Evaluating Risks of Dam-Reservoir Systems Using Efficient Importance Sampling

The occurrence frequency of failure events serve as critical indexes representing the safety status of dam-reservoir systems. Although overtopping is the most common failure mode with significant consequences, this type of event, in most cases, has a small probability. Estimation of such rare event risks for dam-reservoir systems with crude Monte Carlo (CMC) simulation techniques requires a prohibitively large number of trials, where significant computational resources are required to reach the satisfied estimation results. Otherwise, estimation of the disturbances would not be accurate enough. In order to reduce the computation expenses and improve the risk estimation efficiency, an importance sampling (IS) based simulation approach is proposed in this dissertation to address the overtopping risks of dam-reservoir systems. Deliverables of this study mainly include the following five aspects: 1) the reservoir inflow hydrograph model; 2) the dam-reservoir system operation model; 3) the CMC simulation framework; 4) the IS-based Monte Carlo (ISMC) simulation framework; and 5) the overtopping risk estimation comparison of both CMC and ISMC simulation. In a broader sense, this study meets the following three expectations: 1) to address the natural stochastic characteristics of the dam-reservoir system, such as the reservoir inflow rate; 2) to build up the fundamental CMC and ISMC simulation frameworks of the dam-reservoir system in order to estimate the overtopping risks; and 3) to compare the simulation results and the computational performance in order to demonstrate the ISMC simulation advantages. The estimation results of overtopping probability could be used to guide the future dam safety investigations and studies, and to supplement the conventional analyses in decision making on the dam-reservoir system improvements. At the same time, the proposed methodology of ISMC simulation is reasonably robust and proved to improve the overtopping risk estimation. The more accurate estimation, the smaller variance, and the reduced CPU time, expand the application of Monte Carlo (MC) technique on evaluating rare event risks for infrastructures.

Essays on Market Frictions and Securitization

This dissertation provides a novel theory of securitization based on intermediaries minimizing the moral hazard that insiders can misuse assets held on-balance sheet. The model predicts how intermediaries finance different assets. Under deposit funding, the moral hazard is greatest for low-risk assets that yield sizable returns in bad states of nature; under securitization, it is greatest for high-risk assets that require high guarantees and large reserves. Intermediaries thus securitize low-risk assets. In an extension, I identify a novel channel through which government bailouts exacerbate the moral hazard and reduce total investment irrespective of the funding mode. This adverse effect is stronger under deposit funding, implying that intermediaries finance more risky assets off-balance sheet. The dissertation discusses the implications of different forms of guarantees. With explicit guarantees, banks securitize assets with either low information-intensity or low risk. By contrast, with implicit guarantees, banks only securitize assets with high information-intensity and low risk. Two extensions to the benchmark static and dynamic models are discussed. First, an extension to the static model studies the optimality of tranching versus securitization with guarantees. Tranching eliminates agency costs but worsens adverse selection, while securitization with guarantees does the opposite. When the quality of underlying assets in a certain security market is sufficiently heterogeneous, and when the highest quality assets are perceived to be sufficiently safe, securitization with guarantees dominates tranching. Second, in an extension to the dynamic setting, the moral hazard of misusing assets held on-balance sheet naturally gives rise to the moral hazard of weak ex-post monitoring in securitization. The use of guarantees reduces the dependence of banks' ex-post payoffs on monitoring efforts, thereby weakening monitoring incentives. The incentive to monitor under securitization with implicit guarantees is the weakest among all funding modes, as implicit guarantees allow banks to renege on their monitoring promises without being declared bankrupt and punished.

RISKS TO FOOD AVAILABILITY AND ACCESS FROM CLIMATE POLICIES: AN INTEGRATED ASSESSMENT OF REGIONAL FOOD AVAILABILITY AND ACCESS WITH ALTERNATIVE CLIMATE MITIGATION STRATEGIES TO 2050

Although mitigating GHG emissions is necessary to reduce the overall negative climate change impacts on crop yields and agricultural production, certain mitigation measures may generate unintended consequences to food availability and access due to land use competition and economic burden of mitigation. Prior studies have examined the co-impacts on food availability and global producer prices caused by alternative climate policies. More recent studies have looked at the reduction in total caloric intake driven by both changing income and changing food prices under one specific climate policy. However, due to inelastic calorie demand, consumers’ well-being are likely further reduced by increased food expenditures. Built upon existing literature, my dissertation explores how alternative climate policy designs might adversely affect both caloric intake and staple food budget share to 2050, by using the Global Change Assessment Model (GCAM) and a post-estimated metric of food availability and access (FAA). My dissertation first develop a set of new metrics and methods to explore new perspectives of food availability and access under new conditions. The FAA metric consists of two components, the fraction of GDP per capita spent on five categories of staple food and total caloric intake relative to a reference level. By testing the metric against alternate expectations of the future, it shows consistent results with previous studies that economic growth dominates the improvement of FAA. As we increase our ambition to achieve stringent climate targets, two policy conditions tend to have large impacts on FAA driven by competing land use and increasing food prices. Strict conservation policies leave the competition between bioenergy and agriculture production on existing commercial land, while pricing terrestrial carbon encourages large-scale afforestation. To avoid unintended outcomes to food availability and access for the poor, pricing land emissions in frontier forests has the advantage of selecting more productive land for agricultural activities compared to the full conservation approach, but the land carbon price should not be linked to the price of energy system emissions. These results are highly relevant to effective policy-making to reduce land use change emissions, such as the Reduced Emissions from Deforestation and Forest Degradation (REDD).