Date of Award

Fall 2022

Degree Type

Restricted to Claremont Colleges Dissertation

Degree Name

Political Science and Economics, PhD interfield

Program

School of Social Science, Politics, and Evaluation

Advisor/Supervisor/Committee Chair

Mark Abdollahian

Dissertation or Thesis Committee Member

Arthur Denzau

Dissertation or Thesis Committee Member

Zining Yang

Dissertation or Thesis Committee Member

Zining Yang

Terms of Use & License Information

Terms of Use for work posted in Scholarship@Claremont.

Rights Information

© 2022 Ahmed A Almulla

Keywords

Relative Political Allocation, United Arab Emirates

Subject Categories

Economics | Political Science

Abstract

This dissertation evaluates the efficiency of general government expenditure of the United Arab Emirates (UAE) relative to other countries. To achieve this, the case study utilized the Relative Political Allocation model (RPA) paired with Analytic Narrative as a method of analysis. Secondary data of the UAE and other countries are obtained from the latest Relative Political Capacity dataset V2.4 (2020). The aim of this case study was two-fold. First, related to the UAE, it sought to identify the mechanisms and historical sources of efficiencies/inefficiencies over time in the UAE government’s allocation of its public expenditure in four key functional areas. After identifying the sources of varying relative efficiencies, a qualitative analysis of the socioeconomic and political factors effecting changes in allocation preferences was conducted. At the end of this study, specific policy adjustments for improving efficiencies in UAE government expenditure are recommended. Second, related to the model, this study explored whether the RPA model is suitable for explaining the intricacies of UAE’s unique case. This research has found that despite its limitations, RPA is a promising model that provides important insights in a case study setting. A step-by-step guide to the application of the RPA model to a case study has been provided for future replication. Future extension of this research as well as future improvement of the RPA model are suggested.

ISBN

9798845410597

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