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Digital Transformation: A force for a better world?

Alumni Forum Europe 2017

Technology and Inequality: reasons for concern, reasons for

optimism Mark Stabile

Stone Chaired Professor of Wealth Inequality Professor of Economics

INSEAD



Outline

• What’s the inequality problem?

• What’s worked in the past and what’s not working now?

• What’s going to happen next?

• How do we think about inequality and digital transformation?



The Global Financial Crisis & Recovery

-8

-6

-4

-2

0

2

4

6

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

Real GDP Growth Rates

Japan United Kingdom United States EU-27



Recovery has not been equal…

0%

20%

40%

60%

80%

100%

120%

19

49

-53

19

54

-57

19

58

-60

19

61

-69

19

70

-73

19

75

-79

19

82

-90

19

91

-00

20

01

-07

20

09

-12

20

09

-13

Pe

rce

nt

Source: Authors calculations based on data from The World Wealth and Income database

United States: Distribution of Average Income Growth during Periods of Expansions - Bottom 99: Top 1 [1949-2013]

Bottom 99 Top 1



0

0,05

0,1

0,15

0,2

0,25

0,3

19

13

19

16

19

19

19

22

19

25

19

28

19

31

19

34

19

37

19

40

19

43

19

46

19

49

19

52

19

55

19

58

19

61

19

64

19

67

19

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19

73

19

76

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79

19

82

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85

19

88

19

91

19

94

19

97

20

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20

03

20

06

20

09

20

12

20

15

Pe

rce

nt

Top 1% Income Shares in the US with and without Capital Gains [1913-2013]

Top 1% Income Share-Capital Gains Excluded Top 1% Income Share-Capital Gains Included

Source: Author’s calculations using World Wealth and Income Database


Alumni Forum Europe 2017 Author’s calculations from WWI database

0%

2%

4%

6%

8%

10%

12%

14%

16%

18%

19

51

19

53

19

55

19

57

19

59

19

61

19

63

19

65

19

67

19

69

19

71

19

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75

19

77

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79

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81

19

83

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19

87

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19

93

19

95

19

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19

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20

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20

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20

05

20

07

20

09

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11

20

13

Top

1%

Inco

me

Sh

are

, Pe

rce

nt

Data from OECD Stat and The World Wealth and Income Database

UK-Top 1% Income Share [1951-2013]

UK-Top 1% income share-married couples & single adults

UK-Top 1% income share-adults



0%

5%

10%

15%

20%

25%

1915

1917

1919

1921

1923

1925

1927

1929

1931

1933

1935

1937

1939

1941

1943

1945

1947

1949

1951

1953

1955

1957

1959

1961

1963

1965

1967

1969

1971

1973

1975

1977

1979

1981

1983

1985

1987

1989

1991

1993

1995

1997

1999

2001

2003

2005

2007

2009

2011

2013

Top1%

IncomeSh

are,Pe

rcen

t

DatafromOECDStatandTheWorldWealthandIncomeDatabase

France- Top1%IncomeShareandGini[1915-2011]

France- Top1%incomeshare



Why the rise?

• Combination of market forces and policy choices

– Increased globalization

– A decline in top marginal tax rates

– Changes in bargaining and political power

– Skill bias technological change and the return to labor



Connecting inequality and social mobility

• Does the “American Dream” still exist?



Mobility in the OECD

Intergenerational income elasticities among men

Larger number means less mobility



The Fading American Dream

Chetty et al (2016)



Corak, 2011

Larger number means less mobility

Corak, 2013



Recent responses to inequality coupled with stagnant

growth in the middle

• We are seeing movement away from traditional public policy responses toward protest oriented responses.

• People feel insecure (economically and physically) and are reacting to that insecurity.

• Occupy movement • Brexit • Trump • The growth of far right political parties • What’s next?



Is Business A Force for Good?

Source: Branko Milanovic

Change in real income between 1988 and 2005 (in 2005 international dollars)

Rise of the 1%

Decline of the middle class in rich countries India

China … catch-up

The very poor





Technology and Inequality

• What’s the connection between technology and inequality?

• Skill-biased technological change explanation from above.

• Does well at explaining some periods. Not others.



Technological changes over the past century

Source: Card and Dinardo, 2002



“The race between education and technology”

Source: Acemoglu and Autor, 2012



Up to 1.2 billion workers automated?



McKinsey, 2016



“We are being afflicted with a new disease of which some readers may not have heard the name, but of which they will hear a great deal in the years to come — namely, technological unemployment.”

Keynes, 1930



Employment growth is greater when there are more job titles…

Acemoglu and Restrepo, 2016



But how does this effect inequality?

• If new tasks are more complex, they will favor high skilled workers, leaving others behind.

• If, over time, these skills become more available to all workers, there will then be catch up (e.g. computers).

• But… “over time” is a key part of the analysis.

• The same people that are currently losing work are not (for the most part) the ones that will get the new jobs.



So what do we do?

• Innovation and transformation will, of course, continue. • Some will (hopefully) even help instead of hurt inequality. • Need to couple this with interventions that will preserve innovation while managing

inequality and labor market disruption. – Basic income – Changes in education – Redistribution (both to curb inequality and to fund the above)



Thank you.

Mark Stabile

Stone Chaired Professor in Wealth Inequality and Professor of Economics

[email protected]

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