In the economic literature on poverty, various methods have been proposed for measuring a phenomenon known as 'vulnerability'. However, after more than a quarter century of research, no consensus has been reached on how to identify such vulnerable individuals within a given population. Some misunderstandings have also arisen from the overlapping of other closely related concepts, such as the expectation of being poor, expected poverty, multi-period poverty and risk exposure. This paper offers a detailed conceptual discussion on vulnerability to poverty and its related elements, reviewing a wide range of identifying criteria provided in the literature. It is found that according to the state of the art in this field of research, two key elements stand out in identifying vulnerable individuals: an expected well-being below the poverty line and a relevant risk of falling into poverty due to downside deviation from a reference level of well-being. The traditional classification of vulnerability approaches has been updated into four groups: (i) those that stress the element of exposure to risk; (ii) those that emphasize the element of expected poverty; (iii) those that define vulnerability through a utility gap and (iv) those that are supported by a mean-risk dominance criterion. 1 θ 1 − E Min{ y jt ,z} z θ for θ < 1 ∧ θ = 0 E ln z { y jt ,z} for θ = 0 (17)

A method to measure vulnerability to multidimensional poverty is proposed under a mean–risk behaviour approach. We extend the unidimensional downside mean–semideviation measurement of vulnerability to poverty towards the multidimensional space by incorporating this approach into Alkire and Foster’s multidimensional counting framework. The new approach is called the vulnerability to multidimensional poverty index (VMPI), alluding to the fact that it can be used to assess vulnerability to poverty measured by the multidimensional poverty index (MPI). The proposed family of vulnerability indicators can be estimated using cross-sectional data and can include both binary and metric welfare indicators. It is flexible enough to be applied for measuring vulnerability in a wide range of MPI designs, including the Global MPI. An empirical application of the VMPI and its related indicators is illustrated using the official MPI of Chile as the reference poverty measurement. The estimates are performed using the National Socioeconomic Characterisation Survey (CASEN) for the year 2017.

OBJECTIVE To assess the possible presence of inequality of opportunities in the health status of Chileans, according to sociodemographic circumstances.METHODS Self-rated health data were used from the Chilean National Health Survey of 2010 to test the hypothesis of strong and weak equality of opportunities in the health status of the Chilean population. These hypotheses were tested using nonparametric techniques and second-order stochastic dominance criteria.RESULTS Robust empirical evidence was obtained, which indicate that the education level of the mother, household socioeconomic status, sex, zone, and region of residence determine opportunities to achieve good health in Chile.CONCLUSIONS Better health status was identified for Chilean adults whenever their mothers had a higher education level, their household income was higher, they were men, or lived in urban areas. The region of residence also affects opportunities to achieve good health in Chile.

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