The evolution of happiness pre and peri-COVID-19: A Markov Switching Dynamic Regression Model.

ABSTRACT: Happiness levels often fluctuate from one day to the next, and an exogenous shock such as a pandemic can likely disrupt pre-existing happiness dynamics. This paper fits a Marko Switching Dynamic Regression Model (MSDR) to better understand the dynamic patterns of happiness levels before and during a pandemic. The estimated parameters from the MSDR model include each state's mean and duration, volatility and transition probabilities. Once these parameters have been estimated, we use the one-step method to predict the unobserved states' evolution over time. This gives us unique insights into the evolution of happiness. Furthermore, as maximising happiness is a policy priority, we determine the factors that can contribute to the probability of increasing happiness levels. We empirically test

SUBMITTER: Rossouw S 

PROVIDER: S-EPMC8664229 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature