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Introduction Historical context Model Data Empirical results Conclusions Bankruptcy and Investment Evidence from Changes in Marital Property Laws in the U.S. South, 1840-1850. Peter Koudijs (Stanford & NBER) Laura Salisbury (York University & NBER) November 2015 1/27

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Introduction Historical context Model Data Empirical results Conclusions

Bankruptcy and InvestmentEvidence from Changes in Marital Property Laws in the U.S.

South, 1840-1850.

Peter Koudijs (Stanford & NBER) Laura Salisbury (YorkUniversity & NBER)

November 2015

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Introduction Historical context Model Data Empirical results Conclusions

Introduction

How does personal bankruptcy affect household investment?

Fresh start: stimulates entrepreneurshipCredit market implications: financing more costly / more likelyto be rejectedTrade-off: protection vs credit constraints

Evaluate trade-off empirically

Exogenous variation in protection

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Introduction Historical context Model Data Empirical results Conclusions

This paper

U.S. South: Married Women Property Laws in the 1840s

Before: upon marriage, husband (virtually) unrestrictedownership of wife’s assets, full-recourse loansAfter: wife’s estate held in trust; could not be seized byhusband’s creditors; only used for necessities.Both before and after: married couple considered a single legalunit, governed by husband.Law changes not retroactive

Consequences

Inability to use wife’s assets as collateral, wife unable tocontract loans in her own nameProvides downside protection, world without bankruptcy code

Compare couples married before/after law change

Net effect on household investment in 1850 Census

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Introduction Historical context Model Data Empirical results Conclusions

Related literature

Macro

Livshits et al. (2007), Chatterjee et al. (2007)

Micro

Gropp et al. (1997), Fan and White (2003), Berkowitz andWhite (2004), Berger et al. (2011) and Severino et al. (2013)(Homestead) exemptions in bankruptcy: differences acrossstatesImpact of exemptions on top of general bankruptcy protectionGeneral equilibrium effects

Married women’s property laws in the United States

Impact on women’s economic activity (variation at state level):Kahn (1996): patenting; Inwood and Van Sligtenhorst (2004):property holdings; Geddes et al (2012): school attendance.Decision to introduce laws: Geddes and Lueck (2002); Doepkeand Tertilt (2009).

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Introduction Historical context Model Data Empirical results Conclusions

Outline

1 Historical context2 Model3 Data4 Empirical results

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Introduction Historical context Model Data Empirical results Conclusions

American South 1840s

Plantation economy

2/3 families in agriculture in 1850 CensusApprox. 1/4 plantation owners (Wright 2006)

Financial system

Well-developed; slaves and plantations used as collateral(Kilbourne 1995, 2006)Access to loans North, trade-credit UKNo dismissal of debt if insolvent, debtor’s prison, all loans fullrecourse, (minimal) homestead exemptions

Inheritance and dowries

No primogenitureNormal to convey or will property to daughters; marriagemarket and grandchildren

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Introduction Historical context Model Data Empirical results Conclusions

Crisis of 1837 and its aftermath

Crisis of 1837: sharp drop in cotton prices and land and slavevalues; foreclosures

Common Law: husband’s creditors could seize wife’s property

Widespread concern with position wives/daughters, family lifein general

“The reverses of the last few years have shown so muchdevastation of married woman’s property by the misfortunes oftheir husbands, that some new modification of the law seemsthe dictate of justice as well of prudence” (TennesseeObserver, 1843)“[There is no good reason]why property bequeathed to adaughter should go to pay debts of which she knew nothing,had no agency in creating, and the payment of which, with hermeans, would reduce her and her children to beggary. This hasbeen done in hundreds of instances, and should no longer betolerated by the laws of the land.” (Georgia Journal, 1843)

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Introduction Historical context Model Data Empirical results Conclusions

Typical Married Women Property Law

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Introduction Historical context Model Data Empirical results Conclusions

Law changes per state

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Introduction Historical context Model Data Empirical results Conclusions

Setup

Preferences:

UM (c0, c1) = log c0 + θME [log(c1)]

Investment requires two inputs (Leontief):

Fixed asset (land, slaves) - fraction αVariable inputs (wages, slave rents, seeds, etc.) - fraction 1− α

Risky investment

Failure (π = 12 ): αI

Success (π = 12 ): [α+ (1− α)R ] I

R > 2

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Introduction Historical context Model Data Empirical results Conclusions

Financial markets

Lenders are risk neutral

Collateral constraint in the spirit of Hart and Moore (1994)and Kiyotaki and Moore (1997)

Creditors can always seize fixed assets αIIn good state of the world can only seize [α+ (1− α)βR ] IIntuition: borrower can threaten to withdraw human capital;bargaining over surplus (1− α)RI .

Incomplete markets: simple debt contracts

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Introduction Historical context Model Data Empirical results Conclusions

Impact Married Women Property Laws

Total investment, I = wM + wF − c0 + lBefore the law, creditors can seize:

[α+ (1− α)βR ] (wM + wF − c0 + l) (good state)α (wM + wF − c0 + l) (bad state)

After the law, creditors can only seize:

[α+ (1− α)βR ] (wM − c0 + l) (good state)α (wM − c0 + l) (bad state)

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Introduction Historical context Model Data Empirical results Conclusions

Consumption / borrowing decision - before law

Household will always pick a riskfree loan, never at constraint

maxc0,l

log c0 +θM2log {[α+ (1− α)R ] (wM + wF − c0 + l)− l}

+θM2log {α (wM + wF − c0 + l)− l}

l∗ =R(2α− 1)− 2α

2(1− α)(R − 1) (wM + wF − c0)

c∗0 =wM + wF1+ θM

We assume that R(2α− 1) > 2α: always borrow

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Introduction Historical context Model Data Empirical results Conclusions

Consumption / borrowing decision - after law

Risky loan: (1+ ρ)l = (2− α)l − α(wM − c0)

maxc0,l

log c0 +θM2log{[α+ (1− α)R ] (wM + wF − c0 + l)

−(2− α)l + α(wM − c0)

}

s.t. l ≤ l =2α+ (1− α)βR(1− α)(2− βR)

(wM − c0)

c0 ≤ wM

with α+ (1− α)R > 2− α

(2− βR) > 0 (assumption)

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Introduction Historical context Model Data Empirical results Conclusions

Three different cases

1 wM/wF < φ1c0 = wM ; l = 0

2 φ1 ≤ wM/wF ≤ φ2

l = l ; c0 =2

2+ θMwM +

(2− βR) [α+ (1− α)R ](2+ θM ) (1− β)R

wF

3 wM/wF > φ2c0 = c∗0 ; l = l

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Introduction Historical context Model Data Empirical results Conclusions

Main results

φ1 ≤ wM/wF ≤ φ2

Lemma

c0 < c∗0

Lemma

Define y ∗ and y to be optimal total investment before and afterthe law (wm + wF − c0 + l )

1 l − l∗ is strictly increasing in wM/wF2 y − y ∗ is strictly increasing in wM/wF

Lemma

y ∗ > y for at least part of the wM/wF distribution

Note: no general equilibrium effects16/27

Introduction Historical context Model Data Empirical results Conclusions

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Introduction Historical context Model Data Empirical results Conclusions

Data sources

1 Records of individual marriages contracted between 1840 and1850 in US South (familysearch.org)

2 Complete count census of 1850 (NBER)Information about gross value real estate & slave holdingsindividual couples - proxy for total investment

3 Complete count census of 1840 (NBER)Information about slave holdings families - proxy for wife’sand husband’s wealth at marriage

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Introduction Historical context Model Data Empirical results Conclusions

Construction dataset

First step: match (1) to (2)

ID couples living in SouthSearch 1850 census for couples whose names match those ofmarriage records (NYIIS code + test of string similarity)Unique matches: construct distribution of probable agesRefine multiple matches, drop observation if multiplicityremainsOverall match rate around 20%

Second step: construct pre-marital wealth from (3)

Little information: surname of household head and number ofhousehold members onlyCompute average slaveholdings by surname-stateMatch to husband’s surname / wife’s maiden name and stateof birthSouthern born only: 88% of people in 1850 census, 76% ofthese can be linked to 1840 census through surname-state

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Summary statistics

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Investment decision

log Ii ,j ,s ,t = βLAWs ,t +

γ [log(Wi ,1840/Wj ,1840)−median]× LAWs ,t +

δ1 logWi ,1840 + δ2 logWj ,1840 + δ3Xi + δ4Xj +

τt + σs + ui ,j ,s ,t

with:

Ii ,j ,s ,t gross (unemcumbered) value of real estate and slavesi = husband, j = wife, s = state of marriage, t = year ofmarriageXi/j : additional controls including age, state of birth, literacy,state-specific linear time trend.τt : year of marriage fixed effects, σs : state fixed effectsEstimated by OLS and TobitNotes: in state marriages only

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Introduction Historical context Model Data Empirical results Conclusions

Investment - OLS

log(Wi ,1840/Wj ,1840) : p(75)− p(25) = 1.3.22/27

Introduction Historical context Model Data Empirical results Conclusions

Investment - Tobit

log(Wi ,1840/Wj ,1840) : p(75)− p(25) = 1.3.23/27

Introduction Historical context Model Data Empirical results Conclusions

Investment Mix

log(Wi ,1840/Wj ,1840) : p(75)− p(25) = 1.3.24/27

Introduction Historical context Model Data Empirical results Conclusions

Investment vs Endowments

log(Wi ,1840/Wj ,1840) : p(75)− p(25) = 1.3.25/27

Introduction Historical context Model Data Empirical results Conclusions

Results driven by changing marriage matches?

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Introduction Historical context Model Data Empirical results Conclusions

What do we learn?

Exogenous variation in bankruptcy protection

Comparable with a (hypothetical) introduction of a modernbankruptcy codeNo general equilibrium effects

Outcomes

Bankruptcy protection matters for investment decisionNet effect of bankruptcy protection depends on share assetsprotectedIncrease (decrease) in investment for the upper (lower) part ofthe wM/wF distribution

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