1. When is it hard to make ends meet
When is it hard to make ends meet? brian baugh – university of Nebraska lincoln Jesse Leary – financial conduct authority Jialan Wang - University of Illinois at Urbana-Champaign August, 2017
The views expressed are those of the authors and do not necessarily reflect the opinions of the Consumer Financial Protection Bureau, its director or staff, or the United States. The research reported herein was pursuant to a grant from the U.S. Social Security Administration (SSA), funded as part of the Retirement Research Consortium (RRC). The findings and conclusions expressed are solely those of the authors and do not represent the views of SSA, any agency of the federal government, the Universities of Illinois or Nebraska, or the Financial Conduct Authority.

2. Half of All Americans Live Paycheck to Paycheck
One quarter to one half of households cannot come up with $2,000 in 30 days. (Lusardi, Schneider and Tufano 2011)
Concurrent income and expense shock would cost the average family $4,800, but typical liquid assets are only $3,000 (JPMC 2015)
Forty-six percent of individuals could not pay for a $400 emergency using available cash (Federal Reserve Board 2016)
Lusardi et al – 25-50% are liquidity constrained. JPMC – 4800 needed to weather 5th-percentile income and consumption shocks. Median household has 3k in liquid assets.

3. Social Security Benefits Disbursement Schedule
In 1997, the SSA started disbursing old age, survivor and disability insurance (OASDI) payments on the second, third, and fourth Wednesday of each month based on beneficiary date of birth
This schedule generates pay periods that are either 28 or 35 days long
 We examine the effects of the Wednesday payment schedule on the financial behavior and financial health of OASDI beneficiaries

4. Income timing for oasdi beneficiaries

5. Wednesday Groups are Paid at Different Times of the Month
90 million receive these benefits, 30 mil are in the Wednesday groups

6. About Four Pay Periods Per Year Are 35 Days Long
5 Wednesdays  35-day pay period

7. Long Pay Periods Are Evenly Distributed

8. Two Data sources

9. Credit Cards and Bank Accounts from Large Account Aggregator
Users who sign up for a free online service that automatically downloads information from bank and credit card accounts
Transaction-level coverage between
Financial distress measures
Overdrafts, bounced checks
Online payday loans
Other financial measures
Categorized expenditures (cash, check, restaurant, etc.)
Liquidity and savings
Limited demographics in both datasets

10. Loan-level Data From Storefront Payday Lenders
All loans from a number of large storefront payday lenders between
Tens of thousands of borrowers who receive Social Security benefits on one of three Wednesdays*
18% of all payday borrowers receive income from benefits or public assistance (CFPB, 2013)
Unique features of payday loans
Precisely-measured income source and income timing
Requires pay stub to obtain loan
Almost always due exactly on payday
Requires bank account, so most receive benefits through direct deposit
Timing and amount of loan use precisely measured at daily level
* Precise details of sample size and sample period shrouded to protect lender identities

11. Typical Aggregator Household: $1,300 in Benefits
Summary Statistics Per Household Month
Mean
Median
Std. Dev.
Has Recurring
Has Late
Income
$4,535
$3,347
$4,139
Social Security Income
$1,346
$1,387
$562
Other income
$3,189
$2,000
$4,110
Expenses
$6,705
$5,150
$6,801
Recurring
$2,607
$1,761
$2,874
79%
12%
Credit Card Payment
$1,788
$1,000
$2,225
70%
Mortgage
$647 $0
$1,149
32% 2%
Car Payment
$172
$358
23% 3%
Cash and Check
$2,021
$945
$4,659
Other
$2,078
$1,141
$1,496
Financial Shortfalls
13% 0%
34%
Overdrafts
11%
30%
Bounced Check
18%
Online Payday
0.2% 4%
Sumstats_bill

12. Typical Payday Consumer: $1,000 in Benefits
Panel A: Loan Terms at Origination
Mean
Median
Std. Dev.
Loan amount total
$352
$306
$169
Principal
$305
$255
$149
Finance charge
$47
$45
$25
APR
352%
282%
260%
Cost per 100
$16
$15 $4
Contract duration (days)
21.0 20
10.5
Panel B: Borrower Statistics
Monthly benefits income
$962
$864
$503
Total # of loan cycles
7.0 7
4.2
# of fresh loans
1.1 1
0.4
# of rollover cycles
5.9 5
Total fresh credit
$427
$400
$224
Total fees
$370
$320
$288
Total days indebted
196
195
121
-> Our analysis only considers “fresh” loans, since rollover loans always begin
and end on pay dates

13. SSA Benefit Distributions are Identical Across Wednesday Groups
Account Aggregator
Storefront Payday

14. Does income timing affect financial shortfalls?

15. More Shortfalls During Long Pay Periods and Fewer For Fourth Wednesday Group
Outcome: OD
Bounced
Online Payday
Storefront Payday
Sample Mean:
0.70%
0.19%
0.01%
0.05%
Long pay period
0.047
0.028
0.162
0.308
(0.011)
(0.061)
(0.062)
[0.001]
[0.020]
[0.017]
[0.000]
Third Wednesday
0.041
0.110
0.159
0.002
(0.017)
(0.058)
(0.022)
[0.014]
[0.925]
Fourth Wednesday
(0.013)
(0.021)
[0.059]
[0.033]
[0.107]
Regs_od
Table presents coefficients from regression analysis. Regressions include month, year, and day of month fixed effects. Standard errors are clustered by recipient group X year

16. Why does income timing matter?

17. We Test for the Role of Timing Mismatch Between Income and Expenditure Commitments
Hypothesis:
Shortfalls are correlated with timing mismatch between pay date and expenditure due dates
Fourth Wednesday group has less mismatch because many large expenses are due near the beginning of the month, leading to fewer shortfalls
Testing the predictions:
Measure the timing of large recurring bill payments
Measure timing mismatch
Estimate effect of mismatch on shortfalls

18. Timing Mismatch Increases Financial ShortfallsOD
Bounced
Online Payday
Sample mean
0.70%
0.19%
0.01%
Long day period
0.047
0.029
0.163
(0.005)
(0.010)
(0.049)
[0.000]
[0.003]
[0.001]
Timing Mismatch (weeks)
0.096
0.336
0.467
(0.071)
(0.108)
(0.398)
[0.178]
[0.002]
[0.240] R2
0.002
0.000

19. When is it hard to make ends meet?

20. When is it Hard to Make Ends Meet?
During predictably longer pay periods
When there is greater timing mismatch between income and expenses
Implications:
Policies and technologies that help smooth income and align the timing of income and expenditures may make beneficiaries better off

21. What Can We Do About It? Change income timing New technologies
Allow households to choose?
New technologies
Autopay and digital wallets
Liquidity smoothing and prediction
Low-hanging fruit: Encourage consumers to change their credit card due dates!