Bad Credit, No Problem? Credit and Labor Market Consequences of Bad Credit Reports

• Published date: 01 October 2020
• Author: WILL DOBBIE,PAUL GOLDSMITH‐PINKHAM,JAE SONG,NEALE MAHONEY
• DOI: http://doi.org/10.1111/jofi.12954
• Date: 01 October 2020

THE JOURNAL OF FINANCE •VOL. LXXV, NO. 5 •OCTOBER 2020

Bad Credit, No Problem? Credit and Labor

Market Consequences of Bad Credit Reports

WILL DOBBIE, PAUL GOLDSMITH-PINKHAM, NEALE MAHONEY,

and JAE SONG∗

ABSTRACT

We study the financial and labor market impacts of bad credit reports. Using

difference-in-differences variation from the staggered removal of bankruptcy flags,

we show that bankruptcy flag removal leads to economically large increases in credit

limits and borrowing. Using administrative tax records linked to personal bankruptcy

records, we estimate economically small effects of flag removal on employment and

earnings outcomes. We rationalize these contrasting results by showing that, condi-

tional on basic observables, “hidden” bankruptcy flags are strongly correlated with

adverse credit market outcomes but have no predictive power for measures of job

performance.

THE INCREASING AVAILABILITY AND RICHNESS of credit report data is one of

the most significant changes in consumer financial markets over the last 25

years. In the United States, credit reports—and the associated credit scores—

are used in nearly all consumer lending decisions, including both approval and

pricing decisions for credit cards, private student loans, auto loans, and home

mortgages. Credit reports are also widely used in nonlending decisions, such

as rental decisions for apartments and hiring decisions in the labor market.1

∗Will Dobbie is at the Harvard Kennedy School and NBER. Paul Goldsmith-Pinkham is at the

Yale School of Management. Neale Mahoney is at Stanford University and NBER. Jae Song is at

the Social Security Administration. We are indebted to the Editor, Amit Seru, and two anonymous

referees. First version: July 2, 2016. We are extremely grateful to Gerald Ray and David Foster

at the Social Security Administration for their help and support. We also thank Orley Ashenfel-

ter, Emily Breza, Jediphi Cabal, Hank Farber, Donghoon Lee, Alex Mas, Atif Mian, Jon Petkun,

Joelle Scally,Isaac Sorkin, Amir Sufi, Eric Zwick, and numerous seminar participants for helpful

comments and suggestions. Maya Bidanda, Katherine DiLucido, Yin Wei Soon, and Hanbin Yang

provided excellent research assistance. The views expressed are those of the authors and do not

necessarily reflect those of the Federal Reserve Bank of New York, the Federal Reserve System,

or the Social Security Administration. We have read The Journalof Finance disclosure policy and

have no conflicts of interest to disclose.

Correspondence: Paul Goldsmith-Pinkham, YaleSchool of Management, 165 Whitney Ave, New

Haven, CT 06511, USA. e-mail: paul.goldsmith-pinkham@yale.edu

1The SHRM (2010) reported that 60% of employers conducted background checks for some of

their candidates in 2010, up from 25% of employers in 1998. See FRB (2007) and CFPB (2012)for

additional discussion on the uses of credit reports.

DOI: 10.1111/jofi.12954

© 2020 the American Finance Association

2377

2378 The Journal of Finance®

Proponents of this trend argue that the increased use of credit reports is

a key factor driving the expansion of lending to traditionally underserved

segments of the population, including minority communities that have been

historically shut out of formal credit markets (e.g., Staten (2014)). Critics rec-

ognize the importance of credit report data in theory, but argue that these ben-

efits should be weighed against individuals’ rights to privacy (Shorr (1994))

and the so-called right to be forgotten (Steinberg (2014)).

Critics have been particularly concerned about the use of credit reports in

hiring decisions in the labor market. In the years following the Great Reces-

sion, a series of prominent news articles reported on how a bad credit report

can be a major impediment to finding a job.2The importance of credit reports

in the labor market is not lost on the general public. In a recent nationally rep-

resentative survey,52% of respondents reported that credit scores are typically

used “by a potential employer deciding whether to offer you a job” (Armantier

et al. (2017)).

This paper studies the effect of an improved credit report on both finan-

cial and labor market outcomes. Our research design uses the sharp removal

of personal bankruptcy “flags” from credit reports at statutorily determined

time horizons. Nearly all households that declare bankruptcy file under ei-

ther Chapter 7 or Chapter 13 of the U.S. Bankruptcy Code.3Under the Fair

Credit Reporting Act (FCRA), credit bureaus are required to remove Chapter

7 bankruptcy flags 10 years after filing. In contrast, credit bureaus tradition-

ally remove Chapter 13 flags only seven years after filing, three years before

the Chapter 7 flag is removed.4

We use this variation in a difference-in-differences research design that com-

pares outcomes for Chapter 13 filers (the “treatment” group), whose flags are

removed after seven years, to Chapter 7 filers (the “control” group), whose flags

are removed after 10 years and therefore are unaffected at the seven-year time

horizon. The identifying assumption for this difference-in-differences specifi-

cation is that, in the absence of the Chapter 13 bankruptcy flag removal, out-

comes for treated and control individuals would have evolved in parallel. To

provide support for this “parallel trends” assumption, we show that the path

2See National Public Radio (2012) and New York Times (2013). The April 10th, 2016 episode of

the TV Show “Last Week Tonight with JohnOliver” also reported on this issue.

3Under Chapter 7, debtors forfeit all nonexempt assets in exchange for a discharge of eligible

debts and protection from future wage garnishment. Under Chapter 13, filers propose a three- to

five-year plan to repay part of their unsecured debt in exchange for a discharge of the remaining

unsecured debt, protection from future wage garnishment, and protection of most assets. Nearly

all unsecured debts are eligible for discharge under both chapters, including credit card debt,

installment loans, medical debt, unpaid rent and utility bills, tort judgments, and business debt.

See Section III for additional details on the bankruptcy system in the United States.

4Under FCRA, Chapter 13 flags are not mandated to be removed earlier than Chapter 7 flags,

but all three national credit bureaus do so voluntarily.All three credit bureaus state in their docu-

mentation that the Chapter 13 flag is removed at seven years, and we confirmed this independently

using the Equifax credit report data described below.We also confirmed that the Chapter 7 flag is

removed at 10 years, as mandated by the FRCA, using the Equifax data.

Bad Credit, No Problem? 2379

of outcomes for treated and control individuals are virtually identical in the

preflag removal period.

We measure the effects of flag removal using two large administrative data

sets. We examine the effects on credit market outcomes—including measures

of both credit card and mortgage borrowing—using a data set generated from

the Federal Reserve Bank of New York Equifax Consumer Credit Panel (CCP).

Equifax is one of the three main credit bureaus, and their data provide us with

panel information on nearly all credit products held by an individual over time.

To examine the effects on labor market outcomes, we use data from individual

bankruptcy filings merged to administrative tax records at the Social Security

Administration (SSA). Our primary analysis sample, which focuses on prime-

age adults with a bankruptcy flag removal between 2002 and 2011, covers

roughly 300,000 individuals in the Equifax sample and 3.5 million individuals

in the SSA sample.

We begin our analysis by examining the “first-stage” effect of the bankruptcy

flag removal on credit scores. As bankruptcy flags enter the credit score for-

mula, this effect is “mechanical” in the sense that it could be directly calculated

if one had the proprietary credit score formula and all of the input variables.

In practice, we show that bankruptcy flag removal leads to an immediate nine

point increase in credit scores on a preflag removal mean of 594 (26% of the

preflag removal standard deviation). The jump occurs precisely in the quarter

of bankruptcy flag removal and its impact declines over time. As credit scores

are based on a regression of default on observables, we can also interpret this

effect in terms of a change in the implied probability of default. Using this

measure, we find that flag removal leads to a 3 percentage point decline in the

implied default probability on a preflag removal mean of 32% (roughly a 9%

decrease in riskiness).

We next show that flag removal has a statistically significant and economi-

cally large effect on credit card borrowing. The effect appears immediately and

grows linearly over time. At a three-year horizon, we estimate that flag re-

moval increases credit limits by approximately one-half, or $1,328 on a preflag

removal mean of $2,784 (56% of the preflag removal standard deviation), and

raises credit card balances by more than 40%, or $781 on a preflag removal

mean of $1,819 (48% of the preflag removal standard deviation). The ratio of

the increase in balances to the increase in credit limits is 59%. We caution that

this effect should not be interpreted as a pure marginal propensity to consume

out of liquidity because some of the effect may operate through lower inter-

est rates (which we do not observe) and because credit limits may be partially

determined by credit card balances (reverse causality).

We find a similarly large effect on mortgage borrowing. In contrast to the

credit card results, the mortgage effect is concentrated in the first year. One

year after flag removal, the fraction of individuals with a mortgage increases

by 2.0 percentage points on a preflag removal mean of 41.0% (9% of the preflag

removal standard deviation). In our heterogeneity analysis, we show that the

effect is concentrated among individuals who had their flags removed during

the 2008 to 2011 period, with no mortgage effect of flag removal in prior years.