The COVID-19—the worst pandemic since the Spanish flu—has dramatically changed the world, with a significant number of people suffering from and dying of the disease. Some scholars argue that democratic governments are disadvantaged in coping with the current pandemic mainly because they cannot intervene in their citizens' lives as aggressively as their authoritarian counterparts. Other scholars, however, suggest that possible data manipulation may account for the apparent advantage of authoritarian countries. Taking such a possibility seriously, this paper analyzes the relationship between political regimes, data transparency, and COVID-19 deaths using cross-national data for over 108 countries, obtained from Worldometer COVID-19 Data, Polity V Project, Variety of Democracy (V-Dem) Project, HRV Transparency Project among other sources. Regression analyses indicate that authoritarian countries do not necessarily tend to have fewer COVID-19 deaths than their democratic counterparts after controlling for other factors, especially data transparency. The transparency variable itself, on the other hand, is positively correlated with the number of death cases more consistently ( P <0.05). Overall, the estimation results point to the possible data manipulation, not the nature of regime characteristics itself, as a more significant source for the seemingly low casualty rates in authoritarian countries.

This study provides preliminary evidence regarding associations between socioeconomic inequalities and variations in the number of COVID-19 confirmed cases across 923 municipalities in Catalonia, Spain, as of the 14th of May, 2020. We consider three types of inequalities at municipality-level: 1) economic development, i.e., unemployment rate, average income, immigrants proportion, and the prevalence of small residence; 2) health vulnerability, i.e., crude death rate and the proportion of elderly (aged 65 +) population; and 3) information communication, i.e., the proportion of people with tertiary education. In addition to the static analysis with the total sum of COVID-19 cases, the dynamic analysis with daily moving weekly sum of cases is conducted. The result draws a rather complex picture of relationships between contextual socioeconomic inequalities and the spread of COVID-19. Many indicators of economic inequalities imply the opposite relationship as intuitively suggested: economically disadvantaged municipalities tend to have less cases of confirmed infection than economically advantaged counterparts. The implications from health inequality indicators show mixed patterns: crude death rate is positively associated, but elderly population is negatively associated, with the number of confirmed cases. The indicator of information inequality shows a consistent tendency, i.e., municipalities with more university educated have less confirmed cases, but this tendency transforms across time: the negative association is particularly strong during the first month of Spanish “state of alarm” measure (mid-March to mid-April). Our evidence suggests the need for more careful consideration regarding the association between socioeconomic inequalities and the regional progression of COVID-19 pandemic.

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This paper presents an analysis of the impact of political regimes and type of military recruitment on the probability of the occurrence of international conflicts. In the last few years, the (re) introduction of military conscription has been a focus of public debate, but empirical analysis of the issue remains limited. We argue that democratic nations with conscription-based military recruitment in place are less likely to initiate international conflicts than those with voluntary recruitment because public opinion will estimate a higher probability of direct involvement in disputes, causing political leaders to refrain from conflicts, even though stable military resources are in place. On the other hand, authoritarian nations with conscription-based recruitment systems are more likely to engage in conflicts than those with voluntary recruitment systems because political leaders are not accountable to the people, even though the cost of war is calculated in the same manner as that in democratic nations. To test this reasoning, we use directed-dyadic data from 1816 to 2005. Our analysis strongly supports our theoretical expectations.

The COVID-19 pandemic-the worst one since the Spanish flu-has dramatically changed the world, with a great number of people still suffering and dying from the disease. Some scholars argue that the pandemic has severely damaged democratic countries, mainly because these cannot intervene in their citizens' lives, as opposed to their authoritarian counterparts. Another study challenges this view and suggests that authoritarian countries manipulate data on COVID-19-related deaths. This paper aims to determine which view is more persuasive using cross-national data. This article uses statistical evidence to reveal that authoritarian countries are likely to manipulate the data. The result implies that, with this successful manipulation, authoritarian states can strengthen citizens' support for their governments through the COVID-19 pandemic.