This volume of Research on Economic Inequality contains research on how we measure poverty, inequality and welfare and how these measurements contribute towards policies for social mobility. The volume contains eleven papers, some of which focus on the uneven impact of the Covid-19 pandemic on poverty and welfare.

Opening with debates on theoretical issues that lie at the forefront of the measurement of inequality and poverty literature, the first two chapters go on to propose new methods for measuring wellbeing and inequality in multidimensional categorical environments, and for measuring pro-poor growth in a Bayesian setting. The following three papers present theoretical innovations for measuring poverty and inequality, namely, in estimating the dynamic probability of being poor using a Bayesian approach, and when presented with ordinal variables.

The next three chapters are contributions on empirical methods in the measurement of poverty, inclusive economic growth and mobility, with a focus on India, Israel and a unique longitudinal dataset for Chile. The volume concludes with three chapters exploring the impact of the Covid-19 pandemic as an economic shock on income and wealth poverty in EU countries and in an Argentinian city slum.

This volume of Research on Economic Inequality contains research on how we measure poverty, inequality and welfare and how these measurements contribute towards policies for social mobility. The volume contains eleven papers, some of which focus on the uneven impact of the Covid-19 pandemic on poverty and welfare.

Opening with debates on theoretical issues that lie at the forefront of the measurement of inequality and poverty literature, the first two chapters go on to propose new methods for measuring wellbeing and inequality in multidimensional categorical environments, and for measuring pro-poor growth in a Bayesian setting. The following three papers present theoretical innovations for measuring poverty and inequality, namely, in estimating the dynamic probability of being poor using a Bayesian approach, and when presented with ordinal variables.

The next three chapters are contributions on empirical methods in the measurement of poverty, inclusive economic growth and mobility, with a focus on India, Israel and a unique longitudinal dataset for Chile. The volume concludes with three chapters exploring the impact of the Covid-19 pandemic as an economic shock on income and wealth poverty in EU countries and in an Argentinian city slum.

This volume of Research on Economic Inequality contains research on how we measure poverty, inequality and welfare and how these measurements contribute towards policies for social mobility. The volume contains eleven papers, some of which focus on the uneven impact of the Covid-19 pandemic on poverty and welfare.

Opening with debates on theoretical issues that lie at the forefront of the measurement of inequality and poverty literature, the first two chapters go on to propose new methods for measuring wellbeing and inequality in multidimensional categorical environments, and for measuring pro-poor growth in a Bayesian setting. The following three papers present theoretical innovations for measuring poverty and inequality, namely, in estimating the dynamic probability of being poor using a Bayesian approach, and when presented with ordinal variables.

The next three chapters are contributions on empirical methods in the measurement of poverty, inclusive economic growth and mobility, with a focus on India, Israel and a unique longitudinal dataset for Chile. The volume concludes with three chapters exploring the impact of the Covid-19 pandemic as an economic shock on income and wealth poverty in EU countries and in an Argentinian city slum.