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Outline
Slavery, Education, and Inequality
Graziella Bertocchi and Arcangelo Dimico
University of Modena
Junel 03, 2010
Graziella Bertocchi and Arcangelo Dimico University of Modena
Outline
1 Slavery, Education, and InequalityMotivationsSlavery and DevelopmentSlavery and InequalityFrom Slavery to Racial Inequality. Why?Convergence and Divergence in EducationConclusions
Graziella Bertocchi and Arcangelo Dimico University of Modena
Outline
Motivations
Motivation
According to economic historians (Engerman and Sokoloff,1997, 2005), factor endowments have determinedinequality-perpetuating institutions which have hamperedeconomic growth;
In this paper we focus on the long-term influence of a specificinstitution − slavery − within a single country − the UnitedStates;
Current indicators of interest:
income per capita;per capita income inequality;racial income inequality;educational racial inequality.
Graziella Bertocchi and Arcangelo Dimico University of Modena
Outline
Motivations
Slavery in the US
Slavery was initially introduced in the US from in the 16thcentury;
The Middle Passage brought to the US 645,000 slaves, mostlyfrom Africa, initially settled in the coastal Southern colonies;
Between the American Revolution and the Civil War, theSecond Middle Passage relocated one million slaves to theSouthern inland regions;
In 1860, the slave population amounted to 4 millions, i.e.,13% of the population, and was mostly located in South; 90%of the blacks living in the US were slaves;
Graziella Bertocchi and Arcangelo Dimico University of Modena
Outline
Motivations
Slavery in the US
In 1865, slavery was abolished;
After abolition, subsequent waves of migration brought manyformer slaves from the rural South to the urban North;
In 2000 the majority of the blacks (55%) was still living in theSouth, against a minority (16%) of the whites
Graziella Bertocchi and Arcangelo Dimico University of Modena
Outline
Motivations
Related Literature
On the long-term impact of factor endowments andinstitutions:
Engermann and Sokoloff (1997), Acemoglu et al. (2002,2008), Galor et al.(2009);
On the efficiency of slavery:
empirics: Fogel and Engerman (1974), David et al. (1976);models: Lagerlf (2009), Acemoglu and Wolitzky (2009);
Graziella Bertocchi and Arcangelo Dimico University of Modena
Outline
Motivations
Related Literature
On the long-term impact of slavery:
Africa: Nunn (2008);Americas: Engermann and Sokoloff (2005), Nunn (2008);US: Nunn (2008), Mitchener and McLean (2003), Lagerlf(2005)
On race and inequality in the US:
affirmative action;human capital ;
Smith (1984), Smith and Welch (1989), Heckman (1990),Margo (1990), Goldin (1998), Sacerdote (2005)
Graziella Bertocchi and Arcangelo Dimico University of Modena
Outline
Slavery and Development
Income per capita, 2000 vs slaves in 1860/Population: All Counties
ALAL
ALAL
ALAL
AL ALAL AL
ALAL
ALALALAL ALALAL AL
AL
ALAL
AL
AL ALAL
ALAL
AL
ALAL AL
ALAL
ALAL
ALAL
ALAL
ALAL
AL
ALAL
ALAL
ALAL
ALAL
AR ARAR
ARARAR ARAR
ARARARAR
ARARARAR
ARAR
AR ARAR
AR
ARAR AR
AR ARARARARARARAR
AR
AR
AR ARAR ARAR
ARAR
AR
AR AR
ARAR
AR
AR
AR
AR
AR
ARARAR
CA
CACACACA
CA
CA
CA
CACA
CA
CA
CACA
CA
CA
CA
CA
CA
CACA
CA
CA
CA
CACA
CA
CA
CA
CA
CACACA
CA
CA
CACA
CACACACA
CA
CA
CO
CT
CTCTCTCTCTCTCTDE
DE
DEFL
FL
FL
FL
FL
FL
FLFL
FL FL
FL
FLFL
FLFL
FL
FL
FL
FLFL
FL
FL
FL
FL
FLFL
FL
FL
FL
FL
FLFLFL FL
FL FLGA GAGA
GA
GA
GA
GA
GA
GA
GA GAGA
GAGA
GAGA
GA
GAGA
GA
GA
GA
GAGA
GA
GA
GAGA
GAGA
GAGA
GA
GA
GA
GA
GAGA
GA
GAGA
GAGA
GA
GA
GA
GA
GA
GAGA
GA
GA GA
GA
GAGA
GA
GA
GA
GA
GA
GA GA
GAGA
GAGA
GAGAGA
GA
GAGAGA
GAGA
GA
GA
GAGAGA GA
GA
GA
GA
GAGA
GAGA
GAGA GAGA GA GA
GA
GAGA
GAGA
GA
GAGAGA
GAGA
GA GAGA GA
GAGA
GA
GA
GA GAGA GAGAGA
GAGA GA
GA
GA
GA
GAGAGA
IL
ILIL
IL
IL
ILILILILILILILILILIL
IL
ILILILILIL
IL
ILIL
IL
IL
IL
ILILILIL
IL
IL
IL
ILILILILILILILILIL
IL
IL
IL
IL
IL
IL
ILILILILILIL
ILILILILILILILILIL
ILILIL
ILILILILIL
IL
IL
ILILIL
IL
ILILILIL
IL
IL
ILILILILILIL
ILILILIL
IL
ILILILILILILILIN
ININ
ININ
ININ
INININ
ININININ
ININININ
INININ
IN
ININININININ
IN
IN
IN
IN
ININININININININ
IN
ININ
IN
ININININ
IN
ININININININ
ININININININININ
ININ
INININININ
IN
IN
ININ
IN
IN
ININ
ININ
IN
IN
ININININ
IN
INININININIAIAIAIAIAIAIAIAIAIAIAIAIAIAIAIAIAIAIAIA
IAIAIAIA
IA
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IA
IA
IAIAIA
IAIAIAIA
IA
IAIAIAIAIAIAIAIAIAIAIAIAIAIAIAIAIA
IA
IAIA
IAIA
IAIAIAIAIAIAIAIAIAIAIA
IA
IAIAIAIAIA
IA
KSKSKSKSKSKSKS
KSKSKSKSKSKSKSKSKSKS
KS
KS
KSKS
KSKSKSKSKSKSKSKSKS
KSKSKSKSKS
KYKY
KYKYKY
KY
KY KYKY KY
KYKY
KY
KY
KY
KYKYKYKY
KYKY
KY
KY
KY
KY KYKY
KY
KYKY
KY
KYKY
KY
KY
KY KYKYKY
KYKY
KY
KYKY
KY
KY
KY
KYKY
KY
KY
KY
KY
KY
KY
KY
KY
KYKY
KYKY
KY
KY
KYKY
KY
KYKY
KY
KY
KYKY KYKY
KY
KYKY
KY
KY
KYKY
KYKY
KY
KYKY
KYKYKY
KY
KY
KYKYKY
KYKY
KY
KYKY KYKY
KY
KYKY
KY
KY
KY
KY
KY
LA
LALALA
LALALA
LA LALA LALA
LA
LALA
LALA
LA LA
LALA
LA
LALA
LALALA LALA
LA
LA
LA
LALALA
LA LA
LA
LA
LALALA
LA LA
LA
LALA
MEME
ME
ME
MEMEMEME
MEMEME
ME
MEMEME
MEMD
MDMDMD
MD
MDMD
MD
MD
MDMD
MD
MD
MD
MDMD MD
MD
MD
MD MDMD
MA
MAMAMAMA
MAMAMA
MAMAMA
MA
MA
MA
MI
MIMIMIMIMIMIMIMIMIMIMI
MIMIMIMIMI
MI
MI
MIMIMI
MIMI
MIMIMIMIMIMIMIMIMI
MI
MI
MI
MIMIMI
MI
MIMI
MI
MI
MI
MI
MIMIMI
MI
MI
MIMIMIMIMIMIMIMI
MI
MI
MN
MN
MNMNMNMNMN
MN
MN
MNMNMN
MN
MNMNMNMNMN
MN
MN
MNMNMNMN
MN
MNMNMNMNMNMNMNMNMN
MNMNMNMN
MN
MNMN
MNMN
MN
MNMNMN
MN
MNMNMNMN
MN
MNMN
MN
MNMNMN
MS
MSMS MSMS
MSMSMS MS
MSMS
MSMS
MS
MSMS
MSMS MS
MS
MS
MSMS
MS
MS
MS
MSMS
MS
MSMSMS
MS
MS MSMSMS MS
MSMS
MSMS
MSMS
MS
MSMSMS
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MSMS MS
MS
MSMS
MS
MS MS MSMO
MOMO
MOMOMO MO
MOMO
MOMOMO
MOMO
MOMO
MO
MO
MO
MO
MOMOMO
MOMO
MO
MOMOMOMO
MO
MO
MO
MO
MO
MOMOMO
MO
MOMO MO
MO
MOMOMO MO
MO
MOMOMOMOMO
MO
MO MO
MOMOMO
MO
MOMOMO
MOMO
MOMOMO MOMO
MOMOMOMO
MO
MO
MO
MOMO MOMO
MO
MO
MO
MO
MO
MOMOMO
MOMO
MO
MO
MOMO
MO
MO
MO
MO MO
MO
MOMOMOMOMO
MO
MO
MO
MOMOMOMO
NENENE
NENENE
NE
NENENENE
NE
NENE
NE
NE
NE
NE
NE
NE
NENENENENENE
NENENV
NVNHNHNHNH
NHNHNHNH
NHNHNJ
NJ
NJNJNJ
NJ
NJ
NJNJ
NJ
NJNJNJ
NJ
NJNJNJ
NJ
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NJNM
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NYNYNYNYNYNY
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NYNYNYNYNYNYNY
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NYNYNYNYNY
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NYNYNYNYNY
NY
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NY
NYNY
NCNCNC
NCNC NC NCNCNC
NC
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NC
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NC
NC NC
NC
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NC
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NCNC
NC
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NCNC
NC
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NC
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NC NCNC
NC
NC
NC
NCNC
NCNC
NC NCNCNCOH
OHOHOH
OH
OH
OHOH
OH
OHOHOHOHOH
OHOHOH
OH
OHOH
OHOHOH
OH
OHOH
OH
OH
OH
OH
OHOH
OHOH
OH
OHOHOH
OH
OHOHOH
OH
OH
OHOHOHOHOHOHOH
OH
OH
OHOH
OH
OH
OHOHOH
OH
OH
OHOH
OHOH
OHOHOHOHOHOHOHOHOHOHOHOHOHOHOH
OH
OH
OHOHOHOHOH
OROR
OROROROROROROROROROR
OR
OROROR
OR
ORP A
P A
P AP A
P A
P AP AP A
P A
P AP AP AP A
P A
P AP AP AP AP A
P AP AP A
P AP AP AP A
P AP AP AP A
P AP AP A
P A
P AP AP A
P AP AP AP AP AP A
P A
P AP A
P AP AP A
P AP AP A
P A
P AP AP AP AP AP AP AP A
P AP AP AP A
RIRIRI
RI
RI
SCSC
SC
SCSC
SCSCSC SC
SC
SC
SCSC
SC
SCSCSC SC
SC
SC SC
SCSCSC
SCSC
SCSCSC
SCT N
T NT NT N
T NT N
T N
T N T NT N
T N
T NT N
T NT N
T N
T NT NT NT N T N
T NT NT N T N
T N
T N
T N
T N
T NT N
T NT N T N
T N T N
T NT NT NT N
T N
T N
T N
T NT N
T NT NT NT N
T NT N
T N T N
T NT N
T N
T N
T N
T NT N
T N
T N
T NT N
T N T N
T NT N
T N
T N
T NT N
T N T N
T N
T NT N
T NT N
T N
T NT N
T N
T N
T X
T X
T X
T XT XT X
T X
T XT XT X
T X T XT X
T XT XT X
T XT X
T X
T X
T XT X
T XT X
T X
T X
T X
T XT X
T X
T XT X
T XT X
T X
T XT X
T XT X
T XT X
T XT X
T XT X
T X
T XT X
T X
T XT X T X
T X
T XT XT X
T X
T XT X T XT X
T X
T XT X
T XT X
T X
T XT X
T X
T X
T X
T XT X
T XT XT X
T X T XT X
T XT X
T X
T X
T XT XT X
T X
T XT X
T X
T X T XT X T X
T X T X
T X
T X
T X
T XT XT X
T XT XT X
T XT X
T X
T X
T X
T X
T X T X
T X
T XT XT XT X
T X
T X
T X
T X
T X
T X
T X
T X
T X
T X
T XT X
UTUTUT
UT
UTUTUT
UT
UT
UTUTUTUTVTVT
VT
VT
VT
VT
VTVTVTVTVTVTVTVT
VAVA
VAVA
VA
VAVA
VAVA
VA
VAVA
VA
VA VA
VA
VA
VAVA
VA
VA
VAVAVA
VA
VA
VAVA VA
VAVA
VAVA
VA
VAVA
VA
VA
VA
VA
VA
VA
VA
VA
VAVA
VA
VAVA
VAVA
VAVA
VA
VA
VA
VA
VAVAVA
VAVA
VA
VA VAVA
VAVA
VAW AW A
W AW AW A
W A
W AW AW A
W AW AW AW A
W AW AW AW IW IW IW I
W IW I
W I
W IW I
W I
W I
W I
W I
W IW I
W IW IW IW I
W IW IW IW IW I
W I
W I
W I
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W IW I
W I
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W IW I
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W I
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W IW IW I
W I
W I
W I
W I
W I
W I
W I
W I
W I
W I
W I
W I
W I
W I
W IW I
Y=10.0678 - 0.2431(-10.76) X
99.
510
10.5
1111
.5
0 .2 .4 .6 .8 1slave_1860
lnincome_00 Fitted values
Figure: Income pc vs Slavery: All Counties
Graziella Bertocchi and Arcangelo Dimico University of Modena
Outline
Slavery and Development
Income per capita vs Slavery: Slave States Only
ALAL
ALAL
ALAL
AL AL
ALAL
ALAL
ALAL
ALAL ALALAL AL
AL
ALAL
AL
AL ALAL
ALAL
AL
AL
ALAL
ALAL
ALAL
ALAL
AL
ALAL
AL
AL
ALAL
ALAL
ALAL
AL
AL
ARAR
AR
ARARAR AR
ARARARAR
ARARAR
ARAR
AR
AR
AR ARAR
AR
AR
AR ARAR
ARARARAR
ARARAR
AR
AR
ARAR
ARARAR
AR
AR
AR
AR AR
AR
ARAR
AR
AR
AR
AR
AR
ARAR
DE
DE
DEFL
FL
FL
FL
FL
FL
FL
FL
FL FL
FL
FL
FL
FLFL
FL
FL
FL
FL
FLFL
FL
FL
FL
FLFL
FL
FL
FL
FL
FLFL
FL FL
FL FLGAGA
GAGA
GA
GA
GA
GA
GA
GA GAGA
GAGA
GAGA
GA
GAGA
GA
GA
GA
GA
GA
GA
GA
GAGA
GAGA
GA
GA
GA
GA
GA
GA
GAGA
GA
GAGA
GAGA
GA
GA
GA
GA
GA
GA
GA
GA
GA GA
GA
GAGA
GA
GA
GA
GA
GA
GA GA
GAGA
GAGA
GAGA
GA
GA
GAGAGA
GA
GAGA
GA
GAGAGA GA
GA
GA
GA
GA
GAGA
GA
GAGA GAGA GA
GA
GA
GAGA
GAGA
GA
GAGAGA
GAGA
GA GAGA GA
GAGA
GA
GA
GA GAGAGAGA
GA
GAGA GA
GA
GA
GA
GAGAGA
KYKY
KYKY
KY
KY
KY KY
KY KY
KY
KYKY
KY
KY
KYKY
KY
KY
KYKY
KY
KY
KY
KY KYKY
KY
KYKY
KY
KYKY
KY
KY
KY KYKY
KYKY
KY
KY
KY
KY
KY
KY
KY
KY
KY
KY
KY
KY
KY
KY
KY
KY
KY
KYKY
KYKY
KY
KY
KYKY
KY
KYKY
KY
KY
KY
KYKYKY
KY
KYKY
KY
KY
KY
KY
KYKY
KY
KY
KY
KYKYKY
KY
KY
KYKYKY
KYKY
KY
KYKY
KYKY
KY
KY
KYKY
KY
KY
KY
KY
LA
LALA
LA
LALA
LA
LA LALA LA
LA
LA
LALA
LALA
LA LA
LALA
LA
LALA
LALA
LA LALA
LA
LA
LA
LALALA
LA LA
LA
LA
LALA
LALA LA
LA
LALA
MD
MDMDMD
MD
MD
MDMD
MD
MDMD
MD
MD
MD
MDMD MD
MD
MD
MD MDMD
MS
MSMS MS
MSMS
MSMS MS
MSMS
MSMS
MS
MS
MS
MS
MSMS
MS
MS
MSMS
MS
MS
MS
MS
MS
MS
MSMS
MS
MS
MS MSMSMS
MSMS
MS
MSMS
MSMS
MS
MSMSMS
MSMS
MSMS MS
MS
MS
MS
MS
MS MS MS
MO
MOMO
MO
MOMOMOMO
MO
MOMO
MO
MOMO
MOMO
MO
MO
MO
MO
MOMOMO
MO
MOMO
MOMOMOMO
MO
MO
MO
MO
MO
MO
MOMO
MO
MOMO MO
MO
MOMO
MOMO
MO
MOMOMOMO
MO
MO
MO MO
MOMO
MO
MO
MOMOMO
MO
MOMO
MOMO
MOMO
MOMOMOMO
MO
MO
MO
MOMO MOMO
MO
MO
MO
MO
MO
MOMOMO
MOMO
MO
MO
MOMO
MO
MO
MO
MOMO
MO
MOMO
MOMOMO
MO
MO
MO
MOMO
MOMO
NCNC
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NC
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NC
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NC
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NC
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NC
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NC
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NC SC
SCSC
SCSC
SCSCSC SC
SC
SC
SCSC
SC
SCSCSC SC
SC
SC SC
SCSCSC
SC
SC
SCSC
SC
SCT N
T NT N
T N
T NT N
T N
T N T N
T N
T N
T NT N
T NT N
T N
T NT N
T NT N T N
T NT N
T N T N
T N
T N
T N
T N
T N
T N
T NT N T N
T N T N
T NT N
T NT N
T N
T N
T N
T N
T N
T NT NT N
T N
T N
T NT N T N
T NT N
T N
T N
T N
T NT N
T N
T N
T N
T NT N T N
T NT N
T N
T N
T N
T N
T N T N
T N
T NT N
T NT N
T N
T NT N
T N
T N
T X
T X
T X
T XT XT X
T X
T XT XT X
T XT X
T X
T XT XT X
T XT X
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T X
T XT X
T XT X
T X
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T X
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T X
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T XT X
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T XT X T X
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T XT X
T X
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T XT X
T XT X
T X
T XT X
T XT X
T X
T XT X
T X
T X
T X
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T XT X
T X
T XT X
T X
T XT X
T X
T X
T XT XT X
T X
T XT X
T X
T XT XT X T X
T X T X
T X
T X
T X
T X
T XT X
T XT XT X
T XT X
T X
T X
T X
T X
T XT X
T X
T XT X
T XT X
T X
T X
T X
T X
T X
T X
T X
T X
T X
T X
T XT X
VAVA
VAVA
VA
VAVA
VA
VA
VA
VAVA
VA
VA VA
VA
VA
VA
VA
VA
VA
VAVAVA
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VAVA VA
VAVA
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VA
VA
VA
VA
VA
VA
VA
VAVA
VA
VA
VAVA
VA
VA
VA
VA
VAVAVA
VAVA
VA
VA VAVA
VA
VAVA
Y=9.9401+0.0358 (1.22) X9
9.5
1010
.511
0 .2 .4 .6 .8 1slave_1860
lnincome_00 Fitted values
Figure: Income pc vs Slavery: Slave States
Graziella Bertocchi and Arcangelo Dimico University of Modena
Outline
Slavery and Development
Slavery and Development
*** p<0.01, ** p<0.05, * p<0.1. Robust t statistics in parentheses.
Figure: Slavery and Development
Graziella Bertocchi and Arcangelo Dimico University of Modena
Dependent Variable: Per Capita Income 2000Estimation Method: OLS Model 1 Model 2 Model 3 Model 4 Model 5 Slaves/Population 1860 -0.239*** -0.0249 -0.0496 -0.0211 -0.0287
(-10.99) (-0.79) (-1.51) (-0.67) (-0.85)Population Density 1860 0.0444*** 0.0386*** 0.0387*** 0.297 0.263
(7.26) (9.38) (9.23) (1.59) (1.61)North East Dummy 0.0986*** 0.120***
(5.63) (6.91)South Atlantic Dummy 0.107*** 0.111*** 0.103*** 0.107***
(7.57) (7.79) (7.40) (7.55)Slave States Dummy -0.174***
(-13.61)South Dummy -0.148***
(-10.51)Constant 10.06*** 10.09*** 10.08*** 9.911*** 9.911***
(1652.16) (1464.88) (1569.84) (886.96) (753.30)Observations 1960 1960 1960 1026 913R-squared 0.08 0.21 0.18 0.08 0.08Sample All Counties All Counties All Counties Slave States South States*** p<0.01, ** p<0.05, * p<0.1. Robust t statistics in parentheses.
Outline
Slavery and Inequality
Slavery and Income Inequality
Income Inequality: Gini Index for the distribution of Income (2000)across classes of income (Census 2000);
(17.64)South Dummy 0.0353***
(17.34)Constant 0.387*** 0.390*** 0.420***
(408.95) (421.43) (251.81)
Observations 1983 1983 1050R-squared 0.30 0.30 0.11Sample All Counties All Counties Slave States*** p<0.01, ** p<0.05, * p<0.1.Robust t statistics in parentheses.
Figure: Slavery vs Economic Inequality
Graziella Bertocchi and Arcangelo Dimico University of Modena
Dependent Variable: Income InequalityEstimation Method: OLS Model 1 Model 2 Model 3 Slaves/Population 1860 0.0374*** 0.0331*** 0.0375***
(7.42) (6.39) (7.46)Population Density 1860 0.00304*** 0.00302*** 0.0117
(4.28) (4.36) (0.86)North East Dummy 0.0108*** 0.00817***
(6.26) (4.78)South Atlantic Dummy -0.0212*** -0.0240*** -0.0214***
(-9.58) (-10.73) (-9.60)Slave States Dummy 0.0336***
(17.64)South Dummy 0.0353***
(17.34)Constant 0.387*** 0.390*** 0.420***
(408.95) (421.43) (251.81)
Observations 1983 1983 1050R-squared 0.30 0.30 0.11Sample All Counties All Counties Slave States*** p<0.01, ** p<0.05, * p<0.1. Robust t statistics in parentheses
.
Outline
Slavery and Inequality
Slavery and Racial Inequality
R-squared 0.40 0.40 0.40Sample All Counties All Counties Slave States*** p<0.01, ** p<0.05, * p<0.1.Robust t statistics in parentheses.
Figure: Slavery vs Racial Inequality
Graziella Bertocchi and Arcangelo Dimico University of Modena
Racial Inequality: Gini Index for the distribution of Income (2000)across races (Census 2000).
Dependent Variable: Racial InequalityEstimation Method: OLS Model 1 Model 2 Model 3 Slaves/Population 1860 0.178*** 0.162*** 0.179***
(26.33) (22.15) (26.70)Population Density 1860 0.0102*** 0.0102*** 0.0532***
(5.83) (5.84) (2.83)North East Dummy 0.00133 0.00482
(0.43) (1.59)South Atlantic Dummy -0.00537* -0.00842*** -0.00597*
(-1.75) (-2.63) (-1.95)Slave States Dummy -0.00640**
(-2.13)South Dummy 0.00596*
(1.73)Constant 0.0354*** 0.0320*** 0.0279***
(23.29) (23.16) (10.84)
Observations 1983 1983 1050R-squared 0.40 0.40 0.40Sample All Counties All Counties Slave States*** p<0.01, ** p<0.05, * p<0.1.Robust t statistics in parentheses.
Outline
Slavery and Inequality
Effect of Slavery Through Racial Inequality
Sample All Counties All Counties*** p<0.01, ** p<0.05, * p<0.1.Robust t statistics in parentheses.
Figure: Effect of Slavery Through Racial Inequality
Graziella Bertocchi and Arcangelo Dimico University of Modena
Model 1 Model 2Estimation Method: OLS Racial Inequality Income Inequality Slaves/Population 1860 0.156*** -0.00732
(25.03) (-1.38)Population Density 1860 0.00842*** 0.000464
(6.26) (1.44)North East Dummy -0.00510* 0.0104***
(-1.68) (6.18)South Atlantic Dummy 0.00733*** -0.0199***
(2.61) (-9.99)Slave States Dummy -0.0264*** 0.0352***
(-8.47) (19.17)Income Inequality 0.597***
(16.35)Racial Inequality 0.251***
(17.28)Constant -0.196*** 0.378***
(-14.20) (378.49)Observations 1983 1983R-squared 0.49 0.41Sample All Counties All Counties*** p<0.01, ** p<0.05, * p<0.1.Robust t statistics in parentheses.
Outline
From Slavery to Racial Inequality. Why?
Descriptive Statistics
Land Inequality Theory: Distribution of farms’ size (in acres)in 1860;Racial Discrimination Theory: Measured using a Mincerianequation to predict Returns on Education per Race;Human Capital Transmission Theory: Distribution ofeducation for the population 25 and above across races.
Land Inequality 1037 0.479 0.079 0 0.803Ratio (Returns Blacks/ Returns Whites) 1358 0.457 0.176 0.071 2.531Racial Educational Inequality 1405 0.033 0.027 0.0006 0.202
Figure: Descriptive Statistics
Graziella Bertocchi and Arcangelo Dimico University of Modena
All CountiesVariable Obs Mean Std. Dev. Min Max
Land Inequality 1878 0.461 0.080 0 0.803Ratio (Returns Blacks/ Returns Whites) 2798 0.511 0.224 0.028 2.531Racial Educational Inequality 3140 0.023 0.026 0 0.202
Slave States OnlyVariable Obs Mean Std. Dev. Min Max
Land Inequality 1037 0.479 0.079 0 0.803Ratio (Returns Blacks/ Returns Whites) 1358 0.457 0.176 0.071 2.531Racial Educational Inequality 1405 0.033 0.027 0.0006 0.202
Outline
From Slavery to Racial Inequality. Why?
Comparison Among Theories
(84.18) (198.18) (399.95)Observations 1878 1894 1983R-squared 0.32 0.31 0.41*** p<0.01, ** p<0.05, * p<0.1.Robust t statistics in parentheses except for Model 2 in which we bootstrap standard errors because of the predicted variable.
Figure: Comparison Among Theories
Graziella Bertocchi and Arcangelo Dimico University of Modena
Dependent Variable: Income InequalityEstimation Method: OLS Model 1 Model 2 Model 3
Slaves/Population 1860 0.0381*** 0.0366*** 0.000551(7.33) (7.10) (0.10)
Population Density 1860 0.00284*** 0.00295 0.000808**(4.51) (0.41) (2.15)
North East Dummy 0.0108*** 0.0104*** 0.0102***(6.16) (5.55) (6.00)
South Atlantic Dummy -0.0194*** -0.0214*** -0.0231***(-8.71) (-9.65) (-11.37)
Slave States Dummy 0.0310*** 0.0325*** 0.0349***(15.25) (15.65) (19.26)
Land Inequality 1860 0.0456***(4.64)
Returns Blacks/Returns Whites -0.0117***(-3.55)
Racial Educational Inequality 0.569***(17.16)
Constant 0.366*** 0.393*** 0.380***(84.18) (198.18) (399.95)
Observations 1878 1894 1983R-squared 0.32 0.31 0.41*** p<0.01, ** p<0.05, * p<0.1.Robust t statistics in parentheses except for Model 2 in which we bootstrap standard errors because of the predicted variable.
Outline
From Slavery to Racial Inequality. Why?
2SLS Estimates
(94.49) (-3.03)
Cragg Donald Statistics 532.982 532.982Stok and Yogo Critical Values (16.23) (16.23)Endogeneity (p-values) 0.8101 0.0000Anderson LR Statistic (p-values) 0.0000 0.0000Instruments Slaves/Population 1860 Slaves/Population 1860Observations 1831 1831*** p<0.01, ** p<0.05, * p<0.1. Significance Levels
Figure: 2SLS Estimates
Graziella Bertocchi and Arcangelo Dimico University of Modena
Second Stage Regressions Model 1 Model 2Estimation Method: 2SLS Income Inequality Racial Inequality
Racial Educational Inequality 0.590*** 2.746***(7.42) (26.75)
Population Density 1860 0.000608 -0.000493(1.47) (-1.26)
North East Dummy 0.0101*** -0.00260*(5.75) (-1.82)
South Atlantic Dummy -0.0220*** -0.0137***(-10.10) (-5.51)
Slave States Dummy 0.0331*** 0.000086(18.70) (0.01)
Land Inequality 1860 0.0299*** 0.0320**(3.41) (1.98)
Returns Blacks/Returns Whites 0.00146 0.0253***(0.42) (5.78)
Constant 0.366*** -0.0227***(94.49) (-3.03)
Cragg Donald Statistics 532.982 532.982Stok and Yogo Critical Values (16.23) (16.23)Endogeneity (p-values) 0.8101 0.0000Anderson LR Statistic (p-values) 0.0000 0.0000Instruments Slaves/Population 1860 Slaves/Population 1860Observations 1831 1831*** p<0.01, ** p<0.05, * p<0.1. Significance Levels
Outline
Convergence and Divergence in Education
Convergence in Education
Ratio of Whites with either a high school diploma or abachelor degree to Blacks over the period 1940-2000;
AK AKAK AK
AL
AL
AL AL AL AL AL
AR
ARAR AR AR AR AR
AZ
AZ AZ AZCA
CA CA CACO CO CO CO
CT CT CT CTCT CT CT
DCDC DC
DC DC DC DCDE DE DE
DEDE DE DE
FL
FL
FL FLFL FL FL
GA
GA
GA GAGA GA GAHI HI HI HI
IAIA
IAIA
IA IA IA
ID
ID ID ID
IL IL ILIL
IL IL ILIN IN IN IN IN IN INKSKS
KSKS
KS KS KSKY KY KY KYKY KY KY
LA
LA
LALA LA LA LAMA MA
MAMA
MA MA MA
MDMD
MD MDMD MD MDME ME ME ME
MI MI MI MIMI MI MI
MN MN MN MNMO MO MO MO MO MO MO
MS
MS
MS
MSMS MS MS
MT MT MT MT
NCNC NC NC NC NC NC
ND NDND ND
NE NE NENE
NE NE NE
NH NH NH NH
NJ NJNJ NJ
NJ NJ NJNM NM NM NM
NV
NV NV NV
NY NY NYNY
NY NY NYOH OH OH OH
OH OH OHOKOK OK OKOR OR OR OR
P AP A
P A PAPA P A P A
RIRI
RIRI
RI RI RI
SC
SC
SC SC SC SC SC
SD SD SD SD
T NT N T N T N T N T N T N
T X T X T X T XT X T X T XUT UT UT UT
VAVA VA VA
VA VA VA
VT VT VT VT
WAWA W A W A
W I
W IWI
WIWI W I W I
W V W V WV WV WV W V W V
WY
WY W YW Y
05
1015
1940 1960 1980 2000year
gap_bach Fitted values
AKAKAKAK
AL
AL
ALALALALAL
AR
ARARARARARAR
AZAZAZAZ
CACACACACOCOCOCO
CTCTCTCTCTCTCT
DCDCDC
DCDCDCDCDEDEDEDEDEDEDE
FL
FL
FLFLFLFLFL
GA
GA
GAGAGAGAGAHIHIHIHI
IAIAIAIAIAIAIA
ID
IDIDID
ILILILILILILILINININININININKS
KSKSKSKSKSKSKYKYKYKY
KYKYKY
LA
LA
LALALALALAMAMA
MAMAMAMAMA
MDMDMDMDMDMDMDMEMEMEME
MIMIMIMIMIMIMI
MNMNMNMNMOMOMOMOMOMOMO
MS
MS
MSMSMSMS
MTMTMTMT
NCNCNCNCNCNCNC
NDNDNDND
NENENENENENENE
NHNHNHNH
NJNJNJNJNJNJNJNMNMNMNM
NV
NVNVNV
NYNYNYNYNYNYNYOHOHOHOHOHOHOHOK
OKOKOKOROROROR
P AP AP AP AP AP AP A
RIRI
RIRIRIRIRI
SC
SC
SCSCSCSCSC
SDSDSDSD
T NT NT NT NT NT NT N
T XT XT XT XT XT XT XUTUTUTUT
VAVAVAVAVAVAVA
VTVTVTVT
W AW AW AW A
W I
W IW IW IW IW IW I
W VW VW VW VW VW VW V
W Y
W YW YW Y
05
1015
0 5 10 15gap_bach_40
gap_bach Fitted values
AKAKAKAK
AL
AL
ALAL
ALALAL
AR
AR
AR
AR
ARARARAZAZAZAZCACACACACOCOCOCO
CTCTCTCTCTCTCT
DCDCDCDCDCDCDC
DEDEDEDEDEDEDE
FL
FL
FL
FL
FLFLFL
GA
GA
GA
GA
GAGAGAHIHIHIHI
IAIAIAIAIAIAIAIDIDIDIDILILILILILILIL
INININININININKSKSKSKSKSKSKS
KYKYKYKYKYKYKY
LA
LA
LA
LA
LALALAM AM AM AM AM AM AM A
MD
MDMDMDMDMDMDM EM EM EM E
M IM IM IM IM IM IM IMNMNMNMN
M OM OM OM OM OM OM O
MS
MS
MS
MS
MSMSMS
MTMTMTMT
NC
NCNCNCNCNCNC
NDNDNDND
NENENENENENENENHNHNHNH
NJNJNJNJNJNJNJNMNMNMNM
NVNVNVNV
NYNYNYNYNYNYNY
OHOHOHOHOHOHOH
OKOKOKOKOROROROR
P AP AP AP AP AP AP A
RIRIRIRIRIRIRI
SC
SC
SC
SC
SCSCSCSDSDSDSD
T NT NT NT NT NT NT N
T XT X
T XT XT XT XT X
UTUTUTUT
VAVA
VA
VAVAVAVAVTVTVTVTW AW AW AW A
W IW IW IW IW IW IW I
W VW VW VW VW VW VW VW YW YW YW Y
02
46
810
0 2 4 6 8 10gap_high_40
gap_high Fitted values
AK AK AK AK
AL
AL
ALAL
AL AL AL
AR
AR
AR
AR
AR AR ARAZ
AZ AZ AZCA CA CA CACO CO CO CO
CT CT CT CT CT CT CT
DC
DCDC DC DC DC DC
DEDE
DEDE
DE DE DE
FL
FL
FL
FL
FL FL FL
GA
GA
GA
GA
GA GA GAHI HI HI HI
IA IA IA IA IA IA IAID ID ID ID
IL IL IL IL IL IL IL
IN IN IN IN IN IN INKS KS KS KS KS KS KS
KY KY KY KY KY KY KY
LA
LA
LA
LA
LA LA LAMA MA MA MA MA MA MA
MD
MDMD
MDMD MD MDME ME ME ME
MI MI MI MI MI MI MIMN MN MN MN
MO MO MO MO MO MO MO
MS
MS
MS
MS
MSMS MS
MT MT MT MT
NC
NCNC
NCNC NC NC
ND ND ND ND
NE NE NE NE NE NE NENH NH NH NH
NJNJ
NJ NJ NJ NJ NJNM NM NM NM
NVNV NV NV
NY NY NY NY NY NY NY
OHOH OH OH
OH OH OHOK
OK OK OKOR OR OR OR
PAP A
PA P A P A P A P A
RIRI RI RI RI RI RI
SC
SC
SC
SC
SC SC SCSD SD SD SD
T NT N
T NT N
T N T N T N
T XT X
T XT X
T X T X T XUT
UT UT UT
VAVA
VA
VA VA VA VAVT VT VT VTW A W A W A W A
W IW I
W I W IW I W I W I
W V W V W V W V W V W V W VW Y
W Y W Y W Y
02
46
810
1940 1960 1980 2000year
gap_high Fitted values
Figure: Convergence in Education
Graziella Bertocchi and Arcangelo Dimico University of Modena
AKAKAKAK
AL
AL
ALALALALAL
AR
ARARARARARAR
AZAZAZAZ
CACACACACOCOCOCO
CTCTCTCTCTCTCT
DCDCDC
DCDCDCDCDEDEDEDEDEDEDE
FL
FL
FLFLFLFLFL
GA
GA
GAGAGAGAGAHIHIHIHI
IAIAIAIAIAIAIA
ID
IDIDID
ILILILILILILILINININININININKS
KSKSKSKSKSKSKYKYKYKY
KYKYKY
LA
LA
LALALALALAMAMA
MAMAMAMAMA
MDMDMDMDMDMDMDMEMEMEME
MIMIMIMIMIMIMI
MNMNMNMNMOMOMOMOMOMOMO
MS
MS
MS
MSMSMSMS
MTMTMTMT
NCNCNCNCNCNCNC
NDNDNDND
NENENENENENENE
NHNHNHNH
NJNJNJNJNJNJNJNMNMNMNM
NV
NVNVNV
NYNYNYNYNYNYNYOHOHOHOHOHOHOHOK
OKOKOKOROROROR
P AP AP AP AP AP AP A
RIRI
RIRIRIRIRI
SC
SC
SCSCSCSCSC
SDSDSDSD
T NT NT NT NT NT NT N
T XT XT XT XT XT XT XUTUTUTUT
VAVAVAVAVAVAVA
VTVTVTVT
W AW AW AW A
W I
W IW IW IW IW IW I
W VW VW VW VW VW VW V
W Y
W YW YW Y
05
1015
0 5 10 15gap_bach_40
gap_bach Fitted values
AKAKAKAK
AL
AL
ALAL
ALALAL
AR
AR
AR
AR
ARARARAZAZAZAZCACACACACOCOCOCO
CTCTCTCTCTCTCT
DCDCDCDCDCDCDC
DEDEDEDEDEDEDE
FL
FL
FL
FL
FLFLFL
GA
GA
GA
GA
GAGAGAHIHIHIHI
IAIAIAIAIAIAIAIDIDIDIDILILILILILILIL
INININININININKSKSKSKSKSKSKS
KYKYKYKYKYKYKY
LA
LA
LA
LA
LALALAM AM AM AM AM AM AM A
MD
MDMDMDMDMDMDM EM EM EM E
M IM IM IM IM IM IM IMNMNMNMN
M OM OM OM OM OM OM O
MS
MS
MS
MS
MSMSMS
MTMTMTMT
NC
NCNCNCNCNCNC
NDNDNDND
NENENENENENENENHNHNHNH
NJNJNJNJNJNJNJNMNMNMNM
NVNVNVNV
NYNYNYNYNYNYNY
OHOHOHOHOHOHOH
OKOKOKOKOROROROR
P AP AP AP AP AP AP A
RIRIRIRIRIRIRI
SC
SC
SC
SC
SCSCSCSDSDSDSD
T NT NT NT NT NT NT N
T XT X
T XT XT XT XT X
UTUTUTUT
VAVA
VA
VAVAVAVAVTVTVTVTW AW AW AW A
W IW IW IW IW IW IW I
W VW VW VW VW VW VW VW YW YW YW Y
02
46
810
0 2 4 6 8 10gap_high_40
gap_high Fitted values
Outline
Convergence and Divergence in Education
Determinants of the Educational Gap
(6.93) (5.03) (8.02) (4.95)Time Dummies Yes Yes Yes YesObservations 297 297 297 297R-squared 0.55 0.44 0.68 0.53*** p<0.01, ** p<0.05, * p<0.1.Robust t statistics in parentheses.
Figure: Convergence in Education
Graziella Bertocchi and Arcangelo Dimico University of Modena
Estimation Method: Pooled OLS Model 1 Model 2 Model 3 Model 4 Gap High-Schl. Gap Bach. Dgr Gap High-Schl. Gap Bach. Dgr
High-School Diploma in 1940 – Whites 0.0199***(3.46)
High-School Diploma in 1940 – Blacks -0.00917***(-4.98)
Bachelor Degree in 1940– Whites 0.163***(5.62)
Bachelor Degree in 1940– Blacks -0.0897***(-6.46)
Population -0.136*** -0.0922** -0.136*** -0.0729(-3.61) (-2.03) (-4.05) (-1.38)
Slave States Dummy 0.872*** 0.541*** -0.0641 -0.280(5.95) (3.28) (-0.51) (-1.61)
Educational Gap in 1940 (High-School) 0.300***(5.37)
Educational Gap in 1940 (Bachelor Degree) 0.279***(3.60)
Constant 4.774*** 4.529*** 4.545*** 4.154***(6.93) (5.03) (8.02) (4.95)
Time Dummies Yes Yes Yes YesObservations 297 297 297 297R-squared 0.55 0.44 0.68 0.53*** p<0.01, ** p<0.05, * p<0.1.Robust t statistics in parentheses.
Outline
Convergence and Divergence in Education
Determinants of the Educational Gap
(-0.53) (-2.19)Constant 3.280*** 2.753*** 7.334*** -7.726***
(5.04) (3.09) (2.98) (-3.48)Time Dummies Yes Yes Yes YesObservations 238 238 183 183R-squared 0.76 0.62 0.76 0.68*** p<0.01, ** p<0.05, * p<0.1.Robust t statistics in parentheses.
Figure: Convergence in Education
Graziella Bertocchi and Arcangelo Dimico University of Modena
Estimation Method: Pooled OLS Model 1 Model 2 Model 3 Model 4 Gap High-Schl Gap Bach. Dgr Gap High-Schl Gap Bach. Dgr
Educational Gap in 1940 (High-School) 0.221*** 0.143***(2.68) (4.49)
Educational Gap in 1940 (Bachelor Degree) 0.180** 0.0356(2.00) (1.51)
Population -0.0947** -0.00761 -0.00604 0.00821(-2.52) (-0.15) (-0.30) (0.24)
Slave States Dummy -0.253 -0.597** -0.173* -0.104(-1.57) (-2.56) (-1.90) (-1.11)
Black Population Share 0.0336* 0.0481*** 0.00705** 0.0376***(1.85) (4.39) (2.48) (10.27)
Number of Farms 0.0104*** 0.00514(2.84) (0.82)
Number of Manufacturer Establish. -0.0209*** 0.000575(-2.61) (0.04)
Median Family Income -0.640** 1.153***(-2.41) (4.47)
Eudcational Expenditure/Direct General Exp. -0.00178 -0.00946**(-0.53) (-2.19)
Constant 3.280*** 2.753*** 7.334*** -7.726***(5.04) (3.09) (2.98) (-3.48)
Time Dummies Yes Yes Yes YesObservations 238 238 183 183R-squared 0.76 0.62 0.76 0.68*** p<0.01, ** p<0.05, * p<0.1.Robust t statistics in parentheses.
Outline
Conclusions
The institution of slavery still plays a major role in the USeconomy and society;
However, contrary to what suggested in related studies, thelegacy of slavery is not so much on the level of development,but instead on the degree of inequality;
The current level of per capita income inequality is explainedby racial inequality, and that slavery exerts its influence on thelatter through its impact on human capital accumulation;
There is an association among factor endowments, institutionsand inequality as argued by Engermann and Sokoloff;
But the final link between these variables and economicdevelopment is missing in our findings.
Graziella Bertocchi and Arcangelo Dimico University of Modena
Outline
Conclusions
Returns on Education
Median Age 0.0109*** 0.0267***(6.13) (11.03)
North Atlantic Dummy -0.0166 0.0236(-0.52) (0.48)
South Atlantic Dummy 0.0411 0.0277(1.55) (0.59)
South Central Dummy 0.0389 -0.0718**(1.36) (-2.61)
Constant 6.682*** 7.001***(24.26) (51.19)
Sample All Counties All CountiesObservations 3029 2798R-squared 0.76 0.27*** p<0.01, ** p<0.05, * p<0.1 Robust t statistics in parentheses
Figure: Returns on Education
Graziella Bertocchi and Arcangelo Dimico University of Modena
Model 1 Model 2Dependent Variable: Income (2000) Whites Only Income (2000) Blacks OnlyEstimation Method: OLS High-School Diploma 0.684*** 0.532***
(4.85) (3.63)Some Years of College (no Bachelor) 0.594*** 0.789***
(2.95) (6.24)Bachelor Degree 1.648*** 0.259***
(11.52) (2.81)Post-Graduate Education (Master or PhD) 1.889*** 1.409***
(8.54) (7.54)Employment Rate 1.599*** 0.368**
(5.61) (2.68)Whites in Labour Force 0.0330*** 0.0778***
(6.31) (6.78)Blacks in Labour Force 0.0134*** 0.0110
(4.41) (1.49)Median Age 0.0109*** 0.0267***
(6.13) (11.03)North East Dummy -0.0166 0.0236
(-0.52) (0.48)South Atlantic Dummy 0.0411 0.0277
(1.55) (0.59)South Central Dummy 0.0389 -0.0718**
(1.36) (-2.61)Constant 6.682*** 7.001***
(24.26) (51.19)Sample All Counties All CountiesObservations 3029 2798R-squared 0.76 0.27*** p<0.01, ** p<0.05, * p<0.1. Robust t statistics in parentheses.
