Credit Booms and Lending Standards: Evidence from the Subprime Mortgage Market Giovanni Dell’Ariccia Deniz Igan Luc Laeven The views expressed in this

Credit Booms and Lending Credit Booms and Lending Standards: Standards: Evidence from the Subprime Evidence from the Subprime Mortgage MarketMortgage Market

Giovanni Dell’AricciaGiovanni Dell’AricciaDeniz IganDeniz IganLuc LaevenLuc Laeven

The views expressed in this presentation are those of the author and do not necessarily represent those of the IMF.

Credit Booms: Curse or Credit Booms: Curse or Blessing?Blessing?

Financial deepening is associated with economic growthFinancial deepening is associated with economic growth

Booms can be good: only a minority ends in crises, and Booms can be good: only a minority ends in crises, and there is evidence that they contribute to long-term there is evidence that they contribute to long-term financial deepeningfinancial deepening

Yet, credit booms are often seen as a recipe for financial Yet, credit booms are often seen as a recipe for financial disasterdisaster, possibly because several major banking crises , possibly because several major banking crises have been preceded by boomshave been preceded by booms

While there are While there are theoretical explanationstheoretical explanations linking booms linking booms to crisesto crises

Empirical work has primarily relied on aggregate dataEmpirical work has primarily relied on aggregate data

Can we use U.S. subprime mortgage market as a Can we use U.S. subprime mortgage market as a lab studylab study for credit booms? for credit booms?

Credit Booms Can Be a Good Credit Booms Can Be a Good ThingThing

Cyclicality of credit:Cyclicality of credit: Favorable economic conditions might justify Favorable economic conditions might justify

extension of credit at less stringent termsextension of credit at less stringent terms Wealth of profitable opportunities justify fast Wealth of profitable opportunities justify fast

credit expansioncredit expansion

Low interest rate environment reduces Low interest rate environment reduces agency problems allowing sound credit agency problems allowing sound credit growth (opposite of “flight to quality”)growth (opposite of “flight to quality”)

Booms promote Booms promote financial deepeningfinancial deepening and and widen accesswiden access

““Unfortunate tendency” to lend aggressively Unfortunate tendency” to lend aggressively at the peak of a cycle (Greenspan)at the peak of a cycle (Greenspan)

Why Credit Booms Lead to Why Credit Booms Lead to CrisesCrises

““Financial acceleratorsFinancial accelerators”” (Kiyotaki and Moore, (Kiyotaki and Moore, JPE 1997): an increase in value of collateralizable JPE 1997): an increase in value of collateralizable goods releases credit constraints. Boom fuels goods releases credit constraints. Boom fuels further wealth effects etc. Negative shocks inverts further wealth effects etc. Negative shocks inverts cycle, leaving banking system overexposed cycle, leaving banking system overexposed

““Institutional memoryInstitutional memory”” (Berger and Udell, JFI (Berger and Udell, JFI 2004): in periods of fast credit expansion banks find 2004): in periods of fast credit expansion banks find it difficult to recruit enough experienced loan it difficult to recruit enough experienced loan officers (especially if there has not been a crisis for officers (especially if there has not been a crisis for a while). This leads to a deterioration of loan a while). This leads to a deterioration of loan portfoliosportfolios

““Informational capital and adverse selection”Informational capital and adverse selection” (Dell’Ariccia and Marquez, JF 2006): during (Dell’Ariccia and Marquez, JF 2006): during expansions, adverse selection is less severe and expansions, adverse selection is less severe and banks find it optimal to trade quality for market banks find it optimal to trade quality for market share, increasing crisis probabilityshare, increasing crisis probability

Subprime Market Ideal Testing Subprime Market Ideal Testing GroundGround

Asymmetric info relevant since subprime Asymmetric info relevant since subprime borrowers:borrowers: Have poor or blemished credit historiesHave poor or blemished credit histories Provide little or no documentation Provide little or no documentation Have risky income profilesHave risky income profiles

Market has grown fast and is now in a crisisMarket has grown fast and is now in a crisis Loan originations Loan originations tripled since 2000tripled since 2000 Significant changes in market structure and Significant changes in market structure and

financial innovationfinancial innovation Apparent relationshipApparent relationship between delinquencies and between delinquencies and

credit growthcredit growth

Wealth of information on borrowers and Wealth of information on borrowers and lenderslenders Loan application dataLoan application data Rich set of macro variablesRich set of macro variables Significant geographical variation within countrySignificant geographical variation within country

Main ContributionMain Contribution

Examine evolution of lending standards Examine evolution of lending standards during subprime boom to explain origins during subprime boom to explain origins of current crisisof current crisis

Shed light on relationship between Shed light on relationship between booms and banking crises in general booms and banking crises in general

Lend some empirical support to recent Lend some empirical support to recent theories explaining cyclicality of theories explaining cyclicality of standards and their links to financial standards and their links to financial instabilityinstability

Data SourcesData Sources

Loan application data: Loan application data: Home Mortgage Disclosure Act (HMDA)Home Mortgage Disclosure Act (HMDA)

Subprime delinquency rate:Subprime delinquency rate:LoanPerformanceLoanPerformance

Economic and social indicators:Economic and social indicators:Bureau of Economic Analysis, Bureau of Bureau of Economic Analysis, Bureau of Labor Statistics, Census Bureau, Office of Labor Statistics, Census Bureau, Office of Federal Housing Enterprise OversightFederal Housing Enterprise Oversight

Data: HMDAData: HMDA Millions of loan applications / Coverage from Millions of loan applications / Coverage from

2000 to 20062000 to 2006

Depository and non-depository institutions Depository and non-depository institutions issuing mortgages in a metropolitan statistical issuing mortgages in a metropolitan statistical area (MSA)area (MSA)

Both prime and subprime loansBoth prime and subprime loans

Subprime lenders identified using list by Dept. Subprime lenders identified using list by Dept. of Housing and Development (HUD)of Housing and Development (HUD) Robustness using interest rate data after 2004Robustness using interest rate data after 2004

Descriptive statisticsDescriptive statistics

Measuring Lending StandardsMeasuring Lending Standards

Did banks become less choosy during the Did banks become less choosy during the boom?boom?

Two measures of lending standards at MSA Two measures of lending standards at MSA level: level:

1.1. Denial rate (DR) = Loans denied / ApplicationsDenial rate (DR) = Loans denied / Applications

2.2. Loan-to-income ratio (LIR)Loan-to-income ratio (LIR)

Preference for DR as more robust to Preference for DR as more robust to measurement error and fraudmeasurement error and fraud

Linking Boom and Lending Linking Boom and Lending StandardsStandards

Regress measures of lending standards at Regress measures of lending standards at MSA level on:MSA level on:

1.1. Measures of credit expansion (boom)Measures of credit expansion (boom)

2.2. Controls for market structure and entryControls for market structure and entry

3.3. Loan sales (securitization)Loan sales (securitization)

4.4. Macro and local variables controlling for Macro and local variables controlling for economic conditions (including time and economic conditions (including time and MSA fixed effects)MSA fixed effects)

DRit = αt +i+ β1AVGINCit + β2INCGROWit + β3UNEMPit + β4SELFEMPit + β5POPit+ β6COMPit + β7HPAPPit-1 + β8APPLit + εit

Baseline MethodologyBaseline Methodology

OLS regressions with MSA and time fixed OLS regressions with MSA and time fixed effectseffects

379 MSAs, 7 years379 MSAs, 7 years

Basic specification:Basic specification:

Measuring the BoomMeasuring the Boom Main boom variable is the growth rate in the Main boom variable is the growth rate in the

number of loan applications in an MSAnumber of loan applications in an MSA

For robustness we also use:For robustness we also use: Growth rate in the number of loan originations in an MSAGrowth rate in the number of loan originations in an MSA Growth rate in the volume of originated loans in an MSAGrowth rate in the volume of originated loans in an MSA

Preference for application measure because of Preference for application measure because of greater exogeneitygreater exogeneity Growth in originations is obviously the result of changes Growth in originations is obviously the result of changes

in denial ratesin denial rates Exogeneity remains concern – “Neighbor effect” (more on Exogeneity remains concern – “Neighbor effect” (more on

this later)this later)

MAP

Other Control VariablesOther Control Variables Macro variablesMacro variables

Income growth, unemployment rate, population, Income growth, unemployment rate, population, self-employment rateself-employment rate

Market structure variablesMarket structure variables Number of competing lendersNumber of competing lenders Entry by large (top 20) national player (market Entry by large (top 20) national player (market

share of entrants)share of entrants)

Other sectoral variablesOther sectoral variables House price appreciation (endogeneity issues House price appreciation (endogeneity issues

here)here) Percentage of loans soldPercentage of loans sold

Loosening Subprime Lending Loosening Subprime Lending StandardsStandards

Dependent variable: Dependent variable: Denial rateDenial rate

AllAll PrimePrime SubprimSubprimee

House price appreciationHouse price appreciation --0.234**0.234**

**

--0.150***0.150***

--0.308***0.308***

Average incomeAverage income --0.002**0.002**

**

--0.003***0.003***

--0.004***0.004***

Income growthIncome growth 0.0030.003 -0.021-0.021 0.1000.100

UnemploymentUnemployment 0.003**0.003** 0.0020.002 0.003*0.003*

Self employmentSelf employment 0.0460.046 0.0800.080 -0.311**-0.311**

Log populationLog population --0.180**0.180**

**

--0.232***0.232***

--0.353***0.353***

Log number of Log number of competitorscompetitors

0.018**0.018****

-0.003-0.003 --0.069***0.069***

Log number of Log number of applicationsapplications

--0.017**0.017**

**

0.025***0.025*** --0.030***0.030***

ConstantConstant 2.697**2.697****

3.065***3.065*** 5.749***5.749***

R-squaredR-squared 0.690.69 0.710.71 0.440.44

Robustness and Identification Robustness and Identification IssuesIssues

Effects of changes in Effects of changes in applicant poolapplicant pool Estimate denial model with loan level data for 2000Estimate denial model with loan level data for 2000 Forecast denials at loan level for 2001-2006Forecast denials at loan level for 2001-2006 Aggregate errors at MSA level and use as dependent variableAggregate errors at MSA level and use as dependent variable

EndogeneityEndogeneity of application and house appreciation of application and house appreciation variablesvariables Instrument subprime applications with prime applicationsInstrument subprime applications with prime applications Lag house appreciationLag house appreciation Instrument house appreciation with “Rapture Index”Instrument house appreciation with “Rapture Index”

Alternative measures of lending standards and credit Alternative measures of lending standards and credit boomboom Loan-to-income ratioLoan-to-income ratio Loan originations and volumesLoan originations and volumes

Extensions IExtensions I Effects of changes in market structureEffects of changes in market structure

Focus on role of entry of large national playersFocus on role of entry of large national players Threat of competition may induce incumbents to cut Threat of competition may induce incumbents to cut

standardsstandards Augment model with measure of entrants’ market Augment model with measure of entrants’ market

shareshare Focus on incumbents denial ratesFocus on incumbents denial rates

Effects of increased recourse to securitizationEffects of increased recourse to securitization Decreased incentives to monitorDecreased incentives to monitor Augment model with proportion of loans sold within 1 Augment model with proportion of loans sold within 1

yearyear Distinguish between earlier and later periods as Distinguish between earlier and later periods as

securitization became more relevant in the second half securitization became more relevant in the second half of the sampleof the sample

Extensions IIExtensions II

Nonlinearities in boom and market sizeNonlinearities in boom and market size Focus on larger MSA marketsFocus on larger MSA markets Focus on MSA with more pronounced boomsFocus on MSA with more pronounced booms

Was there a role for monetary policy?Was there a role for monetary policy? Low interest rates may have further favored lax Low interest rates may have further favored lax

standardsstandards Interact our boom variable with FF rateInteract our boom variable with FF rate Also control for time trendAlso control for time trend

Similar findings for “Jumbo loan” marketSimilar findings for “Jumbo loan” market Is this the next problem market?Is this the next problem market?

Summary of Findings ISummary of Findings I Fall in lending standards associated with credit Fall in lending standards associated with credit

boomboom Shed light on relationship between booms and crisesShed light on relationship between booms and crises Lend support to recent asy-info based theoriesLend support to recent asy-info based theories

Trend exacerbated by:Trend exacerbated by:

1.1. Housing boomHousing boom Role as collateralRole as collateral Evergreening, speculative behaviorEvergreening, speculative behavior

2.2. Competition by large and aggressive entrantsCompetition by large and aggressive entrants

3.3. Disintermediation through loan sales weakening Disintermediation through loan sales weakening monitoring incentivesmonitoring incentives

4.4. Lax monetary policyLax monetary policy

Summary of Findings IISummary of Findings II

Results appear robust across Results appear robust across several specifications:several specifications:

Lending standard measuresLending standard measures Credit boom measuresCredit boom measures Controlling for pool qualityControlling for pool quality Endogeneity in house pricesEndogeneity in house prices Endogeneity of boom variablesEndogeneity of boom variables Market size effectsMarket size effects

DiscussionDiscussion

Evidence on role of monetary policy in lax lending Evidence on role of monetary policy in lax lending among subprime lendersamong subprime lenders

Should bank risk-taking behavior play role in Should bank risk-taking behavior play role in monetary policy decision making ?monetary policy decision making ?

A case for cyclical regulation?A case for cyclical regulation?

Companion paper will look at bank characteristics: Companion paper will look at bank characteristics: capital ratio, regulator, size, specialization, capital ratio, regulator, size, specialization, corporate structure, etc.corporate structure, etc.

Booms can still be optimalBooms can still be optimal

Controlling for Applicant Pool Controlling for Applicant Pool

Dependent variable: Dependent variable: Prediction errorPrediction error

AllAll PrimePrime SubpriSubprimeme


**

--0.104**0.104**

**

--0.281**0.281**

**

Average incomeAverage income --0.004**0.004**

**

--0.005**0.005**

**

-0.003-0.003

Income growthIncome growth -0.015-0.015 0.0070.007 -0.002-0.002

UnemploymentUnemployment -0.001-0.001 --0.004**0.004**

**

0.0030.003

Self employmentSelf employment -0.120*-0.120* -0.048-0.048 --0.414**0.414**

**


**

--0.166**0.166**

**

--0.335**0.335**

**

Log number of competitorsLog number of competitors 0.021**0.021****

0.0080.008 --0.051**0.051**

**

Log number of applicationsLog number of applications --0.019**0.019**

**

-0.002-0.002 --0.026**0.026**

**


2.355**2.355****

5.026**5.026****


Controlling for EndogeneityControlling for EndogeneityDependent variable: Dependent variable: Denial rateDenial rate

APPL_SAPPL_S IV: IV: APPL_PAPPL_P

IV: IV: RaptRapt

Lag Lag HPAHPA

House price House price appreciationappreciation

-0.329***-0.329*** -0.334***-0.334*** --0.576**0.576**

**

House price apprec., House price apprec., laggedlagged

--0.226**0.226**

**

Average Average incomeincome -0.004**-0.004** -0.003*-0.003* -0.004*-0.004* 0.0020.002

Income growthIncome growth 0.1080.108 0.0510.051 0.189**0.189****

-0.103-0.103

UnemploymentUnemployment 0.003*0.003* 0.0030.003 0.0000.000 0.005**0.005**

Self employmentSelf employment -0.271**-0.271** -0.263**-0.263** --0.289**0.289**

-0.167-0.167

Log populationLog population -0.385***-0.385*** -0.266***-0.266*** --0.304**0.304**

**

--0.313**0.313**

**


-0.074***-0.074*** -0.035***-0.035*** --0.057**0.057**

**

--0.055**0.055**

**

Log number of all Log number of all applicationsapplications

--0.033**0.033**

**

Log number of subprime Log number of subprime appl.appl.

-0.013**-0.013** -0.074***-0.074*** --0.014**0.014**

**

ConstantConstant 5.996***5.996*** 4.679***4.679*** 4.918**4.918****

5.094**5.094****

R-squaredR-squared 0.430.43 0.400.40 0.400.40 0.400.40

Alternative Measure of Alternative Measure of StandardsStandards

Dependent variable: LIRDependent variable: LIR AllAll PrimePrime SubprimSubprimee

House price appreciationHouse price appreciation 0.1050.105 0.1030.103 0.222***0.222***

Average incomeAverage income 0.037**0.037****

0.038***0.038*** 0.029***0.029***

Income growthIncome growth --0.886**0.886**

**

--0.871***0.871***

--0.924***0.924***

UnemploymentUnemployment --0.018**0.018**

**

--0.020***0.020***

-0.009*-0.009*

Self employmentSelf employment 1.559**1.559****

1.523***1.523*** 1.578***1.578***

Log populationLog population 0.255*0.255* 0.315**0.315** -0.176-0.176


0.120**0.120****

0.123***0.123*** 0.277***0.277***


0.109**0.109****

0.090***0.090*** 0.265***0.265***

ConstantConstant -4.301**-4.301** --4.915***4.915***

-0.801-0.801


Effect of Loan SalesEffect of Loan SalesDependent variable: Dependent variable: Denial rateDenial rate

AllAll PrimePrime SubprimSubprimee


**

--0.122***0.122***

--0.269***0.269***

Average incomeAverage income -0.002**-0.002** --0.004***0.004***

-0.002-0.002

Income growthIncome growth 0.0430.043 0.0250.025 0.0960.096

UnemploymentUnemployment 0.003**0.003** 0.0010.001 0.004*0.004*

Self employmentSelf employment 0.0920.092 0.1120.112 -0.271**-0.271**


**

--0.296***0.296***

--0.256***0.256***


0.035**0.035****

0.0090.009 --0.057***0.057***


-0.010*-0.010* 0.034***0.034*** --0.032***0.032***

Proportion of loans soldProportion of loans sold --0.256**0.256**

**

--0.226***0.226***

--0.123***0.123***

Prop. loans sold * Prop. loans sold * Year≥2004Year≥2004

0.0240.024 0.076***0.076*** --0.110***0.110***


3.838***3.838*** 4.444***4.444***


Effect of New EntryEffect of New EntryDependent variable: Incumb. Dependent variable: Incumb. denial ratedenial rate

AllAll PrimePrime SubprimeSubprime

House price appreciationHouse price appreciation -0.205***-0.205*** -0.096***-0.096*** -0.297***-0.297***

Average incomeAverage income -0.004***-0.004*** -0.007***-0.007*** -0.001-0.001

Income growthIncome growth 0.0090.009 0.0410.041 0.0310.031

UnemploymentUnemployment 0.0010.001 -0.001-0.001 0.006**0.006**

Self employmentSelf employment -0.087-0.087 -0.074-0.074 -0.291**-0.291**

Log populationLog population -0.164***-0.164*** -0.224***-0.224*** -0.348***-0.348***

Log number of competitorsLog number of competitors 0.0060.006 0.011**0.011** -0.063***-0.063***

Log number of applicationsLog number of applications -0.052***-0.052*** -0.031***-0.031*** -0.022***-0.022***

Market share of entrantsMarket share of entrants 0.0240.024

MS of entrants to primeMS of entrants to prime -0.023*-0.023*

MS of entrants to subprimeMS of entrants to subprime -0.149***-0.149***

ConstantConstant 2.990***2.990*** 3.568***3.568*** 5.572***5.572***


Effect of Monetary PolicyEffect of Monetary Policy

Dependent variable: Denial Dependent variable: Denial raterate

Time Time trendtrend

Fed Fund Fed Fund raterate

BothBoth

House price appreciationHouse price appreciation -0.322***-0.322*** -0.285***-0.285*** --0.295*0.295*

****

Average incomeAverage income -0.003**-0.003** -0.004***-0.004*** --0.004*0.004*

****

Income growthIncome growth 0.096**0.096** 0.0720.072 0.0700.070

UnemploymentUnemployment 0.004**0.004** 0.006***0.006*** 0.006*0.006*****

Self employmentSelf employment -0.311**-0.311** -0.081-0.081 -0.091-0.091

Log populationLog population -0.314***-0.314*** -0.357***-0.357*** --0.330*0.330*

****

Log number of competitorsLog number of competitors -0.062***-0.062*** -0.076***-0.076*** --0.071*0.071*

****

Log number of applicationsLog number of applications -0.025***-0.025*** -0.032***-0.032*** --0.029*0.029*

****

Log number of appl. * TrendLog number of appl. * Trend -0.001***-0.001*** --0.001*0.001*

**

Log number of appl. * FFRLog number of appl. * FFR 0.004***0.004*** 0.003*0.003*****

ConstantConstant 5.996***5.996*** 4.679***4.679*** 5.094*5.094*****


Booms and Crises0

5010

015

0cp

s_gd

p

1960 1970 1980 1990 2000year

020

4060

cps_

gdp

1960 1970 1980 1990 2000year

2040

6080

100

cps_

gdp

1960 1970 1980 1990 2000year

1020

3040

50cp

s_gd

p

1960 1970 1980 1990 2000year

Thailand 1997

Philippines1997

Finland 1991

Chile 1982

-5

05

10

15

Cha

ng

e in

Delin

qu

en

cy R

ate

200

4-2

00

6 (

in p

erc

en

t)

0 5 10 15 20Growth of Loan Origination Volume 2000-2004 (in percent)

Subprime Crisis: A Credit Boom Subprime Crisis: A Credit Boom Gone Bad?Gone Bad?

MSA level data

Credit Booms and Financial Credit Booms and Financial Deepening Deepening (1985-2004)(1985-2004)

United States

United Kingdom

Austria

Belgium

DenmarkFrance

GermanyItaly

Netherlands

Norway

Sweden

Switzerland

Canada

Japan

Finland

Greece

Ireland

PortugalSpain

Turkey

AustraliaNew Zealand

South Africa

Argentina

Bolivia

Brazil

ChileColombia

Costa RicaDominican Republic

Ecuador El SalvadorGuatemalaHaiti

Honduras

Mexico

Nicaragua Panama

ParaguayPeru

UruguayVenezuela, Rep. Bol.

Guyana

JamaicaTrinidad and Tobago

Bahrain, Kingdom of

Iran, I.R. of

Israel

Jordan

Kuwait

Saudi Arabia

Egypt

Bangladesh

Myanmar

Sri Lanka

IndiaIndonesia

Korea

MalaysiaPakistan

Philippines

Singapore

Thailand

Algeria

BotswanaBurundi

Cameroon

Central African Rep.

Chad

Congo, Republic ofBenin

Ethiopia

GabonGambia, The

Côte d'Ivoire

Kenya

Lesotho

Libya

MadagascarMalawi

Mali

Mauritius

Morocco

NigerNigeria

Zimbabwe

Senegal

SwazilandTogo

Tunisia

Burkina FasoZambiaFiji

Papua New Guinea

China,P.R.: Mainland

Hungary

PolandRomania

-50

05

01

00

Chn

ag

e in

Cre

dit-t

o-G

DP

Ra

tio (

in p

erc

ent)

0 50 100 150Cumulated Change in Credit-to-GDP Ratio During Booms (in percent)

U.S. Subprime Mortgage Boom U.S. Subprime Mortgage Boom

Nationwide Home Purchase Loan Originations(volume of loans in dollars)

0

200

400

600

800

1000

1200

2000 2001 2002 2003 2004 2005 2006

Millions

Subprime

Prime

Data: Summary statisticsData: Summary statisticsVariableVariable ObsObs MeanMean Std. Dev.Std. Dev. MinMin MaxMax

Loan application levelLoan application level

DeniedDenied 72,119,13572,119,135 0.190.19 0.390.39 00 11

SubprimeSubprime 72,119,13572,119,135 0.230.23 0.420.42 00 11

Loan amountLoan amount 72,119,13572,119,135 160.59160.59 125.41125.41 11 18001800

Applicant Applicant incomeincome

72,119,13572,119,135 82.1682.16 50.3250.32 1616 363363

Loan-to-Loan-to-incomeincome

72,119,13572,119,135 4.254.25 0.560.56 11 66

MSA levelMSA level

Denial rateDenial rate 2,702,7099

0.250.25 0.070.07 0.070.07 0.550.55

Denial rate, primeDenial rate, prime 2,702,7099

0.180.18 0.070.07 0.040.04 0.520.52

Denial rate, Denial rate, subprimesubprime

2,702,7033

0.500.50 0.080.08 0.000.00 0.730.73

House price House price appreciationappreciation

2,652,6511

0.070.07 0.060.06 -0.05-0.05 0.410.41

Loan-to-incomeLoan-to-income 2,702,7099

1.881.88 0.370.37 1.051.05 3.403.40

Proportion of loans Proportion of loans soldsold

2,702,7099

0.460.46 0.100.10 0.000.00 0.780.78

Subprime Subprime delinquency ratedelinquency rate

1,131,1377

10.4910.49 3.583.58 1.701.70 35.8035.80

Where was the boom?Where was the boom?

...And where are the ...And where are the delinquencies?delinquencies?

A Rather Exogenous A Rather Exogenous InstrumentInstrument

1. False Christs 2. Occult 3. Satanism 4. Unemployment 5. Inflation 6. Interest Rates 7. The Economy 8. Oil Supply/Price 9. Debt and Trade 10. Financial unrest 11. Leadership 12. Drug abuse 13. Apostasy 14. Supernatural 15. Moral Standards 16. Anti-Christian 17. Crime Rate

3 2 2 3 3 2 4 4-1 3 5 4 2 4 1 3 3 4

18. Ecumenism 19. Globalism 20. Tribulation Temple 21. Anti-Semitism 22. Israel 23. Gog (Russia) 24. Persia (I ran) 25. The False Prophet 26. Nuclear Nations 27. Global Turmoil 28. Arms Proliferation 29. Liberalism 30. The Peace Process 31. Kings of the East 32. Mark of the Beast 33. Beast Government 34. The Antichrist

4 3 2 4 5 5 5 3 5 4 4 4 3+1 4 3 4 2

35. Date Settings 36. Volcanoes 37. Earthquakes 38. Wild Weather 39. Civil Rights 40. Famine 41. Drought 42. Plagues 43. Climate 44. Food Supply 45. Floods

Rapture Index 159 Net Change unch

Udated Dec 3, 2007

2 4 5 5 3 3 5 3 3 5 5

No obvious time-series pattern No obvious time-series pattern ......

1

201

301

401

501

601

70

1996 1998 2000 2002 2004 2006

End Times Beliefs: the Rapture Index

Little overlap with boom areasLittle overlap with boom areas

Less than 10 percent 10-15 percent15-25 percent More than 25 percent

Evangelicals: Share of MSA Population

Documents

Credit Booms and Lending Standards: Evidence from the Subprime Mortgage Market Giovanni Dell’Ariccia Deniz Igan Luc Laeven The views expressed in this