Marginal propensity to consume out of liquidity
Last registered on February 02, 2015


Trial Information
General Information
Marginal propensity to consume out of liquidity
Initial registration date
February 02, 2015
Last updated
February 02, 2015 2:57 PM EST
Primary Investigator
Other Primary Investigator(s)
Additional Trial Information
On going
Start date
End date
Secondary IDs
This experiment uses exogenous variation in borrowing capacity to test competing models of inter temporal consumption behavior. I estimate the marginal propensity to consume (MPC) out of liquidity, the debt response to a change in borrowing capacity, using changes in credit card limits in a randomized controlled trial. I analyze the magnitude, duration and the heterogeneity of the MPC, as well as where the additional liquidity is spent. I test apart theories that predict a high MPC, such as myopia or liquidity constraints/precautionary savings.
External Link(s)
Registration Citation
Aydin, Deniz. 2015. "Marginal propensity to consume out of liquidity." AEA RCT Registry. February 02.
Former Citation
Aydin, Deniz. 2015. "Marginal propensity to consume out of liquidity." AEA RCT Registry. February 02.
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Experimental Details
Intervention Start Date
Intervention End Date
Primary Outcomes
Primary Outcomes (end points)
The main outcome variable of interest is the response of credit card debt to a change in credit card limits. Credit card limit consists of revolving credit card balances, and balances in installments. Secondarily, I am interested in the consumption response in different sectors and other balance sheet effects, such as savings accounts.
Primary Outcomes (explanation)
Secondary Outcomes
Secondary Outcomes (end points)
Secondary Outcomes (explanation)
Experimental Design
Experimental Design
The assignment of credit line is done in three steps. First, the credit sales group pre-selects customers according to a set of profitability criteria. These criteria include the expected value added from limit increase, as well as macro prudential criteria imposed by the banking regulation authority preventing line increases, such as having pre-existing unpaid balances exceed half the card limit. The pre-selected individuals are then filtered by the bank’s risk group, according to a set of risk criteria. Finally, the remaining customers are pushed into the central bank’s credit limit clearing system to check if they are eligible for a credit limit extension, i.e. if their current limit is below four times their income. The randomization is done after the final step, therefore the control group consists of individuals that pass all criteria for being assigned an increased credit limit, but are not.
Experimental Design Details
Randomization Method
Randomization is done in STATA.
Randomization Unit
Individuals are grouped on the basis of credit card utilization, defined as the ratio of end-of-month credit card balances to credit limit. I first estimate a distributed lag-model on the observational data for each utilization decile. The standard errors of the MPC estimates are higher for high utilization individuals, therefore I under-sample individuals that have a low credit card utilization, proportional to the standard errors.
Was the treatment clustered?
Experiment Characteristics
Sample size: planned number of clusters
54524 individuals
Sample size: planned number of observations
54524 individuals
Sample size (or number of clusters) by treatment arms
13438 control, 13416 treatment, 27670 treatment (undersampled)
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
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