Using real platform data, this paper assesses donors’ reactions to a rare event; specifically, we demonstrate how donors were able to compensate for (or stabilize) healthcare deficits and policy restrictions used to mitigate the spread of COVID-19. Based on a sample of 20,784 covid-related donation campaigns promoted on GoFundMe platform from January 30, 2020 to November 23, 2021, the paper shows that donors decided to donate based on campaign purpose and reliability: specifically, campaigns with the purpose to support hospitals or to buy healthcare materials in countries more affected by the pandemic received more funds. Moreover, the paper provides evidence of the impact of different government policy restrictions on campaign outcome in terms of amount raised and number of campaigns promoted in six European countries. As donations during COVID-19 were valuable (in particular, for public institutions) in terms of amount and timeliness, our findings offer valuable insights into how governments encouraged donations via fiscal incentives and policy restrictions.
D.Vaccination Policy Goali is used as a control variable to capture that the value expressed by the organizer may vary according to the specific purpose of the campaign. By introducing controls for donation purpose (D_Purpose) we capture the differential willingness to donate for each campaign purpose. We also include i as an error term. Google Trends Indexes GT Index Donation Weekly Google Trends index of interest in the web toward the word donation. Weekly Google Trends index of interest in the web toward the word covid.
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GT Index Covid Notes: * converted to EUR currency. We use the date of creation as reference time for Amount Goal; we use the date of best donation as reference time for Amount of the Best Donation; we use the date of last donation as reference time for both Amount of the Last Donation and Amount Raised. In the second step of analysis, we investigate if COVID-19 vaccination (available in Europe since December 27, 2020) decreases the risk perception of the emergency (Caserotti et al., 2021) and hence donors contributions. Methodologically, we split our estimation analysis into two periods: pre-vaccine and post-vaccine. To define the role of purpose, we adopted the standard hurdle model (Cragg, 1971) approach commonly used in the charitable giving literature (e.g. Grimalda et al., 2021; Huck & Rasul, 2011; Meer, 2011), which models the decision to support a donation campaign as a function of D_Purpose variables.
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In the third part of the analysis, we explored the relationship between policy restrictions on donation campaigns by estimating the following pooled panel ordinary least squares model: Donationc,w = c,w + 1PolicyRestrictionc,w + D countryw (2) + GTrendIndexesw+i Hurdle models are characterized by the relationship yi = si h* i , where yi is the dependent variable and si is the selection variable which is equal to one if the dependent variable is not bounded and zero otherwise. Specifically: w and c represent week and country, respectively. Donation is the dependent variable, measured i) by the number of new donation campaigns promoted in each country at weekly frequency and ii) by the amount raised by overall donation campaigns in a week for a country. Governments applied pandemic mitigation efforts, such as stay-athome orders, which caused widespread economic displacement and { 1if zi + i 0otherwise
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h* = Xi + i, where Xi is a vector defined by the outcome linear model h* i of explanatory variables, is a vector of coefficients, and i is an error term. 11 We also regress the amount of best donation (converted to in log form) using the same specification to check for significant difference. Regressions are presented in Appendix A, Table 1. JournalofBusinessResearch177(2024)1146157 G. Borello and R. Muri Fig. 4. Amount raised distribution.
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