Human-induced climate change, with its potentially catastrophic impacts on weather patterns, water resources, ecosystems, and agricultural production, is the toughest global problem of modern times. Impeding catastrophic climate change necessitates the widespread deployment of renewable energy technologies for reducing the emissions of heat-trapping gases, especially carbon di-oxide (CO₂). However, the deployment of renewable energy technologies is plagued by various market failures, such as environmental externalities from conventional energy sources, learning-by-doing, innovation spillover effects, and peer effects. In efforts to begin to address these market failures, several governments at all levels—city, state, regional, and national—have instituted various subsidies for promoting the adoption of renewable energy technologies. Public resources are limited and have competing uses. So, it is important to ask: how cost-effective are renewable energy subsidies? Are the subsidies even reaching the intended subjects—the potential adopters of renewable energy technologies? In this empirically-driven dissertation, I analyze these important policy design and evaluation questions with a focus on the solar subsidy programs in California. All programs to incentivize the adoption of renewable energy technologies run into the same key question: what is the optimal (maximum capacity inducing) rebate schedule in the face of volatile product prices and the need for policy certainty? Answering this question requires careful attention to both supply-side (learning-by-doing) and demand-side (peer effects) market dynamics. I use dynamic programming to analyze the effectiveness of the largest state-level solar photovoltaic (PV) subsidy program in the U.S. – the California Solar Initiative (CSI) – in maximizing the cumulative PV installation in California under a budget constraint. I find that previous studies overestimated learning-by-doing in the solar industry. Consistent with other studies, I also find that peer effects are a significant demand driver in the California solar market. The main implication of this empirical finding in the dynamic optimization context is that it forces the optimal solution towards higher subsidies in earlier years of the program, and, hence, leads to a lower program duration (for the same budget). In particular, I find that the optimal rebate schedule would start not at $2.5/W as it actually did in CSI, but instead at $4.2/W; the effective policy period would be only three years instead of the realized period of six years. This optimal (i.e., most cost effective) solution results in total PV adoption of 32.2 MW (8.1%) higher than that installed under CSI, using the same budget. Furthermore, I find that the optimal rebate schedule starts to look like the actual CSI in a ‘policy certainty’ scenario where the variation of periodic subsidy-level changes is constrained. Finally, introduction of stochastic learning-by-doing as a way to better capture the dynamic nature of learning in markets for new products does not yield significantly different results compared to the deterministic case. Another, still-unanswered, redistribution question related to the CSI program is: to what degree have the direct PV incentives in California been passed through from installers to consumers? I address this question by carefully examining the residential PV market in California by applying multiple methods. Specifically, I apply a structural-modeling approach, a reduced-form regression analysis, and regression discontinuity designs to estimate the incentive pass-through rate in California’s solar program. The results consistently suggest a high average pass-through rate of direct incentives of nearly 100%, though with regional differences among California counties and utilities. While these results could have multiple explanations, they suggest a relatively competitive market and a smoothly operating subsidy program. Combining evidence from the optimal subsidy policy design and the incentive pass-through analysis, this dissertation lends credibility to the cost-effectiveness of CSI given CSI’s design goal of providing policy certainty and also finds a near-perfect incidence in CSI. Long-term credible commitment as reflected through CSI’s capacity-triggered step changes in rebates along with policy and data transparency are important factors for CSI’s smooth and cost-effective functioning. Though CSI has now wound down because final solar capacity targets have been reached, the historical performance of CSI is relevant not only as an ex-post analysis in California, but potentially has broader policy implications for other solar incentive programs both nationally and internationally. / text

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ACE inhibitors have been widely used in the treatment of certain diseases of the cardiovascular system, the major use being hypertension, since all ACE inhibitors are prescribed for its treatment. ACE inhibitors is also used in the treatment of congestive heart failure. The angiotensin-converting enzyme (ACE) converts angiotensin 1 into angiotensin I1 and also stimulates the production of aldosterone (a hormone produced in the adrenal glands that influences salt and water retention by the kidneys, increasing blood volume and blood pressure). The cost benefit, cost-effectiveness and cost utility of ACE inhibitors have not been established. The objective of the study was to review and analyse the cost of ACE inhibitors by using a medical aid claims database. Data for the study population consisted of all prescriptions containing one or more ACE inhibitor combinations and were extracted from the central database of Interpharm datasystems for a period of one year, from 1 January 2001 to 31 December 2001. A total of 1 475 532 prescriptions containing a total of 2 953 244 ACE inhibitor items represented the study population. Through the analysis of the general medicine utilisation patterns that were obtained from the medicine claims database, it became evident that ACE inhibitor utilisation contributes considerably to the total prevalence and cost of all the medicine items available on the database. It constituted a total prevalence of 4,62% (n =1 475 532) of all the prescriptions and a total prevalence of 2,31% (n =2 953 244) for all the medicine items in the prescriptions with a cost of 3,65% (n =R379 91 1 472,OO). It was concluded that in the analysis of ACE inhibitors according to the innovator/generic classification, the majority of ACE inhibitors prescribed during the twelve-month period were for the innovator product, with a prevalence of 82,56% (n =68 162) and a cost of 89,11% (n =R13 863 080, 90). The utilisation of the generic ACE inhibitors, with a prevalence of 17,44% (n =68 162) and at a cost of 10,89% (n =R13 863 080, 90), was under-utilised. If the total number of prescriptions containing innovator ACE inhibitors could be generically substituted, (37,54%) R5 204 392,68 in cost expenditure could be saved over a twelve-month period. However, the fact that not all the innovator ACE inhibitors have generic equivalents available must be taken into account. If only the prescriptions containing ACE inhibitor items that have generic equivalents were to be substituted with their generic equivalents, R899 751.29(6.5%) would be saved. This was found by adding all the costs saved by substituting innovator drugs with their generics. Consequently, it can be concluded that the extensive use of the innovator ACE inhibitors could mean an exceptional increase in the cost expenditure associated with ACE inhibitor therapy. In completion of the study, recommendations were formulated as an aim to optimise the utilisation of ACE inhibitor generic equivalents. / Thesis (M. Pharm.)--North-West University, Potchefstroom Campus, 2004.

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Malaria is the one of most important diseases in the world, especially in sub-Sahara Africa. This dissertation outlines the enormous burden of the disease in terms of social and economic costs in southern Africa. This dissertation assessed the range and quality of the cost-effectiveness of malaria prevention in sub-Sahara Africa. Six studies published from 1999 to 2003 are reviewed, covering insecticide treated nets, residual spraying, chemoprophylaxis for infants and environmental management. For infants, ITNs cost from US$ 2019 - $2879 per death averted and cost $ III per DALY; chemoprophylaxis cost $ 4.1 per DALY and chemoprophylaxis plus iron cost $ 5.0 per DALY. For children, ITNs cost $ 1559 per death averted, $ 57 per DALY and $ 61 per sick child averted. For non-specific age group, ITNs cost $ 29 per infection averted, and RHS $ 9. Generally all interventions assessed are cost effective use of resources. The chemoprophylaxis is the least expensive malaria prevention among cost effective malaria prevention interventions, followed by residual spraying one round a year, residual spraying two rounds a year, insecticide treated nets with net treatment only and insecticide treated nets with net provision and treatment. There are operational, managerial and financial challenges faced these most cost-effective malaria interventions. Particularly, chemoprophylaxis is faced the tremendous drug resistance potential and is not being recommended to wide use; financial constraints and the potential delaying of children's immunity acquisition lowers the cost-effectiveness of insecticide treated nets; residual spraying is a relatively simpler, faster and cheaper method, but faces political and economic pressure of concerning environmental issues, especially the use of DDT. The integrated approach of environmental management plus residual spraying could be the most cost-effective method of malaria prevention with least adverse environment effects. However, policy makers should apply their knowledge to local conditions. Further, comprehensive education programmes are needed to gain support and understanding from local communities. This would raise the cost-effectiveness of all interventions. / Thesis (M.B.A.)-University of Natal, Durban, 2003.