Government Spending and the Two-Way Causation between Socioeconomic Status and Health in the UK: A Multilevel Structural Equations Modelling Approach

Policies are critical in contouring patterns of health and mitigating health inequalities. Evidence shows that different policy regimes based on different ideologies have dissimilar impacts on individual and population health. For example, countries adhered to liberal policies are found to entail aggravated health disparities and greater mortality rates compared to countries that implemented less neoliberal policies (Coburn 2004; Navarro et al. 2006; Beckfield and Krieger 2009; Stuckler, King, and McKee 2009; McCartney et al. 2012; Walsh et al. 2017). The fiscal component of policies is central in the materialist explanations of health inequalities. Such explanations are favoured by many researchers since the release of the government-commissioned Black Report in the UK (Black 1980). Particularly, the literature focuses on how the financing of the health system determines an array of population health outcomes (Drastichová and Filzmoser 2020; Rahman and Alam 2020), including those related to the recent COVID-19 pandemic outbreak (Luonga 2020).

However, the literature is relatively scarce in investigating the health benefits of government investments in different sectors than those directly related to health. The existing literature that looks into the implications of policies in non-health sectors on health remains largely theoretical and descriptive (e.g., Smith and Kandlik Eltanani 2015). Yet, investigating the health implications of non-health expenditure is crucial given the potential of policy initiatives in alleviating health disparities by tackling the fundamental causes of such disparities, viz. inequalities in socioeconomic status (SES) (Link and Phelan 1995; Adler and Newman 2002). Indicators of SES are thought to serve as markers of the underlying dimension of social ordering, which determines the distribution of resources including those that enable avoiding risks of illness (Cutler, Lleras-Muney, and Vogl 2011). On the other hand, health conditions may over time also affect SES through social mobility processes (Hoffmann, Kröger, and Geyer 2019). Therefore, taking into account this dynamic simultaneity between SES and health, it is important to assess how government policies shape health inequalities through both (1) public health expenditure and policies which may influence directly individuals' health status, and (2) spending and policies in non-health-related areas such as education, labour, income and taxation which alter individuals' socioeconomic circumstances and in turn may affect health.

The proposed research aims to compare longitudinally the effects of public health and non-health policy domains on indicators of health and SES. The research aims to address the following questions. What are the relative effects of investing directly in people's health versus in policies that improve their socioeconomic position on health? Do these effects of policies change over time, and if so, do they depend on a person's age, ethnicity, and other socio-demographic characteristics? As a general hypothesis, I expect that public health policies will exert a greater short-run effect on health, whereas non-health policies will manifest themselves in the long run. I select the UK to answer the research questions above because of the availability of a wealth of high-quality individual and population level longitudinal data.