  Behind the debt trap concept is the rationale that payday loans exacerbate
consumers' financial vulnerability. To investigate this relationship, we
propose a Mixed Poisson Hidden Markov approach to model the number of payday
loans a borrower obtains in each period. Given the lack of agreement in the
literature on financial vulnerability, we introduce financial distress as an
unobserved binary variable using a hidden Markov process (vulnerable and
non-vulnerable). Using data from 90,523 anonymised transactions for 1,817 UK
consumers, we find that the effect of certain time-varying covariates depends
greatly on the borrower's hidden state. For instance, luxury expenses and
non-recurring income increase the need for payday loans when financially
vulnerable, but the opposite is true when not vulnerable. Additionally, we
demonstrate that almost 60\% of payday loan borrowers remain vulnerable for 12
or more consecutive weeks, with two-thirds experiencing consistent financial
difficulties. Finally, our analysis underscores the need for a nuanced approach
to payday lending that recognises the varying levels of vulnerability among
borrowers, which can prove helpful for policymakers and lenders to enhance
responsible lending practices.
