The Role of Income in Banking
Last registered on April 21, 2014


Trial Information
General Information
The Role of Income in Banking
Initial registration date
Not yet registered
Last updated
April 21, 2014 8:50 PM EDT
Primary Investigator
Goldman School of Public Policy, UC Berkeley
Other Primary Investigator(s)
Additional Trial Information
Start date
End date
Secondary IDs
Researchers and advocates have spent countless resources attempting to bring unbanked people into a bank. Secular demographic and economic trends also play a role in driving determining the proportion of people in a society who are banked. This study uses a fixed effects and regression discontinuity design to estimate the effect of household income on propensity to be banked.
External Link(s)
Registration Citation
Thompson, Dan. 2014. "The Role of Income in Banking." AEA RCT Registry. April 21.
Experimental Details
Intervention Start Date
Intervention End Date
Primary Outcomes
Primary Outcomes (end points)
Having a checking or savings account
Primary Outcomes (explanation)
Our outcome variable of interest is whether anyone in the household has a checking or savings account. This is available in the Current Population Survey as the answer to the question: "Do you or does anyone in your household currently have a checking or savings account?" (HES2) A comparable question is asked in the Survey of Consumer Finances: "Now I'd like to ask about different types of assets that you might have. First, do you (or anyone in your family living here) have any checking accounts?" (3501 N1) combined with "Do you (or anyone in your family living here) have any (other) accounts at banks, savings and loan associations, or credit unions? These could be passbook accounts, share accounts, Christmas Club accounts, or any other type of savings account." (3801 N23)
Secondary Outcomes
Secondary Outcomes (end points)
Secondary Outcomes (explanation)
Experimental Design
Experimental Design
My primary strategy is a fuzzy RDD.
Experimental Design Details
The primary design that motivates this study is a fuzzy regression discontinuity design with the CPS/FDIC data. In this design, we instrument for an as-if-random increase in income with eligibility for SNAP benefits. This design may have limited power to identify an effect due to the weakness of the instrument and the limited, and necessarily, impermanent increase in income. We use the SCF to model the effects of within-family changes in income on banking status. This estimate likely suffers from serious bias, and is intended as supplementary. This model is expected to reveal a stronger effect of income on banking status.
Randomization Method
Regression discontinuity
Randomization Unit
SNAP benefits are determined based on family characteristics, so the randomization--assuming that is observed--is occurring on the family level.
Was the treatment clustered?
Experiment Characteristics
Sample size: planned number of clusters
151,884 in CPS
Sample size: planned number of observations
151,884 in CPS
Sample size (or number of clusters) by treatment arms
151,884 in CPS
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
My data set is already given, and I have selected my tests in advance, so I cannot manipulate my power unless by including and removing covariates. My regression discontinuity design should provide a balance without matching or controlling for covariates if the design works.
IRB Name
IRB Approval Date
IRB Approval Number
Post Trial Information
Study Withdrawal
Is the intervention completed?
Is data collection complete?
Data Publication
Data Publication
Is public data available?
Program Files
Program Files
Reports and Papers
Preliminary Reports
Relevant Papers