Women’s Liberation as a Financial Innovation Moshe Hazan David Weiss Hosny Zoabi

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Women’s Liberation as a Financial Innovation
Moshe Hazan1
David Weiss2
1 Tel-Aviv
Hosny Zoabi3
University and CEPR
2 Tel-Aviv
3 New
University
Economic School
July 2015
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
1 / 41
Introduction
Introduction
Common law included ‘Coverture’: limited legal economic status of
married women.
Men gave women economic rights, even before granting political
rights.
The question is: Why?
Our view: Coverture caused economic distortions, specifically through
capital allocation.
Build model to show that development → men giving rights → further
development.
Test hypotheses with cross-state variation in timing of rights.
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
2 / 41
Introduction
Introduction
Common law included ‘Coverture’: limited legal economic status of
married women.
Men gave women economic rights, even before granting political
rights.
The question is: Why?
Our view: Coverture caused economic distortions, specifically through
capital allocation.
Build model to show that development → men giving rights → further
development.
Test hypotheses with cross-state variation in timing of rights.
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
2 / 41
Introduction
Introduction
Common law included ‘Coverture’: limited legal economic status of
married women.
Men gave women economic rights, even before granting political
rights.
The question is: Why?
Our view: Coverture caused economic distortions, specifically through
capital allocation.
Build model to show that development → men giving rights → further
development.
Test hypotheses with cross-state variation in timing of rights.
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
2 / 41
Introduction
Introduction
Common law included ‘Coverture’: limited legal economic status of
married women.
Men gave women economic rights, even before granting political
rights.
The question is: Why?
Our view: Coverture caused economic distortions, specifically through
capital allocation.
Build model to show that development → men giving rights → further
development.
Test hypotheses with cross-state variation in timing of rights.
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
2 / 41
Introduction
Introduction
Common law included ‘Coverture’: limited legal economic status of
married women.
Men gave women economic rights, even before granting political
rights.
The question is: Why?
Our view: Coverture caused economic distortions, specifically through
capital allocation.
Build model to show that development → men giving rights → further
development.
Test hypotheses with cross-state variation in timing of rights.
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
2 / 41
Introduction
Introduction
Common law included ‘Coverture’: limited legal economic status of
married women.
Men gave women economic rights, even before granting political
rights.
The question is: Why?
Our view: Coverture caused economic distortions, specifically through
capital allocation.
Build model to show that development → men giving rights → further
development.
Test hypotheses with cross-state variation in timing of rights.
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
2 / 41
Introduction
Coverture
Property Laws:
“Moveable” assets, such as money, stocks, bonds, became the husbands’.
“Real” assets, such as land & structures, remained in the wife’s name,
but under the husbands’ control.
Earning laws: Wive’s income went to husband.
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
3 / 41
Introduction
Coverture
Property Laws:
“Moveable” assets, such as money, stocks, bonds, became the husbands’.
“Real” assets, such as land & structures, remained in the wife’s name,
but under the husbands’ control.
Earning laws: Wive’s income went to husband.
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
3 / 41
Introduction
Coverture
Property Laws:
“Moveable” assets, such as money, stocks, bonds, became the husbands’.
“Real” assets, such as land & structures, remained in the wife’s name,
but under the husbands’ control.
Earning laws: Wive’s income went to husband.
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
3 / 41
Introduction
Considerations of Coverture
Strong disincentive for women to invest in anything but land &
structures.
Leads to under-investment in capital.
As states industrialize, this distortion becomes worse.
Men’s considerations – Giving rights:
Lose bargaining power at home.
Higher income.
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
4 / 41
Introduction
Considerations of Coverture
Strong disincentive for women to invest in anything but land &
structures.
Leads to under-investment in capital.
As states industrialize, this distortion becomes worse.
Men’s considerations – Giving rights:
Lose bargaining power at home.
Higher income.
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
4 / 41
Introduction
Considerations of Coverture
Strong disincentive for women to invest in anything but land &
structures.
Leads to under-investment in capital.
As states industrialize, this distortion becomes worse.
Men’s considerations – Giving rights:
Lose bargaining power at home.
Higher income.
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
4 / 41
Introduction
Considerations of Coverture
Strong disincentive for women to invest in anything but land &
structures.
Leads to under-investment in capital.
As states industrialize, this distortion becomes worse.
Men’s considerations – Giving rights:
Lose bargaining power at home.
Higher income.
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
4 / 41
Introduction
Considerations of Coverture
Strong disincentive for women to invest in anything but land &
structures.
Leads to under-investment in capital.
As states industrialize, this distortion becomes worse.
Men’s considerations – Giving rights:
Lose bargaining power at home.
Higher income.
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
4 / 41
Introduction
Considerations of Coverture
Strong disincentive for women to invest in anything but land &
structures.
Leads to under-investment in capital.
As states industrialize, this distortion becomes worse.
Men’s considerations – Giving rights:
Lose bargaining power at home.
Higher income.
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
4 / 41
Introduction
Historical Context
1
Coverture’s Effect on Portfolio Choices:
Combs (2005) studies the portfolio allocation of women married before
and after the 1870 Property Act in England. Portfolio
Baskerville (2008) studies the “Silent Revolution” in Canada after rights.
Shows portfolios begin to resemble male portfolios.
Shows the effects on the bequest left to daughters.
2
Growing importance & democratization of financial markets. (Michie
2011)
3
Awareness of Tradeoff:
Alexander Hope (British MP): “. . . would completely revolutionise the
whole system of credit in the retail trade of this country.” (Morning Post,
1869)
Also: “. . . wantonly interfered with the relations of married life.”
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
5 / 41
Introduction
Historical Context
1
Coverture’s Effect on Portfolio Choices:
Combs (2005) studies the portfolio allocation of women married before
and after the 1870 Property Act in England. Portfolio
Baskerville (2008) studies the “Silent Revolution” in Canada after rights.
Shows portfolios begin to resemble male portfolios.
Shows the effects on the bequest left to daughters.
2
Growing importance & democratization of financial markets. (Michie
2011)
3
Awareness of Tradeoff:
Alexander Hope (British MP): “. . . would completely revolutionise the
whole system of credit in the retail trade of this country.” (Morning Post,
1869)
Also: “. . . wantonly interfered with the relations of married life.”
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
5 / 41
Introduction
Historical Context
1
Coverture’s Effect on Portfolio Choices:
Combs (2005) studies the portfolio allocation of women married before
and after the 1870 Property Act in England. Portfolio
Baskerville (2008) studies the “Silent Revolution” in Canada after rights.
Shows portfolios begin to resemble male portfolios.
Shows the effects on the bequest left to daughters.
2
Growing importance & democratization of financial markets. (Michie
2011)
3
Awareness of Tradeoff:
Alexander Hope (British MP): “. . . would completely revolutionise the
whole system of credit in the retail trade of this country.” (Morning Post,
1869)
Also: “. . . wantonly interfered with the relations of married life.”
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
5 / 41
Introduction
Historical Context
1
Coverture’s Effect on Portfolio Choices:
Combs (2005) studies the portfolio allocation of women married before
and after the 1870 Property Act in England. Portfolio
Baskerville (2008) studies the “Silent Revolution” in Canada after rights.
Shows portfolios begin to resemble male portfolios.
Shows the effects on the bequest left to daughters.
2
Growing importance & democratization of financial markets. (Michie
2011)
3
Awareness of Tradeoff:
Alexander Hope (British MP): “. . . would completely revolutionise the
whole system of credit in the retail trade of this country.” (Morning Post,
1869)
Also: “. . . wantonly interfered with the relations of married life.”
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
5 / 41
Introduction
Historical Context
1
Coverture’s Effect on Portfolio Choices:
Combs (2005) studies the portfolio allocation of women married before
and after the 1870 Property Act in England. Portfolio
Baskerville (2008) studies the “Silent Revolution” in Canada after rights.
Shows portfolios begin to resemble male portfolios.
Shows the effects on the bequest left to daughters.
2
Growing importance & democratization of financial markets. (Michie
2011)
3
Awareness of Tradeoff:
Alexander Hope (British MP): “. . . would completely revolutionise the
whole system of credit in the retail trade of this country.” (Morning Post,
1869)
Also: “. . . wantonly interfered with the relations of married life.”
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
5 / 41
Introduction
Historical Context
1
Coverture’s Effect on Portfolio Choices:
Combs (2005) studies the portfolio allocation of women married before
and after the 1870 Property Act in England. Portfolio
Baskerville (2008) studies the “Silent Revolution” in Canada after rights.
Shows portfolios begin to resemble male portfolios.
Shows the effects on the bequest left to daughters.
2
Growing importance & democratization of financial markets. (Michie
2011)
3
Awareness of Tradeoff:
Alexander Hope (British MP): “. . . would completely revolutionise the
whole system of credit in the retail trade of this country.” (Morning Post,
1869)
Also: “. . . wantonly interfered with the relations of married life.”
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
5 / 41
Introduction
Historical Context
1
Coverture’s Effect on Portfolio Choices:
Combs (2005) studies the portfolio allocation of women married before
and after the 1870 Property Act in England. Portfolio
Baskerville (2008) studies the “Silent Revolution” in Canada after rights.
Shows portfolios begin to resemble male portfolios.
Shows the effects on the bequest left to daughters.
2
Growing importance & democratization of financial markets. (Michie
2011)
3
Awareness of Tradeoff:
Alexander Hope (British MP): “. . . would completely revolutionise the
whole system of credit in the retail trade of this country.” (Morning Post,
1869)
Also: “. . . wantonly interfered with the relations of married life.”
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
5 / 41
Introduction
Historical Context
1
Coverture’s Effect on Portfolio Choices:
Combs (2005) studies the portfolio allocation of women married before
and after the 1870 Property Act in England. Portfolio
Baskerville (2008) studies the “Silent Revolution” in Canada after rights.
Shows portfolios begin to resemble male portfolios.
Shows the effects on the bequest left to daughters.
2
Growing importance & democratization of financial markets. (Michie
2011)
3
Awareness of Tradeoff:
Alexander Hope (British MP): “. . . would completely revolutionise the
whole system of credit in the retail trade of this country.” (Morning Post,
1869)
Also: “. . . wantonly interfered with the relations of married life.”
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
5 / 41
Introduction
Outline of Paper
1
Build/analyze Model.
When technology is low in manufacturing (non-agriculture), no
distortion.
As technology develops, distortion gets stronger.
When rights are granted, there is a structural shift towards
manufacturing. TFP
2
Using cross-state variation in US data, we find that:
1
2
Higher TFP in non-agriculture predicts granting rights.
Rights →
Increase in the fraction of workers in non-agriculture.
Increase in firm-level value-added per worker and capital.
The effects were dynamic and lasted for decades.
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
6 / 41
Introduction
Outline of Paper
1
Build/analyze Model.
When technology is low in manufacturing (non-agriculture), no
distortion.
As technology develops, distortion gets stronger.
When rights are granted, there is a structural shift towards
manufacturing. TFP
2
Using cross-state variation in US data, we find that:
1
2
Higher TFP in non-agriculture predicts granting rights.
Rights →
Increase in the fraction of workers in non-agriculture.
Increase in firm-level value-added per worker and capital.
The effects were dynamic and lasted for decades.
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
6 / 41
Introduction
Outline of Paper
1
Build/analyze Model.
When technology is low in manufacturing (non-agriculture), no
distortion.
As technology develops, distortion gets stronger.
When rights are granted, there is a structural shift towards
manufacturing. TFP
2
Using cross-state variation in US data, we find that:
1
2
Higher TFP in non-agriculture predicts granting rights.
Rights →
Increase in the fraction of workers in non-agriculture.
Increase in firm-level value-added per worker and capital.
The effects were dynamic and lasted for decades.
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
6 / 41
Introduction
Outline of Paper
1
Build/analyze Model.
When technology is low in manufacturing (non-agriculture), no
distortion.
As technology develops, distortion gets stronger.
When rights are granted, there is a structural shift towards
manufacturing. TFP
2
Using cross-state variation in US data, we find that:
1
2
Higher TFP in non-agriculture predicts granting rights.
Rights →
Increase in the fraction of workers in non-agriculture.
Increase in firm-level value-added per worker and capital.
The effects were dynamic and lasted for decades.
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
6 / 41
Introduction
Outline of Paper
1
Build/analyze Model.
When technology is low in manufacturing (non-agriculture), no
distortion.
As technology develops, distortion gets stronger.
When rights are granted, there is a structural shift towards
manufacturing. TFP
2
Using cross-state variation in US data, we find that:
1
2
Higher TFP in non-agriculture predicts granting rights.
Rights →
Increase in the fraction of workers in non-agriculture.
Increase in firm-level value-added per worker and capital.
The effects were dynamic and lasted for decades.
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
6 / 41
Introduction
Outline of Paper
1
Build/analyze Model.
When technology is low in manufacturing (non-agriculture), no
distortion.
As technology develops, distortion gets stronger.
When rights are granted, there is a structural shift towards
manufacturing. TFP
2
Using cross-state variation in US data, we find that:
1
2
Higher TFP in non-agriculture predicts granting rights.
Rights →
Increase in the fraction of workers in non-agriculture.
Increase in firm-level value-added per worker and capital.
The effects were dynamic and lasted for decades.
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
6 / 41
Introduction
Outline of Paper
1
Build/analyze Model.
When technology is low in manufacturing (non-agriculture), no
distortion.
As technology develops, distortion gets stronger.
When rights are granted, there is a structural shift towards
manufacturing. TFP
2
Using cross-state variation in US data, we find that:
1
2
Higher TFP in non-agriculture predicts granting rights.
Rights →
Increase in the fraction of workers in non-agriculture.
Increase in firm-level value-added per worker and capital.
The effects were dynamic and lasted for decades.
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
6 / 41
Introduction
Outline of Paper
1
Build/analyze Model.
When technology is low in manufacturing (non-agriculture), no
distortion.
As technology develops, distortion gets stronger.
When rights are granted, there is a structural shift towards
manufacturing. TFP
2
Using cross-state variation in US data, we find that:
1
2
Higher TFP in non-agriculture predicts granting rights.
Rights →
Increase in the fraction of workers in non-agriculture.
Increase in firm-level value-added per worker and capital.
The effects were dynamic and lasted for decades.
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
6 / 41
Introduction
Outline of Paper
1
Build/analyze Model.
When technology is low in manufacturing (non-agriculture), no
distortion.
As technology develops, distortion gets stronger.
When rights are granted, there is a structural shift towards
manufacturing. TFP
2
Using cross-state variation in US data, we find that:
1
2
Higher TFP in non-agriculture predicts granting rights.
Rights →
Increase in the fraction of workers in non-agriculture.
Increase in firm-level value-added per worker and capital.
The effects were dynamic and lasted for decades.
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
6 / 41
Introduction
Outline of Paper
1
Build/analyze Model.
When technology is low in manufacturing (non-agriculture), no
distortion.
As technology develops, distortion gets stronger.
When rights are granted, there is a structural shift towards
manufacturing. TFP
2
Using cross-state variation in US data, we find that:
1
2
Higher TFP in non-agriculture predicts granting rights.
Rights →
Increase in the fraction of workers in non-agriculture.
Increase in firm-level value-added per worker and capital.
The effects were dynamic and lasted for decades.
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
6 / 41
Introduction
Literature Review
1
Women’s Rights:
Doepke & Tertilt (2009), Fernandez (2014), Gueddes & Lueck (2002),
Combs (2005, 2006, 2013), Khan (1996).
2
Finance and Development:
Acemoglu & Zilibotti (1997), Rajan & Zingales (1998), King & Levine
(1993)
3
Women’s empowerment and development:
Doepke and Tertilt (2014), Duflo (2012)
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
7 / 41
Introduction
Literature Review
1
Women’s Rights:
Doepke & Tertilt (2009), Fernandez (2014), Gueddes & Lueck (2002),
Combs (2005, 2006, 2013), Khan (1996).
2
Finance and Development:
Acemoglu & Zilibotti (1997), Rajan & Zingales (1998), King & Levine
(1993)
3
Women’s empowerment and development:
Doepke and Tertilt (2014), Duflo (2012)
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
7 / 41
Introduction
Literature Review
1
Women’s Rights:
Doepke & Tertilt (2009), Fernandez (2014), Gueddes & Lueck (2002),
Combs (2005, 2006, 2013), Khan (1996).
2
Finance and Development:
Acemoglu & Zilibotti (1997), Rajan & Zingales (1998), King & Levine
(1993)
3
Women’s empowerment and development:
Doepke and Tertilt (2014), Duflo (2012)
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
7 / 41
Model
Production
Production of a final good, Y is CES in two input goods:
(1/ρ)
Yt = (YtA )ρ + (YtM )ρ
, ρ ∈ (0, 1]
Agriculture, A, which uses land, T , & labor LA :
α
A (1−α)
YtA = AA
.
t (T ) (Lt )
Manufacturing, M , which uses capital, K, structures, S, & labor LM :
α M (1−α)
σ
σ σ
YtM = AM
(Lt )
.
t (Kt ) + (St )
Land is fixed whereas structures and capital can be produced at a
relative price of 1 and they fully depreciate within one period.
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
8 / 41
Model
Production
Production of a final good, Y is CES in two input goods:
(1/ρ)
Yt = (YtA )ρ + (YtM )ρ
, ρ ∈ (0, 1]
Agriculture, A, which uses land, T , & labor LA :
α
A (1−α)
YtA = AA
.
t (T ) (Lt )
Manufacturing, M , which uses capital, K, structures, S, & labor LM :
α M (1−α)
σ
σ σ
YtM = AM
(Lt )
.
t (Kt ) + (St )
Land is fixed whereas structures and capital can be produced at a
relative price of 1 and they fully depreciate within one period.
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
8 / 41
Model
Production
Production of a final good, Y is CES in two input goods:
(1/ρ)
Yt = (YtA )ρ + (YtM )ρ
, ρ ∈ (0, 1]
Agriculture, A, which uses land, T , & labor LA :
α
A (1−α)
YtA = AA
.
t (T ) (Lt )
Manufacturing, M , which uses capital, K, structures, S, & labor LM :
α M (1−α)
σ
σ σ
YtM = AM
(Lt )
.
t (Kt ) + (St )
Land is fixed whereas structures and capital can be produced at a
relative price of 1 and they fully depreciate within one period.
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
8 / 41
Model
Production
Production of a final good, Y is CES in two input goods:
(1/ρ)
Yt = (YtA )ρ + (YtM )ρ
, ρ ∈ (0, 1]
Agriculture, A, which uses land, T , & labor LA :
α
A (1−α)
YtA = AA
.
t (T ) (Lt )
Manufacturing, M , which uses capital, K, structures, S, & labor LM :
α M (1−α)
σ
σ σ
YtM = AM
(Lt )
.
t (Kt ) + (St )
Land is fixed whereas structures and capital can be produced at a
relative price of 1 and they fully depreciate within one period.
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
8 / 41
Model
Production
The final good sector as well as the two intermediate sectors are
competitive.
⇒ In equilibrium, all factors of production: capital, structures, land and
labor receive their marginal product.
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
9 / 41
Model
Production
The final good sector as well as the two intermediate sectors are
competitive.
⇒ In equilibrium, all factors of production: capital, structures, land and
labor receive their marginal product.
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
9 / 41
Model
Individuals
Unit measure of men and women are born, and live for 2 periods.
Children do nothing.
Adults have one son and one daughter, make all economic choices.
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
10 / 41
Model
Individuals
Unit measure of men and women are born, and live for 2 periods.
Children do nothing.
Adults have one son and one daughter, make all economic choices.
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
10 / 41
Model
Individuals
Unit measure of men and women are born, and live for 2 periods.
Children do nothing.
Adults have one son and one daughter, make all economic choices.
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
10 / 41
Model
Model: Sequence of Events at Adulthood
HH is
Formed
Men Choose
Political Regime
Receive
Bequest
Hazan, Weiss, Zoabi
Men & Women
Choose Portfolio
Women’s Liberation as a Financial Innovation
Production,
Consumption,
Leave Bequest “Money”
Leave Land to offspring
July 2015
11 / 41
Model
Decision Making: Married Households
Individual i utility is given by:
U (cit , bt ) = log(cit ) + γ log(2bt ),
where i ∈ {m, f }.
Households choose consumption of adults and bequest to children.
Decision making is assumed to follow a Pareto Problem:
f
m
{cft , cm
t , bt } = argmax{θt log(ct ) + (1 − θt ) log(ct ) + γ log(2bt )},
subject to their budget constraint:
f
K
S
T
cm
t + ct + 2bt = rt Kt + rt St + rt T + wt ≡ It .
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
12 / 41
Model
Decision Making: Married Households
Individual i utility is given by:
U (cit , bt ) = log(cit ) + γ log(2bt ),
where i ∈ {m, f }.
Households choose consumption of adults and bequest to children.
Decision making is assumed to follow a Pareto Problem:
f
m
{cft , cm
t , bt } = argmax{θt log(ct ) + (1 − θt ) log(ct ) + γ log(2bt )},
subject to their budget constraint:
f
K
S
T
cm
t + ct + 2bt = rt Kt + rt St + rt T + wt ≡ It .
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
12 / 41
Model
Decision Making: Married Households
The Pareto weight of the female, θt , is determined by her relative
wealth.
When there are rights:
θt =
rtK Ktf + rtS Stf + rtT T /2
,
It
When there are no rights:
θt =
(1 − λ)(rtS Stf + rtT T /2)
.
It
1 − λ captures the fraction of a woman’s real assets she controls.
Under coverture, real assets remain in the woman’s name.
Husband gets rental income from the wife’s real assets, cannot sell.
λ is a reduced form way of capturing the woman’s partial control.
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
13 / 41
Model
Decision Making: Married Households
The Pareto weight of the female, θt , is determined by her relative
wealth.
When there are rights:
θt =
rtK Ktf + rtS Stf + rtT T /2
,
It
When there are no rights:
θt =
(1 − λ)(rtS Stf + rtT T /2)
.
It
1 − λ captures the fraction of a woman’s real assets she controls.
Under coverture, real assets remain in the woman’s name.
Husband gets rental income from the wife’s real assets, cannot sell.
λ is a reduced form way of capturing the woman’s partial control.
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
13 / 41
Model
Decision Making: Married Households
The Pareto weight of the female, θt , is determined by her relative
wealth.
When there are rights:
θt =
rtK Ktf + rtS Stf + rtT T /2
,
It
When there are no rights:
θt =
(1 − λ)(rtS Stf + rtT T /2)
.
It
1 − λ captures the fraction of a woman’s real assets she controls.
Under coverture, real assets remain in the woman’s name.
Husband gets rental income from the wife’s real assets, cannot sell.
λ is a reduced form way of capturing the woman’s partial control.
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
13 / 41
Model
Decision Making: Married Households
The Pareto weight of the female, θt , is determined by her relative
wealth.
When there are rights:
θt =
rtK Ktf + rtS Stf + rtT T /2
,
It
When there are no rights:
θt =
(1 − λ)(rtS Stf + rtT T /2)
.
It
1 − λ captures the fraction of a woman’s real assets she controls.
Under coverture, real assets remain in the woman’s name.
Husband gets rental income from the wife’s real assets, cannot sell.
λ is a reduced form way of capturing the woman’s partial control.
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
13 / 41
Model
Decision Making: Married Households
The Pareto weight of the female, θt , is determined by her relative
wealth.
When there are rights:
θt =
rtK Ktf + rtS Stf + rtT T /2
,
It
When there are no rights:
θt =
(1 − λ)(rtS Stf + rtT T /2)
.
It
1 − λ captures the fraction of a woman’s real assets she controls.
Under coverture, real assets remain in the woman’s name.
Husband gets rental income from the wife’s real assets, cannot sell.
λ is a reduced form way of capturing the woman’s partial control.
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
13 / 41
Model
Decision Making: Married Households
The Pareto weight of the female, θt , is determined by her relative
wealth.
When there are rights:
θt =
rtK Ktf + rtS Stf + rtT T /2
,
It
When there are no rights:
θt =
(1 − λ)(rtS Stf + rtT T /2)
.
It
1 − λ captures the fraction of a woman’s real assets she controls.
Under coverture, real assets remain in the woman’s name.
Husband gets rental income from the wife’s real assets, cannot sell.
λ is a reduced form way of capturing the woman’s partial control.
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
13 / 41
Model
Decision Making: Married Households
The Pareto weight of the female, θt , is determined by her relative
wealth.
When there are rights:
θt =
rtK Ktf + rtS Stf + rtT T /2
,
It
When there are no rights:
θt =
(1 − λ)(rtS Stf + rtT T /2)
.
It
1 − λ captures the fraction of a woman’s real assets she controls.
Under coverture, real assets remain in the woman’s name.
Husband gets rental income from the wife’s real assets, cannot sell.
λ is a reduced form way of capturing the woman’s partial control.
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
13 / 41
Model
Solution to Household Problem
Given I and θ, the solution to the married household problem is given
by:
θt It
cft =
,
1+γ
cm
t =
and
bt =
Hazan, Weiss, Zoabi
(1 − θt )It
,
1+γ
γIt
.
(1 + γ)
Women’s Liberation as a Financial Innovation
July 2015
14 / 41
Model
Portfolio Choice Before Marriage
Singles receive a bequest.
Divide money between structures and capital: bt−1 = Sti + Kti
Men always invest in the asset with highest return, as do women when
they have rights.
Women under coverture face tradeoff. Investing in capital:
Increases total household income (when rtK > rtS ).
Decreases relative household income, as money goes to husband.
Formally:
(
Stf = argmax log
θ(Stf )I(Stf )
1+γ
!
γI(Stf )
+ γ log 2
1+γ
!)
,
where Stf is the amount of the woman’s wealth she invests in
structures.
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
15 / 41
Model
Portfolio Choice Before Marriage
Singles receive a bequest.
Divide money between structures and capital: bt−1 = Sti + Kti
Men always invest in the asset with highest return, as do women when
they have rights.
Women under coverture face tradeoff. Investing in capital:
Increases total household income (when rtK > rtS ).
Decreases relative household income, as money goes to husband.
Formally:
(
Stf = argmax log
θ(Stf )I(Stf )
1+γ
!
γI(Stf )
+ γ log 2
1+γ
!)
,
where Stf is the amount of the woman’s wealth she invests in
structures.
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
15 / 41
Model
Portfolio Choice Before Marriage
Singles receive a bequest.
Divide money between structures and capital: bt−1 = Sti + Kti
Men always invest in the asset with highest return, as do women when
they have rights.
Women under coverture face tradeoff. Investing in capital:
Increases total household income (when rtK > rtS ).
Decreases relative household income, as money goes to husband.
Formally:
(
Stf = argmax log
θ(Stf )I(Stf )
1+γ
!
γI(Stf )
+ γ log 2
1+γ
!)
,
where Stf is the amount of the woman’s wealth she invests in
structures.
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
15 / 41
Model
Portfolio Choice Before Marriage
Singles receive a bequest.
Divide money between structures and capital: bt−1 = Sti + Kti
Men always invest in the asset with highest return, as do women when
they have rights.
Women under coverture face tradeoff. Investing in capital:
Increases total household income (when rtK > rtS ).
Decreases relative household income, as money goes to husband.
Formally:
(
Stf = argmax log
θ(Stf )I(Stf )
1+γ
!
γI(Stf )
+ γ log 2
1+γ
!)
,
where Stf is the amount of the woman’s wealth she invests in
structures.
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
15 / 41
Model
Portfolio Choice Before Marriage
Singles receive a bequest.
Divide money between structures and capital: bt−1 = Sti + Kti
Men always invest in the asset with highest return, as do women when
they have rights.
Women under coverture face tradeoff. Investing in capital:
Increases total household income (when rtK > rtS ).
Decreases relative household income, as money goes to husband.
Formally:
(
Stf = argmax log
θ(Stf )I(Stf )
1+γ
!
γI(Stf )
+ γ log 2
1+γ
!)
,
where Stf is the amount of the woman’s wealth she invests in
structures.
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
15 / 41
Model
Portfolio Choice Before Marriage
Singles receive a bequest.
Divide money between structures and capital: bt−1 = Sti + Kti
Men always invest in the asset with highest return, as do women when
they have rights.
Women under coverture face tradeoff. Investing in capital:
Increases total household income (when rtK > rtS ).
Decreases relative household income, as money goes to husband.
Formally:
(
Stf = argmax log
θ(Stf )I(Stf )
1+γ
!
γI(Stf )
+ γ log 2
1+γ
!)
,
where Stf is the amount of the woman’s wealth she invests in
structures.
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
15 / 41
Model
Portfolio Choice Before Marriage
Singles receive a bequest.
Divide money between structures and capital: bt−1 = Sti + Kti
Men always invest in the asset with highest return, as do women when
they have rights.
Women under coverture face tradeoff. Investing in capital:
Increases total household income (when rtK > rtS ).
Decreases relative household income, as money goes to husband.
Formally:
(
Stf = argmax log
θ(Stf )I(Stf )
1+γ
!
γI(Stf )
+ γ log 2
1+γ
!)
,
where Stf is the amount of the woman’s wealth she invests in
structures.
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
15 / 41
Model
Portfolio Choice Before Marriage
Under coverture, women’s optimal investment in structures, Stf , is
given by:
(i)
bt−1
(ii)



min bt−1 ,



K
S rt −rt

rtS Stm +(bt−1 +Ktm )rtK +rtT T 1− γ
+w 
2
rS
t
(1+γ)(rtK −rtS )
if
rtS ≥ rtK .
if
rtS < rtK .


Men’s optimal investment in structures, Stf , is given by:
(i)
bt−1
if
rtS > rtK .
(ii)
0
if
rtS < rtK .
(iii)
∈ (0, bt−1 )
if
rtS = rtK .
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
16 / 41
Model
Portfolio Choice Before Marriage
Under coverture, women’s optimal investment in structures, Stf , is
given by:
(i)
bt−1
(ii)



min bt−1 ,



K
S rt −rt

rtS Stm +(bt−1 +Ktm )rtK +rtT T 1− γ
+w 
2
rS
t
(1+γ)(rtK −rtS )
if
rtS ≥ rtK .
if
rtS < rtK .


Men’s optimal investment in structures, Stf , is given by:
(i)
bt−1
if
rtS > rtK .
(ii)
0
if
rtS < rtK .
(iii)
∈ (0, bt−1 )
if
rtS = rtK .
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
16 / 41
Model
Decision Making: Rights?
Men give women rights if their utility is higher under the rights regime:
(Utm )R > (Utm )N R .
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
17 / 41
Model
General Equilibrium
General equilibrium in the economy is a set of prices
{PtA , PtM , wt , rtK , rtS , rtT }, allocations in the production side
M
{Yt , YtM , YtA , T, Kt , St , LA
t , Lt }, portfolio choices of the household
f
f
{St , Stm , Kt , Ktm }, household allocation {cft , cm
t , bt }, and a series of
political regimes for each date t, such that:
1
2
3
M
Given prices and a rights regime, {Yt , YtM , YtA , T, Kt , St , LA
t , Lt } solve
f m
the production side and {ct , ct , bt } solve the household problem.
Markets clear.
The political regime at each time t is determined by (Utm )R compared to
(Utm )N R .
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
18 / 41
Model
General Equilibrium
General equilibrium in the economy is a set of prices
{PtA , PtM , wt , rtK , rtS , rtT }, allocations in the production side
M
{Yt , YtM , YtA , T, Kt , St , LA
t , Lt }, portfolio choices of the household
f
f
{St , Stm , Kt , Ktm }, household allocation {cft , cm
t , bt }, and a series of
political regimes for each date t, such that:
1
2
3
M
Given prices and a rights regime, {Yt , YtM , YtA , T, Kt , St , LA
t , Lt } solve
f m
the production side and {ct , ct , bt } solve the household problem.
Markets clear.
The political regime at each time t is determined by (Utm )R compared to
(Utm )N R .
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
18 / 41
Model
General Equilibrium
General equilibrium in the economy is a set of prices
{PtA , PtM , wt , rtK , rtS , rtT }, allocations in the production side
M
{Yt , YtM , YtA , T, Kt , St , LA
t , Lt }, portfolio choices of the household
f
f
{St , Stm , Kt , Ktm }, household allocation {cft , cm
t , bt }, and a series of
political regimes for each date t, such that:
1
2
3
M
Given prices and a rights regime, {Yt , YtM , YtA , T, Kt , St , LA
t , Lt } solve
f m
the production side and {ct , ct , bt } solve the household problem.
Markets clear.
The political regime at each time t is determined by (Utm )R compared to
(Utm )N R .
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
18 / 41
Model
General Equilibrium
General equilibrium in the economy is a set of prices
{PtA , PtM , wt , rtK , rtS , rtT }, allocations in the production side
M
{Yt , YtM , YtA , T, Kt , St , LA
t , Lt }, portfolio choices of the household
f
f
{St , Stm , Kt , Ktm }, household allocation {cft , cm
t , bt }, and a series of
political regimes for each date t, such that:
1
2
3
M
Given prices and a rights regime, {Yt , YtM , YtA , T, Kt , St , LA
t , Lt } solve
f m
the production side and {ct , ct , bt } solve the household problem.
Markets clear.
The political regime at each time t is determined by (Utm )R compared to
(Utm )N R .
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
18 / 41
Model
Model Predictions
Economic development goes through 3 phases:
S
K
Low AM
t , s.t. even with coverture rt = rt .
S
K
Medium AM
t , s.t. with coverture rt < rt (distortions), but still not
worth giving rights.
S
K
High AM
t , s.t. with coverture rt < rt (distortions), but men give rights,
S
so in practice distortion is gone (rt = rtK ).
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
19 / 41
Model
Model Predictions
Economic development goes through 3 phases:
S
K
Low AM
t , s.t. even with coverture rt = rt .
S
K
Medium AM
t , s.t. with coverture rt < rt (distortions), but still not
worth giving rights.
S
K
High AM
t , s.t. with coverture rt < rt (distortions), but men give rights,
S
so in practice distortion is gone (rt = rtK ).
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
19 / 41
Model
Model Predictions
Economic development goes through 3 phases:
S
K
Low AM
t , s.t. even with coverture rt = rt .
S
K
Medium AM
t , s.t. with coverture rt < rt (distortions), but still not
worth giving rights.
S
K
High AM
t , s.t. with coverture rt < rt (distortions), but men give rights,
S
so in practice distortion is gone (rt = rtK ).
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
19 / 41
Model
Model Predictions
Economic development goes through 3 phases:
S
K
Low AM
t , s.t. even with coverture rt = rt .
S
K
Medium AM
t , s.t. with coverture rt < rt (distortions), but still not
worth giving rights.
S
K
High AM
t , s.t. with coverture rt < rt (distortions), but men give rights,
S
so in practice distortion is gone (rt = rtK ).
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
19 / 41
Model
Numerical Example
M
Fix AA
t = 1 ∀t, and let At grow exogenously.
Take some parameters.
Solve for:
1
2
3
Parameters
Women never have rights.
Women always have rights.
Men choose when to give rights.
Numerical Methods
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
20 / 41
Model
Numerical Example
M
Fix AA
t = 1 ∀t, and let At grow exogenously.
Take some parameters.
Solve for:
1
2
3
Parameters
Women never have rights.
Women always have rights.
Men choose when to give rights.
Numerical Methods
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
20 / 41
Model
Numerical Example
M
Fix AA
t = 1 ∀t, and let At grow exogenously.
Take some parameters.
Solve for:
1
2
3
Parameters
Women never have rights.
Women always have rights.
Men choose when to give rights.
Numerical Methods
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
20 / 41
Model
Numerical Example
M
Fix AA
t = 1 ∀t, and let At grow exogenously.
Take some parameters.
Solve for:
1
2
3
Parameters
Women never have rights.
Women always have rights.
Men choose when to give rights.
Numerical Methods
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
20 / 41
Model
Numerical Example
M
Fix AA
t = 1 ∀t, and let At grow exogenously.
Take some parameters.
Solve for:
1
2
3
Parameters
Women never have rights.
Women always have rights.
Men choose when to give rights.
Numerical Methods
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
20 / 41
Model
Numerical Example
M
Fix AA
t = 1 ∀t, and let At grow exogenously.
Take some parameters.
Solve for:
1
2
3
Parameters
Women never have rights.
Women always have rights.
Men choose when to give rights.
Numerical Methods
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
20 / 41
Model
Women’s bargaining power (left) and Household Income
(right)
2.2
0.5
No Rights
Rights
optimal rights
No Rights
Rights
optimal rights
2
0.4
1.8
0.35
1.6
0.3
1.4
Log Income
theta
0.45
0.25
1.2
0.2
1
0.15
0.8
0.1
0.6
0.05
0.4
0
0.2
0
2
4
6
8
10
12
14
16
18
20
0
2
4
Time
Hazan, Weiss, Zoabi
6
8
10
12
14
16
18
20
Time
Women’s Liberation as a Financial Innovation
July 2015
21 / 41
Model
Fraction of Labor in Manufacturing (LM
t )
1
No Rights
Rights
optimal rights
0.9
Labor-Manufacturing
0.8
0.7
0.6
0.5
0.4
0
2
4
6
8
10
12
14
16
18
20
Time
Back to Data
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
22 / 41
Model
Value Added per Worker (left) & per Capital (right)
11
2.8
optimal rights
2.6
9
2.4
8
2.2
value added/capital
value added/worker
optimal rights
10
7
6
5
2
1.8
1.6
4
1.4
3
1.2
2
1
1
0.8
0
2
4
6
8
10
12
14
16
18
20
0
2
4
6
Time
Back to Data
More- Bequest
Hazan, Weiss, Zoabi
8
10
12
14
16
18
20
Time
More- Capital & Structures
More- Rents K, S
Women’s Liberation as a Financial Innovation
More- Rents T
More- UM
July 2015
23 / 41
Empirical Analysis
Overview
Testing Model Predictions
Exploit cross-state variation in timing of women’s economic rights.
1
Development → Rights
TFP in non-agriculture predicts rights being granted.
2
Rights → Development
US Population Census:
Rights → labor shifts towards non-agriculture.
US Census of Manufactures (firm level data):
Rights → Greater value added per worker & per capital.
Regional Interest Rates
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
24 / 41
Empirical Analysis
Overview
Testing Model Predictions
Exploit cross-state variation in timing of women’s economic rights.
1
Development → Rights
TFP in non-agriculture predicts rights being granted.
2
Rights → Development
US Population Census:
Rights → labor shifts towards non-agriculture.
US Census of Manufactures (firm level data):
Rights → Greater value added per worker & per capital.
Regional Interest Rates
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
24 / 41
Empirical Analysis
Overview
Testing Model Predictions
Exploit cross-state variation in timing of women’s economic rights.
1
Development → Rights
TFP in non-agriculture predicts rights being granted.
2
Rights → Development
US Population Census:
Rights → labor shifts towards non-agriculture.
US Census of Manufactures (firm level data):
Rights → Greater value added per worker & per capital.
Regional Interest Rates
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
24 / 41
Empirical Analysis
Overview
Testing Model Predictions
Exploit cross-state variation in timing of women’s economic rights.
1
Development → Rights
TFP in non-agriculture predicts rights being granted.
2
Rights → Development
US Population Census:
Rights → labor shifts towards non-agriculture.
US Census of Manufactures (firm level data):
Rights → Greater value added per worker & per capital.
Regional Interest Rates
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
24 / 41
Empirical Analysis
Overview
Testing Model Predictions
Exploit cross-state variation in timing of women’s economic rights.
1
Development → Rights
TFP in non-agriculture predicts rights being granted.
2
Rights → Development
US Population Census:
Rights → labor shifts towards non-agriculture.
US Census of Manufactures (firm level data):
Rights → Greater value added per worker & per capital.
Regional Interest Rates
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
24 / 41
Empirical Analysis
Overview
Testing Model Predictions
Exploit cross-state variation in timing of women’s economic rights.
1
Development → Rights
TFP in non-agriculture predicts rights being granted.
2
Rights → Development
US Population Census:
Rights → labor shifts towards non-agriculture.
US Census of Manufactures (firm level data):
Rights → Greater value added per worker & per capital.
Regional Interest Rates
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
24 / 41
Empirical Analysis
Overview
Testing Model Predictions
Exploit cross-state variation in timing of women’s economic rights.
1
Development → Rights
TFP in non-agriculture predicts rights being granted.
2
Rights → Development
US Population Census:
Rights → labor shifts towards non-agriculture.
US Census of Manufactures (firm level data):
Rights → Greater value added per worker & per capital.
Regional Interest Rates
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
24 / 41
Empirical Analysis
Overview
Timing of Women’s Rights by State: (Geddes & Lueck 2002)
1920
1910
1900
1890
1880
1870
1860
1850
1840
MA ME KS MD NY OH NH CO IL MN WY MS NE CA PA RI WI AR DE GA IA KY NV NC NJ MO CT ND SD OR VA IN AL MT SC VT WA WV UT OK MI TX ID TN
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
25 / 41
Empirical Analysis
TFP Predicts Rights
TFP Predicts Rights
A
Rightsst = β1 AM
st + β2 Ast + dt + λs + λs × t + controlsst + st
Ast is TFP in state s, year t, in non-agriculture (M ) or agriculture (A).
dt is year fixed effects, λs is state fixed effects, & λs × t is state specific
linear time trend.
Controls: South in 1870/1880 dummies, fraction women, fraction of
women in school, fraction of non-whites, territory, fraction under 35,
Fertility 10.
TFP data from Turner et. al. (2013). Other data from IPUMS.
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
26 / 41
Empirical Analysis
TFP Predicts Rights
TFP Predicts Rights
A
Rightsst = β1 AM
st + β2 Ast + dt + λs + λs × t + controlsst + st
Ast is TFP in state s, year t, in non-agriculture (M ) or agriculture (A).
dt is year fixed effects, λs is state fixed effects, & λs × t is state specific
linear time trend.
Controls: South in 1870/1880 dummies, fraction women, fraction of
women in school, fraction of non-whites, territory, fraction under 35,
Fertility 10.
TFP data from Turner et. al. (2013). Other data from IPUMS.
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
26 / 41
Empirical Analysis
TFP Predicts Rights
TFP Predicts Rights
A
Rightsst = β1 AM
st + β2 Ast + dt + λs + λs × t + controlsst + st
Ast is TFP in state s, year t, in non-agriculture (M ) or agriculture (A).
dt is year fixed effects, λs is state fixed effects, & λs × t is state specific
linear time trend.
Controls: South in 1870/1880 dummies, fraction women, fraction of
women in school, fraction of non-whites, territory, fraction under 35,
Fertility 10.
TFP data from Turner et. al. (2013). Other data from IPUMS.
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
26 / 41
Empirical Analysis
TFP Predicts Rights
TFP Predicts Rights
A
Rightsst = β1 AM
st + β2 Ast + dt + λs + λs × t + controlsst + st
Ast is TFP in state s, year t, in non-agriculture (M ) or agriculture (A).
dt is year fixed effects, λs is state fixed effects, & λs × t is state specific
linear time trend.
Controls: South in 1870/1880 dummies, fraction women, fraction of
women in school, fraction of non-whites, territory, fraction under 35,
Fertility 10.
TFP data from Turner et. al. (2013). Other data from IPUMS.
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
26 / 41
Empirical Analysis
TFP Predicts Rights
TFP Predicts Rights:
Table 1
Dependent Variable: Rights
(1)
Rights
AM
9.528∗∗∗
(2.909)
(2)
Rights
Probit
14.833∗∗∗
(5.019)
AA
10.168
(6.682)
No
19.690
(16.275)
No
FERT 10
(3)
Rights
(4)
Rights
(5)
Rights
9.332∗∗∗
(2.847)
8.175∗∗∗
(2.212)
9.158∗∗∗
(2.134)
(6)
Rights
Round Up
8.459∗∗∗
(1.635)
12.265∗
(6.287)
Yes
3.853
(9.462)
Yes
-5.726
(7.545)
Yes
-8.339
(4.993)
Yes
State dummies
No
No
No
Yes
Yes
Yes
State Time Trend
N
No
349
No
349
No
349
No
349
Yes
349
Yes
349
NOTE. Standard errors, clustered at the state level in parentheses. ∗ p < 0.10, ∗∗ p < 0.05, ∗∗∗ p < 0.01.
All regressions include year dummies, dummy for being a territory, having community property, equity
courts, fraction of female in school, fraction female, South×1870 and South×1880 dummies, fraction nonwhite, and fraction of adults under 35.
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
27 / 41
Empirical Analysis
Rights & Non-Agricultural Employment
Analysis – Population Census
1
Data from U.S. census (IPUMS).
2
See what happens to non-agricultural employment (industrialization)
dynamically after rights are given. Non-Agricultural Employment
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
28 / 41
Empirical Analysis
Rights & Non-Agricultural Employment
Analysis – Population Census
1
Data from U.S. census (IPUMS).
2
See what happens to non-agricultural employment (industrialization)
dynamically after rights are given. Non-Agricultural Employment
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
28 / 41
Empirical Analysis
Rights & Non-Agricultural Employment
Male Non-Agriculture Employment Over Time
1.0
0.895
0.9
0.779
0.8
0.717
0.7
0.919
0.839
0.660
0.721
0.714
0.673
0.656
0.607
0.6
0.5
0.543
0.480
0.444
0.456
0.477
0.469
0.430
0.4
0.355
0.305
0.3
0.273
0.248
0.188
0.2
0.222
0.1
1850
1860
1870
1880
1890
1900
1910
1920
year
National Average
10th Percentile
90th Percentile
By Rights
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
29 / 41
Empirical Analysis
Rights & Non-Agricultural Employment
Empirical Specification
LM
st =
X
k
αk · rightskst + λs + dt + λs × t + controlsst + st
LM
st is the fraction of workers in non-agricultural sectors in state s in
year t, t ∈ {1850, 1860, . . . , 1920}.
rightskst is a series of dummy variables set equal to one if a state had
granted rights k years ago, where
k ∈ {≤ −30, −20, −10, 0, 10, 20, ≥ 30}.
dt is year fixed effects, λs is state fixed effects, & λs × t is state specific
linear time trend.
controlsst include south in 1870/1880 dummies, fraction women,
fraction of women in school, fraction of non-whites, territory, fraction
under 35
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
30 / 41
Empirical Analysis
Rights & Non-Agricultural Employment
Empirical Specification
LM
st =
X
k
αk · rightskst + λs + dt + λs × t + controlsst + st
LM
st is the fraction of workers in non-agricultural sectors in state s in
year t, t ∈ {1850, 1860, . . . , 1920}.
rightskst is a series of dummy variables set equal to one if a state had
granted rights k years ago, where
k ∈ {≤ −30, −20, −10, 0, 10, 20, ≥ 30}.
dt is year fixed effects, λs is state fixed effects, & λs × t is state specific
linear time trend.
controlsst include south in 1870/1880 dummies, fraction women,
fraction of women in school, fraction of non-whites, territory, fraction
under 35
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
30 / 41
Empirical Analysis
Rights & Non-Agricultural Employment
Empirical Specification
LM
st =
X
k
αk · rightskst + λs + dt + λs × t + controlsst + st
LM
st is the fraction of workers in non-agricultural sectors in state s in
year t, t ∈ {1850, 1860, . . . , 1920}.
rightskst is a series of dummy variables set equal to one if a state had
granted rights k years ago, where
k ∈ {≤ −30, −20, −10, 0, 10, 20, ≥ 30}.
dt is year fixed effects, λs is state fixed effects, & λs × t is state specific
linear time trend.
controlsst include south in 1870/1880 dummies, fraction women,
fraction of women in school, fraction of non-whites, territory, fraction
under 35
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
30 / 41
Empirical Analysis
Rights & Non-Agricultural Employment
Empirical Specification
LM
st =
X
k
αk · rightskst + λs + dt + λs × t + controlsst + st
LM
st is the fraction of workers in non-agricultural sectors in state s in
year t, t ∈ {1850, 1860, . . . , 1920}.
rightskst is a series of dummy variables set equal to one if a state had
granted rights k years ago, where
k ∈ {≤ −30, −20, −10, 0, 10, 20, ≥ 30}.
dt is year fixed effects, λs is state fixed effects, & λs × t is state specific
linear time trend.
controlsst include south in 1870/1880 dummies, fraction women,
fraction of women in school, fraction of non-whites, territory, fraction
under 35
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
30 / 41
Empirical Analysis
Rights & Non-Agricultural Employment
The Dynamics Response of Non-Agriculture Employment
Table 1
Dependent Variable: Fraction of Workers in Non-Agriculture – Basic Coding
≥ 3 decades before
2 decades before
(1)
-0.013
(0.032)
(2)
-0.019
(0.031)
(3)
-0.033
(0.026)
(4)
-0.039∗
(0.023)
(5)
-0.030
(0.022)
(6)
0.007
(0.019)
0.021
(0.021)
0.022
(0.022)
0.011
(0.022)
0.008
(0.019)
0.008
(0.017)
0.010
(0.012)
0
0
0
0
0
0
Rights given
0.035∗∗∗
(0.011)
0.036∗∗∗
(0.010)
0.038∗∗∗
(0.011)
0.036∗∗∗
(0.010)
0.035∗∗∗
(0.010)
0.019∗∗
(0.007)
1 decade after
0.072∗∗∗
(0.018)
0.074∗∗∗
(0.016)
0.077∗∗∗
(0.016)
0.070∗∗∗
(0.016)
0.069∗∗∗
(0.016)
0.044∗∗∗
(0.012)
2 decades after
0.088∗∗∗
(0.028)
0.092∗∗∗
(0.027)
0.101∗∗∗
(0.027)
0.086∗∗∗
(0.027)
0.084∗∗∗
(0.025)
0.059∗∗∗
(0.015)
≥ 3 decades after
0.106∗∗∗
(0.039)
0.115∗∗∗
(0.037)
0.124∗∗∗
(0.035)
0.104∗∗∗
(0.036)
0.100∗∗∗
(0.033)
0.077∗∗∗
(0.019)
Yes
1 decade before
1
Year dummies
Yes
Yes
Yes
Yes
Yes
State dummies
Yes
Yes
Yes
Yes
Yes
Yes
Territory
Yes
Yes
Yes
Yes
Yes
Yes
South×1870
No
Yes
Yes
Yes
Yes
Yes
South×1880
No
Yes
Yes
Yes
Yes
Yes
Fraction Female
No
Yes
Yes
Yes
Yes
Yes
Fraction of Female in school
No
No
Yes
Yes
Yes
Yes
Fraction Non-White
No
No
No
Yes
Yes
Yes
Fraction under 35
No
No
No
No
Yes
Yes
State time trend
N
No
356
No
356
No
356
No
356
No
356
Yes
356
Hazan, Weiss,
Zoabi using state population
Women’s
Liberation
as aerrors,
Financial
Innovation
July 2015
NOTE. Estimated
weights.
Standard
clustered
at the state level in parentheses. ∗ p < 0.10,
31 / 41
Empirical Analysis
Rights & Non-Agricultural Employment
The Dynamics Response of Non-Agriculture Employment
0.14
Change in Employment in the Non-Agricultural Sector
0.12
0.1
0.08
0.06
0.04
0.02
0
>=-30
-0.02
-0.04
Hazan, Weiss, Zoabi
-20
-10
0
10
20
>=30
Decades since (until) rights granted
estimate
95% CI
Women’s Liberation as a Financial Innovation
July 2015
32 / 41
Empirical Analysis
Rights & Non-Agricultural Employment
The Dynamics Response of Non-Agriculture Employment – Robustness 1
Table 2
Dependent Variable: Fraction of Workers in Non-Agriculture – Alternative Coding
≥ 3 decades before
2 decades before
(1)
-0.004
(0.030)
(2)
-0.010
(0.030)
(3)
-0.030
(0.026)
(4)
-0.038
(0.023)
(5)
-0.030
(0.022)
(6)
-0.029∗∗
(0.012)
0.009
(0.021)
0.008
(0.021)
0.000
(0.022)
-0.002
(0.019)
-0.003
(0.017)
-0.007
(0.012)
0
0
0
0
0
0
Rights given
0.032∗∗∗
(0.010)
0.030∗∗∗
(0.009)
0.030∗∗∗
(0.010)
0.027∗∗
(0.010)
0.027∗∗
(0.011)
0.024∗∗∗
(0.008)
1 decade after
0.045∗∗
(0.018)
0.042∗∗
(0.018)
0.045∗∗
(0.018)
0.040∗∗
(0.019)
0.037∗∗
(0.018)
0.050∗∗∗
(0.015)
2 decades after
0.062∗∗
(0.028)
0.061∗∗
(0.028)
0.068∗∗
(0.027)
0.056∗∗
(0.027)
0.052∗∗
(0.026)
0.071∗∗∗
(0.019)
≥3 decades after
0.066∗
(0.036)
0.070∗
(0.036)
0.077∗∗
(0.036)
0.061∗
(0.035)
0.054
(0.033)
0.087∗∗∗
(0.024)
Yes
1 decade before
2
Year dummies
Yes
Yes
Yes
Yes
Yes
State dummies
Yes
Yes
Yes
Yes
Yes
Yes
Territory
Yes
Yes
Yes
Yes
Yes
Yes
South×1870
No
Yes
Yes
Yes
Yes
Yes
South×1880
No
Yes
Yes
Yes
Yes
Yes
Fraction Female
No
Yes
Yes
Yes
Yes
Yes
Fraction of Female in school
No
No
Yes
Yes
Yes
Yes
Fraction Non-White
No
No
No
Yes
Yes
Yes
Fraction under 35
No
No
No
No
Yes
Yes
State time trend
N
No
356
No
356
No
356
No
356
No
356
Yes
356
Hazan, Weiss,
Women’s Liberation
as a Financial
July∗ 2015
NOTE. Zoabi
Estimated using state population
weights. Standard
errors, Innovation
clustered at the state level in parentheses.
33 / 41
Empirical Analysis
Rights & Non-Agricultural Employment
The Dynamics Response of Non-Agriculture Employment – Robustness 2
Table 3
Robustness
(1)
Industry
(2)
Occupation
(3)
Drop 1890
(4)
Alternate FE
≥ 3 decades before
-0.001
(0.012)
0.002
(0.014)
-0.001
(0.021)
0.009
(0.018)
(5)
w/o Rights
btwn. 1870-1880
0.017
(0.03)
2 decades before
0.009
(0.011)
0.013
(0.012)
0.002
(0.007)
0.003
(0.007)
0.028
(0.023)
1 decade before
0
0
0
0
0.015∗∗
(0.007)
0.019∗∗∗
(0.007)
0.019∗∗
(0.008)
0.015∗∗
(0.007)
0.014
(0.010)
1 decade after
0.039∗∗∗
(0.011)
0.043∗∗∗
(0.012)
0.038∗∗∗
(0.012)
0.031∗∗
(0.012)
0.045∗∗∗
(0.012)
2 decades after
0.053∗∗∗
(0.014)
0.059∗∗∗
(0.015)
0.058∗∗∗
(0.018)
0.047∗∗∗
(0.017)
0.067∗∗∗
(0.019)
≥ 3 decades after
0.069∗∗∗
(0.019)
356
0.081∗∗∗
(0.021)
356
0.077∗∗∗
(0.022)
308
0.058∗∗∗
(0.021)
356
0.088∗∗∗
(0.023)
197
3
0
Rights given
N
NOTE. Estimated using state population weights. Standard errors, clustered at the state level in parentheses. ∗
p < 0.10, ∗∗ p < 0.05, ∗∗∗ p < 0.01. All regressions include year dummies, state dummies, territory dummies, south
interacted with 1870 and 1880, fraction female, fraction of female in school, fraction non white, fraction under 35,
and state linear time trend.
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
34 / 41
Empirical Analysis
Rights & Value Added (Manufacturing)
Data – Manufactures Census
1
Data from U.S. Census of Manufactures, via Atack and Bateman (1999).
2
Repeated cross section of firms from 1850-1880.
3
See what happens to value-added per worker & per capital after rights
at firm level.
Mean value added per worker (sd): $678 (847). Per capital: 2.2 (3.8)
1860 $ (Hoover 1960)
16,647 firm in 122 industries (after cleaning)
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
35 / 41
Empirical Analysis
Rights & Value Added (Manufacturing)
Data – Manufactures Census
1
Data from U.S. Census of Manufactures, via Atack and Bateman (1999).
2
Repeated cross section of firms from 1850-1880.
3
See what happens to value-added per worker & per capital after rights
at firm level.
Mean value added per worker (sd): $678 (847). Per capital: 2.2 (3.8)
1860 $ (Hoover 1960)
16,647 firm in 122 industries (after cleaning)
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
35 / 41
Empirical Analysis
Rights & Value Added (Manufacturing)
Data – Manufactures Census
1
Data from U.S. Census of Manufactures, via Atack and Bateman (1999).
2
Repeated cross section of firms from 1850-1880.
3
See what happens to value-added per worker & per capital after rights
at firm level.
Mean value added per worker (sd): $678 (847). Per capital: 2.2 (3.8)
1860 $ (Hoover 1960)
16,647 firm in 122 industries (after cleaning)
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
35 / 41
Empirical Analysis
Rights & Value Added (Manufacturing)
Data – Manufactures Census
1
Data from U.S. Census of Manufactures, via Atack and Bateman (1999).
2
Repeated cross section of firms from 1850-1880.
3
See what happens to value-added per worker & per capital after rights
at firm level.
Mean value added per worker (sd): $678 (847). Per capital: 2.2 (3.8)
1860 $ (Hoover 1960)
16,647 firm in 122 industries (after cleaning)
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
35 / 41
Empirical Analysis
Rights & Value Added (Manufacturing)
Data – Manufactures Census
1
Data from U.S. Census of Manufactures, via Atack and Bateman (1999).
2
Repeated cross section of firms from 1850-1880.
3
See what happens to value-added per worker & per capital after rights
at firm level.
Mean value added per worker (sd): $678 (847). Per capital: 2.2 (3.8)
1860 $ (Hoover 1960)
16,647 firm in 122 industries (after cleaning)
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
35 / 41
Empirical Analysis
Rights & Value Added (Manufacturing)
Data – Manufactures Census
1
Data from U.S. Census of Manufactures, via Atack and Bateman (1999).
2
Repeated cross section of firms from 1850-1880.
3
See what happens to value-added per worker & per capital after rights
at firm level.
Mean value added per worker (sd): $678 (847). Per capital: 2.2 (3.8)
1860 $ (Hoover 1960)
16,647 firm in 122 industries (after cleaning)
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
35 / 41
Empirical Analysis
Rights & Value Added (Manufacturing)
Empirical Specification
vadjist =
X
k
αk · rightskst + dt + λs + Ii + λs × t + I × t + controlsst + jist
vadjist is the value added of firm j, belong to industry i, operates in
state s, in year t, d ∈ {L, K}.
rightskst is a series of dummy variables set equal to one if a state s had
granted rights k years ago at time t, where
k ∈ {≤ −20, −10, 0, 10, ≥ 20}.
dt is year fixed effects, λs is state fixed effects, Ii is industry fixed
effects, & λs × t & Ii × t are state & industry specific linear time trend.
controlsst include south in 1870/1880 dummies.
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
36 / 41
Empirical Analysis
Rights & Value Added (Manufacturing)
Empirical Specification
vadjist =
X
k
αk · rightskst + dt + λs + Ii + λs × t + I × t + controlsst + jist
vadjist is the value added of firm j, belong to industry i, operates in
state s, in year t, d ∈ {L, K}.
rightskst is a series of dummy variables set equal to one if a state s had
granted rights k years ago at time t, where
k ∈ {≤ −20, −10, 0, 10, ≥ 20}.
dt is year fixed effects, λs is state fixed effects, Ii is industry fixed
effects, & λs × t & Ii × t are state & industry specific linear time trend.
controlsst include south in 1870/1880 dummies.
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
36 / 41
Empirical Analysis
Rights & Value Added (Manufacturing)
Empirical Specification
vadjist =
X
k
αk · rightskst + dt + λs + Ii + λs × t + I × t + controlsst + jist
vadjist is the value added of firm j, belong to industry i, operates in
state s, in year t, d ∈ {L, K}.
rightskst is a series of dummy variables set equal to one if a state s had
granted rights k years ago at time t, where
k ∈ {≤ −20, −10, 0, 10, ≥ 20}.
dt is year fixed effects, λs is state fixed effects, Ii is industry fixed
effects, & λs × t & Ii × t are state & industry specific linear time trend.
controlsst include south in 1870/1880 dummies.
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
36 / 41
Empirical Analysis
Rights & Value Added (Manufacturing)
Empirical Specification
vadjist =
X
k
αk · rightskst + dt + λs + Ii + λs × t + I × t + controlsst + jist
vadjist is the value added of firm j, belong to industry i, operates in
state s, in year t, d ∈ {L, K}.
rightskst is a series of dummy variables set equal to one if a state s had
granted rights k years ago at time t, where
k ∈ {≤ −20, −10, 0, 10, ≥ 20}.
dt is year fixed effects, λs is state fixed effects, Ii is industry fixed
effects, & λs × t & Ii × t are state & industry specific linear time trend.
controlsst include south in 1870/1880 dummies.
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
36 / 41
Empirical Analysis
Rights & Value Added (Manufacturing)
The Dynamic Response of Value Added
Table 4
Effects of Rights on Firms
≥ 2 decades before
1 decade before
(2)
value added
per capital
-0.051
(0.271)
4
0
0
Rights given
67.710
(51.519)
0.620∗∗∗
(0.216)
1 decade after
201.938∗∗
(95.290)
1.353∗∗∗
(0.330)
≥ 2 decades after
187.207
(131.159)
1.987∗∗∗
(0.412)
Year dummies
Yes
Yes
State dummies
Yes
Yes
Industry dummies
Yes
Yes
South×1870
Yes
Yes
South×1880
Yes
Yes
Industry time trend
Yes
Yes
Yes
16,647
0.211
Yes
16,647
0.243
State time trend
N
R2
∗∗
(1)
value added
per worker
30.081
(66.786)
NOTE. Standard errors, clustered at the state-year level in parentheses. ∗ p < 0.10,
p < 0.05, ∗∗∗ p < 0.01.
more
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
37 / 41
Empirical Analysis
Rights & Value Added (Manufacturing)
The Dynamic Response of Value Added
Table 5
Effects of Rights on Firms
≥ 2 decades before
1 decade before
(2)
value added
per capital
-0.459
(0.441)
5
0
0
Rights given
193.769∗∗
(90.251)
0.963∗∗∗
(0.333)
1 decade after
283.734∗∗
(137.417)
1.459∗∗∗
(0.518)
≥ 2 decades after
325.968∗
(179.516)
2.286∗∗∗
(0.642)
Year dummies
Yes
Yes
State dummies
Yes
Yes
Industry dummies
Yes
Yes
South×1870
Yes
Yes
South×1880
Yes
Yes
Industry time trend
Yes
Yes
Yes
16,647
0.212
Yes
16,647
0.244
State time trend
N
R2
∗∗
(1)
value added
per worker
-103.194
(101.103)
NOTE. Standard errors, clustered at the state-year level in parentheses. ∗ p < 0.10,
p < 0.05, ∗∗∗ p < 0.01.
more
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
38 / 41
1920
Economic Rights vs. Political Rights
TN
coefficient = -0.092 t = -0.81
TX
MI
OK
UT
WV
WA
MT
OR
CA
WY
CO
1860
economic rights
1880
1900
ID
NV
IL
KS
VT
AL
SC
IN
ND
SD VA
CT
MO
AR WI
IANJ
GA
DE
KY
NC
RI
NE PA
MS
MN
NH
NY OH
MD
ME
1840
MA
1870
1880
1890
1900
1910
1920
suffrage
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
39 / 41
Conclusions
Conclusions
Examine how rules regarding asset ownership upon marriage affected
economic allocations with coverture.
Argue that development caused men to give rights to undo
misallocations.
Examine mechanism in a model.
Verify with cross-state evidence.
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
40 / 41
Conclusions
Conclusions
Examine how rules regarding asset ownership upon marriage affected
economic allocations with coverture.
Argue that development caused men to give rights to undo
misallocations.
Examine mechanism in a model.
Verify with cross-state evidence.
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
40 / 41
Conclusions
Conclusions
Examine how rules regarding asset ownership upon marriage affected
economic allocations with coverture.
Argue that development caused men to give rights to undo
misallocations.
Examine mechanism in a model.
Verify with cross-state evidence.
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
40 / 41
Conclusions
Conclusions
Examine how rules regarding asset ownership upon marriage affected
economic allocations with coverture.
Argue that development caused men to give rights to undo
misallocations.
Examine mechanism in a model.
Verify with cross-state evidence.
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
40 / 41
Thank you!
Hazan, Weiss, Zoabi
Women’s Liberation as a Financial Innovation
July 2015
41 / 41
Portfolio Choice before and after the 1870 Married
Women’s Property Act
Shopkeepers’ Wives, Died 1901-1903
Married
Tot. Records
Ave. Real
(£)
Ave. Moveable
(£)
Ave. Total
(£)
123
518
958
435
762
1,299
1,720
1,734
Before 1870
After 1870
Source: Combs (2005), Table 2.
Back
TFP by Sector: UK 1780s- 1860s
Table 2: Sources of Industrial Revolution Efficiency Advance, 1780s-1860s
Sector
Contribution to
National Efficiency
Growth Rate (%
per year)
All Textiles
2.3
0.11
0.25
Iron and Steel
Coal Mining
Transport
1.8
0.2
1.5
0.01
0.02
0.08
0.02
0.00
0.12
Agriculture
0.4
0.30
0.11
Identified Advance
-
0.51
0.49
Whole Economy
-
1.00
0.58
Source: Clark, 2007, table 12.1.
Back
Efficiency Share
Growth of value
Rate (%)
added
10
Interest Rates in 1893-7 and Years Since Rights
CO
WA
coefficient = -0.032 t = -2.26
Annual Interest Rate
6
8
WA
TX
TX
UT
AL
TX
SC
TN
MI
IN
TN
ARNE
GA
OR
MN
CA
MO
MO
KY MN
MN
WI
CA
VA MO
PA IL
RI
PA
NY ME
OH
MD
NY
4
CT
OH
MA
-20
0
20
years since rights
interest rate
Fitted values
Source: Breckenridge 1898
Back
40
60
Real Returns - stocks and short bonds (Siegel 1992)
244
J.J. Se&,
The real rute
of tnterest
from 1800-1990
-I-
MEHRA-PRESCOm
PERIOD
3
:
‘,
2
0
‘,
------
-3
~~
1800
10
FREE
20
_~
RATE
,:
L
i
30
Fig. 6. Real returns
~_~
40
50
~
60
_~
70
80
- stocks and short bonds,
/.--~
90
~__
1900
30-year
1. I>,,_.I
; ,,’
‘-
UKRISKFREEFLATE
~_~
,,
:
‘, :
USSTOCKS
US RISK
-2
,,’ ”
,,‘L
: :
:
-1
Back
I’
,:
,. ,*
,‘.1
:
1
10
~~
20
centered
~~
30
40
,“, ,,’
.,,,*y ‘, :
‘,
,,
.~~~
~~~
50
60
movmg average.
70
I
l-
:
80
1990
1806-1990.
analysis presented
in table 2. Utilizing the data on nominal stock returns
computed by Schwert (1990) and the data on the price level developed in this
paper, the real returns
on U.S. stocks are summarized
in table la and
Returns to Farmland (Clark 2010)
Figure 5: The Return on Land and on Rent Charges, 1170-2003 (by decade)
Back
Notes: For the years before 1350 the land returns are the moving average of 3 decades because in
More
Table 6
Effects of Rights on Firms
≥ 2 decades before
1 decade before
(1)
Capital/Worker
3.139
(55.435)
(2)
Capital
-1581.670∗
(901.675)
(3)
Workers
-5.527∗∗∗
(1.458)
6
0
0
0
Rights given
-101.692
(65.628)
1807.401
(1206.800)
9.385∗∗∗
(1.915)
1 decade after
-171.834
(140.471)
3013.081
(2235.417)
21.436∗∗∗
(3.115)
≥ 2 decades after
-379.233
(258.426)
16,647
0.193
-3810.320
(3596.823)
16,647
0.143
22.187∗∗∗
(5.558)
16,647
0.132
N
r2
NOTE. Standard errors, clustered at the state-year level in parentheses. ∗ p < 0.10, ∗∗ p < 0.05, ∗∗∗ p < 0.01.
Back
More- Alternative Coding
Table 7
Effects of Rights on Firms
≥ 2 decades before
1 decade before
(1)
Capital/Worker
12.218
(69.554)
(2)
Capital
-280.401
(808.462)
(3)
Workers
-3.986∗∗∗
(1.234)
7
0
0
0
Rights given
-61.736
(66.937)
918.187
(1095.491)
8.374∗∗∗
(1.736)
1 decade after
-149.527
(147.392)
1997.335
(1870.405)
19.912∗∗∗
(2.801)
≥ 2 decades after
-342.511
(276.077)
16,647
0.193
-8137.454∗∗∗
(2969.339)
16,647
0.143
15.903∗∗∗
(5.194)
16,647
0.133
N
r2
NOTE. Standard errors, clustered at the state-year level in parentheses. ∗ p < 0.10, ∗∗ p < 0.05, ∗∗∗ p < 0.01.
Back
Composition of Wealth: England and the U.S. (Pikkety 2014)
Capital in the United States, 1770-1910 (Pikkety 2014, Figure 4.6)
Capital in Britain, 1700-1910 (Piketty 2014, Figure 3.1)
800%
800%
Net foreign capital
700%
Value of national capital (% national income)
Value of national capital (% national income)
700%
600%
500%
400%
300%
200%
1750
Agricultural land
Back
Housing
Agricultural land
500%
400%
300%
200%
100%
100%
0%
1700
Other domestic capital
600%
1810
Housing
1850
Other domestic capital
1880
Net foreign capital
1910
0%
1770
1810
1850
1880
1910
Numerical Example – Solution Method
In every t, take AM
t and bt−1 as given.
back
1
Guess wt , rtK , rtS , rtT and infer portfolio allocations for men and women,
and thus Kt and St .
2
A
Using the production side, solve for LM
t and Lt .
3
A
K S
T
Using Kt , St , T, LM
t , and Lt , infer wt , rt , rt and rt from FOCs.
4
Update guess and iterate until convergence.
Numerical Example – Solution Method
In every t, take AM
t and bt−1 as given.
back
1
Guess wt , rtK , rtS , rtT and infer portfolio allocations for men and women,
and thus Kt and St .
2
A
Using the production side, solve for LM
t and Lt .
3
A
K S
T
Using Kt , St , T, LM
t , and Lt , infer wt , rt , rt and rt from FOCs.
4
Update guess and iterate until convergence.
Numerical Example – Solution Method
In every t, take AM
t and bt−1 as given.
back
1
Guess wt , rtK , rtS , rtT and infer portfolio allocations for men and women,
and thus Kt and St .
2
A
Using the production side, solve for LM
t and Lt .
3
A
K S
T
Using Kt , St , T, LM
t , and Lt , infer wt , rt , rt and rt from FOCs.
4
Update guess and iterate until convergence.
Numerical Example – Solution Method
In every t, take AM
t and bt−1 as given.
back
1
Guess wt , rtK , rtS , rtT and infer portfolio allocations for men and women,
and thus Kt and St .
2
A
Using the production side, solve for LM
t and Lt .
3
A
K S
T
Using Kt , St , T, LM
t , and Lt , infer wt , rt , rt and rt from FOCs.
4
Update guess and iterate until convergence.
Numerical Example – Solution Method
In every t, take AM
t and bt−1 as given.
back
1
Guess wt , rtK , rtS , rtT and infer portfolio allocations for men and women,
and thus Kt and St .
2
A
Using the production side, solve for LM
t and Lt .
3
A
K S
T
Using Kt , St , T, LM
t , and Lt , infer wt , rt , rt and rt from FOCs.
4
Update guess and iterate until convergence.
Numerical Example – Parameters
We solve the model using the following (illustrative) parameter values:
back
Weight on Children
γ=1
Women’s share of land
λ = 0.5
Elast. Subst. btw. Y M and Y A
ρ = 0.9
Elast. Subst. btw. K and S
σ = 0.5
Capital/Land Share Inc.
α = 0.5
Land
T =1
Tech in Land
AA
t =1
Bequests (bt )
0.8
No Rights
Rights
optimal rights
0.6
0.4
0.2
log(b)
0
-0.2
-0.4
-0.6
-0.8
-1
-1.2
0
2
4
6
8
10
Time
Back
12
14
16
18
20
Capital (Kt ) and Structures (St )
0.5
1.5
No Rights
Rights
optimal rights
No Rights
Rights
optimal rights
1
0
0.5
Log Structures
Log Capital
-0.5
0
-0.5
-1
-1.5
-1
-2
-1.5
-2.5
-2
0
2
4
6
8
10
12
14
16
18
0
20
2
4
6
8
10
Time
Time
Back
12
14
16
18
20
Returns to Capital (rtK ) and Structures (rtS )
2
2
rs , no rights
rk , no rights
rs , rights
1.8
rk , rights
1.8
optimal rights
optimal rights
1.6
1.6
1.4
Return to structure
Return to capital
1.4
1.2
1
0.8
1.2
1
0.8
0.6
0.6
0.4
0.4
0.2
0.2
0
0
0
2
4
6
8
10
12
14
16
18
20
0
Returns to Capital
Back
2
4
6
8
10
Time
Time
12
14
16
18
20
Returns to Land (rtT )
0.4
rt , no rights
r , rights
t
optimal rights
0.35
Return to land
0.3
0.25
0.2
0.15
0.1
0
2
4
6
8
10
Time
Returns to Land
National Portfolio
Back
12
14
16
18
20
Difference in Men’s Utility: Rights - No Rights
mens utility, no rights
mens utility, E.P.N.
2
1.5
Um
1
0.5
0
-0.5
0
2
4
6
8
10
Time
Back
12
14
16
18
20
Regional Interest Rate – Breckenridge (1898)
Denver, CO
Tacoma, WA
Little Rock, AR
Portland, OR
Birmingham, AL
Savannah, GA
Mobile, AL
Duluth, MN
Charleston, SC
Kansas City, MO
Louisville, KY
St. Paul, MN
Cleveland, OH
Milwaukee, WI
Memphis, TN
Richmond, VA
St. Louis, MO
Pittsburg, PA
Cincinnati, OH
Philadelphia, PA
Baltimore, MD
Boston, MA
0
1
2
3
4
5
the average interest rate
Back
6
7
8
9
Cross State Comparison of Non-Agriculture Employment
0.80
0.75
0.72
0.68
0.70
Fraction of Workers in the Non-Agricultural Sector
0.63
0.56
0.50
0.48
0.44
0.55
0.54
0.52
0.51
0.43
0.63
0.61
0.59
0.60
0.71
0.67
0.48
0.46
0.45
0.46
1890
1900
0.42
0.40
0.34
0.31
0.30
0.20
0.10
0.00
1850
1860
1870
1880
Year
Rights
Back
No Rights
All
1910
1920
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