Whose brighter future? Parent-bias and investments in children.

This study will document whether parents make plans to invest in their children’s in the future, but are tempted to reverse them at the moment the investment needs to be done, favoring their own consumption at the expense of investments in their children. Additionally, we will measure whether parents, at the time of making investment decisions, are aware of the risk that they could change their mind in the future, and demand commitment devices to help them stick to their plans. Answering these questions could contribute to explain why investments in children’s health and education are so low. Moreover, it would produce important insights to design cost-effective interventions, such as commitment devices, to reduce the temptation to divert resources away from children.
We present here the design of a lab-in-the-field experiment designed to test the following hypotheses: 1) Do parents discount their own future consumption and that of their children differently?
2) Does this differential discounting give rise to within-household inconsistencies (parent-bias)? 2
3) Is there demand for commitment devices to help mitigate parent-bias, above and beyond demand for commitment devices that help mitigate classical present-bias?
4) Do parents demand to involve their children in future decisions as a commitment device?
5) Is the demand for commitment explained by parents’ beliefs that they might be tempted to change their plans in the future?
6) Can labeling mitigate parent-bias?
7) Can encouraging children to participate in household decisions increase investments in children and mitigate parent-bias?

To be able to document the joint distribution of “Traditional” and “Withinhousehold” time-inconsistencies, our experiment follows a three-step data collection process. We ask the parents to split the consumption of a tempting, non-fungible and immediately consumable good (peanuts) between them and their children and across time, cross-randomizing the type of commitment devices which are made available to the households. Our design allows us to observe the parents’ plan at t = 1, its potential revision at t = 2 and the consumption of the good. Peanuts have been chosen because they are a nutritious food that Malawians are familiar with and because they are consumed by both parents and children in Malawi. The experiment took place during the lean season, when the stock of peanuts that households may have had at home from the previous harvest has been depleted. This timing ensures that peanuts are a tempting good.

A. Structure of the experiment

The date of the first visit is randomly assigned to villages. A respondent speaks to a different experimenter in each visit and the visits have been scheduled to take place at a similar time of the day. At the beginning of the first and second visits, the surveyor tells the parents that they are interested in learning about peanut consumption in Malawi and that, depending on the choices they make and a random implementation rule, they and their child may be invited to consume some peanuts and share their thoughts about their experience with the team. Note that informing the respondents from the onset that the peanuts will be consumed in front of the enumerator inform them that, depending on the random implementation rule, the decisions they make are binding. The respondents are first invited to taste a small quantity of peanuts to ensure that they are making those decisions in a “hot” state.

The respondents are then presented with two different scenarios. The order in which the respondents are presented with the different scenarios will randomly vary. In scenario Blue, the respondent allocates 3 packets of 15 grams of peanuts between t = 2 and t = 3, that they will consume themselves. Each packet of groundnuts whose consumption is delayed from t = 2 to t = 3 yields an interest rate of r. The team presents the different possible allocations to the respondent, who picks one. The respondent has to make this choice for three interest rates: 0.5, 1 and 1.5. A picture of the possible allocations is presented to the respondent to facilitate comprehension. In scenario Red, the respondent allocates 5 packs of groundnuts between themselves and their child to be consumed at t = 2 and t = 3. This relates to our model’s second decision: the parents have a trade-off between their consumption and that of their children at t = 2 and at t = 3. To help with this decision, the parents are invited to share 5 packets of peanuts between two plates, one entitled ”you, in two days”, the other one “Your child in two days”. The enumerator records this decision. Then the parents are invited to do the same thing for the t = 3 allocation. In the second visit, the respondents and the children are invited to meet the surveying team separately from the rest of the family. The respondents are invited to taste a small quantity of peanuts first and then asked how they would like to act in both scenarios. At the end of the second visit, one of those scenarios is implemented according to the following random implementation rule:

1) Scenario Red or Blue is randomly picked,
2) t = 1 or t = 2 decision is randomly chosen to be executed,
3) If Scenario Blue is chosen, the interest rate that counts is randomly selected.

If scenario Blue is picked: the respondent is given the packets for the day.

If scenario Red is picked: the respondent and the child are given the packets for the day according to the chosen split. While they eat the peanuts, they are asked a series of questions about peanuts and whether they are appreciating eating them. This ensures that the enumerator will observe the actual peanut consumption and that the respondent’s decision has been followed-through. During the third visit, the peanuts that were allocated to be received on that day are distributed to the respondents and they are asked a series of questions about their peanut consumption to ensure that they are consuming the peanuts in front of the enumerator. At the end of the visit, the parents are also asked a series of survey questions about investments in children and whether they would be interested in a series of commitment devices, such a safe-boxes or a separate meal plan for their child.

2018-11-05

2019-01-31

-Share of peanuts to be consumed by the child at t = j (j ∈{2,3}), when making the decision at t = 1;
-Share of peanuts to be consumed by the child at t =2, when making the decision at t =k, (k ∈{1,2});
-Difference between the share of peanuts allocated to be consumed by the child at t = 2 while making the decision at t = 1 and t = 2;
- Difference between the share of peanuts allocated to be consumed by the child at t = 3 and t = 2 while making the decision at t = 1 and t = 2;
-Take-up of the probabilistic commitment devices,
-Willingness to let the child participate in round 2 decision.

We will define the following dummy variables:
-Parent-bias;
-Child-bias;
-Present-bias;
-Present-bias.

We will define the following dummy variables:
-Parent-bias: Equal to 1 if parents reallocate more towards their own consumption than they had originally planned;
-Child-bias: Equal to 1 if parents reallocate more towards their child's consumption than they had originally planned;
-Present-bias: Equal to 1 if parents choose to receive more, on average across interest rates, in the earlier time period when making the decision at t=2 than t=1 in part Blue.
-Present-bias: Equal to 1 if parents choose to reallocate more peanuts

This experiment will be conducted in 80 villages of Salima district in Malawi, with 2,400 participants.

This experiment will be conducted in 80 villages of Salima district in Malawi, with 2,400 participants. As this experiment will be conducted alongside another project’s baseline survey, this sample size was based on the power calculations for our other project. Within each village, our sample is built using a random walk approach: the enumerators assess the eligibility of every 5th or 4th house they encounter in the village while following a pre-determined path. The households are considered eligible to participate in the experiment if:
1) There is at least one child aged 3-12 in the household, 2) Both parents live in the household, 3) Nobody is allergic to peanuts in the household.
The second criteria was added to guarantee that households in which we interrogate fathers are not on average different from households in which we interrogate mothers. Only mothers are invited to take part in the experiment in 64 villages. In the remaining 16 villages, we randomly select whether the mother or the father, within the eligible household, will be invited to participate in the experiment. In those villages, we over-sample fathers to ensure that we will have a large enough number of fathers in our experiment. We aim to have 360 fathers in our sample. If the household has more than one child aged 3-12, we will randomly select which child will be invited to take part in the experiment.

The subjects are randomized across treatment arms in two steps:

• They are first allocated to be offered different commitment devices: a “Probabilistic commitment” or “Child’s participation (chosen)”.

•Subjects allocated to being offered a probabilistic commitment device are then allocated to different framings of choice at t = 2: "Baseline", "Labeling", "Random", "Child's participation (imposed)".

A. Commitment devices

Probabilistic commitment devices

We offer the respondents in those treatment arms a probabilistic commitment device (following Augenblick, Niederle and Sprenger (2015)), which decreases the likelihood that the t = 2 allocation is chosen over the t = 1 allocation. In other treatment arms or if the respondents do not wish to take up a commitment device, the t = 1 decision will be executed with a 10% probablity. If the respondents take up a commitment device, the probability that the t = 1 decision will be executed increases to 90%. This allows us to observe both t = 1 and t = 2 decisions for all

respondents, irrespective of commitment and guarantees the credibility of both decisions because the respondents are aware in each round that their decision can be selected to be executed. The respondents are offered to take up a probabilistic commitment device after making a decision for each scenario during the first visit. We randomly vary the price of the commitment device: to purchase the commitment device, the respondent will have to forego 0.5/1/1.5 packets of peanuts at t = 3.

Child’s participation (chosen)

We ask respondents in this subsample whether they would like to invite their child to make the t = 2 decision for part Red with them. This could be a way for t = 1 parents to force their t = 2 self to stick to the plan they had made for their child. We randomly vary the price of this commitment device: to purchase the commitment device, the respondent will have to forego 0/0.5/1/1.5 packets of peanuts at t = 3.

B. Framing of choices

Baseline

The enumerators speak to the respondents alone during the second visit. The respondents are invited to taste a small quantity of peanuts at the beginning of the interview, explained the rules of the experiment one more time and asked how they would like to act in each scenario.

Labeling treatment

The enumerators speak to the respondents alone during the second visit. The respondents are invited to taste a small quantity of peanuts at the beginning of the interview, explained the rules of the experiment one more time, presented with the allocation choice they have made in scenario Red at t = 1 and asked how they would like to act in each scenario.

Random Anchoring treatment

The enumerators speak to the respondents alone during the second visit. The respondents are invited to taste a small quantity of peanuts at the beginning of the interview, explained the rules of the experiment one more time, presented with a random allocation in scenario Red and asked how they would like to act in each scenario. This treatment arm enables us to distinguish between the effect of labeling itself and of anchoring.

Child’s participation (imposed)

During the second visit, the children are asked to participate in part Red decision in this treatment arm. The respondents and the children are invited to taste a small quantity of peanuts at the beginning of the interview, explained the rule of the experiment. The respondent makes a decision on part Blue alone and on part Red jointly with the child. This treatment arm enables us to measure the impact of an increase in the child’s bargaining power on parent-bias, without the self-selection inherent to parents having chosen to involve their child as a commitment device.

C. Survey instruments
Naive and sophisticates

Understanding how sophisticated individuals are with regards to their future behavior is key to interpreting the demand for commitment devices. However, incentivizing questions eliciting beliefs about one’s own future behavior can lead to changes in this future behavior (Acland and Levy, 2015) or can encourage individuals to use predictions about their own behavior as a commitment device (Augenblick and Rabin, Forthcoming). To circumvent this problem, we adopt a strategy following closely that of Toussaert (2018). After making a choice for each scenario, respondents are asked an incentivized question eliciting their beliefs about others’ behavior:

• Scenario Blue: We are asking many other households to make those decisions. Do you think that two days from now most other people will...
– Choose to receive MORE peanuts immediately than they did today?
– Choose to receive LESS peanuts immediately than they did today?
– Choose to receive the same amount of peanuts immediately as they did today?

• Scenario Red: We are asking many other households to make those decisions. Do you think that two days from now most other people will..
– Choose to give LESS peanuts to the child than they did today?
– Choose to give MORE peanuts to the child than they did today?
– Choose to give the same amount of peanuts to the child as they did today?
Correctly predicting the behavior of the majority of the population will earn the respondents one additional packet of peanuts at the end of round three. Those questions are motivated by research that shows that people use information about their own behavior to inform their beliefs about the behavior of others.

The randomization will happen alongside the first visit of data collection, and will be done with the tablet.

Individual

No

2400

2400

Type of Commitment :
Probabilistic (2000 respondents) // Child’s participation (chosen) (400 respondents)

Framing
Baseline (800 respondents)// Labeling (400 respondents) // Random Anchoring (400 respondents)// Child's participation (imposed) (400 respondents)

1. Do parents discount their own future consumption and that of their children differently? Hypothesis 1a: Parents discount their own future consumption more than that of their children. We are testing whether parents allocate a larger share of peanuts for their child to consume at t=2 than at t=3, when making the decision at t=1. We will pool the observations from all our subsamples except “Child’s participation (imposed)” to conduct this analysis. This would allow us to detect a 0.0886 s.d. difference in the share of peanuts allocated to the child at t = 2 and t = 3, which is 2.55% of the mean of the outcome variable, as measured in the pilot. For consistency with the rest of our analyses, we will also conduct the same regression in the “Probabilistic commitment device × Baseline” sample, which would allow us to detect a 0.1402 s.d. difference, which represents 4.21% of the pilot mean of the outcome variable 2. Does this differential discounting give rise to within-household inconsistencies (parent-bias)? Hypothesis 2a: Parents exhibit parent-bias. We are testing whether parents allocate a smaller share of peanuts for their children to consume at t=2 when making the decision at t=2 rather than t=1. We will conduct this regression in the “Probabilistic commitment device × Baseline” sample, which would allow us to detect a 0.1402 s.d. difference, which is 3.46% of the pilot value of the mean outcome variable. Hypothesis 2b: Parents exhibit Within-household Present-Bias. We are testing whether the gap between the planned t=2 and t=3 allocations is larger when parents make the decision at t=2 than t=1. We will conduct this regression in the “Probabilistic commitment device × Baseline” sample, which would allow us to detect a 0.1402 s.d. difference between both gaps (90% of the mean outcome variable, as measured in the pilot). 3. Is there demand for commitment devices to help mitigate parent-bias, above and beyond demand for commitment devices that help mitigate present-bias? Hypothesis 3a: Parents demand commitment devices to help them stick to their within-household allocation plans. 2,000 respondents in our sample are offered a probabilistic commitment device to help them stick to their planned within-household allocation. They are offered this probabilistic commitment device at 3 different prices: 0.5/1/1.5 packets of peanuts. We will plot the demand curve for this commitment device, at different level of prices. Hypothesis 3b: The demand for commitment devices to help parents stick to their within-household allocation plans is smaller than the demand for commitment devices to help them stick to their inter-temporal allocations. The respondents are also offered a probabilistic commitment device to help them stick to their inter-temporal allocation. We will pool the observations from all our “Probabilistic commitment devices” subsamples except “Child’s participation (chosen)” to conduct this analysis. This would allow us to detect a 0.0991 s.d. difference between the take-up of both types of commitment devices (2.4% of the mean value of the outcome variable, as measured in the pilot). For consistency with the rest of our analyses, we will also conduct the same regression in the “Probabilistic commitment device×Baseline” sample, which would allow us to detect a 0.1402 s.d. difference (3.4% of the mean outcome variable). 6. Can labeling mitigate time-inconsistencies? Hypothesis 6: Reminding parents of their past choices will decrease time inconsistencies. -Pooling samples from the “Baseline” and “Labeling” treatment arms, we will measure whether labeling help mitigate time-inconsistencies. This sample size enables us to detect a 0.1717 standard deviation decrease in the change of the share of peanuts allocated to be consumed by the child at t=2 following the introduction of labeling (160% of the mean of the outcome variable in the Baseline treatment arm, as measured in the pilot). Distinguishing between the role of labeling and anchoring We will distinguish between the role played by labeling and anchoring, by polling the “Labeling” and “Anchoring” samples. This sample size enables us to detect a 0.1983 standard deviation difference in the distance between the amount of peanuts allocated to the child by the parents at t = 2 and in the allocation presented to them. 7. Can encouraging children to participate in household decisions increase investments in children and mitigate parent-bias? Hypothesis 7a: Making children participate in household decisions increases investments in children We will test this hypothesis by pooling the “Baseline” and “Child’s decision (imposed)” samples. This sample size enables us to detect a 0.1717 standard deviation increase in the share of peanuts allocated to the child following the increase in child{'}s bargaining power (3.55% of the mean outcome variable in the baseline treatment arm, as measured in the pilot). Hypothesis 7b: Making children participate in household decisions decreases reallocation towards parents We will test this hypothesis by pooling the “Control” and “Child’s decision (imposed)” samples. This sample size enables us to detect a 0.1717 standard deviation decrease in the change in the share of peanuts allocated to the child following the increase in child{'}s bargaining power. 8. Heterogeneity analysis: do mothers and fathers discount the future differently? We will look at whether mothers and fathers differ in terms of investments in children on different dimensions: 8a. Do mothers plan to invest more in their children in the future? We will test this hypothesis in our baseline sample. Our sample size allows us to detect a 0.2949 s.d. difference in the share of peanuts mothers and fathers plan to allocate for their child’s t=2 consumption, when making the plan at t=1 (7.70% of the mean outcome variable in the pilot) 8b. Do mothers invest more in the children when the time comes? We will test this hypothesis in our baseline sample. Our sample size allows us to detect a 0.2949 s.d. difference in the share of peanuts mothers and fathers plan to allocate for their child’s t=2 consumption, when making the decisionplan at t=2 (6.1% of the mean outcome variable in the pilot) 8c. Are fathers more time-inconsistent than mothers? We will test this hypothesis in our baseline sample. Our sample size allows us to detect a 0.2949 s.d. difference in the change in the share of peanuts mothers and fathers plan to allocate for their child’s t=2 consumption, when making the decision plan at t=2 and t=1. (316% of the mean outcome variable in the pilot) 8d. Do mothers demand more commitment devices to stick to their within- household allocation plans? We will test this hypothesis in our probabilistic commitment device sample. Our sample size allows us to detect a 0.2084 s.d. difference in the take-up of the probabilistic commitment device between mothers and fathers (4.8% of the mean of the outcome variable, as measured in the pilot). 8e. Do mothers demand to let their children participate in the t = 2 decision more? We will test this hypothesis in our “Child’s commitment (chosen)” subsample. Our sample size allows us to detect a 0.3243 s.d. difference in the willingness to let the child participate between mothers and fathers. (37% of the mean of the outcome variable, as measured in the pilot).

Pre-analysis Plan