Pardee Center

The RAND Frederick S. Pardee Center for Longer Range Global Policy and the Future Human Condition was established in 2001 through a generous $5 million pledge from RAND alumnus Frederick S. Pardee. The RAND Pardee Center aims to enhance the overall future quality and condition of human life by aggressively disseminating and applying new methods for long-term policy analysis in a wide variety of policy areas where they are needed most.

The Pardee Center organizes its activities around two main themes: (1) advancing the state-of the-art in conducting long-term policy analysis so organizations can implement better long-range policy; and (2) developing and disseminating approaches that will help make proper stewardship for the future be more commonly practiced.

Identifying Key Indicators for Adaptive Management of the Los Angeles Metropolitan Integrated Resources Plan — May 2012
The Los Angeles Metropolitan Water District’s 2010 Integrated Resource Plan Update describes a preferred resource mix that would meet projected demand and most expected contingencies through 2035. However, recognizing that Metropolitan and the region face many significant uncertainties over the next 25 years, the Plan also describes an adaptive management approach that will monitor key trends and modify the preferred resource mix as necessary. In this project, RAND is assisting Metropolitan to determine which trends it should most usefully monitor in order to implement this adaptive management strategy.

Using RDM to Manage Climate and Other Uncertainties in EPA’s National Water Program— May 2011 – September 2013
RAND is conducting a project for the EPA to determine the utility of Robust Decision Making (RDM) methods for evaluating the agency’s needs and priorities under the National Water Program. EPA may find RDM valuable because providing safe and reliable drinking water supplies and managing water quality and ecosystem health present a challenge of decision making under conditions of deep uncertainty. Maintaining safe and reliable supplies depends on timely investments in water treatment, storage, and delivery infrastructure, and the success of these investment decisions relies on predictions about water availability, system needs, and infrastructure performance many decades into the future. The project will culminate in two pilot RDM applications on NWP activities to test the applicability and usefulness of such methods for the future.

Testing the Scenario Hypothesis: The Effect of Alternative Characterizations of Uncertainty on Decision Structuring— May 2011 – April 2013
There is much current interest in decision support approaches to help improve groups’ and individuals’ ability to make difficult decisions, such as those planners must make when considering uncertain, long-term environmental changes. This project, supported by the National Science Foundation in partnership with researchers at Columbia University, is aimed at testing the hypothesis that decision support processes employing scenarios to characterize deep uncertainty will help contentious groups make more effective decisions than decision support processes that characterize uncertainty using a single set of best-estimate probability distributions. Testing this scenario hypothesis requires an experimental design where decision makers can augment the initial choice set by designing additional options – uncommon in judgment and decision making experiments because it can prove difficult to give subjects the flexibility to design new decision options while nonetheless working within a believable set of constraints. To address this challenge, the proposed experiments will focus on a real-world decision – managing a fishery.

Informing Climate-Related Decisions with Earth Systems Models— April 2011 – April 2014
An interdisciplinary grand challenge seeks to develop next-generation Earth System Models (EaSMs) not only to improve fundamental scientific understanding of the climate and related systems but also to improve decision makers' ability to proactively plan for the impacts of climate variability and change. But decades of research on decision making and support confirm that merely providing additional information in complicated situations such as posed by climate change does not necessarily improve the quality of the decisions. The proposed project aims to provide a deeper understanding of how best to use information from next generation EaSMs to improve climate-related decisions by tightly linking three different research activities: generating different types of information from ensembles of such models, using this information in real-world decision support applications, and measuring the value of this information to decision makers through field evaluations and psychology laboratory experiments.

Applying RDM to Water Resource Management in Vietnam— August 2011 – June 2012
Ho Chi Minh City ranks fourth globally among port cities most vulnerable to climate change. Ho Chi Minh City already experiences extensive routine flooding, but rising sea levels could permanently inundate a large portion of the city’s population, place the poor at particular risk, and threaten new economic development that has occurred in low-lying areas. In this World Bank-sponsored project, RAND researchers Dr. Robert Lempert, Dr. Nidhi Kalra, and Dr. Jordan Fischbach are working with the Ho Chi Minh City Steering Committee for Flood Control (SCFC) to use RDM to develop long-term flood defenses that will be robust to these uncertainties. RAND researchers have traveled to Ho Chi Minh City and met with key stakeholders including the SCFC and local World Bank officers in order to understand the city’s flood concerns, existing infrastructure, and current planning efforts, as well as to present RDM. RAND is developing a design of the analysis of vulnerabilities, adapting the SCFC's models for this analysis, identifying vulnerabilities, and evaluating adaptation options to develop a robust, iterative risk management plan.

Investigation Of A Methodology For Robust Defense Planning Under Conditions Of Complexity And Deep Uncertainty— April 2012 – September 2013
As its overarching goal, this study aims to help improve the value and character of defense resource planning in an era of growing uncertainty and corresponding complexity. To address similar societal challenges and concerns over the past decades, RAND developed and matured RDM, a quantitative decision support methodology for informing decisions under conditions of deep uncertainty and complexity. While widely applied in many policy areas, RDM has not yet been used to address defense resource planning. Nonetheless, such an approach appears to hold promise for many of the Department of Defense's (the Department) planning needs. This study will specifically apply RDM's proven approaches to demonstrate the method's utility for defense resource planning and then help the Department to adopt the approach as an in-house capability.

Analytic Tools To Evaluate Policies For Market Transformations— through August 2012
Limiting climate change requires a transformation of energy and transportation systems. To hold global atmospheric concentrations of greenhouse gases within what appear to be acceptably safe levels will require the carbon intensity of these systems to drop much faster over the coming decades than any relevant historical experience. But attempting to force too fast a decline could impose unnecessary costs to the economy. In addition, costs and benefits will not be equally distributed during any transformation to low carbon intensity, so that any policy must contend with differing pressures from various groups within society. We have designed a policy simulation tool and supporting decision framework to examine how alternative designs of market-based policy instruments might or might not facilitate such transformations.