Confusion of wealth extraction with wealth generation in modern
capitalism (Mazzucato, 2018)

29. The digital economy and income inequality

30. Employment and income effects
• Conflicting employment effects of the digital economy
• Creation of tremendous opportunities for new and interesting jobs
• Potentially significant loss of jobs (e.g. Osborne & Frey, 2017 find that 60% of
U.S. jobs are at risk by 2050; more recent studies find smaller negative effects)
• Change in the skill composition of the workforce (e.g. Autor, 2015)
• Whether the digital economy reduces or aggravates unemployment
and income inequality depends on
• Whether work relations can be transformed in positive ways
• How well countries transition to and participate in the digital economy
• Provision of complementary services (e.g. continuing education, universal basic
income support, infrastructure services, R&D support)

31. Disappearance of middle-skill jobs in the U.S.
“Market share” of
these jobs increased
“Market share” of
these jobs decreased
20 40 60 80 1000
1979-1989
1989-1999
2007-2012
1999-2007
Skill percentile (ranked by 1979 mean log wage) Sources: Autor (2015);
McAfee (2018)

32. … and in other countries
Source: McAfee (2018); Goos,
Manning, Salomons (2014)

33. Micro and macro dynamics of the gig economy
• At the individual (micro) level,
increased connectivity
typically goes hand in hand
with higher income
• At an aggregate (macro) level,
counteracting forces exist
• Winner-takes-all effects (first
mover advantages)
• Automation of routine jobs and
deskilling
• International mobility of work,
capital, and knowledge
• Productivity effects of ICTs
• Increased connectivity may
reduce or increase income
inequality Bauer (2017)
Individual
level of use
Individual
income
Income
inequality
Aggregate
level
Individual
level
+
+
+
+
–
Level of
use
Emergence,
Determination
Net effect?

34. Expected contribution to household income
• Empirical study by Garcia-
Murillo, MacInnes, Bauer,
& Hong (2016)
• M-Turk survey in June 2016
• N=420 individuals
• Located in the U.S.
• 18 years or older
• Explored participation in
the sharing, gig and
freelance economy
• Studied key drivers of
participation and effects
0.00
5.00
10.00
15.00
20.00
25.00
30.00
35.00
40.00
45.00
Sharing Gig Freelance
Percentofparticipants
0-25%
25-50%
50-75%
75-100%

35. Estimated actual contribution to income
Source: Farrell & Greig, 2016

36. Income
gap to
traditional
work

37. Harnessing the power of the gig economy
• New forms of digitally mediated work allow innovative models to
integrate work and other aspects of life
• Individual firms may adopt contracts with benefit options to stabilize
platform participation (e.g. Hong 2018)
• Measures at the aggregate level (labor markets, social policy, tax
policy)
• Provision of new opportunities for lifelong education and retraining
• Design of social safety nets that are not tied to traditional employment
• Minimal income policies (e.g. negative income tax, universal basic income)
• Even though societies with higher average income can accommodate
higher levels of inequality, the biggest challenge may be overcoming
persistent and rising income and wealth disparities

38. Recap of main points
• The gig economy is shaped by technological, economic, and political
forces
• It promises tremendous opportunities to create new jobs and
innovative work arrangements
• At the same time, it risks undermining aspects of social goals tied to
traditional employment
• Emerging technologies (autonomous vehicles, Internet of Things, AI)
will further change the nature of work and the gig economy

39. References
• Autor, D. H. (2015). Why are there still so many jobs? The history and future of workplace automation. Journal of Economic
Perspectives, 29(3), 3-30.
• Bauer, J. M. (2017). The Internet and income inequality: Socio-economic challenges in a hyperconnected society.
Telecommunications Policy. doi:10.1016/j.telpol.2017.05.009. Published online 16 June 2017.
• Benkler, Y. (2016). Peer production and cooperation. In J. M. Bauer & M. Latzer (Eds.), Handbook on the economics of the Internet
(pp. 91-119). Cheltenham, UK; Northampton, MA: Edward Elgar.
• Botsman, R., & Rogers, R. (2010). What's mine is yours: The rise of collaborative consumption. New York: Harper Business.
• BLS. (2018). Contingent and alternative employment arrangements. Washington, DC: United States Department of Labor, Bureau
of Labor Statistics.
• Coase, R. H. (1937). The nature of the firm. Economica N.S., 4(16), 386-405.
• Eubanks, V. (2017). Automating inequality: How high-tech tools profile, police, and punish the poor. New York: St. Martin's Press.
• Farrell, D., & Greig, F. (2016). Paychecks, paydays, and the online platform economy. New York: J.P. Morgan Chase & Co. Institute.
• Federal Reserve System. (2018). Report on the economic well-being of U.S. households in 2017-2018. Washington, DC, Board of
the Governors of the Federal Research System.
• Felson, M., & Spaeth, J. L. (1978). Community structure and collaborative consumption: A routine activity approach. American
Behavioral Scientist, 21(4), 614-624.
• Garcia-Murillo, M., MacInnes, I., Bauer, J. M., & Hong, S. J. (2016). Individual to individual services and the future of work. Paper
presented at the 2016 Biennial Conference of the International Telecommunications Society (ITS) Taipei, Taiwan.

40. References …
• Goos, M., Manning, A. & Salomons, A. (2014). Explaining job polarization: Routine-biased technological change and
offshoring. American Economic Review, 104(8): 2509-2526.
• Haskel, J., & Westlake, S. (2017). Capitalism without Capital. Princeton, NJ; Oxford, UK: Princeton University Press.
• Henten, A., & Windekilde, I. M. (2016). Transaction costs and the sharing economy. Info, 18(1), 1-15.
• Hong, S.J. (2018). Effects of flexibility and stability on the decision to work for ride-sharing services. Ph.D. Dissertation,
Department of Media and Information, Michigan State University, USA.
• McAfee, A. (2018). Technology, jobs and wages. Paper presented at the Summit on Technology and Jobs, Washington, D.C.
• McAfee, A., & Brynjolfsson, E. (2017). Machine, platform, crowd: Harnessing our digital future. New York: W. W. Norton &
Company.
• Manpower Group. (2017). #Gig Responsibility: The Rise of NextGen Work. Milwaukee, WI: Manpower Group.
• Mazzucato, M. (2013). The entrepreneurial state: Debunking public vs. private sector myth. London: Anthem Press.
• Mazzucato, M. (2018). The value of everything: Making and taking in the global economy: Allen Lane.
• Parker, G. G., Van Alstyne, M. W., & Choudary, S. P. (2016). Platform Revolution: How Networked Markets Are Transforming
the Economy--And How to Make Them Work for You. New York: W.W. Norton.
• Piketty, T. (2014). Capital in the twenty-first century. Cambridge, MA: The Belknap Press of Harvard University Press.

41. References …
• Srnicek, N. (2017). Platform capitalism. Malden, MA: Polity Press.
• Sundararajan, A. (2016). The sharing economy: The end of employment and the rise of crowd-based capitalism. Cambridge,
MA: MIT Press.

42. Johannes M. Bauer
Professor and Chairperson
Department of Media and Information
Michigan State University, East Lansing, MI 48824, USA
bauerj@msu.edu, +1.517.944.4154
http://www.msu.edu/~bauerj
42