# Causal effect estimation of public policies on purchasing behaviors, consumption and health outcomes

> **NIH NIH R01** · UNIVERSITY OF PENNSYLVANIA · 2024 · $412,411

## Abstract

PROJECT SUMMARY
 The proper evaluation of public policies on health and other outcomes is vital for determining whether a
policy was effective and also whether it should be continued or implemented in other regions. For example,
Philadelphia, along with six other U.S. cities, has implemented excise taxes on sweetened beverages with the goal
of decreasing consumption of added sugars which have been associated with obesity and other serious health
conditions. However, what if consumers try to avoid the tax by purchasing beverages in neighboring regions that
did not implement the tax? Consumers may also be encouraged by the higher price of sweetened beverages
to purchase other high-sugar snacks and drinks rather than purchase the taxed beverages. Without properly
understanding and accounting for these complex but common situations (called interference), researchers may
grossly overestimate the health impact of public policies. Further, policy evaluations often rely on survey data
for more granular insights on the causal mechanisms of a policy, like individual-level changes in consumption.
However, these data may not represent populations of interest, such as those that are underserved. To address
these challenges we propose new causal estimands, specify unique identification assumptions, construct doubly
robust semi-parametric estimators, and apply them to multiple studies of the Philadelphia beverage tax.
 This proposal addresses critical gaps in the evaluation of public policies. Our work is organized under the
following aims: Aim 1 will develop innovative causal methods to estimate heterogeneous policy effects under
diverse direct and indirect (e.g., spillover) exposures and generalize and transport these heterogeneous policy
effects to settings with different exposure, sociodemographic, and geographic contexts. Aim 2 will develop novel
causal methods to examine substitution effects using a potential outcomes framework under a set of newly estab-
lished identification conditions. Aim 3 will develop a novel synthetic control approach that allows the assessment
of individual-level outcomes obtained via surveys. The first two aims will apply these new methods to evaluate the
effects of the Philadelphia beverage tax on purchasing behaviors using volume sales data and transport these
effects to other U.S. cities. Here, we will also estimate beverage tax effects in regions that implemented similar
taxes (e.g., San Francisco, CA; Seattle, WA) to assess effect generalizability. The third aim will analyze the effect
of the tax on consumption and obesity outcomes using data from the Youth Risk Behavior Surveillance System.
User-friendly software will be produced and made publicly available for all proposed methods. This project will
provide robust and flexible tools for policymakers to evaluate, transport, and generalize public policies under
complex real-world settings.

## Key facts

- **NIH application ID:** 10878130
- **Project number:** 1R01DK136515-01A1
- **Recipient organization:** UNIVERSITY OF PENNSYLVANIA
- **Principal Investigator:** NANDITA MITRA
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $412,411
- **Award type:** 1
- **Project period:** 2024-04-01 → 2028-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10878130

## Citation

> US National Institutes of Health, RePORTER application 10878130, Causal effect estimation of public policies on purchasing behaviors, consumption and health outcomes (1R01DK136515-01A1). Retrieved via AI Analytics 2026-05-29 from https://api.ai-analytics.org/grant/nih/10878130. Licensed CC0.

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