Does Bankruptcy Protection Affect Risk-Takingin Household Portfolios?

By Mariela Dal Borgo

Bank of Mexico

June 20th, 2017

XVIII World Congress of the International Economic Association (IEA)Santa Fe, Mexico City

Limited participation and background risk

Stockholding should be widespread if positive equity premium (Campbell,06’).

Exposure to background risk can explain non-participation (Kimball, 93’).Fear of negative wealth shocks (e.g. income volatility, unemployment,out-of-pocket medical expenses) may reduce stockholdings.

Institutional factors can affect exposure to background risk.

US bankruptcy law: Large social program, very generous with debtors.

US households own more unsecure debt and also more stocks.

Can bankruptcy insurance increase participation by reducing exposure tobackground risk? (Elmendorf & Kimball, 00’)

Does Chapter 7 bankruptcy protection encourage (discourage)financial risk-taking?

Dischargeable debt: Credit card debt, instalment loans, medical bills.

Repayment options:

1. Chapter 7 (asset tax): Seize assets above the state exemption, retain future income.

Protected assets: Housing, vehicles, retirement assets, bank deposits.After 2005 reform (BAPCPA): High income borrowers not eligible.

2. Chapter 13 (wage tax): Pay out of post-bankruptcy income, retain all assets.

Bankruptcy protection may encourage stock market participation:

Bankruptcy insurance reduces downside background risk (’risk channel’).

Bankruptcy protection may discourage stock market participation:

If unprotected assets become less attractive (’protection channel’).

Does Chapter 7 bankruptcy protection encourage (discourage)financial risk-taking?

Dischargeable debt: Credit card debt, instalment loans, medical bills.

Repayment options:

1. Chapter 7 (asset tax): Seize assets above the state exemption, retain future income.

Protected assets: Housing, vehicles, retirement assets, bank deposits.After 2005 reform (BAPCPA): High income borrowers not eligible.

2. Chapter 13 (wage tax): Pay out of post-bankruptcy income, retain all assets.

Bankruptcy protection may encourage stock market participation:

Bankruptcy insurance reduces downside background risk (’risk channel’).

Bankruptcy protection may discourage stock market participation:

If unprotected assets become less attractive (’protection channel’).

Does Chapter 7 bankruptcy protection encourage (discourage)financial risk-taking?

Dischargeable debt: Credit card debt, instalment loans, medical bills.

Repayment options:

1. Chapter 7 (asset tax): Seize assets above the state exemption, retain future income.

Protected assets: Housing, vehicles, retirement assets, bank deposits.After 2005 reform (BAPCPA): High income borrowers not eligible.

2. Chapter 13 (wage tax): Pay out of post-bankruptcy income, retain all assets.

Bankruptcy protection may encourage stock market participation:

Bankruptcy insurance reduces downside background risk (’risk channel’).

Bankruptcy protection may discourage stock market participation:

If unprotected assets become less attractive (’protection channel’).

This paper

EMPIRICAL APPROACH:

Identify the causal effect of homestead exemptions on stockholdings.

Exemptions: Maximum value of home equity that can be protected inbankruptcy.

Exploit cross-state and over time variation in exemptions.

Use household-level (not only state-level) fixed-effects.

Allow non-linear marginal effects: Splines rather than polynomials.

Homestead + wildcard state exemption levels, 1999

EXEMPTIONS FOR COUPLES; VALUES IN REAL 2004 USD.1999

< $22,000

$22,000 - $60,000

$98,000 - $310,000

$60,000 - $98,000

Unlimited

Homestead + wildcard state exemption levels, 2011

EXEMPTIONS FOR COUPLES; VALUES IN REAL 2004 USD.2011

< $22,000

$22,000 - $60,000

$60,000 - $98,000

$98,000 - $1,000,000

Unlimited

˙LOG STATE EXEMPTION LEVELS FOR COUPLES, 1999-2011; 2004 USD

VermontWyoming

ConnecticutHawaii

AlaskaNorth Dakota

New JerseyKentuky

MississippiAlabama

CaliforniaPennsylvania

OregonLousiana

MaineWest Virginia

MichiganMontana

ArizonaMinnesota

New MexicoTennessee

Missouri

IllinoisIdahoNew Hampshire

Georgia

North CarolinaWashington

MassachusettsMaryland

NebraskaOhio

New YorkNevada

Rhode IslandSouth Carolina

8 9 10 11 12 13 14

Log homestead + wildcard exemption

1999 2011

Virginia

Wisconsin

Colorado

Indiana

Utah

Outliers

Does higher protection affect stockholdings?

Exemptions have a non-linear effect on stock market participation ofhigh-asset households.

Mechanism: In anticipation to the bankruptcy reform, there is a spike infilings and households leave the stock market.

With a 1 std. dev. increase in the exemption (intermediate levels),participation decreases by 2.2p.p. more in 2005.Stronger effects on households with high non-mortgage debt and highincome.

No support to the ’risk’ channel:

No stronger effects on self-employed or sick households.Higher consumption floor does not reduce savings in safe liquid assets.

Outline

1 Related Literature

2 Data

3 Empirical Approach and Results

4 Conclusions

Outline

1 Related Literature

2 Data

3 Empirical Approach and Results

4 Conclusions

Outline

1 Related Literature

2 Data

3 Empirical Approach and Results

4 Conclusions

Outline

1 Related Literature

2 Data

3 Empirical Approach and Results

4 Conclusions

Related Literature

Related literature

Empirical literature on bankruptcy:

Bankruptcy reform and foreclosure: Li et al., 11’; Morgan et al., 12’;Mitman, 16’

Household financial risk-taking: Persad, 05’

Household credit: Gropp et al., 97’, Severino & Brown, 16’

Asset accumulation: Greenhalgh-Stanley & Rohlin, 13’

Entrepreneurship: Berkowitz & White, 04’; Berger et al., 11’

Effects of insurance / background risk on financial risk-taking:

Medical expense risk: Atella et al., 12’; Goldman & Maestas, 13’

Any formal insurance: Gormley et al., 10’

Labor income risk: Heaton & Lucas, 00’; Fagereng et al., 16’

Data

Outline

1 Related Literature

2 Data

3 Empirical Approach and Results

4 Conclusions

Data

Data

Household data:

Panel Study of Income Dynamics: Longitudinal household data for1999-2011 (odd years).

Sample of heads 65 y.o. or younger.

Stock ownership: Stocks from publicly held corporations, mutual funds orinvestment trusts (excludes IRA’s).

Stock value: High measurement error in survey data; no distinction betweenactive and passive savings.

State-level exemption data:

Wildcard + homestead exemptions deflated by the inflation-adjusted statehouse price index.

Data

Summary statistics by home equity, 1999-2011Means and standard deviations by home equity level

Bottom Middle TopStock market participation (%) 9.14 18.23 36.20

(28.82) (38.61) (48.06)Stock market entry (%) 4.29 9.29 14.46

(20.26) (29.03) (35.17)Stock market exit (%) 54.54 47.38 29.59

(49.81) (49.95) (45.65)Income ($) 26, 091 41, 952 55, 875

(25, 094) (33, 157) (55, 401)House ownership (%) 13.57 83.57 91.24

(34.25) (37.06) (28.28)Home equity ($) 1, 508 40, 722 138, 195

(12, 711) (50, 728) (147, 836)Non-mortgage debt ownership (%) 57.82 65.40 50.92

(49.39) (47.57) (49.99)Non-mortgage debt ($) 8, 762 9, 340 6, 941

(17, 900) (16, 963) (16, 179)Non-business bankruptcy filings (per 1,000 inh.) 5.82 6.08 4.51

(76.04) (77.75) (66.99)

Homestead + wildcard exemption ($) 0 0 0Homestead + wildcard exemption (excl. unlimited) ($)0 0 0House price index 0.00 0.00 0.00Unemployment rate (%) 0.00 0.00 0.00Number of non-business bankruptcy filings 0.00 0.00 0.00Per capita medical expenses ($) 0.00 0.00 0.00

Empirical Approach and Results

Outline

1 Related Literature

2 Data

3 Empirical Approach and Results

4 Conclusions

Empirical Approach and Results

Empirical strategy

FE estimation; identification obtains across states and over time.

Regression model for household i , living in state s, at time t:

Yist = β0 + βt + βs + βs × t + βi + βjX jst + β2Qist + β3Rst + εist

Xjst = fj (Xst) j = 1, 2, 3

Outcome variable:Yist : Dummy for stock ownership

Explanatory variables:βt , βs , βi : Year, state and individual fixed-effectsβs × t: State-specific linear trendsfj (Xst): Restricted cubic spline of the log homestead + wilcard exemption ($)Qist , Rst : Socio-economic and demographic, state-level controls

Control for individual FE: Biased estimates from cross-section or state FE.

EFFECTS ON STOCK MARKET PARTICIPATION BY HOME EQUITY LEVEL

Bottom tercile Middle tercile Top tercile(1) (2) (3) (4) (5) (6) (7) (8) (9)

Log exemptions -.009 -.014 -.015∗ .017 -.002 .014 .038∗∗ .062∗∗ .037∗∗(.008) (.015) (.008) (.015) (.021) (.017) (.015) (.025) (.015)

Log exemptions’ .090 .091 .114∗∗ .029 .065 .030 -.225∗∗ -.300∗∗ -.236∗∗(.061) (.094) (.055) (.091) (.104) (.100) (.096) (.134) (.101)

Log exemptions” -.238 -.248 -.307∗∗ -.215 -.035 -.182 .501∗ .666∗ .526∗(.153) (.235) (.142) (.283) (.319) (.316) (.262) (.348) (.275)

Log income -.000 -.000 -.000 -.006 -.005 -.006 .003 .003 .003(.002) (.002) (.002) (.004) (.004) (.004) (.004) (.004) (.004)

Log income’ .000 .000 .000 .006 .005 .006 -.006 -.006 -.006(.002) (.002) (.002) (.004) (.005) (.005) (.005) (.005) (.006)

Log income” 1.224∗∗ 1.238∗∗ 1.208∗∗ 2.039 2.425 2.274 3.178∗∗∗ 3.103∗∗ 3.255∗∗(.488) (.481) (.574) (2.199) (2.224) (2.471) (1.173) (1.179) (1.305)

Constant .143 .346∗∗ .014 .352 .195 -.016(.089) (.137) (.205) (.287) (.205) (.282)

Year FE Y Y Y Y Y Y Y Y YState FE Y Y Y Y Y YIndividual FE Y Y Y Y Y YState x individual FE Y Y YState x time trend Linear Linear LinearMean dep. var. .065 .065 .064 .159 .159 .160 .310 .310 .314No. of Obs. 19,973 19,973 17,945 10,121 10,121 9,747 14,811 14,811 14,280No. of Clusters 51 51 51 50 50 50 51 51 51R-Squared .01 .02 .60 .02 .03 .56 .02 .02 .64

Notes. Robust standard errors (clustered at the state level) are in parentheses. *p

MARGINAL EFFECTS ON STOCK MARKET PARTICIPATION BY HOMEEQUITY LEVEL

−.1

−.05

0

.05

.1

d[P

r(O

wn S

tock)]

/d(L

og e

xem

ptions)

6 7 8 9 10 11 12 13 14

Log exemptions ($)

Conditional Marginal Effects with 90% CIs

Bottom tercile

−.1

−.05

0

.05

.1

d[P

r(O

wn S

tock)]

/d(L

og e

xem

ptions)

6 7 8 9 10 11 12 13 14

Log exemptions ($)

Conditional Marginal Effects with 90% CIs

Middle tercile

−.1

−.05

0

.05

.1

d[P

r(O

wn S

tock)]

/d(L

og e

xem

ptions)

6 7 8 9 10 11 12 13 14

Log exemptions ($)

Conditional Marginal Effects with 90% CIs

Top tercile

NUMBER OF CHAPTER 7 FILINGS PER CAPITA

0

1

2

3

4

5

6

1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

Nu

mb

er

of

ba

nk

rup

tcy

fil

ing

s

Number of bankruptcy filings per 1,000 inhabitants

Number of bankruptcy filings per 1,000 inhabitants

HETEROGENEOUS EFFECTS ON PARTICIPATION IN 2005

By home equity levelBottom Middle Top

(1) (2) (3) (4) (5) (6)Log exemptions x 05’ -.001 -.006 -.026 -.024 .071∗∗ .035

(.013) (.015) (.016) (.025) (.032) (.029)Log exemptions’ x 05’ .001 .040 .042 .105 -.477∗∗∗ -.277∗

(.063) (.077) (.089) (.120) (.157) (.142)Log exemptions” x 05’ .046 -.030 .066 -.218 1.288∗∗∗ .769∗∗

(.156) (.194) (.267) (.346) (.369) (.339)Log exemptions x High debt x 05’ .016 -.005 .131∗∗

(.034) (.044) (.052)Log exemptions’ x High debt x 05’ -.162 -.174 -.743∗∗∗

(.222) (.186) (.273)Log exemptions” x High debt x 05’ .360 .779 1.943∗∗∗

(.595) (.551) (.649)Log exemptions x High debt .022 .010 -.024

(.022) (.044) (.041)Log exemptions’ x High debt -.037 -.069 .003

(.129) (.247) (.253)Log exemptions” x High debt -.035 .277 -.032

(.350) (.686) (.619)Log exemptions -.009 -.011 .026 .023 .025∗ .031

(.010) (.009) (.016) (.022) (.015) (.019)Log exemptions’ .086 .084 -.001 .025 -.164 -.159

(.067) (.062) (.093) (.149) (.100) (.126)Log exemptions” -.227 -.184 -.147 -.248 .335 .326

(.166) (.166) (.296) (.439) (.274) (.325)High debt x 05’ -.119 .062 -1.267∗∗

(.317) (.420) (.488)Constant .148 .134 -.067 -.091 .327 .332

(.094) (.096) (.211) (.218) (.205) (.211)Income, demogr., state-level controls Y Y Y Y Y YState, indiv., year FE Y Y Y Y Y YMean dependent variable .065 .065 .159 .159 .310 .310No. of Obs. 19,973 19,973 10,121 10,121 14,811 14,811R-Squared .01 .01 .02 .02 .02 .02

HETEROGENEOUS EFFECTS ON PARTICIPATION IN 2005

By home equity levelBottom Middle Top

(1) (2) (3) (4) (5) (6)Log exemptions x 05’ -.001 -.001 -.026 -.031∗ .071∗∗ .060

(.013) (.013) (.016) (.016) (.032) (.038)Log exemptions’ x 05’ .001 -.010 .042 .105 -.477∗∗∗ -.396∗∗

(.063) (.065) (.089) (.084) (.157) (.181)Log exemptions” x 05’ .046 .082 .066 -.161 1.288∗∗∗ 1.097∗∗

(.156) (.159) (.267) (.251) (.369) (.433)Log exemptions x High income x 05’ .031 .065 .106

(.125) (.088) (.100)Log exemptions’ x High income x 05’ .486 -1.036∗∗ -.593

(.785) (.460) (.509)Log exemptions” x High income x 05’ -1.701 3.797∗∗ 1.356

(2.184) (1.440) (1.241)Log exemptions x High income -.120 -.060 .007

(.111) (.092) (.060)Log exemptions’ x High income -.009 .623∗ -.338

(.561) (.370) (.238)Log exemptions” x High income .225 -1.974∗ .997∗

(1.430) (1.016) (.547)Log exemptions -.009 -.008 .026 .032∗ .025∗ .017

(.010) (.010) (.016) (.017) (.015) (.015)Log exemptions’ .086 .097 -.001 -.048 -.164 -.066

(.067) (.071) (.093) (.103) (.100) (.105)Log exemptions” -.227 -.251 -.147 .010 .335 .061

(.166) (.185) (.296) (.316) (.274) (.299)High income x 05’ -.327 -.546 -1.019

(1.148) (.830) (.959)Constant .148 .168∗ -.067 -.060 .327 .379∗

(.094) (.090) (.211) (.211) (.205) (.223)Income, demogr., state-level controls Y Y Y Y Y YState, indiv., year FE Y Y Y Y Y YMean dependent variable .065 .065 .159 .159 .310 .310No. of Obs. 19,973 19,973 10,121 10,121 14,811 14,811R-Squared .01 .02 .02 .02 .02 .02

HETEROGENEOUS EFFECTS: HIGHER BACKGROUND RISK

By home equity levelBottom Middle Top Bottom Middle Top

Log exemptions x Self-employed -.219 -.019 .040(.212) (.156) (.094)

Log exemptions’ x Self-employed .847 .208 -.628(1.015) (1.067) (.496)

Log exemptions” x Self-employed -2.360 .370 1.482(2.706) (3.449) (1.208)

Log exemptions x Bad health .010 -.037 -.038(.023) (.047) (.093)

Log exemptions’ x Bad health .026 .336 .261(.181) (.291) (.757)

Log exemptions” x Bad health -.095 -1.048 -1.100(.491) (.928) (1.831)

Log exemptions -.007 .023∗ .041∗∗ -.001 .028 .035∗∗(.009) (.013) (.016) (.009) (.017) (.016)

Log exemptions’ .074 -.001 -.199∗ .061 -.011 -.213∗∗(.066) (.084) (.106) (.060) (.098) (.098)

Log exemptions” -.175 -.126 .434 -.160 -.107 .493∗(.168) (.264) (.289) (.155) (.299) (.268)

Self-employed 2.072 .057 -.264(1.964) (1.482) (.897)

Bad health -.082 .393 .363(.212) (.435) (.862)

Constant .118 .091 .270 .101 -.034 .266(.082) (.226) (.250) (.106) (.225) (.216)

Income, demographic, state-level controls Y Y Y Y Y YYear, state, individual FE Y Y Y Y Y YMean dependent variable .064 .157 .310 .072 .165 .325No. of Obs. 18,112 9,386 13,551 16,626 8,991 13,344R-Squared .01 .02 .02 .02 .02 .02

EFFECTS ON THE HOLDINGS OF OTHER UNPROTECTED ASSETS

Dependent variable: Log safe assets (conditional on ownership)By home equity level

Bottom Middle Top(1) (2) (3) (4) (5) (6)

Log exemptions -.029 -.075 .151 .217 .037 .101(.126) (.157) (.163) (.178) (.241) (.243)

Log exemptions’ .360 .516 -1.034∗ -1.274∗∗ -.312 -.531(.723) (.850) (.531) (.565) (1.317) (1.332)

Log exemptions” -1.542 -1.968 2.895∗ 3.573∗∗ .609 1.104(1.802) (2.137) (1.502) (1.572) (3.060) (3.094)

Log exemption x 05’ .224 -.271 -.238∗∗(.306) (.186) (.106)

Log exemption’ x 05’ -1.299 1.133 1.000(1.513) (.734) (.650)

Log exemption” x 05’ 3.551 -3.375 -2.330(3.878) (2.132) (1.619)

Log income -.187∗∗∗ -.188∗∗∗ -.032 -.034 -.043 -.043(.044) (.045) (.038) (.039) (.043) (.042)

Log income’ .310∗∗∗ .311∗∗∗ .063 .064 .065 .066(.064) (.064) (.043) (.043) (.069) (.068)

Log income” -3.372 -3.344 13.134 12.596 7.168 7.132(5.647) (5.547) (11.871) (11.899) (12.153) (12.031)

Inverse Mills ratio 9.695∗ 9.620∗ -5.377 -5.414 -5.458 -5.321(5.252) (5.290) (4.941) (4.993) (11.510) (11.317)

Demographic, state-level controls Y Y Y Y Y YYear, state, individual FE Y Y Y Y Y YMean dependent variable 7.434 7.434 8.344 8.344 9.290 9.290No. of Obs. 8,297 8,297 7,237 7,237 12,060 12,060No. of Clusters 51 51 49 49 51 51R-Squared .04 .04 .03 .03 .02 .03

EFFECTS ON THE HOLDINGS OF PROTECTED ASSETS

Dependent variable: Log home equity (conditional on ownership)By home equity level

Bottom Middle Top(1) (2) (3) (4) (5) (6)

Log exemptions -1.922 -1.549 .161 .225 .024 .015(1.242) (1.216) (.160) (.167) (.098) (.092)

Log exemptions’ 9.021 7.438 -.675 -.936 -.497 -.448(6.229) (6.252) (.588) (.599) (.437) (.432)

Log exemptions” -21.486 -17.832 1.587 2.353 1.275 1.168(14.289) (14.346) (1.617) (1.623) (.952) (.959)

Log exemption x 05’ -1.859 -.416∗∗ .029(1.323) (.185) (.143)

Log exemption’ x 05’ 7.814 1.907∗∗ -.052(5.936) (.894) (.635)

Log exemption” x 05’ -17.735 -5.369∗ .135(14.663) (2.730) (1.460)

Log income -.139 -.164 -.086∗∗ -.086∗∗ .011 .012(.305) (.313) (.041) (.040) (.022) (.021)

Log income’ .228 .248 .126∗∗ .126∗∗ -.015 -.016(.377) (.383) (.059) (.058) (.028) (.028)

Log income” -16.497 -15.075 9.688 9.206 5.538∗ 5.621∗(76.776) (75.245) (12.487) (12.322) (3.183) (3.166)

Inverse Mills ratio -4.156 -3.553 5.542 5.472 -5.797 -5.872(28.078) (27.935) (3.893) (3.866) (3.624) (3.579)

Demographic, state-level controls Y Y Y Y Y YYear, state, individual FE Y Y Y Y Y YMean dependent variable 8.559 8.559 10.208 10.208 11.367 11.367No. of Obs. 1,592 1,592 7,191 7,191 12,590 12,590No. of Clusters 48 48 50 50 51 51R-Squared .06 .06 .07 .07 .10 .10

Empirical Approach and Results

Identification assumptions

1 Exemptions changes only affect households from the corresponding state.

Sample selection

Dynamic effects Dynamic Effects

2 Exemption changes are exogenous to the demand for stocks.

Effect of state background variables on exemptions. State Variables

Empirical Approach and Results

Alternative explanations

1 Credit market conditions. Credit market

2 Housing market conditions. Housing market

3 Other robustness checks

Functional Form: Replace splines by cubic polynomial regressions.

Total asset exemptions: Add exemptions for vehicles and bank deposits.

Use of sample weights: PSID Core/Immigrant Family Longitudinal Weight.

Exclusion of outliers: Drop observations with log exemptions < 8.

Polynomials Excl. outliers

Conclusions

Outline

1 Related Literature

2 Data

3 Empirical Approach and Results

4 Conclusions

Conclusions

Conclusions

The ex-ante bankruptcy protection does not affect participation by:

Increasing household risk-taking.

Reducing the demand for unprotected assets in general.

As incentives to file become unusually large, people sell unprotected assets,including stocks.

Effects at intermediate protection levels, stronger for households moreaffected by the reform.

Low exemptions: Lower insurance

High exemptions: Homes fully protected, no additional insurance.

Anticipatory reponses to social programs’ reforms can have unintendedconsequences on households’ financial decisions.

Thank you!

References

References I

Atella, V., Brunetti, M. & Maestas, N. (2012), ‘Household portfolio choices,health status and health care systems: A cross-country analysis based onSHARE’, Journal of Banking and Finance 36(5), 1320–1335.

Berger, A. N., Cerqueiro, G. & Penas, M. F. (2011), ‘Does debtor protectionreally protect debtors? Evidence from the small business credit market’,Journal of Banking and Finance 35(7), 1843–1857.

Berkowitz, M. K. & White, M. J. (2004), ‘Bankruptcy and small firms’ accessto credit’, RAND Journal of Economics 35(1), 69–84.

Campbell, J. Y. (2006), ‘Household finance’, The Journal of Finance61(4), 1553–1604.

Elmendorf, D. W. & Kimball, M. S. (2000), ‘Taxation of labor income and thedemand for risky assets’, International Economic Review 41(3), 801–834.

Fagereng, A., Guiso, L. & Pistaferri, L. (2016), Back to background risk?Discussion Paper No. 834, Statistics Norway, Research Department.

Goldman, D. & Maestas, N. (2013), ‘Medical expenditure risk and householdportfolio choice’, Journal of Applied Econometrics 28(4), 527–550.

References

References II

Gormley, T., Liu, H. & Zhou, G. (2010), ‘Limited participation andconsumption-saving puzzles: A simple explanation and the role of insurance’,Journal of Financial Economics 96(2), 331–344.

Greenhalgh-Stanley, N. & Rohlin, S. (2013), ‘How does bankruptcy law impactthe elderly’s business and housing decisions?’, Journal of Law and Economics56(2), 417–451.

Gropp, R., Scholz, J. K. & White, M. J. (1997), ‘Personal bankruptcy and creditsupply and demand’, The Quarterly Journal of Economics 112(1), 217–251.

Heaton, J. & Lucas, D. (2000), ‘Portfolio choice and asset prices: Theimportance of entrepreneurial risk’, Journal of Finance 55(3), 1163–1198.

Kimball, M. S. (1993), ‘Standard risk aversion’, Econometrica 61(3), 589–611.Li, W., White, M. J. & Zhu, N. (2011), ‘Did bankruptcy reform cause mortgagedefaults to rise?’, American Economic Journal: Economic Policy3(4), 123–147.

Mitman, K. (2016), ‘Macroeconomic effects of bankruptcy and foreclosurepolicies’, American Economic Review 106(8), 2219–2255.

References

References III

Morgan, D. P., Iverson, B. & Botsch, M. (2012), ‘Subprime foreclosures and the2005 bankruptcy reform’, FRBNY Economic Policy Review 18(1), 47–57.

Persad, S. (2005), Does availability of consumption insurance influence portfolioallocation? A real options approach to bankruptcy exemptions, Workingpaper, Columbia University.

Severino, F. & Brown, M. (2016), Personal bankruptcy protection andhousehold debt. Available at SSRN: http://ssrn.com/abstract=2447687 orhttp://dx.doi.org/10.2139/ssrn.2447687.

DYNAMIC EFFECTS ON STOCK MARKET PARTICIPATION

By home equity levelBottom Middle Top

(1) (2) (3) (4) (5) (6) (7) (8) (9)Log exemptionst+1 -.003 -.010 -.006 .021 -.003 .033 -.029 -.023 .011

(.008) (.008) (.012) (.016) (.020) (.035) (.029) (.025) (.023)Log exemptionst+1 ’ .058 .118∗∗ .157∗∗ -.079 .044 -.011 .049 -.038 -.061

(.065) (.056) (.065) (.081) (.102) (.110) (.175) (.158) (.134)Log exemptionst+1” -.140 -.390∗∗ -.574∗∗∗ -.042 -.506 -.458 .001 .239 .331

(.213) (.188) (.201) (.277) (.447) (.508) (.479) (.441) (.386)Log exemptionst -.007 -.007 .021 -.011 -.006 .052 .050∗ .057∗ .100∗∗

(.011) (.012) (.016) (.022) (.023) (.058) (.025) (.030) (.040)Log exemptionst ’ .040 .071 -.051 .107 .073 -.062 -.287 -.330 -.536∗∗

(.082) (.094) (.101) (.105) (.119) (.150) (.175) (.204) (.228)Log exemptionst” -.099 -.235 .048 .105 .234 .471 .663 .773 1.298∗

(.208) (.257) (.309) (.341) (.383) (.613) (.451) (.521) (.677)Log exemptionst−1 -.004 .009 -.006 -.002 .029 .098 -.025 .019 -.023

(.016) (.018) (.024) (.025) (.045) (.092) (.044) (.040) (.045)Log exemptionst−1 ’ .059 -.037 .062 .028 -.136 -.390 .119 -.109 .021

(.092) (.092) (.113) (.117) (.195) (.237) (.203) (.178) (.240)Log exemptionst−1” -.127 .134 -.060 -.405 .264 .884 -.290 .284 .074

(.227) (.218) (.275) (.332) (.479) (.568) (.507) (.443) (.610)Log income -.001 -.001 -.001 -.004 -.003 -.003 .002 .002 .002

(.002) (.002) (.002) (.006) (.006) (.006) (.004) (.004) (.004)Log income’ .001 .001 .002 .007 .006 .006 -.005 -.005 -.006

(.003) (.003) (.003) (.007) (.007) (.007) (.006) (.006) (.006)Log income” .798 .780 .790 -.544 -.140 -.181 2.070 2.032 1.961

(.684) (.695) (.703) (2.987) (3.033) (3.119) (1.293) (1.314) (1.290)Demographic controls Y Y Y Y Y Y Y Y YState-level controls Y Y Y Y Y Y Y Y YYear, state FE Y Y Y Y Y Y Y Y YIndividual FE Y Y Y Y Y Y Y Y YState x time trend Linear Quadratic Linear Quadratic Linear QuadraticNo. of Obs. 13,835 13,835 13,835 7,334 7,334 7,334 10,740 10,740 10,740No. of Clusters 51 51 51 50 50 50 51 51 51R-Squared .02 .02 .03 .02 .03 .04 .02 .03 .03

Identification Assumptions

EFFECT OF STATE BACKGROUND VARIABLES ON EXEMPTIONS

Homestead + wildcard exemptionLevels Logs

(1) (2) (3) (4) (5) (6) (7) (8)Inflation-adjusted house price -2.892∗∗ .218 .278 -2.092∗∗ .480 .245

(1.336) (.469) (.520) (.801) (1.073) (.737)Unemployment rate -.127 .212 .087 -.047 .088∗ .053

(.170) (.153) (.081) (.102) (.045) (.046)Proprietor employment .472∗∗∗ -.158 -.075 .302∗∗∗ -.037 .001

(.150) (.108) (.077) (.071) (.054) (.049)Per capita personal income 5.789 -1.368 -5.490 4.303 -3.100 -6.860

(4.834) (2.891) (7.056) (3.171) (4.966) (6.996)State GDP -1.092∗∗∗ .409 .134 -.712∗∗∗ -.013 -.126

(.333) (.392) (.298) (.172) (.204) (.171)Non-business filings -.092 .119∗ .091 -.165∗ .076 .032

(.122) (.066) (.083) (.095) (.080) (.044)Per capita medical expenses 28.860 32.572

(39.759) (26.586)Couples .144∗∗∗ .171∗∗∗ .164∗∗∗ .371∗∗∗ .376∗∗∗ .380∗∗∗

(.042) (.035) (.035) (.054) (.048) (.049)Year FE Y Y Y Y Y Y Y YState FE Y Y Y Y Y YNo. of Obs. 697 697 596 596 697 697 596 596R-Squared .16 .92 .94 .93 .20 .90 .92 .90

Identification Assumptions

MARGINAL EFFECTS ON THE OWNERSHIP OF NON-MORTGAGE DEBT

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Conditional Marginal Effects with 90% CIs

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Conditional Marginal Effects with 90% CIs

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Robustness checks

HETEROGENEOUS EFFECTS: STATES WITH LARGER HOUSING BUBBLE

By home equity levelBottom Middle Top

(1) (2) (3) (4) (5) (6)Log exemptions x Housing bubble-4 -.705 -3.117 -4.494∗∗∗

(.482) (4.471) (.616)Log exemptions’ x Housing bubble-4 1.968 6.548 12.100∗∗∗

(1.270) (9.632) (1.699)Log exemptions” x Housing bubble-4 -4.010 -13.728 -22.993∗∗∗

(2.542) (20.537) (3.309)Log exemptions x Housing bubble-9 .012 .045 .018

(.017) (.030) (.023)Log exemptions’ x Housing bubble-9 .014 -.134 -.083

(.104) (.155) (.137)Log exemptions” x Housing bubble-9 -.035 .492 .368

(.254) (.447) (.333)Log exemptions -.006 -.008 .013 .015 .035∗∗ .036∗∗

(.010) (.010) (.016) (.017) (.016) (.017)Log exemptions’ .074 .083 .052 .051 -.188∗ -.189∗

(.067) (.076) (.100) (.106) (.101) (.108)Log exemptions” -.209 -.236 -.294 -.354 .362 .320

(.171) (.192) (.306) (.304) (.270) (.274)Unlimited exemption -.004 .003 .100∗∗ .135∗∗∗ .081∗∗ .115∗∗∗

(.046) (.048) (.047) (.031) (.040) (.029)Income and demographic controls Y Y Y Y Y YState-level controls Y Y Y Y Y YYear FE Y Y Y Y Y YState FE Y Y Y Y Y YIndividual FE Y Y Y Y Y YMean dependent variable .065 .065 .159 .159 .310 .310No. of Obs. 19,973 19,973 10,121 10,121 14,811 14,811No. of Clusters 51 51 50 50 51 51R-Squared .01 .01 .02 .02 .02 .02

Notes. Robust standard errors (clustered at the state level) are in parentheses. *p

ROBUSTNESS CHECK:

MARGINAL EFFECTS ON STOCK MARKET PARTICIPATION: CUBICPOLYNOMIALS AT HIGH HOME EQUITY LEVEL

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Conditional Marginal Effects with 90% CIs

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Conditional Marginal Effects with 90% CIs

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Robustness checks

ROBUSTNESS CHECK: MARGINAL EFFECTS ON STOCK MARKET

PARTICIPATION EXCLUDING OUTLIERS

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Conditional Marginal Effects with 90% CIs

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Conditional Marginal Effects with 90% CIs

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Conditional Marginal Effects with 90% CIs

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Graph all sample Robustness checks

Related LiteratureDataEmpirical Approach and ResultsConclusions