Utilizing a Bayesian vector autoregressive (BVAR) model with time-varying conditional mean equations, we treat our n-dimensional model as a collection of n univariate estimation problems. Cross-dependence is addressed using a student-t skewed distribution with latent autoregressive factors.
This study investigates the relationship between happiness and household debt repayments during the COVID-19 pandemic in the UK.
Our findings suggest that the pandemic has led to a decline in happiness, but an increase in household debt repayments appears to have a positive effect on happiness. Interestingly, various government interventions, including lockdown measures, pharmaceutical interventions such as vaccination policies and financial support measures like income support and debt relief, are associated with increased happiness and life satisfaction. However, stay-at-home policies are linked to heightened anxiety.
Inspired by the framework proposed by Kahneman and Krueger (2006), which emphasizes the importance of assessing well-being through happiness as a lens to unveil household financial preferences, our analysis delves into the intricate interplay between individual happiness, household debt repayments and the dynamics of the pandemic. Acknowledging the complex and evolving dynamics among these variables, we adopt a unique BVAR model, incorporating a student-t, time-varying, skewed copula. This modelling approach offers the necessary flexibility to accurately capture the dynamics of diverse data series, while its estimation techniques remain accessible. Given the dynamic nature of happiness, debt repayments and COVID-19 infections and deaths, the incorporation of a time-varying copula within the BVAR framework is deemed appropriate, treating these variables as endogenous. The subsequent section details our methodology in Section 2. Section 3 presents the data, while Section 4 showcases the results, and Section 5 concludes with insights and policy implications.
