It is well accepted that a country's GDP may not fully reflect its level of well-being. In recent years, happiness has emerged as an alternative indicator of well-being, and research has mainly focused on determining the level of happiness. While it is important to look at the level, the distribution of happiness is also a salient aspect in any evaluation of inequality. There has been a growing interest in the distribution of happiness, although the ordinal nature of the data makes the use of standard inequality measures problematic. Our paper contributes to the literature by exploring the distributions for the U.S. from 1972 to 2010. Based on new methods developed for ordinal data, we are able to overcome the problems associated with ordinality and obtain unambiguous rankings of happiness distributions. We also compute the level of happiness inequality using existing measures based on median centred approaches. Further, we decompose the median based inequality measures of happiness by gender, race, and region. JEL Codes: D39, I393 For a good discussion of the different methods to cardinalize an ordinal variable, refer to Kalmijn and Arends (2010).Variance or standard deviation is an unsatisfactory measure of inequality under a cardinal scale (see Sen, 1973). Further, Foster and Ok (1999) show that even the more commonly used variance of logarithms might be unsuitable when it comes to measuring inequality.Note: NW refers to number of women in each year; NM refers to number of men in each year.

There is a growing interest on dynamic and broader concepts of deprivation such as vulnerability, which takes in to account the destitution of individuals from future shocks. We use the framework of decision making under uncertainty to arrive at a new measure of vulnerability to poverty. We highlight the importance of current standard of living to better capture the notion of vulnerability. In conceptualizing the new class of measures of vulnerability we thus move beyond the standard expected poverty measures that is commonly found in the literature. We also axiomatically characterize the new class of measure and discuss some of it's properties. April, 2010.We are highly indebted to Tony Shorrocks for introducing us to this topic and for his constant encouragement and generous support. We are grateful to Sabina Alkire, Joydeep Dutta, Sashi Nandiebam, Prasanta Pattanaik, Horst Zank and conference and seminar participants at the University of Bath, University of Manchester, UC Riverside, OPHI, Oxford and WIDER, Helsinki and RES, Surrey for their comments. We are also grateful to an anonymous referee whose comments have signi…cantly improved the paper.

In measuring social deprivation in a multidimensional framework, ideally one should first measure each individual's overall deprivation, and then aggregate the overall deprivation levels of all individuals. However, given only aggregate data, one is often forced to measure social deprivation in terms of each attribute separately and then to aggregate them so as to get the overall social deprivation. This paper shows that it is only under extremely stringent conditions that this procedure would always yield the same result as the conceptually sound procedure referred to earlier. A similar difficulty also arises in measuring a society's standard of living.

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This paper proposes classes of intertemporal poverty measures which take into account both the debilitating impact of prolonged spells in poverty and the mitigating e¤ect of periods of a-uence on subsequent poverty. The weight assigned to the level of poverty in each time period depends on the length of the preceding spell of poverty or of non-poverty. The proposed classes of intertemporal poverty measures are quite general and allow for a range of possible judgements as to the overall impact on a poor period of preceding spells of poverty or a-uence. We discuss the properties of the proposed classes of measures and axiomatically characterize these measures.