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Public spending on families in aging populations: a survey experiment

Last registered on July 03, 2025

Pre-Trial

Trial Information

General Information

Title
Public spending on families in aging populations: a survey experiment
RCT ID
AEARCTR-0016312
Initial registration date
June 30, 2025

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
July 03, 2025, 2:58 PM EDT

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

Locations

Region
Region

Primary Investigator

Affiliation
Corvinus University of Budapest

Other Primary Investigator(s)

PI Affiliation
Maastricht University

Additional Trial Information

Status
In development
Start date
2025-07-15
End date
2025-08-31
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
European welfare states face a dual demographic challenge of sustained low fertility and rapid population aging. While public investment in children is widely recognized as critical for mitigating the long-run fiscal and economic consequences of these trends, the political feasibility of such investment remains uncertain. The conventional view, rooted in overlapping generations models, suggests that aging societies will increasingly prioritize spending on the elderly, sidelining expenditures on families and children. Yet these models typically overlook the intertemporal nature of self-interest and the potential endogeneity of future pension sustainability to present-day child-oriented spending.
This paper studies how the public forms preferences over intergenerational redistribution in aging societies, with a focus on public spending for families with children. We develop a stylized extension of Galasso and Profeta's (2007) model to demonstrate that current expenditures on children—via their impact on future fertility and human capital—can enhance the fiscal sustainability of pension systems. This creates a long-term economic interest for even the childless median voter to support such policies. Nevertheless, these dynamic linkages are often not salient to the electorate, raising the question of whether communication and framing strategies can shift public attitudes.
To address this, we design and implement a large-scale survey experiment in Germany and Hungary (target N = 7,000), two countries with contrasting welfare state models and demographic trajectories. The survey measures respondents’ perceptions of demographic change, their policy preferences, and their responses to randomized informational treatments. These treatments present child and family policies either as a means to support current families (short-term frame) or as investments to ensure the sustainability of the welfare state (long-term frame). This design enables me to test whether emphasizing future economic benefits can broaden support beyond the directly affected population.
This paper contributes to the literature on the political economy of intergenerational redistribution by identifying when and how framing can mobilize support for forward-looking social investment. It also speaks to broader debates on welfare state adaptation and the role of strategic communication in fostering politically viable responses to structural demographic shifts.
External Link(s)

Registration Citation

Citation
Gassmann, Franziska and Eszter Timár. 2025. "Public spending on families in aging populations: a survey experiment." AEA RCT Registry. July 03. https://doi.org/10.1257/rct.16312-1.0
Experimental Details

Interventions

Intervention(s)
The experiment will be embedded into the survey questionnaire.
The experimental block will follow a quasi-prepost design. This means that the outcome variables are measured before and after the treatment, but with similar (rather than identical) questions. This is a form of repeated measurement design which aims to minimize the consistency pressure arising from measuring the outcome twice (Clifford et al., 2021). Eliciting a prior first-stage outcome variable allows the researcher to test the heterogeneity of treatment effect dependent on prior beliefs (Stantcheva, 2023). For example, one can check whether the treatment effects are greater for those who received a larger “shock” from the treatment (ibid.). Pre-testing also allows the researcher to control for individual fix-effects, contributing to greater measurement precision (Clifford et al., 2021).
Pre-test. In the pre-test, respondents are asked to rank government expenditure areas in order of their importance. Supporting families with children will be listed alongside other conventional functions (such as health care, infrastructure, pensions for the elderly) and functions not typically associated with government duties (e.g., supporting international corporations). The multiple choice question will avoid drawing explicit attention to our topic of interest, which minimizes priming, experimental demand effect, and consistency pressures.
The treatment. In the experimental section, respondents will be randomly assigned to three equally sized groups (one control and two treatment arms). This will be done using Qualtrics’ built-in randomize function. Each experimental arm will be shown a short (2-minute) video about child and family policies. No video will be presented to the control group.
The video treatment administered to one treatment arm will emphasize the immediate benefits of spending on children and families, such as reducing the burden of parents and improving the well-being of children. The expectation is that this will prime respondents to think about their immediate self-interest, which will depend on whether they (intend to) raise children. This frame may also increase support among non-parents and the elderly who are altruistic (i.e., utility through altruism).
The other video treatment will introduce the notion of endogeneity of future pensions to current child benefits. It will thus emphasize the long-term benefits for the economy and for pension sustainability. It is expected to increase support particularly among childless, but young individuals, for whom the direct utility from child benefits is zero. In terms of our utility model developed in the theoretical section, the treatment aims to activate the forward-looking term. Because of discounting or bounded rationality, the intertemporal link may be undervalued without the provision of information on it.
Post-test. Following the treatment, I will measure both the first-stage and second-stage outcomes. It is important to measure the first-stage outcome because it is the only opportunity to check if the treatment has worked (successfully shifted perceptions). The second-stage outcome refers to my main variables of interest, i.e., respondents’ policy preferences. For more details, see the operationalization of key variables in the Analysis Plan section.
Intervention (Hidden)
Intervention Start Date
2025-07-15
Intervention End Date
2025-08-31

Primary Outcomes

Primary Outcomes (end points)
Support for public spending family policies, support for public spending on family policies at the expense of pensions, and willingness to pay for family policies via a small increase in taxes.
Primary Outcomes (explanation)
We will measure both first stage and second-stage outcomes. The latter are my main outcomes of interest. My first-stage outcome tests if the experiment has successfully shifted perceptions of the program. Since my objective is to create a cognitive link between the policy problem (demographic change) and my policy of interest (family policies), the first-stage outcome will measure what outcomes respondents associate with family policies. If the treatment is successful at shifting perceptions, then those exposed to the long-term treatment should be more likely to select pension sustainability then those exposed to the short-term treatment.
My main outcome of interest (i.e., second-stage outcomes) consists of three measures of support for spending on children and families. These measures will be based on questions where respondents are asked how much they agree or disagree with a statement on a Likert-scale from 0 to 10. The three statements will capture general support for public spending family policies, public spending on family policies at the expense of pensions, and willingness to pay for family policies via a small increase in taxes.
Each will be re-coded to binary outcomes: selecting a score greater than 5 will be assigned the value of 1. Binary coding with a threshold of 5 is used to be consistent with prior survey experiments on redistributive preferences (Kuziemko et al., 2015). I will also conduct robustness tests using a higher threshold (e.g., >7).

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
The experiment relies on an information/framing treatment using a video, embedded in a survey. Respondents will be randomly assigned to three equally sized groups (one control and two treatment arms). Each experimental arm will be shown a short (2-minute) video about child and family policies. No video will be presented to the countrol group.
The video treatment administered to one treatment arm will emphasize the immediate benefits of spending on children and families, such as reducing the burden of parents and improving the well-being of children. The other video treatment will introduce the notion of endogeneity of future pensions to current child benefits.
Experimental Design Details
Randomization Method
Randomization done by a computer (using the randomization function of the Qualtrics survey software).
Randomization Unit
Individual
Was the treatment clustered?
Yes

Experiment Characteristics

Sample size: planned number of clusters
2 countries
Sample size: planned number of observations
7000 individuals
Sample size (or number of clusters) by treatment arms
2333 control, 2333 treatment condition A, 2300 treatment condition B.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Determining MDE is difficult given that we do not know the true population mean. Power calculations will be recomputed once the population mean is known. Because preferences for pro-child spending have not been measured before, we take the share of respondents who chose “Education” and “Assisting the poor/reducing inequality” as the first priority for government spending in the 4th wave Life in Transition Survey to proxy the expected population mean. The corresponding share was 31% in Hungary and 30% in Germany, giving an unweighted average of 30.5%. Therefore, in our calculations, we assume the population mean to be 30.5%. We calculate the smallest effect size using R’s pwr package. We choose a significance level of 𝛼=0.05 and a power level of 0.8, and specify for two-sided tests. With these specifications, we would be able to detect small to moderate effect sizes starting from approximately 4 percentage points.
IRB

Institutional Review Boards (IRBs)

IRB Name
Corvinus University of Budapest - Ethical Review Board
IRB Approval Date
2025-06-12
IRB Approval Number
KRH/152/2025
Analysis Plan

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Post-Trial

Post Trial Information

Study Withdrawal

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Intervention

Is the intervention completed?
No
Data Collection Complete
Data Publication

Data Publication

Is public data available?
No

Program Files

Program Files
Reports, Papers & Other Materials

Relevant Paper(s)

Reports & Other Materials