Why do consumers ignore hidden costs?

Last registered on August 03, 2022


Trial Information

General Information

Why do consumers ignore hidden costs?
Initial registration date
July 28, 2022

Initial registration date is when the trial was registered.

It corresponds to when the registration was submitted to the Registry to be reviewed for publication.

First published
August 03, 2022, 2:10 PM EDT

First published corresponds to when the trial was first made public on the Registry after being reviewed.



Primary Investigator


Other Primary Investigator(s)

PI Affiliation
Swarthmore College

Additional Trial Information

Start date
End date
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Prior research has documented that consumers act as if they ignore hidden costs (such as sales tax). The goal of our research is to understand why this is the case, by explicitly testing several hypotheses. In prior work, we have tested whether inattention is likely attributable to lack of knowledge, lack of accurate information, or forgetfulness. These hypotheses are not supported by the data. We also tested whether constraints on cognitive resources, slack budget constraints, how prices and costs are presented affect attention.
External Link(s)

Registration Citation

Bengali, Leila and Syon Bhanot. 2022. "Why do consumers ignore hidden costs?." AEA RCT Registry. August 03. https://doi.org/10.1257/rct.9817
Experimental Details


In the current study, our goal is to test two hypotheses: 1) whether the pursuit of transaction utility could lead individuals to disregard hidden costs; and 2) whether present bias or numerical literacy affects an individual’s tendency to disregard hidden costs.
Intervention Start Date
Intervention End Date

Primary Outcomes

Primary Outcomes (end points)
Intended analysis
Does deal utility exist in the context of transactions with hidden costs? (i.e. do people get more utility from transactions in which sales taxes are not shown compared to transactions in which sales taxes are shown?)
We will compare the subjective ‘deal’ rating responses by treatment group. These ratings were designed to be a direct subjective measure of transaction utility.
As a secondary analysis, we will compare the probability of choosing to buy the product between those randomly assigned to see prices with sales taxes (tax-inclusive treatment arm) and those randomly assigned to see prices without (tax-exclusive treatment arm). If seeing prices without sales tax increases transaction utility, we would expect this to result in an increased probability that the participant will choose to buy the product.
In both cases, we will make simple comparisons of proportions (or means) as well as testing the hypotheses using regressions that control for the amount of transaction utility (as defined in prior theoretical work as the difference between the expected price and the actual price), demographic characteristics, and other factors that have been shown to affect attention such as a change in the left-most digit once sales taxes are included.
Do measures of present bias or numeracy affect transaction utility when prices are shown with or without sales tax?
We will use regression analyses to test whether any difference between transaction utility (using the subjective ‘deal’ questions and also the decision to buy the products) in the tax-exclusive and tax-inclusive treatment arms varies systematically by numeracy and/or present bias.
Do people make choices to preserve transaction utility?
We will compare the subjective ratings and the probability of purchasing the products between respondents who saw prices as they indicated that they would prefer to see prices and those who saw prices the other way. That is, we will see whether seeing prices in the preferred way results in more transaction utility from a given purchase decision.
How do individuals prefer to see prices and taxes?
We will test whether participants’ preference for how to see prices (tax-inclusive, tax-exclusive, all-in) and their level of support for an all-in price policy varies by treatment arm, numeracy score, or presence of present bias (using the simple definition of choosing $100 now and $110 in eight days). We will run these analyses as simple comparisons of means and in regressions with controls as noted above.
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
In the current study, our goal is to test two hypotheses: 1) whether the pursuit of transaction utility could lead individuals to disregard hidden costs; and 2) whether present bias or numerical literacy affects an individual’s tendency to disregard hidden costs.
Experimental Design Details
In our study (an online experiment run with a representative sample of the U.S.), participants are shown a series of consumer products. Participants are asked for their state of residence so that we are able to record the applicable state sales tax rate. First, we ask participants for the price they would expect to pay for these products in a store, to establish a “reference price.” Participants are then shown each of those products one at a time along with an auto-generated price. Participants are randomly assigned to see prices with or without sales tax explicitly shown. (For example, a participant in the tax-exclusive treatment arm would see prices as they are normally displayed in stores in the U.S., as $4.99, for example. A participant in the tax-inclusive treatment arm would see this price as $4.99 + $0.36 tax, $5.35 total.) Participants then indicate whether they would or would not buy at the price they see and are asked several subjective questions about how good of a ‘deal’ the price is. Participants are asked how they would prefer to see prices in the future (tax-inclusive or tax-exclusive). Participants are then asked if they would instead prefer to see all-in prices (i.e., just the total tax-inclusive price as is done for gasoline in the U.S. and in countries that have a VAT tax such as England) and their level of support for such a policy in the U.S. Participants are also given a short numeracy test (a five-question quiz that asks participants to calculate proportions and percentages in real-world situations such as leaving tips and lottery winning probabilities) and answer two questions to assess present bias (choose $100 today or $110 tomorrow and choose $110 in eight days or $100 in seven days).
Randomization Method
randomization done by a computer
Randomization Unit
Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters
Sample size: planned number of observations
Sample size (or number of clusters) by treatment arms
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)

Institutional Review Boards (IRBs)

IRB Name
University of California Los Angeles IRB
IRB Approval Date
IRB Approval Number


Post Trial Information

Study Withdrawal

There is information in this trial unavailable to the public. Use the button below to request access.

Request Information


Is the intervention completed?
Data Collection Complete
Data Publication

Data Publication

Is public data available?

Program Files

Program Files
Reports, Papers & Other Materials

Relevant Paper(s)

Reports & Other Materials