VoxEU Column COVID-19 Europe's nations and regions Health Economics

COVID-19: Narrative economics, public policy and mental health

The general public’s mental health can be affected by different public policy responses to a pandemic threat. Italy, the UK and Sweden implemented distinct approaches to the COVID-19 pandemic: early lockdown, delayed lockdown, and no lockdown. This column presents a novel culture-based Development approach using narrative economics of language and Google trend data. It is evident that countries had a pre-existing culturally relative dispositions towards death-related anxiety and their sensitivity to COVID-19 public policy was country-specific. Further, one country’s lockdown policy can affect another country’s mental health, suggesting that policymakers should account for this spillover effect.

Under the influence of the same negative shock (the Covid-19 pandemic), three European countries adopted very different public policy responses, generating, in essence, a natural quasi-experiment with regard to the public policy response to pandemics. In Italy and the UK, public policies switched from ‘business as usual’ to ‘complete lockdown’, but at different speeds and response timings. Sweden endured the ‘business-as-usual’ policy throughout. Was this a purely economically relevant decision and was it just a matter of internal policy, or did a country’s behaviour affect the rest of the world?

Recent pre-pandemic events have left economists with a new term – economic resilience – which, in essence, alludes to the durability of an economy to negative shocks (Reggiani et al. 2002, Bristow and Healy 2020). We make two main contributions to the literature. First, we argue that there is an important aspect of resilience that is often ignored – the psychological one – which is of great importance for handling any economic or health crisis. Maintaining the people’s trust in public policy is an instinctively felt necessity (Goldberg 2020), and we document why this is so.

Mental health exists on a spectrum of normality (Spiker et al. 2010, Gotts et al. 2012). The ability to maintain an individual’s (or a societal aggregate) mental health around the spectrum’s central value is defined as ‘psychological resilience’ (Fletcher and Sarkar 2013).

Public policy towards managing scarce economic resources and our public goods (such as our nation’s health) are causing what an economist would call an economic endogeneity of psychological resilience. Put differently, psychological resilience is partially dependent on the economic and public policy implemented in a country (Cornum et al. 2011).

Our deeply rooted survival drive is our main evolutionary concern, while the fear for survival is one important and basal determining factors of psychological states (LeDoux 1995, Akerlof and Shiller 2010, Tversky and Kahneman 1979). Hence, anxiety due to fear for survival is a natural psychological response to the COVID-19 pandemic. Public policy creates a socioeconomic context that can either increase public anxiety or improve psychological resilience to survival threats. Socioeconomic context is a function of the manner in which life is organised and the security network to which people rely on for their survival (Castells 1996, Kloosterman et al. 1999, Tubadji et al. 2020), which makes it surprising that the importance of public policy is not recognised as an important factor contributing to the general public’s mental health.

As a second contribution to the literature, we hypothesise that the decisions in one country affect the general context and influence citizens in other counties’ mental health. The reality of such spillovers is an empirical question.

Humans are herd animals. Hall (1966) shows us that animals use the herd as a source of signalling for danger through their own behaviour. From an evolutionary perspective, it is natural to assume that people would perceive the response to the pandemic of other countries as a set of signals. In this setting, inter-country inconsistencies in public policies will generate anxiety because of a lack of signalling for certainty or a clearly established survival strategy.

The prominent work of Michel Foucault (1954, 1961) opened an important debate about the importance of public mental health policy and the handling of psychiatric institutions. This approach has been widely embraced and has been influential in redefining the social handling of psychopathology (Frank and McGuire 2000a, 2000b). However, the importance of general public policy for general public mental health is not recognised as an issue worth monitoring and planning.

In our past research, we developed a quantitative analytical approach relying on the Culture Based Development (CBD) paradigm (Tubadji 2012, 2013) that enables the study of the emerging narrative economics of language (Tubadji 2020a, Tubadji et al. 2020), exploring how public policy affects public mental health. Our CBD method uses linguistic online search data from Google trends, focusing on seed keywords that are signifiers for anxiety related to death. Figures 1a and 1b illustrate an upsurge in the search for the word ‘death’, and a downward tendency in the interest of ‘suicide’ as the COVID-19 pandemic developed over time. These search trends have different intensities in Italy and the UK, although both countries adopted distinct lockdown responses to the pandemic.

How can this data be used to monitor the impact of public policy on public mental health? Our CBD method suggests this can be done on a weekly, daily, and even hourly basis.

Figure 1a Searches for ‘death’ before and during the pandemic

Figure 1b Searches for ‘suicide’ before and during the pandemic

Note: Figures 1a & 1b are derived using Google trend data.

A CBD method for detecting public policy impact on mental health

Building on Alesina and Perotti’s (1994) perspective that politics is an endogenous source of socioeconomic development, CBD suggests that public policy affects not only the economic but also the psychological wellbeing of the population. Moreover, CBD originally postulated that public policy generates an impact both within and between countries (the latter in the form of inter-country spillovers).

Consistent with the CBD’s cultural economics approach, the methodology we propose in Tubadji et al. (2020) accounts for the cultural relativity of the state of a population’s mental health before the public policy treatment has occurred. Differences between countries are calculated and then the difference-in-differences method is used to establish the effect of the public policy treatment. The cross-country public policy impact is analysed by assessing one country’s public policy as a confounding factor in another country’s mental health data over time.

Next, the CBD narrative economics of language method suggests that linguistic markers in big data (seed keywords) signify certain mental health states that can be monitored over time in order to detect the mental health response to public policies.

Public policy effects on mental health

When we investigated the levels of anxiety from death in Sweden, Italy, and the UK, we found two important pre-pandemic cultural differences in the level of such experienced anxiety. First, application of the CBD approach exposes that between-country inconsistencies in lockdown policies had important impacts on public mental health across countries. Figure 2 reveals that early inconsistencies in the response to Covid-19 between Italy and the UK were associated with increases in the anxiety from death in both countries. Further, a subsequent switch to a common lockdown approach decreased anxiety in both countries (Tubadji et al. 2020). These findings were confirmed by similar findings for other European countries (Armbruster and Klotzbücher 2020). Further applications of the interrupted time-series approach confirms the presence of spillovers from national public policies across countries.

Second, examination of the daily and hourly impacts of the lockdown effect within a country can be seen in Figure 3. We split the searches into three samples, each corresponding to a fortnight: a baseline period of 01 January to 14 January 2020, the fortnight leading up to the lockdown, and the fortnight immediately after the lockdown. We observe three outcomes: (i) search intensity for the word death peaks between the hours of 20:00 and 02:00, (ii) at the scale of the day, there is a temporal pattern of keyword search for the word death that existed prior to the lockdown and is preserved thereafter, and (iii) the lockdown policy smoothed the frequency of search for the word death during the day, which illustrates more consistent daily levels of experienced anxiety among the UK population. The hours leading up to ‘bedtime’ remained the most difficult for handling anxiety from death.

Figure 2 Weekly death anxiety lockdown effects: UK vs. Italy

Panel a UK

Panel b Italy

Notes: For each panel, the top figure shows the frequency of searches for the word ‘death’.

Figure 3 Daily hourly differences in death anxiety in the UK

Notes: The figure presents the frequency of search for the word ‘death’. Source: Google trends.

The future of monitoring the impact of public policy

Public policy creates a general context in which a society operates and is a major factor that contributes to the complexities of socioeconomic decisions and behaviours that are embedded in a place. Context contributes to the explanation of differences in responses and effects of identical conditions across space and specifically to the asymmetric responses to an identical shock. Following this reasoning, in Tubadji et al. (2020) we suggest a Culture-Based Development approach for the analysis and understanding of the culturally-embedded spatially-diverse differences in public policy responses to the Covid-19 pandemic, as revealed in lockdown policy decisions. This approach can then be applied more generally.

The monitoring of aggregate mental health responses to any public policy can be achieved through the use of readily available social media and internet big data. Reliable monitoring of the effects of public policies on public mental health should be a focus of attention for responsible public policymakers concerned about the impact on a population’s psychological context and wellbeing. Thus, the need to be more aware about the moral hazards involved in policy design (Wyplosz 2020) is underscored in our research, and we stress the need for policymakers to take responsibility for the effects they produce on the mental health of their own incumbents, and across the rest of the world through spillovers effects.


Alesina, A, and H Rosenthal (1995), Partisan politics, divided government, and the economy, Cambridge, UK: Cambridge University Press.

Alesina, A and R Perotti (1994), “The political economy of growth: a critical survey of the recent literature”, The World Bank Economic Review 8(3): 351-371.

Akerlof, G and R Shiller (2010), Animal spirits: How human psychology drives the economy, and why it matters for global capitalism, Princeton, NJ: Princeton University Press.

Armbruster, S and V Klotzbücher (2020), “Lost in lockdown? COVID-19, social distancing and mental health in Germany”, Covid Economics, CEPR: Vetted and Real Time Papers Review, 22: 117-153.

Goldberg, P (2020). “Policy in times of coronavirus”, in Baldwin, R and B Wider di Mauro (eds), Mitigating the COVID Economic Crisis: Act Fast and Do Whatever it Takes, VoxEU eBook, CEPR.

Bristow, G and A Healy (2020), Handbook of regional economic resilience, Cheltenham, UK: Edward Elgar.

Castells, M (1996), The Rise of the Network Society, Oxford, UK: Blackwell.

Cornum, R, M Matthews and M Seligman (2011), “Comprehensive soldier fitness: building resilience in a challenging institutional context”, American Psychologist 66(1): 4.

Fletcher, D and M Sarkar (2013), “Psychological resilience: A review and critique of definitions, concepts, and theory”, European psychologist 18(1): 12.

Foucault, M (1961), Madness and Civilisation: A History of Insanity in the Age of Reason, London: Routledge.

Foucault, M (1954), Mental Illness and Psychology, London: University of California Press.

Frank, R G and T McGuire (2000a), “Economics and mental health”, in Handbook of health economics 1: 893-954.

Frank, R G and T McGuire (2000b), “Economics and mental health”, in Handbook of health economics 1: 893-954.

Gotts, S J, W K Simmons, L A Milbury, G L Wallace, R W Cox and A Martin (2012), “Fractionation of social brain circuits in autism spectrum disorders”, Brain 135(9): 2711-2725.

Hall, E (1966), The Hidden Dimension, Garden City, NY: Doubleday.

Kloosterman, R, J Van Der Leun and J Rath (1999), “Mixed embeddedness: (in)formal economic activities and immigrant businesses in the Netherlands”, International journal of urban and regional research 23(2): 252-266.

LeDoux, J E (1995), “Emotion: Clues from the brain”, Annual review of psychology 46(1): 209-235.

Reggiani, A, T De Graaff and P Nijkamp (2002), “Resilience: an evolutionary approach to spatial economic systems”, Networks and Spatial Economics 2(2): 211-229.

Spijker, J, R de Graaf, M Ten Have, W A Nolen and A Speckens (2010), “Predictors of suicidality in depressive spectrum disorders in the general population: results of the Netherlands Mental Health Survey and Incidence Study”, Social psychiatry and psychiatric epidemiology 45(5): 513-521.

Tversky, A and D Kahneman (1979), “Prospect theory: An analysis of decision under risk”, Econometrica 47(2): 263-291.

Tubadji, A (2012), “Culture-Based Development: Empirical Evidence for Germany”, International Journal of Social Economics 39(9): 690-703.

Tubadji, A (2013), “Culture-Based Development: Culture and Institutions – Economic Development in the Regions of Europe”, International Journal of Society Systems Science 5(4): 355-391.

Tubadji, A (2020a), “Narrative Economics of Religion: The Witch Question”, forthcoming.

Tubadji, A, F A Boy and D J Webber (2020), Narrative Economics, Public Policy and Mental Health, The COVID-19 Pandemic in the UK”, Covid Economics, CEPR: Vetted and Real Time Papers Review 20: 109-131.

Tubadji, A, P Nijkamp and P Pattitoni (2020), “Language and the Regional Economy: Cultural Persistence, Resilience or Path-dependence”, forthcoming.

Tubadji, A, D J Webber and F A Boy (2020), “Cultural and Economic Discrimination by the Great Leveller: The COVID-19 Pandemic in the UK”, Covid Economics, CEPR: Vetted and Real Time Papers Review 13: 51-71.

Wyplosz, C (2020). “So far, so good: And now don’t be afraid of moral hazard”, in Baldwin, R and B Weder di Mauro (eds) Mitigating the COVID Economic Crisis: Act Fast and Do Whatever it Takes, VoxEU eBook, CEPR.

3,150 Reads