Using Disaggregated and Latent Variable Analysis to Investigate the Role of Socioeconomic Factors in Concerns and Expectations Related to the Covid-19 Pandemic in Chile

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dc.catalogadorgjm
dc.contributor.authorTirachini, Alejandro
dc.contributor.authorGuevara, Angelo
dc.contributor.authorMunizaga, Marcela
dc.contributor.authorCarrasco, Juan Antonio
dc.contributor.authorAstroza, Sebastián
dc.contributor.authorHurtubia González, Ricardo
dc.date.accessioned2024-03-27T13:32:11Z
dc.date.available2024-03-27T13:32:11Z
dc.date.issued2022
dc.description.abstractThe COVID-19 pandemic has triggered a complex set of psychosocial effects, such as anxiety, depression, financial loss, burnout, and fear of infection. We study the role of socioeconomic factors in the concerns related to the COVID-19 pandemic, as well as the expectations of social changes on a post-pandemic future. The analysis is performed by collecting 22 indicators from a sample of 4,395 adults in Chile. The analysis is performed first by descriptive statistics, then by fusing the indictors into three latent variables, and finally by modelling each indicator as a separate choice. We find that lower-income people are significantly more worried about a range of financial and health issues arising from the COVID-19 pandemic, including concerns about being infected by the virus, losing their job and not being able to pay debts. The concern about facing a large economic crisis is significantly larger in the extremes, i.e., for low- and high-income groups. Age, gender, having a university degree, the possibility of working from home, and the general health status also influence the fears related to the COVID-19 pandemic. From a policy point of view, we conclude that strong policy interventions are necessary to reduce the uneven negative effects of COVID-19 in society, including material and mental health problems. From a methodological point of view, our results show that, while using a latent variable approach allows disentangling the main drivers of the phenomenon, rich content may be omitted when a disaggregated analysis is neglected, therefore both approaches are complementary.
dc.fuente.origenORCID
dc.identifier.urihttps://papers.ssrn.com/sol3/papers.cfm?abstract_id=4022866
dc.identifier.urihttps://repositorio.uc.cl/handle/11534/84820
dc.information.autorucEscuela de Ingeniería; Hurtubia González, Ricardo; 0000-0002-3553-610X; 1015343
dc.language.isoen
dc.nota.accesocontenido completo
dc.rightsacceso abierto
dc.subjectSocial effects
dc.subjectGender effects
dc.subjectHealthcare
dc.subjectSocial security
dc.subjectCoronavirus
dc.titleUsing Disaggregated and Latent Variable Analysis to Investigate the Role of Socioeconomic Factors in Concerns and Expectations Related to the Covid-19 Pandemic in Chile
dc.typepreprint
sipa.codpersvinculados1015343
sipa.trazabilidadORCID;2024-03-25
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