Well‐Being, Deprivation, and the Great Recession in the U.S.: A Study in A Multidimensional Framework

Abstract

We study changes in social well-being and deprivation in the U.S. during the Great Recession and the subsequent recovery. We outline an analytical framework for measuring well-being and deprivation in a multidimensional fashion when data on achievement in each dimension is assumed to be ordinal and binary in nature. We use data from the American Community Survey between 2008 and 2015 and find that there was a decline in social well-being and a rise in social deprivation in the U.S. during the recession followed by a reversal of trends during the recovery. Despite low deprivation levels among the White population, this population experienced the largest increase in deprivation during the recession and the least decline in deprivation in the recovery period. These results underscore the fact that the impact of recession and the subsequent recovery varied significantly across population groups. JEL Codes: D36, I31, J10focus on the overall deprivation of the deprived individuals only, we introduce a benchmark level t (t > 0) such that an individual is considered deprived if and only if her overall achievement falls short of t. Our measure of social deprivation is then computed as the sum of overall deprivations of all individuals who are classified as deprived.Our measures are related to some existing measures introduced in the literature on measuring multi-dimensional well-being and deprivation (see, for example, Aaberge and Brandolini (2015), for an extensive survey on related studies). For example, if the transformation function that is used to transform an individual's overall achievement to well-being is linear, then our measure is equivalent to the counting measure (Atkinson, 2003) widely used in the literature. However, if the transformation function is not linear, then the family of our measures behaves very differently from counting measures, and can avoid many pitfalls suffered by various counting measures. By appropriately choosing a transformation function to transform an individual's overall achievement to her well-being (see our discussions in Section 3), we ensure that our measure satisfies certain attractive properties.We estimate the proposed indices using data from the American Community Survey (ACS), which is the largest household level surveys in the U.S. Our sample comprises more than 2 million individuals each year from ACS rounds: 2008 to 2015. We use the recommendations of the Commission on the Measurement of Economic Performance and Social Progress (Stiglitz et al., 2009) as a guide in choosing the different dimensions or dimensions in terms of which we assess an individual's well-being. We choose 9 variables from the ACS which broadly capture the well-being dimensions mentioned in the Commission's report. We estimate trends in overall well-being and deprivation over time and test their sensitivity to multiple thresholds and weights. We also estimate these indices for population groups based on age, gender, nativity, race and ethnicity and find some interesting differences among the different...

Multidimensional economic deprivation during the coronavirus pandemic: Early evidence from the United States

“…Dhongde and Haveman [ 4 ] found that between 2008 and 2013, about 40% of Hispanics were multidimensional poor compared with 14% in the general population. Similarly, Dhongde et al [ 5 ] found deprivation levels to be one of the highest among Hispanics between 2008 and 2015.…”

“…This paper uses a set of indices proposed by Alkire and Foster [ 24 ]. Except for Dhongde et al (2019) [ 5 ] who propose a different set of indices, all of the previous studies estimating multidimensional poverty in the United States, have used the Alkire and Foster [ 24 ] indices (e.g. see [ 4 , 6 , 7 ]) largely because of their ease of interpretation.…”

“…A multidimensional index measures the extent of deprivation experienced by an individual in multiple indicators simultaneously. Previously, multidimensional indices have been used in the United States to measure changes in poverty over time [4][5][6][7]. This paper is the first to use a multidimensional framework in a novel way; it uses qualitative data from survey responses to measure economic deprivation in the midst of the coronavirus pandemic in the United States.…”

Multidimensional Indices with Data-driven Dimensional Weights: A Multidimensional Coefficient of Variation

“…We may note here that a number of such norms are also discussed in the literature on the measurement of multidimensional deprivation and well-being. Dhongde, Li, Pattanaik, and Xu (2016), Dhongde, Pattanaik, and Xu (2017) and Pattanaik and Xu (2018) are among the important recent contributions to this literature. (We are indebted to an anonymous referee for these references.)…”

Analyzing Racial and Ethnic Differences in the USA through the Lens of Multidimensional Poverty

“…Dhongde and Haveman (2017),Dhongde et al (2019),Glassman (2019),Mitra and Brucker (2019).10 Dhongde and Haveman (2017) andDhongde et al (2019) use ACS data; Glassman (2019) also uses ACS but combines information from CPS Mitra and Brucker (2019). is the only study which has used only CPS data.…”