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Landslides are a serious problem in many parts of the world; they cause public casualties, property damage, and loss of service, and they cost significant resources to prevent and mitigate. Traditional approaches to landslide issues generally work well, but they only implicitly consider the significant uncertainties and consequences involved. An integrated risk assessment and risk management approach corrects this limitation. Quantitative risk assessment (QRA) is an established methodology that provides input for practical risk management of landslide issues and supplements traditional approaches. QRA provides a framework for anticipating and definitively evaluating potential slope-related problems so they can be accepted or cost-effectively mitigated and the residual risks can be communicated. In QRA, the potential slope-related problems (i.e., various types and sizes of landslides) are evaluated with respect to their probability (over a particular period) or frequency of occurrence and their consequences (e.g., public casualties) if they do occur. QRA can be done correctly in various ways, with the best way depending on the specific application, ranging from global issues for developing program policy to site-specific issues for detailed slope design. However, users skilled in geotechnical engineering and risk assessment are needed to perform QRA correctly and cost-effectively and to understand the limitations of the results. Perceived limitations of QRA include accuracy issues, acceptability issues (e.g., by regulators), and aversion issues (e.g., liability). However, many of these issues are easily resolved and are not real limitations, so that QRA, although not perfect, is advantageous in many cases.

Landslides are a serious problem in many parts of the world; they cause public casualties, property damage, and loss of service, and they cost significant resources to prevent and mitigate. Traditional approaches to landslide issues generally work well, but they only implicitly consider the significant uncertainties and consequences involved. An integrated risk assessment and risk management approach corrects this limitation. Quantitative risk assessment (QRA) is an established methodology that provides input for practical risk management of landslide issues and supplements traditional approaches. QRA provides a framework for anticipating and definitively evaluating potential slope-related problems so they can be accepted or cost-effectively mitigated and the residual risks can be communicated. In QRA, the potential slope-related problems (i.e., various types and sizes of landslides) are evaluated with respect to their probability (over a particular period) or frequency of occurrence and their consequences (e.g., public casualties) if they do occur. QRA can be done correctly in various ways, with the best way depending on the specific application, ranging from global issues for developing program policy to site-specific issues for detailed slope design. However, users skilled in geotechnical engineering and risk assessment are needed to perform QRA correctly and cost-effectively and to understand the limitations of the results. Perceived limitations of QRA include accuracy issues, acceptability issues (e.g., by regulators), and aversion issues (e.g., liability). However, many of these issues are easily resolved and are not real limitations, so that QRA, although not perfect, is advantageous in many cases.

Banks are modeled as Bryant/Diamond-Dybvig "insurers" against the risk of early consumption. Consumption claims must be verified by clearing and settlement. A clearinghouse does this efficiently as long as banks are sufficiently liquid. If liquidity requirements cannot be enforced against all banks then the threat of panics is necessary to induce banks to hold sufficient liquidity. If the clearinghouse can issue emergency currency, then banks can coexist with less liquid institutions. However, if banks′ return to holding reserves is low during "normal times," then there must be times when the return to liquidity is abnormally high. We associate these episodes with the panics of the National Banking Era. Journal of Economic LiteratureClassification Numbers: 042, 311, 314.