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

• In last 30 years, significant increase in income inequality

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

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

Mexico)

Mexico) • referring here to inequality increases within

countries

countries – inequality has been falling across countries

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

China) are catching up

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

China) are catching up • Increases are theoretically puzzling

First, take inequality increase in U.S.

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

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

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)

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

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

– but wage schedule not fixed

– but wage schedule not fixed • Why not?

• One popular answer: skill-biased technological change

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

• 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

• Objection:

• Objection: – difficult to measure such technological change

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

• Propose a different (simpler) theory based on matching

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

• 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

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

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

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

variation across firms

variation across firms • Illustrative examples

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

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

– 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

– 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

Second, growth of inequality in Mexico

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

– Mexico joined GATT in 1985

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

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

• white-collar wages increased by 16%

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

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

inequality

Contradicts Heckscher-Ohlin theory

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

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

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

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

• opposite true in U.S.:

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

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

• after trade opened, factor prices should equalize

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

• 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

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

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

• 1-good economy

• 1-good economy • good produced by competitive firms

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

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

• 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 =

All firms have same production process

All firms have same production process • 2 tasks

– one “managerial” - - sensitive to skill level

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

s mq q

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

• formula incorporates 3 critical features

2s mq q

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

2s mq q

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

2s mq q

• 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

(i) workers of different skills imperfect substitutes

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

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

• 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

(ii) different tasks complementary

(ii) different tasks complementary • if instead

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

optimal choice of independent of that of

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

skill levels in firm

(iii) different tasks differentially sensitive to skill

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

output ,s mq q=

get complete segregation of skill:

output ,s mq q=

s mq q=

– fully assortative matching

output ,s mq q=

s mq q=

– fully assortative matching • differential sensitivity

output ,s mq q=

s mq q=

2output s mq q=

– still have some assortative matching

output ,s mq q=

s mq q=

2output s mq q=

– still have some assortative matching – also have second force

output ,s mq q=

s mq q=

2output s mq q=

– still have some assortative matching – also have second force

output ,s mq q=

s mq q=

implies m sq q>

2output s mq q=

Competitive equilibrium

Competitive equilibrium • wage schedule ( )w q∗

Competitive equilibrium • wage schedule • matching rule

( )w q∗

( ), equilibrium fraction of matches with , s m

q qq q q q

π ′ =

′= =

( )w q∗

( )( ) ( )2

, ,, arg max , (output maximized)

q qq q q q

ππ π∗

⋅ ⋅ ′

′ ′⋅ ⋅ = ∑

q qq q q q

π ′ =

′= =

( )w q∗

( )( ) ( )2

q qq q q q

ππ π∗

⋅ ⋅ ′

′ ′⋅ ⋅ = ∑

q qq q q q

π ′ =

′= =

( )w q∗

( ) ( ) ( )2 0q q w q w q∗ ∗′ ′− − ≤

( )( ) ( )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 ∗ ′− >

suppose

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

suppose

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

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

suppose

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

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

suppose

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

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

3 2 2>

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> +

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> +

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> +

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∗ ∗= +

( )2 2 2

2LM LH MHw L∗ + −

( )2 2 2

2LM MH LHw M∗ + −

( )2 2 2

2LH MH LMw H∗ + −

• Notice

( )2 2 2

( ) ( )0 0w L w H

∗ ∗∂ ∂> <

∂ ∂

• 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

( ) ( )0 0w L w H

∗ ∗∂ ∂> <

∂ ∂

2 H L<

But opposite occurs if skill distribution dispersed

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

Proposition 2: Starting from sufficiently dispersed skill distribution

increase in median inequality:M magnifies( )34

3 2 and ,M L H M> >

increase in median inequality:M magnifies

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

∗ ∗∂ ∂≤ ≥

∂ ∂

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

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

∗ ∗∂ ∂≤ ≥

∂ ∂

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

Proof: Suppose

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

Proof: Suppose (2)

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

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

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> + > +

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

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

Proof: Suppose (2)

( ) , 0 because L H H Lπ ∗ = >>

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

(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

Proof: Suppose (2)

• •

( ) , 0 because L H H Lπ ∗ = >>

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

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

Proof: Suppose (2)

• •

( ) , 0 because L H H Lπ ∗ = >>

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

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

Proof: Suppose (2)

• •

( ) , 0 because L H H Lπ ∗ = >>

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

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

∗∂= − > >

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

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

Segregation

Segregation Index of relative segregation

B = skill variation between firms

( ) ( )2

2 - , mean skill in populationq q

q qq qµ π µ′+ ∗

′= =∑∑

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

( ) ( )2

′= =∑∑

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

( ) ( )2

′= =∑∑

( ) ( )2 *2 ,q q

q qq q qπ′+

′= −∑∑

Proposition 2: Suppose

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

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

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

segregation index

Proof: Suppose

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

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= = = = = + = −

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∗ = +

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∗ = +

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∗ = +

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∗ = +

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∗ = +

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+ + + − + + − − + −

( ) 13, 2M Hπ ε∗ = −

( ), 3H Hπ ε∗ =

( ) 1 16 2,L Lπ ε∗ = +

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

( ) ( ) ( )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∗ = +

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

( ) ( ) ( )2 2 2

1 1 16 2 3 2 3

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

increasing in BB W

( ) 13, 2M Hπ ε∗ = −

( ), 3H Hπ ε∗ =

( ) 1 16 2,L Lπ ε∗ = +

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

( ) ( ) ( )2 2 2

1 1 16 2 3 2 3

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

increasing in BB W

( ) 13, 2M Hπ ε∗ = −

( ), 3H Hπ ε∗ =

( ) 1 16 2,L Lπ ε∗ = +

Return to globalization and Mexico

Return to globalization and Mexico Puzzles:

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

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

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

– contradicts Heckscher-Ohlin theory

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

should trade more

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

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.

Resolution:

Resolution: • think of globalization as increase in

international production

international production – Delhi call centers (outsourcing)

international production – Delhi call centers (outsourcing) – computers

designed in U.S.

designed in U.S. programmed in Europe

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

• due to lower communication/transport costs

• 2 countries – one rich, one poor

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

– workers of skill levels A and B

– poor country

– poor country – workers of skill levels C and D

A B C D> > >

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

• production

2output s mq q=

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

match only domestically

2output s mq q=

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

match only domestically • after globalization, international matching possible

2output s mq q=

countrypoor

countryrich

DCBA >>>

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

countrypoor

countryrich

DCBA >>>

countrypoor

countryrich

DCBA >>>

1 5 ,2

(*) then globalization increases inequality in poor

country

countrypoor

countryrich

DCBA >>>

1 5 ,2

Proof: 2 cases

1 5(*) 2

rich poor country country

A B C D> > >

Proof: 2 cases

Case I

1 5(*) 2

A B C D> > >

( ) ( )p D p C>

Proof: 2 cases

Case I •

1 5(*) 2

A B C D> > >

( ) ( )p D p C>

( ), 0,a D Dπ ∗ >

Proof: 2 cases

Case I •

1 5(*) 2

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= =

Proof: 2 cases

Case I •

1 5(*) 2

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∗ ∗≥

Proof: 2 cases

Case I •

• Hence,

1 5(*) 2

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∗ ∗≥

Case II

( ) ( )p D p C<

rich poor

A B C D> > >

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> > >

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> > >

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> > >

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> > >

Model also explains Malawi:

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

Policy?

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

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

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

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

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

q∆ ( )c q∆

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

q∆ ( )c q∆

– 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∆

– 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∆

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