We use a new formal, practical, and easily decomposable measure to examine vulnerability to poverty in Tajikistan during the global financial crisis. Our strategy is to estimate a first-order Markov model of household expenditure with the aim of identifying the vulnerability of households to poverty. We use Bayesian methods which allow us to estimate the limiting expenditure distribution. Importantly, by introducing the index of vulnerability as the weighted probability of a household falling into poverty over a given time horizon, we can use the estimated dynamics to assess short, medium and long-run vulnerability. We find that during the “recession transition” almost all households were vulnerable to poverty while almost none were during the “recovery period”. Overall, urban households, more educated households and households receiving remittances from international labor migrants were less vulnerable to poverty. While households with a current or very recent migrant did not have a significantly lower measured vulnerability to poverty, those households receiving remittances from migrants had a lower vulnerability to poverty. Our findings stress that the international labor migration from Tajikistan may not be a reliable means of welfare security for households because external economic shocks and internal political decisions can negatively affect the Russian economy and lead to a reduction of remittance flows to Tajikistan.
All Science Journal Classification (ASJC) codes
- Developmental and Educational Psychology
- Arts and Humanities (miscellaneous)
- Sociology and Political Science
- Social Sciences(all)
- Mobility measurement