Tipo di tesi | Tesi di laurea magistrale | ||||||||||||||||||||||||||||||
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Autore | SHAHRZAD, YALDA | ||||||||||||||||||||||||||||||
URN | etd-09222021-161232 | ||||||||||||||||||||||||||||||
Titolo | INCOME INEQUALITY AND COVID19 PANDEMIC | ||||||||||||||||||||||||||||||
Titolo in inglese | INCOME INEQUALITY AND COVID19 PANDEMIC | ||||||||||||||||||||||||||||||
Struttura | Dipartimento di Economia "Marco Biagi" | ||||||||||||||||||||||||||||||
Corso di studi | INTERNATIONAL MANAGEMENT - Management internazionale (D.M.270/04) | ||||||||||||||||||||||||||||||
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Data inizio appello | 2021-10-22 | ||||||||||||||||||||||||||||||
Disponibilità | Accesso limitato: si può decidere quali file della tesi rendere accessibili. Disponibilità mixed (scegli questa opzione se vuoi rendere inaccessibili tutti i file della tesi o parte di essi) | ||||||||||||||||||||||||||||||
Data di rilascio | 2061-10-22 | ||||||||||||||||||||||||||||||
Riassunto analitico
It is known that countries around the world have been disproportionately affected by the COVID19 pandemic. In addition to biological and epidemiological factors, various social and economic criteria equally determine the extent to which coronavirus disease spreads through the population. This study aims to investigate the impact of pre-existed income inequality as an indicator of several social deprivations on the number of COVID19 cases and deaths per million in 71 middle- and low-income countries. Subsequently, this study considers the potential of some other determinants, describing a range of different socioeconomic characteristics to explain the outcome of the coronavirus pandemic. Pooled OLS regression tests are used to estimate these effects. |
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Abstract
It is known that countries around the world have been disproportionately affected by the COVID19 pandemic. In addition to biological and epidemiological factors, various social and economic criteria equally determine the extent to which coronavirus disease spreads through the population. This study aims to investigate the impact of pre-existed income inequality as an indicator of several social deprivations on the number of COVID19 cases and deaths per million in 71 middle- and low-income countries. Subsequently, this study considers the potential of some other determinants, describing a range of different socioeconomic characteristics to explain the outcome of the coronavirus pandemic. Pooled OLS regression tests are used to estimate these effects. Results show that the COVID19 outcomes depend significantly on the intensity of income inequality. Moreover, it finds a positive association between income inequality and COVID19 cases and deaths per million in all estimated models. One percent increase in the Gini index is associated with an approximately 4.18% increase in the number of infected cases per million and a 7.25% increase in the number of deaths caused directly by COVID19 per million population. |
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