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12
2) Societal Determinants of HIV/AIDS - those societal factors that can affect
HIV/AIDS rates in developing countries.
3) Political Determinants of HIV/AIDS - those political variables that can
affect HIV/AIDS rates in developing countries.
4) Multisectoral HIV/AIDS Programs - those general variables that explain a
government’s adoption of a multisectoral HIV/AIDS program.
Economic Effects of HIV/AIDS
A number of studies have estimated the relationship between HIV/AIDS and
economic growth overtime to show that the disease does, in fact, hurt growth. Other
studies have employed simulation models to gauge what could happen to economic
growth in a country should the HIV/AIDS epidemic go unmanaged. Examples of
both types of studies are reviewed below.
In 1992, Mankiw et al. extended the standard Solow model of economic
growth to include human capital (skilled labor) H as well as the original inputs to
growth: capital K, labor L (and later an exogenous measure for technological
progress A). In doing so, they observed that the level of skilled labor differs among
rich and poor economies and this has important implications for economic growth.
In answering the question as to why some countries are richer than others Mankiw et
al. (1992) summarize a model that has been interpreted to mean: “Countries are rich
because they have high investment rates in physical capital [K}, spend a large
fraction of time accumulating skills [H], have low population growth rates, and have
high levels of technology [A]” (Jones 2002:57). While this growth model has proven
Object Description
| Title | Political determinants and economic effects of HIV/AIDS: a push for the multisectoral approach |
| Author | Davis, Dollie |
| Author email | dollieda@usc.edu; dolliesdavis@gmail.com |
| Degree | Doctor of Philosophy |
| Document type | Dissertation |
| Degree program | Political Economy & Public Policy |
| School | College of Letters, Arts and Sciences |
| Date defended/completed | 2008-07-15 |
| Date submitted | 2008 |
| Restricted until | Unrestricted |
| Date published | 2008-10-30 |
| Advisor (committee chair) | Wise, Carol |
| Advisor (committee member) |
Nugent, Jeffrey B. Chi, Iris |
| Abstract | The proposed dissertation offers an explanation for the large differences in HIV/AIDS rates among 89 low and middle-income countries throughout the Sub Saharan African, Asian, and Latin American regions over a ten-year period (1995-2005). The HIV/AIDS rates in these countries vary widely and seemingly independently of economic wealth. One possible determinant of these differences is the presence and degree of development of strong multisectoral programs aimed at both prevention and cure of HIV/AIDS. The main hypothesis for this dissertation is: "A country's success in combating HIV/AIDS lies in the government's ability to implement an effective multisectoral program." This hypothesis is explored through quantitative models using data from the ten-year period (1995-2005). Results show that the presence of a multisectoral program over the ten-year period is associated with a significantly lower HIV/AIDS incidence rate by 2005. This effect is produced by controlling for various political, economic, societal, and institutional factors. Although there is some anecdotal evidence which suggests that multisectoral programs help to improve the HIV/AIDS problem in developing countries, there has been little if any empirical work done on this subject to date. |
| Keyword | multisectoral; HIV/AIDS; economic development |
| Geographic subject (region) | Carribbean |
| Geographic subject (continent) | Africa; Asia; South America |
| Coverage date | 1995/2005 |
| Language | English |
| Part of collection | University of Southern California dissertations and theses |
| Publisher (of the original version) | University of Southern California |
| Place of publication (of the original version) | Los Angeles, California |
| Publisher (of the digital version) | University of Southern California. Libraries |
| Provenance | Electronically uploaded by the author |
| Type | texts |
| Legacy record ID | usctheses-m1724 |
| Contributing entity | University of Southern California |
| Rights | Davis, Dollie |
| Repository name | Libraries, University of Southern California |
| Repository address | Los Angeles, California |
| Repository email | cisadmin@lib.usc.edu |
| Filename | etd-Davis-2422 |
| Archival file | uscthesesreloadpub_Volume44/etd-Davis-2422.pdf |
Description
| Title | Page 20 |
| Contributing entity | University of Southern California |
| Repository email | cisadmin@lib.usc.edu |
| Full text | 12 2) Societal Determinants of HIV/AIDS - those societal factors that can affect HIV/AIDS rates in developing countries. 3) Political Determinants of HIV/AIDS - those political variables that can affect HIV/AIDS rates in developing countries. 4) Multisectoral HIV/AIDS Programs - those general variables that explain a government’s adoption of a multisectoral HIV/AIDS program. Economic Effects of HIV/AIDS A number of studies have estimated the relationship between HIV/AIDS and economic growth overtime to show that the disease does, in fact, hurt growth. Other studies have employed simulation models to gauge what could happen to economic growth in a country should the HIV/AIDS epidemic go unmanaged. Examples of both types of studies are reviewed below. In 1992, Mankiw et al. extended the standard Solow model of economic growth to include human capital (skilled labor) H as well as the original inputs to growth: capital K, labor L (and later an exogenous measure for technological progress A). In doing so, they observed that the level of skilled labor differs among rich and poor economies and this has important implications for economic growth. In answering the question as to why some countries are richer than others Mankiw et al. (1992) summarize a model that has been interpreted to mean: “Countries are rich because they have high investment rates in physical capital [K}, spend a large fraction of time accumulating skills [H], have low population growth rates, and have high levels of technology [A]” (Jones 2002:57). While this growth model has proven |
