Boosting Demand in Markets for Experience Goods

Last registered on March 30, 2023


Trial Information

General Information

Boosting Demand in Markets for Experience Goods
Initial registration date
March 24, 2023

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
March 30, 2023, 3:30 PM EDT

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



Primary Investigator

University of Wisconsin-Madison

Other Primary Investigator(s)

PI Affiliation
University of Chicago
PI Affiliation
Monash University

Additional Trial Information

On going
Start date
End date
Secondary IDs
Prior work
This trial is based on or builds upon one or more prior RCTs.
Trust is a desirable feature in markets for experience goods as it induces demand. Therefore, if consumers believe it is very unlikely to find sellers that offer high-quality goods, this type of markets may break down. Consequently, a change in consumer beliefs can boost demand for experience goods. In this paper, we experimentally test if a shock to consumer beliefs, namely the entry of a quality-conscious seller into the market, can boost demand for an experience good. We conduct a lab-in-the-field experiment with farmers in Western Kenya, where we recreate an agricultural input market. Specifically, participants choose between two types of goods: one with fixed quality and another one with varying quality, which is unknown ex-ante. Some randomly selected respondents also have the chance to select the varying-quality good from two types of distributions, which respondents partially know. One of those quality distributions, which represents the quality-conscious entrant seller, has a smaller mean and variance than the incumbent distribution. Additionally, we elicit respondents' beliefs about the quality distributions to test whether the effect of entry on demand depends on consumer beliefs rather than the true quality distribution of the experience good in the market. Finally, we elicit participants willingness-to-pay for the different goods offered throughout the game to observe if their valuation varies depending on the quality distribution they face.
External Link(s)

Registration Citation

Deutschmann, Joshua, Felipe Parra Escobar and Emilia Tjernstrom. 2023. "Boosting Demand in Markets for Experience Goods." AEA RCT Registry. March 30.
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Experimental Details


Intervention Start Date
Intervention End Date

Primary Outcomes

Primary Outcomes (end points)
Our main outcomes of interest are
- Respondents' demand of the experience good (i.e., seeds)
- Respondents' valuation of the experience good sold by the quality-conscious entrant seller with respect to the valuation go the experience good sold by the incumbent store.
Primary Outcomes (explanation)
We construct the variables in the following way:
- We obtain the respondents' demand for the experience good from the market game. Specifically, we record whether the participant choose the experience good (i.e., seeds) over the alternative good in each one of the rounds of the game.
- We obtain respondents' valuation of the experience good from the willingness-to-pay exercise. We will compute the ratio of the entrant's good WTP to the incumbent's good WTP.

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
1. Market game:
Participants play for 20 rounds. In each round, respondents choose between hybrid maize seeds sold by a hypothetical incumbent store and an alternative good. We assume the quality of maize seeds is not fixed, for that reason, the amount of high-quality seeds that they might receive varies in each round. To achieve this in the experiment, participants choosing seeds take out 10 marbles out of a bag that we denote as the incumbent's bag. Participants can trade each black marble that they take out for 100 grams of hybrid maize seeds of their preferred variety with a germination rate above 90%. Participants face two different incumbent stores during the experiment; one in the first 10 rounds and a different one for the second 10. Each incumbent store has a different quality distribution. In particular, we consider four different quality distributions:
- High-quality and high-dispersion (HQ/HD): 80 black and 20 white marbles
- High-quality and low-dispersion (HQ/LD): 16 black and 4 white marbles
- Low-quality and high-dispersion (LQ/HD): 60 black and 40 white marbles
- Low-quality and low-dispersion (LQ/LD): 12 black and 8 white marbles.

Each session is randomly assigned to a pair of distributions before starting the game. In each round, participants have the chance to choose an alternative good instead of hybrid maize seeds. Before we start the game, respondents choose between 3 kg of maize flour, 1 liter of cooking oil, and 2 kg of sugar as the alternative good for all 20 rounds. The quantities chosen are monetary similar to 1 kg of hybrid maize seeds by March 2023. In order to inform participants about the quality distributions they will face during the game, we take 10 draws out of each incumbent's bag before round 1 and 11 and write them down in a whiteboard visible to all respondents.

After rounds 5 and 15, we conduct an exercise to elicit participants' beliefs about the incumbent's quality distribution. We ask respondents to imagine they will play the game for an additional 20 rounds, and each time they will choose seeds over the alternative good. We then ask them how many white marbles they believe they would take out each time. We provide participants with a chart with 20 boxes on it, each one representing these hypothetical rounds of the game. We instruct respondents to place some beans in each box depending on how many white marbles they believe they would take each time.

To observe the consumers' reaction to the entry of a quality-conscious seller, we add a new bag to the choice set of some participants that are randomly selected after round 5 and 15. This new bag which represents the entrant store has a quality distribution with higher mean and lower variance than the incumbent store. In particular, this new bag has 18 black and 2 white marbles. In case selected participants choose maize seeds over the alternative good, they can decide to take marbles out from the incumbent's or the entrant's bag. Finally, we incentive the game by giving to participants the good they chose in a randomly selected round.

2. Willingness-to-pay elicitation:
After we conclude the market game, we conduct an exercise to elicit participants' willingness-to-pay for six different goods:
- Bag of maize seeds sold by the incumbent store of the first 10 rounds
- Bag of maize seeds sold by the incumbent store of the second 10 rounds
- Bag of maize seeds sold by the entrant store
- 1 kg of maize seeds with a germination rate between 90 and 95%
- 1 kg of maize seeds with a germination rate above 95%
- The alternative good selected by the participant at the beginning of the game.
For the first three items, we ask participants to take 10 marbles out of each bag and put them in separate smaller bags that we seal. We reveal the content of the bags after we have concluded the exercise.

We conduct a multiple price list approach to elicit respondents' WTP. For each item, we ask participants whether they are willing to buy the good at different prices. We offer the items at prices ranging between 0 and 300 KES. To check for inconsistent choices in the form of single- or multiple-switching behavior, we offer the good at all prices in the list (Jack et al., 2022). In addition, we also randomize the order in which the choices are presented to respondents to take into account any framing effect on the participants' valuations. Specifically, we randomize whether we start asking a participant the question with the smallest price and then continue in ascending order, or we begin with the biggest price and then proceed in descending order.

To incentivize participants to reveal their true WTP, we inform them that we will randomly select one price from the list. If at the selected price, the participant expressed to be willing to purchase the good, then she buys it at that price. Conversely, if the participant stated she is not willing to buy the item at the selected price, then she will not be able to purchase it. To increase power, we elicit WTP for all six items but only incentivize one of them, which is randomly selected. In other words, we randomly select one good and then they draw the price. Finally, participants receive 500 KES for their participation in the experiment. They use this money to pay for the good chosen in case they purchase it.

3. Survey
After concluding the experiment, we administer a survey to each participant to collect data on their previous experience with One Acre Fund and agricultural input purchasing decisions for the last year. In addition, we ask about their perception of input quality of their local market and quality check practices that they may have when purchasing inputs. Finally, we administer a module on risk and time preferences with questions taken from the Global Preferences Survey (Falk et al., 2018).
Experimental Design Details
Randomization Method
Randomization into incumbent's quality distribution and entry treatment occurs in the field, before enumerators recruit participants for a session.
Randomization Unit
Randomization into incumbent's quality distribution occurs at the session level (i.e., groups of five participants), whereas randomization into the entry treatment occurs at the individual level.
Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters
63 sessions of five participants (i.e., three sessions in 21 market centers).
Sample size: planned number of observations
315 farmers.
Sample size (or number of clusters) by treatment arms
158 farmers assign to the treatment group (entry) and 157 to the control group
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
We are powered to detect an increase in the odds ratio of 2.22 for participants experiencing entry in a market where the incumbent has low average quality. Similarly, we are powered to detect a decrease in the odds ratio of 2.22 for participants experiencing entry in a market where the incumbent has low quality dispersion.

Institutional Review Boards (IRBs)

IRB Name
University of Wisconsin-Madison
IRB Approval Date
IRB Approval Number
Analysis Plan

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Post Trial Information

Study Withdrawal

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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