Purpose This study/paper innovates by modeling household vulnerability through a 50-period dynamic programming set-up, in the backdrop of income uncertainty, subsistence consumption requirements and financial exclusion. Design/methodology/approach To better understand the roles of various policies in alleviating consumption vulnerability, the authors consider a representative household consisting of a financially excluded single worker with a dependent and earning the minimum wage which is stochastic. Per period borrowing constraints apply and the authors consider a subsistence level of consumption (poverty-line) which the household always attempts to achieve, in the absence of which it suffers a major utility loss. Findings Simulation results show that financial access is the strongest influencer of mean consumption as well as in reducing household vulnerability (defined as probability of future consumption falling below subsistence). Similarly, subsidized insurance against income shocks is the second most cost-effective policy in alleviating vulnerability. These policies are 8.33 and 2.33 times more cost-effective than a policy which makes uniform income transfers to the household. Other policies like one-time upfront cash payment (impacts early period vulnerability) or policy-maker funded income growth (impacts later-period vulnerability) are also computed to be 1.29 times more cost-effective than uniform income transfer. Originality/value This work numerically computes the relative strengths of policies like- financial access, one time upfront cash payment, staggered cash payments and insurance against shocks-in reducing household level vulnerability. To the best of the authors’ knowledge, this is the only study which models vulnerability in a multi-period dynamic programming set-up and uses simulations to rank policies with regard to their effectiveness in reducing vulnerability.
Thakurata et al. (Mon,) studied this question.