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Multidimensional Human Opportunity Index

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Abstract

One fact that emerges from the evaluation of the Millennium Development Goals is that not all countries met all the goals and there are significant complementaries among failing on specific goals. This paper proposes the Multidimensional Human Opportunity Index (MHOI) that focuses on the complementaries among access to multiple services. We focus on access to services for children, with the aim of capturing equality in opportunity for children from diverse socio-economic backgrounds. This index builds on the Human Opportunity Index of the World Bank that measures children’s access to a basic service, such as access to clean water. However, the MHOI differs from the parent index in that we measure joint access to multiple services or access to a bundle of services. We apply the MHOI on two Himalayan states of South Asia, Nepal and Bhutan, and show that although each basic service is available to a large proportion of the population, only two-thirds in Bhutan and one half in Nepal have access to the bundle of basic services in 2011–2012.

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Notes

  1. This literature shows that the correlation of income between fathers and sons is very high in the US (Lee and Solon 2009; Mazumder 2005; Solon 1992; Zimmerman 1992), which can reduce upward mobility of an individual born to poor parents. The evidence from other countries is mixed; in countries like Britain and Germany, intergenerational mobility is low Wiegand (1997), while it is high in Finland and Sweden (Osterbacka 2001; Osterberg 2000). Evidence from Latin American countries and China show that mobility is much lower in those countries when compared to that seen in the US (Behrman et al. 2001; Ferreira and Veloso 2006; Gong et al. 2012). Currie (2009) show that children who are born into poor families do have a lower birth weight, worse health and learning outcomes than children born into richer families. Access to proper healthcare and education could improve the chances of a child having a favorable adult life.

  2. Although some papers do not find improvements in a community leading to improvements of individual outcomes in the short run (Kling et al. 2005; Katz et al. 2001), recent research by Chetty et al. (2015) shows that neighborhood quality can have an effect on individual outcomes. Neighborhood school quality can increase returns to schooling of an individual (Altonji and Dunn 1996), which shows the importance of proper and quality services in improving the future outcomes of a child.

  3. For each of the services we assume that the metric we use to quantify access has a lower and upper bound signifying no access and complete access, respectively.

  4. A permutation matrix \(\Pi\) is a square matrix with a single ‘1’ in each row and each column, and the rest ‘0’s.

  5. The full explanation of how each variable has been calculated is presented in Table 5.

  6. See the Table 5 for the specific definitions of each service.

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Correspondence to T. M. Tonmoy Islam.

Additional information

We would like to thank Jose Molinas Vega, Ambar Narayan and James Foster for helpful discussions. Of course, all remaining errors are solely ours.

Appendix

Appendix

See Table 5.

Table 5 Service list and definitions

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Islam, T.M.T., Mitra, S. Multidimensional Human Opportunity Index. Soc Indic Res 130, 523–535 (2017). https://doi.org/10.1007/s11205-015-1202-4

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