Propelled: evidence on the impact of vaccination against COVID-19 on travel propensity

ABSTRACT

Do people vaccinated against COVID-19 exhibit a greater propensity to take a vacation trip? This paper answers this research question using nationwide survey microdata for a representative sample of the Spanish population in the summer of 2021. To provide a causal estimate of how COVID-19 vaccine affects travel propensity, our identification strategy uses an Inverse Probability Weighting Regression Adjustment (IPWRA) estimator that deals with selection and compositional effects. Consistent with the Health Belief Model and the Protection Motivation Theory, we find robust evidence that vaccination against COVID-19 increases the probability of taking a holiday trip during the summer period by 8.3 percentage points among the general population and 11.3 percentage points among the vaccinated subsample. Therefore, we document that vaccination propels tourism participation. Our results provide important insights for the recovery of the tourism industry.

KEYWORDS:

• Vaccination
• covid-19
• travel propensity
• Inverse Probability Weighting Regression Adjustment
• behavioural intentions
• crisis

Conflict of interest statement

The author(s) have nothing to report.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1 Pharmaceutical interventions are defined in this context as biopharmaceutical treatments (protective antibodies) used to prevent disease (i.e., vaccines).

2 We use the July wave because it is the only wave in which respondents are asked about their vacation plans for the summer. We exploit the fact respondents are also asked about their vaccination status to link both dimensions.

3 In particular, the barometer implements a multi-stage sampling procedure, stratified by conglomerates, with primary (municipalities) and secondary (sections) units selected in a proportional random way. Individuals are subsequently selected randomly by gender and age quotas. The sampling protocol ensures that a minimum of 100 respondents are interviewed per each Autonomous Community. Further information about the dataset is available at: http://www.cis.es/cis/opencm/ES/1_encuestas/estudios/ver.jsp?estudio=14577

4 Those who answer affirmatively are subsequently questioned about the length of the trip, whether they intend to travel domestically or abroad, and the mode of transport selected. Most tourists indicate they travel domestically (88%), to coastal destinations mainly (60%) and by private car (78%). Concerning the length of the stay, 12.2% indicate less than one week, 28.2% report one week, 28.7% plan between one and two weeks and the remaining 29.2% state more than two weeks. The analysis of travel preferences regarding these dimensions is beyond the scope of this paper.

5 The wording of the question is: Focusing now on what is happening because of the pandemic, how is it affecting your personal life? The possible answers are: ‘It is affecting me a lot’ (Affects Pers. Life = 5), ‘It is affecting me quite a bit’ (Affects Pers. Life = 4), ‘It is affecting me neither much nor little’ (Affects Pers. Life = 3), ‘It is affecting me little’ (Affects Pers. Life = 2), and ‘It is not affecting me /almost nothing’ (Affects Pers. Life = 1).

6 The dataset is available for being downloaded without cost at http://www.cis.es/cis/opencm/ES/1_encuestas/estudios/ver.jsp?estudio=14577

7 The exact wording of the question is: How would you assess your current personal economic situation? The possible answers are ‘Very bad’, ‘Bad’, ‘Ordinary’, ‘Good’ and ‘Very Good’. Since these answers have a natural ordering, they are coded 1-5, respectively. The use of 1–5 scales is a common way to proceed when working with qualitative survey questions posited by the CIS Barometer and can be found in related studies that use this monthly poll (Núñez-Barriopedro et al., 2020; Fernández-Prados et al., 2020).

8 Binned scatterplots are a non-parametric tool that is becoming widely used in applied microeconomics as a method to inspect the functional form of the relationship between two variables. It consists of splitting the domain of the variables into a set of predefined bins based on the quantiles and plot the mean values for each bin.

9 Table A1 in Supplementary Material provides descriptive statistics of the share of respondents that plan to travel, are vaccinated and have suffered COVID-19 per sociodemographic profile.

10 We consider a squared polynomial of age based on the inverse U-shaped relationship documented in Figure 2 between age and travel propensity.

11 The coefficient estimates for the province fixed effects are not shown to save space but are presented in Table A3 in Supplementary Material.