why has inequality been rising? · second, growth of inequality in mexico • followed a period of...

Why Has Inequality Been Rising? (based on work with M. Kremer)

E. Maskin

I.S.E.O. Summer School June 2017

2

• In last 30 years, significant increase in income inequality

3

• In last 30 years, significant increase in income inequality – in many rich countries (including U.S.)

4

• In last 30 years, significant increase in income inequality – in many rich countries (including U.S.) – in many poor countries (including India and

Mexico)

5


Mexico) • referring here to inequality increases within

countries

6



countries – inequality has been falling across countries

7



countries – inequality has been falling across countries – many poor countries (especially India and

China) are catching up

8



countries – inequality has been falling across countries – many poor countries (especially India and

China) are catching up • Increases are theoretically puzzling

9

First, take inequality increase in U.S.

10

First, take inequality increase in U.S. • well accepted relationship

11

First, take inequality increase in U.S. • well accepted relationship wage education/training (skill) ↔

12

First, take inequality increase in U.S. • well accepted relationship wage education/training (skill) • dispersion of skill has risen in U.S. (also the

median)

↔

13


median) • but not nearly so much as dispersion in income

↔

14



– holding wage as a function of skill fixed, shift in skill distribution explains only 20% of increase in income dispersion between 1980 and 2000

↔

15




– but wage schedule not fixed

↔

16




– but wage schedule not fixed • Why not?

↔

17

• One popular answer: skill-biased technological change

18

• One popular answer: skill-biased technological change – technology biased in favor of high skills

19

• One popular answer: skill-biased technological change – technology biased in favor of high skills – marginal product of high-skill workers enhanced their wages rise relative to low-skill workers’ wages

⇒

20


• Objection:

⇒

21


• Objection: – difficult to measure such technological change

⇒

22


• Objection: – difficult to measure such technological change – rather complicated theory

⇒

23



• Propose a different (simpler) theory based on matching

⇒

24



• Propose a different (simpler) theory based on matching – firm matches workers of different skills to produce output

⇒

25



• Propose a different (simpler) theory based on matching – firm matches workers of different skills to produce output – as skill dispersion and median increase, pattern of matching

between workers of different skills within firm changes

⇒

26




between workers of different skills within firm changes – can induce even bigger increase in income dispersion

⇒

27




between workers of different skills within firm changes – can induce even bigger increase in income dispersion – leads to greater relative segregation of skill within firms

⇒

28

• This last prediction is novel to our theory: variation of skills within firm falls relative to

variation across firms

29


variation across firms • Illustrative examples

30



– General Motors: typical large firm of generation ago mixed high-skill labor (engineers) with low-skill labor (assembly-line workers)

31



– General Motors: typical large firm of generation ago mixed high-skill labor (engineers) with low-skill labor (assembly-line workers) – typical firms of today:

32



– General Motors: typical large firm of generation ago mixed high-skill labor (engineers) with low-skill labor (assembly-line workers) – typical firms of today: Microsoft (mainly high-skill) and

33



– General Motors: typical large firm of generation ago mixed high-skill labor (engineers) with low-skill labor (assembly-line workers) – typical firms of today: Microsoft (mainly high-skill) and McDonald’s (mainly low-skill)

34



– General Motors: typical large firm of generation ago mixed high-skill labor (engineers) with low-skill labor (assembly-line workers) – typical firms of today: Microsoft (mainly high-skill) and McDonald’s (mainly low-skill)

• segregation prediction borne out by evidence for U.S., U.K., and France

35

Second, growth of inequality in Mexico

36

Second, growth of inequality in Mexico • followed a period of liberalized trade

37


– Mexico joined GATT in 1985

38


– Mexico joined GATT in 1985 – in 2 years average tariffs fell by 50%

39


– Mexico joined GATT in 1985 – in 2 years average tariffs fell by 50% – FDI quadrupled

40



• white-collar wages increased by 16%

41



• white-collar wages increased by 16% • blue-collar wages fell by 14%

42



• white-collar wages increased by 16% • blue-collar wages fell by 14% • globalization (increase in trade) aggravated

inequality

43

Contradicts Heckscher-Ohlin theory

44

Contradicts Heckscher-Ohlin theory • Mexico has comparative advantage in low-skill labor

45

Contradicts Heckscher-Ohlin theory • Mexico has comparative advantage in low-skill labor • in autarky,

46


– high-skill labor in short supply, so commands especially high wage

47


– high-skill labor in short supply, so commands especially high wage – low-skill labor paid correspondingly poorly

48



• opposite true in U.S.:

49



• opposite true in U.S.: – high-skill labor gets comparatively low wage

50



• opposite true in U.S.: – high-skill labor gets comparatively low wage – low-skill labor paid comparatively well

51




• after trade opened, factor prices should equalize

52




• after trade opened, factor prices should equalize – high-skill wages in Mexico should fall

53




• after trade opened, factor prices should equalize – high-skill wages in Mexico should fall – low-skill wages in Mexico rise

54




• after trade opened, factor prices should equalize – high-skill wages in Mexico should fall – low-skill wages in Mexico rise

• trade should decrease inequality in Mexico

55

• Will argue that same matching model explains Mexico’s higher inequality

56

• Will argue that same matching model explains Mexico’s higher inequality

• But first return to inequality in U.S. (also U.K. and France)

57

• 1-good economy

58

• 1-good economy • good produced by competitive firms

59

• 1-good economy • good produced by competitive firms • labor only input

60

• 1-good economy • good produced by competitive firms • labor only input • labor comes in 3 skill levels q L < M < H

61

• 1-good economy • good produced by competitive firms • labor only input • labor comes in 3 skill levels q L < M < H • proportion of workers having skill q

( )p q =

62

All firms have same production process

63

All firms have same production process • 2 tasks

64


– one “managerial” - - sensitive to skill level

65


– one “managerial” - - sensitive to skill level – one “subordinate” - - less sensitive to skill output = 2

s mq q

66


– one “managerial” - - sensitive to skill level – one “subordinate” - - less sensitive to skill output =

• formula incorporates 3 critical features

2s mq q

67



• formula incorporates 3 critical features (i) workers of different skills imperfect substitutes

2s mq q

68



• formula incorporates 3 critical features (i) workers of different skills imperfect substitutes (ii) different tasks within firm complementary

2s mq q

69



• formula incorporates 3 critical features (i) workers of different skills imperfect substitutes (ii) different tasks within firm complementary (iii) different tasks differentially sensitive to skill

2s mq q

70

(i) workers of different skills imperfect substitutes

71


• if perfect substitutability, q-worker (worker of skill q) can be replaced by 2 -workers

2q

72



• so, no prediction about skill levels in firm - - no segregation

2q

73



• so, no prediction about skill levels in firm - - no segregation • q-worker always paid twice as much as -worker

2q

2q

74



• so, no prediction about skill levels in firm - - no segregation • q-worker always paid twice as much as -worker

– so inequality between q-worker and -worker can’t increase

2q

2q

2q

75

(ii) different tasks complementary

76

(ii) different tasks complementary • if instead

77


( ) ( )output s mf q g q= +

78


optimal choice of independent of that of


sq mq

79


optimal choice of independent of that of • so again no prediction about combination of

skill levels in firm


sq mq

80

(iii) different tasks differentially sensitive to skill

81

(iii) different tasks differentially sensitive to skill • if instead

82


output ,s mq q=

83


get complete segregation of skill:

output ,s mq q=

s mq q=

84



– fully assortative matching

output ,s mq q=

s mq q=

85



– fully assortative matching • differential sensitivity

output ,s mq q=

s mq q=

2output s mq q=

86




– still have some assortative matching

output ,s mq q=

s mq q=

2output s mq q=

87




– still have some assortative matching – also have second force

output ,s mq q=

s mq q=

2output s mq q=

88




– still have some assortative matching – also have second force

output ,s mq q=

s mq q=

implies m sq q>

2output s mq q=

89

Competitive equilibrium

90

Competitive equilibrium • wage schedule ( )w q∗

91

Competitive equilibrium • wage schedule • matching rule

( )w q∗

92


( ), equilibrium fraction of matches with , s m

q qq q q q

π ′ =

′= =

( )w q∗

93


( )

( )( ) ( )2

, ,, arg max , (output maximized)

q qq q q q

ππ π∗

⋅ ⋅ ′

′ ′⋅ ⋅ = ∑


q qq q q q

π ′ =

′= =

( )w q∗

94


( )

( )( ) ( )2


q qq q q q

ππ π∗

⋅ ⋅ ′

′ ′⋅ ⋅ = ∑


q qq q q q

π ′ =

′= =

( )w q∗

( ) ( ) ( )2 0q q w q w q∗ ∗′ ′− − ≤

95


( )

( )( ) ( )2


q qq q q q

ππ π∗

⋅ ⋅ ′

′ ′⋅ ⋅ = ∑


q qq q q q

π ′ =

′= =

( )w q∗

( ) ( ) ( )2 0q q w q w q∗ ∗′ ′− − ≤

( ) equality if , 0 (no profit in equilibrium)q qπ ∗ ′− >

96

suppose

97

suppose

( ) ( ) ( ) 13p L p M p H= = =

98

suppose

claim: if low dispersion ( 2 ), thenH L<

( ) ( ) ( ) 13p L p M p H= = =

99

suppose

( ) ( ) ( ) 13, , ,L M L H M Hπ π π∗ ∗ ∗= = =


( ) ( ) ( ) 13p L p M p H= = =

100

suppose

•

( ) ( ) ( ) 13, , ,L M L H M Hπ π π∗ ∗ ∗= = =


( ) ( ) ( ) 13p L p M p H= = =

3 2 2>

101

suppose

• • so

( ) ( ) ( ) 13, , ,L M L H M Hπ π π∗ ∗ ∗= = =


( ) ( ) ( ) 13p L p M p H= = =

3 2 2>3 3 34 2 2 , and soL L L> +

102

suppose

• • so

( ) ( ) ( ) 13, , ,L M L H M Hπ π π∗ ∗ ∗= = =


( ) ( ) ( ) 13p L p M p H= = =

3 2 2>3 3 34 2 2 , and soL L L> +

2 3 3(1) 2LM L M> +

103

suppose

• • so

• if then

( ) ( ) ( ) 13, , ,L M L H M Hπ π π∗ ∗ ∗= = =


( ) ( ) ( ) 13p L p M p H= = =

( ), 0 ( -workers "self-matched")L L Lπ ∗ >

3 2 2>3 3 34 2 2 , and soL L L> +

2 3 3(1) 2LM L M> +

104

suppose

• • so

• if then

( ) ( ) ( ) 13, , ,L M L H M Hπ π π∗ ∗ ∗= = =


( ) ( ) ( ) 13p L p M p H= = =

( ), 0 ( -workers "self-matched")L L Lπ ∗ >

( ), 0 from (1)M Mπ ∗ =

3 2 2>3 3 34 2 2 , and soL L L> +

2 3 3(1) 2LM L M> +

105 105

− +

( ) 2 3 3 similarly, , 0 because 2 H H LH L Hπ ∗ = >

106 106

− + − hence,


( ) , 0M Hπ ∗ >

107 107

− + − hence, − but


( ) , 0M Hπ ∗ >2 2 3 2 , contradictionLM LH L MH+ > +

108 108

− + − hence, − but • hence,

( ) ( ) ( ) , 0; similarly , , 0L L M M H Hπ π π∗ ∗= = =



109 109

− + − hence, − but • hence, • +




( ) ( )2 ,LM w L w M∗ ∗=

110 110





( ) ( )2 ,LM w L w M∗ ∗=

( ) ( )2 ,LH w L w H∗ ∗= +

111 111





( ) ( )2 ,LM w L w M∗ ∗=

( ) ( )2 ,LH w L w H∗ ∗= +

( ) ( )2MH w M w H∗ ∗= +

112

•

( )2 2 2

2LM LH MHw L∗ + −

=

113

•

( )2 2 2


=

( )2 2 2

2LM MH LHw M∗ + −

=

114

•

( )2 2 2


=

( )2 2 2


=

( )2 2 2

2LH MH LMw H∗ + −

=

115

•

• Notice

( )2 2 2


=

( )2 2 2


=

( )2 2 2


=

( ) ( )0 0w L w H

M M

∗ ∗∂ ∂> <

∂ ∂

116

•

• Notice Proposition 1: Starting from low skill dispersion, ,

increase in median skill reduces inequality in wages (and raises mean and median wage)

( )2 2 2


=

( )2 2 2


=

( )2 2 2


=

( ) ( )0 0w L w H

M M

∗ ∗∂ ∂> <

∂ ∂

2 H L<

117

But opposite occurs if skill distribution dispersed

118

But opposite occurs if skill distribution dispersed – claim: this what happened in U.S., U.K., and France

119


Proposition 2: Starting from sufficiently dispersed skill distribution

increase in median inequality:M magnifies( )34

3 2 and ,M L H M> >

120



increase in median inequality:M magnifies

( ) ( )0 and 0,w L w H

M M

∗ ∗∂ ∂≤ ≥

∂ ∂

( )343 2 and ,M L H M> >

121



and if either L-workers or M-workers not self-

matched, at least one equality strict

increase in median inequality:M magnifies

( ) ( )0 and 0,w L w H

M M

∗ ∗∂ ∂≤ ≥

∂ ∂

( )343 2 and ,M L H M> >

122

Proof: Suppose

( ) ( ) ( ) 315 5p L p H p M= = =

123

Proof: Suppose (2)

( ) ( ) ( ) 315 5p L p H p M= = =

2 3 3 2 3 32 2LM L M MH M H> + > +

124

Proof: Suppose (2)

•

( ) , 0 because L H H Lπ ∗ = >>

( ) ( ) ( ) 315 5p L p H p M= = =

2 3 3 2 3 32 2LM L M MH M H> + > +

125

Proof: Suppose (2)

•

•

( ) , 0 because L H H Lπ ∗ = >>

( ) ( ) ( ) 315 5p L p H p M= = =

2 3 3 2 3 32 2LM L M MH M H> + > +

* * ( , ) = ( , ) = 0 from (2)L L H Hπ π

126

Proof: Suppose (2)

•

•

•

( ) , 0 because L H H Lπ ∗ = >>

( ) ( ) ( ) 315 5p L p H p M= = =

( ) ( ) ( )2 15 5, , ,L M M H M Mπ π π∗ ∗ ∗= = =

2 3 3 2 3 32 2LM L M MH M H> + > +

* * ( , ) = ( , ) = 0 from (2)L L H Hπ π

127

Proof: Suppose (2)

•

•

•

•

( ) , 0 because L H H Lπ ∗ = >>

( ) ( ) ( ) 315 5p L p H p M= = =

( )3

(from self-matching)2

Mw M∗ =

( ) ( ) ( )2 15 5, , ,L M M H M Mπ π π∗ ∗ ∗= = =

2 3 3 2 3 32 2LM L M MH M H> + > +

* * ( , ) = ( , ) = 0 from (2)L L H Hπ π

128

Proof: Suppose (2)

•

•

•

• •

( ) , 0 because L H H Lπ ∗ = >>

( ) ( ) ( ) 315 5p L p H p M= = =

( )3


Mw M∗ =

( ) ( ) ( )2 15 5, , ,L M M H M Mπ π π∗ ∗ ∗= = =

( ) ( )3 3

2 2,2 2

M Mw L LM w H MH∗ ∗= − = −

2 3 3 2 3 32 2LM L M MH M H> + > +

* * ( , ) = ( , ) = 0 from (2)L L H Hπ π

129

Proof: Suppose (2)

•

•

•

• •

•

( ) , 0 because L H H Lπ ∗ = >>

( ) ( ) ( ) 315 5p L p H p M= = =

( )3


Mw M∗ =

( ) 243

32 0, since 2

w L MLM M LM

∗∂= − < >

∂

( ) ( ) ( )2 15 5, , ,L M M H M Mπ π π∗ ∗ ∗= = =

( ) ( )3 3

2 2,2 2

M Mw L LM w H MH∗ ∗= − = −

2 3 3 2 3 32 2LM L M MH M H> + > +

* * ( , ) = ( , ) = 0 from (2)L L H Hπ π

130

Proof: Suppose (2)

•

•

•

• •

•

•

( ) , 0 because L H H Lπ ∗ = >>

( ) ( ) ( ) 315 5p L p H p M= = =

( )3


Mw M∗ =

( ) 243

32 0, since 2

w L MLM M LM

∗∂= − < >

∂

( ) ( ) ( )2 15 5, , ,L M M H M Mπ π π∗ ∗ ∗= = =

( ) ( )3 3

2 2,2 2

M Mw L LM w H MH∗ ∗= − = −

( ) 22 3

23 0, since

2w H MH H M

M

∗∂= − > >

∂

2 3 3 2 3 32 2LM L M MH M H> + > +

* * ( , ) = ( , ) = 0 from (2)L L H Hπ π

131

Segregation

132

Segregation Index of relative segregation

133


,BB W

ρ =+

134


B = skill variation between firms

,BB W

ρ =+

135


B = skill variation between firms

( ) ( )2

2 - , mean skill in populationq q

q qq qµ π µ′+ ∗

′

′= =∑∑

,BB W

ρ =+

136


B = skill variation between firms W = skill variation within firms

( ) ( )2



′

′= =∑∑

,BB W

ρ =+

137


B = skill variation between firms W = skill variation within firms

( ) ( )2



′

′= =∑∑

,BB W

ρ =+

( ) ( )2 *2 ,q q

q qq q qπ′+

′

′= −∑∑

138

Proposition 2: Suppose

139


( ) ( ) ( ) ( ) mean skillp L p M M p H H M M+ + = =

140


If dispersion of skills big enough, i.e.,


141


If dispersion of skills big enough, i.e.,

1 52

H L +

>


142


If dispersion of skills big enough, i.e., then mean-preserving spread in distribution increases

segregation index

1 52

H L +

>


ρ

143

Proof: Suppose

( ) ( ) ( )1 13 32, 3, 4 and 2L M H p L p H p Mε ε= = = = = + = −

144

Proof: Suppose

•

2 3 2 3Then 2 2MH L LM H+ > +

( ) ( ) ( )1 13 32, 3, 4 and 2L M H p L p H p Mε ε= = = = = + = −

145

Proof: Suppose

• • So

2 3 2 3Then 2 2MH L LM H+ > +

( ) ( ) ( )1 13 32, 3, 4 and 2L M H p L p H p Mε ε= = = = = + = −

( ) 1 16 2,L Lπ ε∗ = +

146

Proof: Suppose

• • So

2 3 2 3Then 2 2MH L LM H+ > +

( ) ( ) ( )1 13 32, 3, 4 and 2L M H p L p H p Mε ε= = = = = + = −

( ) 13, 2M Hπ ε∗ = −

( ) 1 16 2,L Lπ ε∗ = +

147

Proof: Suppose

• • So

2 3 2 3Then 2 2MH L LM H+ > +

( ) ( ) ( )1 13 32, 3, 4 and 2L M H p L p H p Mε ε= = = = = + = −

( ) 13, 2M Hπ ε∗ = −

( ), 3H Hπ ε∗ =

( ) 1 16 2,L Lπ ε∗ = +

148

Proof: Suppose

• • So

• B =

2 3 2 3Then 2 2MH L LM H+ > +

( ) ( ) ( )1 13 32, 3, 4 and 2L M H p L p H p Mε ε= = = = = + = −

( ) ( ) ( )2 2 2

1 1 16 2 3 2 3

2 2 2L L M H H HM M Mε ε ε+ + + − + + − − + −

( ) 13, 2M Hπ ε∗ = −

( ), 3H Hπ ε∗ =

( ) 1 16 2,L Lπ ε∗ = +

149

Proof: Suppose

• • So

• B =

• W =

2 3 2 3Then 2 2MH L LM H+ > +

( ) ( ) ( )1 13 32, 3, 4 and 2L M H p L p H p Mε ε= = = = = + = −

( ) ( ) ( ) ( )2 2 2 2

1 1 1 16 2 3 3

1 12 2 32 2 2 2 2 2

L L M H M H H HL M H Hε ε ε ε+ + + + − + + − − + − − + −

( ) ( ) ( )2 2 2

1 1 16 2 3 2 3

2 2 2L L M H H HM M Mε ε ε+ + + − + + − − + −

( ) 13, 2M Hπ ε∗ = −

( ), 3H Hπ ε∗ =

( ) 1 16 2,L Lπ ε∗ = +

150

Proof: Suppose

• • So

• B =

• W =

• B increasing in

2 3 2 3Then 2 2MH L LM H+ > +

( ) ( ) ( )1 13 32, 3, 4 and 2L M H p L p H p Mε ε= = = = = + = −

( ) ( ) ( ) ( )2 2 2 2

1 1 1 16 2 3 3

1 12 2 32 2 2 2 2 2


( ) ( ) ( )2 2 2

1 1 16 2 3 2 3

2 2 2L L M H H HM M Mε ε ε+ + + − + + − − + −

ε

( ) 13, 2M Hπ ε∗ = −

( ), 3H Hπ ε∗ =

( ) 1 16 2,L Lπ ε∗ = +

151

Proof: Suppose

• • So

• B =

• W =

• B increasing in

• W decreasing in

2 3 2 3Then 2 2MH L LM H+ > +

( ) ( ) ( )1 13 32, 3, 4 and 2L M H p L p H p Mε ε= = = = = + = −

( ) ( ) ( ) ( )2 2 2 2

1 1 1 16 2 3 3

1 12 2 32 2 2 2 2 2


ε

( ) ( ) ( )2 2 2

1 1 16 2 3 2 3

2 2 2L L M H H HM M Mε ε ε+ + + − + + − − + −

ε

( ) 13, 2M Hπ ε∗ = −

( ), 3H Hπ ε∗ =

( ) 1 16 2,L Lπ ε∗ = +

152

Proof: Suppose

• • So

• B =

• W =

• B increasing in

• W decreasing in

• So

2 3 2 3Then 2 2MH L LM H+ > +

( ) ( ) ( )1 13 32, 3, 4 and 2L M H p L p H p Mε ε= = = = = + = −

( ) ( ) ( ) ( )2 2 2 2

1 1 1 16 2 3 3

1 12 2 32 2 2 2 2 2


ε

( ) ( ) ( )2 2 2

1 1 16 2 3 2 3

2 2 2L L M H H HM M Mε ε ε+ + + − + + − − + −

ε

increasing in BB W

ε+

( ) 13, 2M Hπ ε∗ = −

( ), 3H Hπ ε∗ =

( ) 1 16 2,L Lπ ε∗ = +

153

Proof: Suppose

• • So

• B =

• W =

• B increasing in

• W decreasing in

• So • intuitively, B rises as weight in tails increases

2 3 2 3Then 2 2MH L LM H+ > +

( ) ( ) ( )1 13 32, 3, 4 and 2L M H p L p H p Mε ε= = = = = + = −

( ) ( ) ( ) ( )2 2 2 2

1 1 1 16 2 3 3

1 12 2 32 2 2 2 2 2


ε

( ) ( ) ( )2 2 2

1 1 16 2 3 2 3

2 2 2L L M H H HM M Mε ε ε+ + + − + + − − + −

ε

increasing in BB W

ε+

( ) 13, 2M Hπ ε∗ = −

( ), 3H Hπ ε∗ =

( ) 1 16 2,L Lπ ε∗ = +

154

Return to globalization and Mexico

155

Return to globalization and Mexico Puzzles:

156

Return to globalization and Mexico Puzzles: • Mexico has comparative advantage in low-skill labor

157

Return to globalization and Mexico Puzzles: • Mexico has comparative advantage in low-skill labor but

158

Return to globalization and Mexico Puzzles: • Mexico has comparative advantage in low-skill labor but trade increased gap between high- and low-skill workers

159


– contradicts Heckscher-Ohlin theory

160


– contradicts Heckscher-Ohlin theory • H-O implies that as 2 countries become more different (in factor endowments),

should trade more

161



should trade more – hence, U.S. and Malawi should trade more than U.S. and Mexico (Malawi more different than Mexico from U.S.)

162



should trade more – hence, U.S. and Malawi should trade more than U.S. and Mexico (Malawi more different than Mexico from U.S.) – but Mexico trades much more than Malawi with U.S.

163

Resolution:

164

Resolution: • think of globalization as increase in

international production

165


international production – Delhi call centers (outsourcing)

166


international production – Delhi call centers (outsourcing) – computers

167



designed in U.S.

168



designed in U.S. programmed in Europe

169



designed in U.S. programmed in Europe assembled in China

170



designed in U.S. programmed in Europe assembled in China

• due to lower communication/transport costs

171

• 2 countries – one rich, one poor

172

• 2 countries – one rich, one poor – rich country

173


– workers of skill levels A and B

174



– poor country

175



– poor country – workers of skill levels C and D

176




A B C D> > >

177




A B C D> > >(conclusions still hold if )C B>

178




• production


2output s mq q=

179




• production • before globalization (i.e., in autarky), workers can

match only domestically


2output s mq q=

180




• production • before globalization (i.e., in autarky), workers can

match only domestically • after globalization, international matching possible


2output s mq q=

181

countrypoor

countryrich

DCBA >>>

182

Proposition 3: If D-workers have sufficiently low skill, i.e.,

countrypoor

countryrich

DCBA >>>

183


(*)

countrypoor

countryrich

DCBA >>>

1 5 ,2

B D +

>

184


(*) then globalization increases inequality in poor

country

countrypoor

countryrich

DCBA >>>

1 5 ,2

B D +

>

185

Proof: 2 cases

1 5(*) 2

B D +

>

rich poor country country

A B C D> > >

186

Proof: 2 cases

Case I

1 5(*) 2

B D +

>


A B C D> > >

( ) ( )p D p C>

187

Proof: 2 cases

Case I •

1 5(*) 2

B D +

>


A B C D> > >

( ) ( )p D p C>

( ), 0,a D Dπ ∗ >

188

Proof: 2 cases

Case I •

•

1 5(*) 2

B D +

>


A B C D> > >

( ), 0 (because, from (*), -worker can't match with - or -worker)g D D D A Bπ ∗ >

( ) ( )3

2a gDw D w D∗ ∗= =

( ) ( )p D p C>

( ), 0,a D Dπ ∗ >

autarky post-globalizationa g= =

189

Proof: 2 cases

Case I •

•

•

1 5(*) 2

B D +

>


A B C D> > >


( ) ( )3

2a gDw D w D∗ ∗= =

( ) ( )p D p C>

( ), 0,a D Dπ ∗ >

( ) ( ) because of possible matching with or g aw C w C B A∗ ∗≥


190

Proof: 2 cases

Case I •

•

•

• Hence,

1 5(*) 2

B D +

>


A B C D> > >


( ) ( )3

2a gDw D w D∗ ∗= =

( ) ( ) ( ) ( ) - - globalization causes rise in inequalityg g a aw C w D w C w D∗ ∗ ∗ ∗− ≥ −

( ) ( )p D p C>

( ), 0,a D Dπ ∗ >

( ) ( ) because of possible matching with or g aw C w C B A∗ ∗≥


191

Case II

( ) ( )p D p C<

rich poor

A B C D> > >

192

Case II •

( ) ( )3

2max ,2a a

Dw D DC w C∗ ∗ ⇒ = −

( ) ( )p D p C<

( ) ( )3

, 02a a

CC C w Cπ ∗ ∗> ⇒ =

rich poor

A B C D> > >

193

Case II •

•

( ) ( ) - - at worst -workers can self-match g aw C w C C∗ ∗≥

( ) ( )3

2max ,2a a

Dw D DC w C∗ ∗ ⇒ = −

( ) ( )p D p C<

( ) ( )3

, 02a a

CC C w Cπ ∗ ∗> ⇒ =

rich poor

A B C D> > >

194

Case II •

•

•


( ) ( )3

2max ,2a a

Dw D DC w C∗ ∗ ⇒ = −

( ) ( ) ( )3 3 3

2 2max , max ,2 2 2g g a

D D Cw D DC w C w D DC∗ ∗ ∗ = − ≤ = −

( ) ( )p D p C<

( ) ( )3

, 02a a

CC C w Cπ ∗ ∗> ⇒ =

rich poor

A B C D> > >

195

Case II •

•

•

• Hence, again


( ) ( )3

2max ,2a a

Dw D DC w C∗ ∗ ⇒ = −

( ) ( ) ( )3 3 3

2 2max , max ,2 2 2g g a

D D Cw D DC w C w D DC∗ ∗ ∗ = − ≤ = −

( ) ( )p D p C<

( ) ( )3

, 02a a

CC C w Cπ ∗ ∗> ⇒ =

( ) ( ) rises with globalizationw C w D∗ ∗−

rich poor

A B C D> > >

196

Model also explains Malawi:

197

Model also explains Malawi: • workers in Malawi have very low skills no international matching opportunities

⇒

198

Policy?

199

Policy? • How can D-workers benefit from globalization?

200

Policy? • How can D-workers benefit from globalization? • Suppose can increase q by at cost q∆ ( )c q∆

201

Policy? • How can D-workers benefit from globalization? • Suppose can increase q by at cost

– may give D better matching opportunities q∆ ( )c q∆

202


– may give D better matching opportunities • who will bear cost?

q∆ ( )c q∆

203



– not firm - - education raises worker’s productivity, but then have to pay higher wage

q∆ ( )c q∆

204



– not firm - - education raises worker’s productivity, but then have to pay higher wage – not worker perhaps can’t afford to pay

q∆ ( )c q∆

205



– not firm - - education raises worker’s productivity, but then have to pay higher wage – not worker perhaps can’t afford to pay – role for investment by third parties domestic government international agencies, NGOs foreign aid private foundations

q∆ ( )c q∆

why has inequality been rising? · second, growth of inequality in mexico • followed a period of...

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