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Vaccinating Now or Vaccinating Later: Separating Pull-Forward and Net Effects Using a Dynamic Regression Discontinuity Design

Fabio I. Martinenghi, Mesfin Genie, Katie Attwell, Huong Le, Hannah Moore, Aregawi G. Gebremariam, Bette Liu, Francesco Paolucci, Christopher C. Blyth

Abstract

We study the impact of a novel COVID-19 vaccine mandate, targeting graduating high-school students, on first vaccine uptake. In 2021, the State Government of Western Australia (WA) required attendees at "Leavers" -- a large-scale state-supported graduation party held annually in November in a WA regional town -- to be vaccinated. Using administrative data that link date-of-birth (at the month level), school attendance, and first-dose vaccination records, we exploit the strict school-age laws in WA to run regression discontinuity designs (RDDs). In other words, we use the date-of-birth cutoff for starting compulsory schooling in WA to build the counterfactual vaccination outcomes for Year-12 (i.e. graduating) students. We run both static and dynamic RDDs, the latter consisting of daily RDD estimations in a one-year window centred around the policy deadline in November 2021. We find that the "Leavers mandate" -- which excluded unvaccinated Year-12 students from popular post-graduation events -- raised vaccination rates by 9.3 percentage points at the mandate deadline. The dynamic RDD estimates show that this effect is entirely due to pulling forward future vaccinations by 46-80 days, with no net increase in ultimate uptake. Our paper is first to disentangle "pull-forward" (intensive margin) versus "net" (extensive margin) effects of a vaccine mandate in a pandemic context -- meaning that we identify how much the mandate made eventually-vaccinated people anticipate their vaccination, and how much it induced vaccinations that would not have happened absent the mandate. We also bring new evidence on the efficacy of time-limited non-monetary incentives for accelerating vaccination campaigns. Keywords: mandate; vaccination; incentives; uptake; adolescents; timing; coverage. JEL: I12; I18.

Vaccinating Now or Vaccinating Later: Separating Pull-Forward and Net Effects Using a Dynamic Regression Discontinuity Design

Abstract

We study the impact of a novel COVID-19 vaccine mandate, targeting graduating high-school students, on first vaccine uptake. In 2021, the State Government of Western Australia (WA) required attendees at "Leavers" -- a large-scale state-supported graduation party held annually in November in a WA regional town -- to be vaccinated. Using administrative data that link date-of-birth (at the month level), school attendance, and first-dose vaccination records, we exploit the strict school-age laws in WA to run regression discontinuity designs (RDDs). In other words, we use the date-of-birth cutoff for starting compulsory schooling in WA to build the counterfactual vaccination outcomes for Year-12 (i.e. graduating) students. We run both static and dynamic RDDs, the latter consisting of daily RDD estimations in a one-year window centred around the policy deadline in November 2021. We find that the "Leavers mandate" -- which excluded unvaccinated Year-12 students from popular post-graduation events -- raised vaccination rates by 9.3 percentage points at the mandate deadline. The dynamic RDD estimates show that this effect is entirely due to pulling forward future vaccinations by 46-80 days, with no net increase in ultimate uptake. Our paper is first to disentangle "pull-forward" (intensive margin) versus "net" (extensive margin) effects of a vaccine mandate in a pandemic context -- meaning that we identify how much the mandate made eventually-vaccinated people anticipate their vaccination, and how much it induced vaccinations that would not have happened absent the mandate. We also bring new evidence on the efficacy of time-limited non-monetary incentives for accelerating vaccination campaigns. Keywords: mandate; vaccination; incentives; uptake; adolescents; timing; coverage. JEL: I12; I18.

Paper Structure

This paper contains 18 sections, 21 equations, 4 figures, 2 tables.

Table of Contents

  1. Introduction
  2. Background
  3. The Leavers Event & its vaccine mandate
  4. School age law in WA
  5. Data
  6. Empirical Strategy
  7. Results
  8. A model of vaccination decisions
  9. Conclusion and policy implications
  10. Extra tables
  11. Toy model of vaccination decisions
  12. Primitives
  13. Continuation value and one-period increment
  14. Decision rule
  15. Total effect and channel decomposition
  16. ...and 3 more sections

Figures (4)

  • Figure 1: Vaccination rates in WA at the policy deadline by date of birth (at the month-year level)
  • Figure 2: Student vaccination rates in WA
  • Figure 3: McCrary test for continuity in the density of the running variable at the cutoff
  • Figure 4: Dynamic RDD treatment effects of the policy