Why nanny statism matters: evidence from the first wave of COVID-19.

BACKGROUND: A nanny state imposes restrictions on people's liberty and freedom of action in order to advance their interest and welfare. The extent to which this is desirable, or even ethically acceptable, is debated in the literature. This paper formulates and tests the following hypothesis: the more of a nanny a state has been in the past, the more likely it is that the incumbent government will respond to a new, unknown threat with interventions of a paternalist nature, irrespective of other factors that might contribute to shaping government's response. This hypothesis is then taken to the data using the first wave of COVID-19 as an empirical test. METHODS: Data are collected from secondary sources for a sample of 99 countries. Nanny statism is measured by the number of paternalist laws and regulations adopted by a country in the past. The response to COVID is proxied by the time of adoption of control and containment measures and their stringency. The public health outcome is measured by the COVID-19 death toll at the end of June 2020. These variables, plus several controls, are then used to estimate a set of linear and probit regressions and a proportional hazard model of the timing of adoption of control and containment measures. RESULTS: An increase in nanny statism by 0.1 (on a scale from 0 to 10) on average increases the probability of adoption of control and containment measures by 0.077 (i.e. 7.7 percentage points). The central tenement of the hypothesis is therefore consistent with the empirical evidence. The linear and probit regressions also show that there is no evidence of a significant effect of nanny statism on the stringency of the measures adopted. Irrespective of stringency, however, early adoption of control and containment measures is found to reduce the death toll of COVID-19 in the first half of 2020: an increase in nanny statism by 0.1 reduces the COVID death toll by approximately 7%. CONCLUSIONS: A tradition of nanny statism potentially leads to a more timely and effective public policy response to a new, unknown crisis. Further tests of the hypothesis should look at the relationship between nanny statism and public health outcomes from natural disasters.

Personality, gender, and age resilience to the mental health effects of COVID-19.

RATIONALE: Understanding the impact of COVID-19 on different population cohorts and which personality traits affected individual's coping responses can help identify strategies to promote self-directed behaviours, thereby enhancing and maintaining individual's mental well-being. OBJECTIVE: Using longitudinal data for the UK, we examine the impact of the COVID-19 pandemic on individuals' mental well-being, focusing on age, gender, and personality traits as possible modifiers. METHODS: We explore the longitudinal nature of the data using individual fixed effects models, which implicitly control for unobserved time-invariant individual-level characteristics. Our sample is an unbalanced panel consisting of 373,555 person-years observations, observed from 2009 until June 2020. RESULTS: The negative impacts of the first months of the pandemic period are found to be larger for young adults (aged 16-25 years) and vary by personality traits. The increase in psychological distress symptoms is more pronounced for individuals who score higher in neuroticism, extroversion, and openness to experience. Indeed, for introverted young people, recent events may have actually brought a sense of calm. Other findings indicate that worsening in the psychological distress level occurs alongside with increased feelings of loneliness. CONCLUSIONS: Our findings support the theoretical knowledge that different people have different psychological and behaviour responses and personality concepts can be used when studying individual's adaptive behaviour in critical situations such as COVID-19. Our results indicate the necessity of public health programmes to assist distressed young individuals.

Addressing the unemployment-mortality conundrum: non-linearity is the answer.

The effect of unemployment on mortality is the object of a lively literature. However, this literature is characterized by sharply conflicting results. We revisit this issue and suggest that the relationship might be non-linear. We use data for 265 territorial units (regions) within 23 European countries over the period 2000-2012 to estimate a multivariate regression of mortality. The estimating equation allows for a quadratic relationship between unemployment and mortality. We control for various other determinants of mortality at regional and national level and we include region-specific and time-specific fixed effects. The model is also extended to account for the dynamic adjustment of mortality and possible lagged effects of unemployment. We find that the relationship between mortality and unemployment is U shaped. In the benchmark regression, when the unemployment rate is low, at 3%, an increase by one percentage point decreases average mortality by 0.7%. As unemployment increases, the effect decays: when the unemployment rate is 8% (sample average) a further increase by one percentage point decreases average mortality by 0.4%. The effect changes sign, turning from negative to positive, when unemployment is around 17%. When the unemployment rate is 25%, a further increase by one percentage point raises average mortality by 0.4%. Results hold for different causes of death and across different specifications of the estimating equation. We argue that the non-linearity arises because the level of unemployment affects the psychological and behavioural response of individuals to worsening economic conditions.

Identifying covariates of population health using extreme bound analysis.

BACKGROUND: The literature is full of lively discussion on the determinants of population health outcomes. However, different papers focus on small and different sets of variables according to their research agenda. Because many of these variables are measures of different aspects of development and are thus correlated, the results for one variable can be sensitive to the inclusion/exclusion of others. METHOD: We tested for the robustness of potential predictors of population health using the extreme bounds analysis. Population health was measured by life expectancy at birth and infant mortality rate. RESULTS: We found that only about half a dozen variables are robust predictors for life expectancy and infant mortality rate. Among them, adolescent fertility rate, improved water sources, and gender equality are the most robust. All institutional variables and environment variables are systematically non-robust predictors of population health. CONCLUSION: The results highlight the importance of robustness tests in identifying predictors or potential determinants of population health, and cast doubts on the findings of previous studies that fail to do so.

Does donor assistance for HIV respond to media pressure?

HIV/AIDS is a heavily mediatised disease. In this article, we test whether media attention is affecting donors' disbursement of aid for HIV to African countries. We use information available on the number of articles and press documents on HIV issues and other health concerns published in donor countries to construct a proxy of media coverage. This proxy is then included as an explanatory variable in a regression of aid for HIV to Africa. After controlling for several donor characteristics, we find that greater media coverage increases aid disbursement. This may be good news for the HIV campaign but may result in displacement effects to the extent that other diseases that cause greater mortality and morbidity receive less media coverage than HIV and thus less health aid.

Has HIV/AIDS displaced other health funding priorities? Evidence from a new dataset of development aid for health.

In recent times there has been a sense that HIV/AIDS control has been attracting a significantly larger portion of donor health funding to the extent that it crowds out funding for other health concerns. Although there is no doubt that HIV/AIDS has absorbed a large share of development assistance for health (DAH), whether HIV/AIDS is actually diverting funding away from other health concerns has yet to be analyzed fully. To fill this vacuum, this study aims to test if a higher level of HIV/AIDS funding is related to a displacement in funding for other health concerns, and if yes, to quantify the magnitude of the displacement effect. Specifically, we consider whether HIV/AIDS DAH has displaced i) TB, ii) malaria iii) health sector and 'other' DAH in terms of the dollar amount received for aid. We consider this question within a regression framework controlling for time and recipient heterogeneity. We find displacement effects for malaria and health sector funding but not TB. In particular, the displacement effect for malaria is large and worrying.