Escaping Energy Poverty: A Comparative Analysis of 17 European Countries

A comparative analysis of energy poverty transitions and persistence can provide valuable suggestions for long-term policy actions. This study examines the dynamics of energy poverty in 17 European countries based on the longitudinal household data from the EU Survey on Income and Living Conditions, waves 2015–2018. The study pursues two goals. First, we explore households’ chances of transitioning in and out of energy poverty in each country following the discrete-time Markov process. On average, the probability to stay in energy poverty is 51.5%, and there is a lot of heterogeneity across countries. Households in Bulgaria, Greece, Romania, and Lithuania are quite close to the energy poverty trap. Second, we identify factors that help energy-poor households leave energy poverty. Demographic, technical, and socio-economic factors are the drivers in escaping energy poverty, which suggests common EU policy.

Long-Term Dynamics of Poverty Transitions in India

I use a stochastic model to explore the dynamics of poverty in India from 1952 to 2006 and find that temporal transitions into and out of poverty are common. Model outcomes suggest that transitions out of poverty outnumber transitions into poverty in recent times, but that there is still a nontrivial proportion of individuals transitioning annually into poverty, highlighting the economic fragility of those near the poverty line. There is also a marked persistence of poverty over time, and although this has been slowly declining, past poverty remains a good predictor of current poverty. Particularly concerning in this context are the income trajectories of those in the bottom decile of the income distribution for whom escape from poverty appears infeasible given extant income dynamics. Finally, the dynamics suggest that transitional and persistent poverty are distinct phenomena that require distinct policy responses involving both missing markets and state action.

Poverty transitions in severe mental illness: longitudinal analysis of social drift in China, 1994–2015

Background Although poverty associated with severe mental illness (SMI) has been documented in many studies, little long-term evidence of social drift exists. This study aimed to unravel the poverty transitions among persons with SMI in a fast change community in China. Methods Two mental health surveys, using the International Classification of Disease (ICD-10), were conducted in the same six townships of Xinjin county, Chengdu, China in 1994 and 2015. A total of 308 persons with SMI identified in 1994 were followed up in 2015. The profiles of poverty transitions were identified and regression modelling methods were applied to determine the predictive factors of poverty transitions. Results The poverty rate of persons with SMI increased from 39.9% to 49.4% in 1994 and 2015. A larger proportion of them had fallen into poverty (27.3%) rather than moved out of it (17.8%). Those persons with SMI who had lost work ability, had physical illness and more severe mental disabilities in 1994, as well as those who had experienced negative changes on these factors were more likely to live in persistent poverty or fall into poverty. Higher education level and medical treatment were major protective factors of falling into poverty. Conclusions This study shows long-term evidence on the social drift of persons with SMI during the period of rapid social development in China. Further targeted poverty alleviation interventions should be crucial for improving treatment and mental recovery and alleviating poverty related to SMI.

Estimating poverty transitions in Mozambique using synthetic panels: A validation exercise and an application to cross-sectional survey data

In this paper we first validate the use of the synthetic panels technique in the context of the 2014/15 intra-year panel survey data for Mozambique, and then apply the same technique to the 1996/97, 2002/03, 2008/09, and 2014/15 cross-sectional household budget surveys for the same country. We find that in most analyses poverty rates and poverty transitions estimated using synthetic panels provide results that are close to the true values obtained using the 2014/15 panel data. With respect to intra-year poverty dynamics, we find that Mozambique has a high intra-year variability in consumption and poverty, and a very high degree of intra-year poverty immobility, with a big portion of the population remaining either in poverty or out of poverty over the whole year, with smaller percentages of individuals moving upward or downward. With respect to the 1996/97, 2002/03, 2008/09, and 2014/15 cross-sectional surveys, our results suggest that in most year-to-year comparisons there is a greater proportion of people getting out of poverty than falling into poverty, consistent with the poverty-reduction process observed, but the percentage of people staying in poverty over time appears to be substantially higher, involving about one-third of the population in most years. Further analyses on the 2008/09 and 2014/15 surveys estimate that for an individual who was in the vulnerable group in 2008/09, there is a 60 per cent probability of remaining in the same group, whereas the probability of becoming non-vulnerable is lower than the probability of entering poverty. This constitutes the first attempt to provide an insight into poverty dynamics in Mozambique using all the available survey data.

The Specification of Dynamic Discrete-Time Two-State Panel Data Models

This paper compares two approaches to analyzing longitudinal discrete-time binary outcomes. Dynamic binary response models focus on state occupancy and typically specify low-order Markovian state dependence. Multi-spell duration models focus on transitions between states and typically allow for state-specific duration dependence. We show that the former implicitly impose strong and testable restrictions on the transition probabilities. In a case study of poverty transitions, we show that these restrictions are severely rejected against the more flexible multi-spell duration models.