Education as a Legacy in Kaduna (Fathers only)

Study Name: Education as a Legacy in Kaduna, Northern Nigeria (Fathers only) 1) Have any data been collected for this study yet? 1 (a) No data have been collected 0 (b) Some data have been collected but not analyzed 0 (c) Some data have been collected and analyzed 2) Hypothesis: What’s the main question being asked, or hypothesis being tested? Hypotheses Among parents in Northern Nigeria, a treatment which frames education as a legacy which can be bequeathed to one’s grandchildren compared to a control which suggests the benefits of nutrition to the immediate family will: Report increased intention to devote resources to girls’ education (self-report assessed immediately). This will include reports of a. intention to increase financial allocation to girl child education vs boy education b. intention to allocate more money to girl child education vs household expenses c. willingness to engage with an elder in the community who disagrees with an allocation for girl child education 3) Give a brief (1-2 sentence) overview of the methods. Using a lab-in-the-field design, we will randomly assign 600 fathers who live in the environs of Kaduna (especially in communities where there are schools for children yet the enrolment rates for girls are lower than those of boys) to either the treatment (education as a legacy) condition or the control (value of nutrition) condition. We will thereafter assess an increase in behavioral indicators of investment in girls’ education. 4) Independent variables: Describe the conditions (for an experimental study) or predictor variables (for a correlational study). Participants who are parents will randomly be assigned to one of two between-subjects conditions: 1. A control consisting of 3 testimonials and 1 recall question highlighting the benefits of good nutrition for children in their education 2. A treatment consisting of 5 testimonials and 4 open-ended, reflection questions suggesting that education of children could have intergenerational benefits 5) Dependent variables: Describe the key dependent variable(s) specifying how they will be measured. PRIMARY OUTCOME Scholarship (Allocation task 1, total must equal N500,000) Sometimes the Kaduna state government puts on a city-wide scholarship lottery. Imagine that you have 2 children, and you have no money set aside for their education, so you enter the lottery for this scholarship. You have two children: ● Version A ○ A boy who is 12 & a girl who is 10 (Counterbalancing version B) ● Version B ○ A girl who is 12 & a boy who is 10 (Counterbalancing version A) The scholarship lottery is worth N500,000. Imagine you win the lottery. And you can put this money in an education savings account for each child. How much would you put out of the N500,000 in each child’s education savings account? ● Version A ○ Amount to the boy who is 12: N___________ ○ Amount to the girl who is 10: N___________ ● Version B ○ Amount to the girl who is 12: N___________ ○ Amount to the boy who is 10: N___________ Why did you divide the money this way? We will analyze the amount allocated to the girl (0-500,000). We will also analyze the responses to the open-ended question. Windfall (Allocation task 2, total must equal N100,000) Imagine that you have a younger cousin who lives in your community. His uncle from his mother’s side just got appointed as an aide to the Office of the State Governor. As a result, he is now a small contractor with the state government and he finds himself making an additional N100,000 per month from his business. Imagine that this cousin wants your advice on how to spend that N100,000. He wants to set the same allocation for every month going forward. The are 3 things he is considering are: - Save for future school expenses for his 12-year-old daughter for Senior Secondary School - Save for a medium sized generator - Save for a car for personal use Divide the N100,000 among the three things in a way you think would be best for the family in the long run. You can allocate all of the money to one thing, or give some to two things, or some to all three things. Willingness to engage (Binary outcome; yes/no) Suppose you decide to spend some money so your daughter can go to Senior Secondary School next year. There are other needs in the family, but you think this is best. Who is an elder in your life who might not agree with what you did? [name] What would you tell [name] to help him/her understand why you think this is best? [response] If [name] disagreed with this decision, would you actually talk with him/her about why you think this is best? [yes/no] 6) Analyses: Describe what analyses (e.g., t-test, repeated-measures ANOVA) you will use to test your main hypotheses. Allocation tasks Given the ratio scale of these variables, we will use linear regression to compare the allocations made to girls’ education between the treatment and the control group. The main outcomes would be whether respondents in the treatment group made a significantly larger allocation to education broadly and girls’ education specifically than the control group. This will be done in the financial allocation to girl education vs boy education dependent variable as well as the educational vs household expenses variable. Nominal measures These are binary variables which will be compared using linear regression. We will compare the extent to which respondents in each condition chose to speak to a disagreeable elder about girl child education. Natural language analyses For natural language processing, we use a set of open-vocabulary, bottom-up approaches. With the DLATK package, we will use word, phrase, and topic correlations to cluster parent’s responses into 20 topics that occur in similar semantic contexts, yielding semantically coherent topics of related words. We will compare participants’ responses to the open-ended questions in the scholarship and preference measures across condition. 7) More analyses. Are there any secondary analyses you plan to conduct? (e.g., order or gender effects) Other analyses could explore how the following variables moderate the effect of the treatment: • Gender of respondents • Age of respondents • Number of children • Income 8) Sample. Where and from whom will data be collected? How will you decide when to stop collecting data (e.g., target sample size based on power analysis, set amount of time)? If you plan to look at the data using sequential analysis, describe that here. To achieve power of 0.8 and detect a minimum effect size of Cohen’s d = 0.3 and of Cohen’s h = .16 for binary outcomes between both conditions for continuous outcomes, the target sample size is 300 for each condition or 600 in total. We have identified a list of 6 communities in and around Kaduna with both free and paid schools for children yet the enrolment rates for girls are lower than those of boys. We will visit these communities in person to recruit participants (aged between 30 and 60) who have at least one child. We plan to stop once 800 surveys are completed. Data will be excluded if the total time spent with the respondent as logged on Qualtrics is less than 15 minutes or more than 90 minutes. Any respondents who fall outside the age range, fail to complete the survey, or do not consent to participate will be excluded. Missing data will be examined for randomness and will also be excluded if it is missing at random. Pre-registration written by (initials): AD