We use two waves of nationally representative India Human Development Survey to examine factors driving the cooking fuel choice in urban and rural India, separately. We utilize a random effects multinomial logit model that controls for unobserved household heterogeneity. We find that a...

In multilevel modelling, interest in modeling the nested structure of hierarchical data has been accompanied by increasing attention to di¤erent forms of spatial interactions across different levels of the hierarchy. Neglecting such interactions is likely to create problems of inference, which...

In this paper we consider a possible way of measuring equity in health as the absence of systematic disparities in health (or in the major social determinants of health) between groups with different levels of underlying social advantage/disadvantage. Starting from the fairness approach...

Multilevel or mixed effects models are commonly applied to hierarchical data; for example, see Goldstein (2003), Raudenbush and Bryk (2002), and Laird and Ware (1982). Although there exist many outputs from such an analysis, the level-2 residuals, otherwise known as random effects, are often of...