Economics ETDs

Publication Date

Spring 2-15-2024


This dissertation is organized in five chapters. The first chapter provides a summary of the three research articles that are combined in this dissertation. It highlights the goals of each research paper, and outlines their contribution to the existing literature and the field of economics. Chapters 2 and 3 are based on a field study that I conducted on cancer and non-cancer patients in various cancer hospitals in Nepal. Chapter 4 uses data from field survey conducted by scholars of the Nepal Study Center, UNM, including me, in Sindhupalchok district of Nepal after the devastating earthquake of 2015. The final chapter summarizes major findings of the three chapters, and discusses policy options.

The second chapter focuses on cancer patients’ quality of life. In particular, I focus on the utility that the patients attain from different attributes of quality of life, and their willingness to pay for improved quality of life. I use the Euro-QoL instrument for measuring quality of life and exploit the discrete choice experiment design. For the empirical analysis, I employ a random parameter logit model on field survey data collected from cancer and non-cancer patients in various hospitals in Nepal. I find that cancer patients derive utility from all attributes of quality of life, with the highest utility received from the most desirable level of the “Usual Activities” attribute, followed by the most desirable level of the “Pain” attribute. Overall, cancer patients are willing to pay about NRS 2.6 million [about USD 26,000] for improving their quality of life from their current state to the one with the most desirable level of each attribute.

Moving forward, the third chapter explores factors that affect cancer and non-cancer patients’ quality of life, with a particular focus on social support. To put this in context, using the same field survey data as before, I analyze the relationship between social support, stress, access to health care services, and quality of life of Nepalese cancer and non-cancer patients. In addition to the EuroQoL five dimension three level instrument for measuring quality of life of patients, I also use the 11-item De Jong Gierveld Loneliness Scale for measuring social support and stress. I unpair the relationships and effects among variables by treating social support, stress, and quality of life as latent constructs in a general (mixed) structural equation modeling framework. The empirical results show that social support plays a positive role in determining quality of life only for cancer patients. However, stress and easy access to health care services have a positive relationship with the quality of life of both cancer and non-cancer patients. In addition, as expected, higher wealth and education display a positive association with patients’ quality of life.

Since social support was found to improve the quality of life of cancer patients, I divert my attention from cancer patients and examine the significance of social support in the recovery of disaster-affected people in the fourth chapter. In 2015, a 7.8 magnitude earthquake struck Nepal that claimed around 9000 lives and destroyed more than 800,000 homes. While a few systematic economic assessment studies of this disaster have been conducted, most do not provide a comprehensive analysis that encompasses economic as well as non-economic dimensions. Using data from a 2017 field survey, this chapter examines the critical role of social support in post-disaster recovery, and highlights the fact that social infrastructure drives resilience. The empirical estimates from an ordered logit model show that of the financial support measures wealth positively affects only housing while borrowing affects all recovery measures except housing. Similarly, social support measures positively influence all recovery measures except housing; the effect is more pronounced for volunteering (bridging social support) than family status and number of friends (bonding social support). Combining individual measures to create two composite indices, I find that the social support index is at least as effective as the financial support index in post-earthquake recovery.

Degree Name


Level of Degree


Department Name

Department of Economics

First Committee Member (Chair)

Alok Bohara

Second Committee Member

Christine Sauer

Third Committee Member

Sarah Stith

Fourth Committee Member

Xiaoxue Li

Fifth Committee Member

Vinish Shrestha




Quality of Life; Social Capital; Cancer, Post-disaster Recovery; Willingness to Pay; Discrete Choice Experiment

Document Type


Available for download on Wednesday, May 15, 2024

Included in

Economics Commons