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.

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.

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

Income timing for oasdi beneficiaries

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

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

Long Pay Periods Are Evenly Distributed

Two Data sources

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 2010-2015 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

Loan-level Data From Storefront Payday Lenders All loans from a number of large storefront payday lenders between 2010-2012 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

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

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

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

Does income timing affect financial shortfalls?

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 - 0.026 - 0.104 - 0.142 - 0.036 (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

Why does income timing matter?

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

Timing Mismatch Increases Financial Shortfalls OD 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

When is it hard to make ends meet?

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

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!