Researchers frequently require a quantitative understanding of the likely consequences of different actions before they can advise decisionmakers and design effective policies. RAND develops and uses statistical, econometric, and other exploratory models and simulations to analyze the potential outcomes of different policies in a range of areas such as transportation usage, health care, patient safety, and military campaigns.
Research conducted by:
RAND National Security Research Division;
RAND Project AIR FORCE;
RAND Arroyo Center;
RAND Drug Policy Research Center
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RAND Europe's "Choice Modelling and Valuation" group provides specific expertise in using discrete choice modeling methods to understand and predict choice behavior as a result of policy intervention. This work is frequently undertaken in the transport sector, but expertise is increasingly applied in sectors including health and social care, post and communications, and provision of regulated consumer services.
A collaboration among RAND, the Pardee RAND Graduate School, Evolving Logic, and network partners, RDMlab promotes the development and use of Robust Decision Making (RDM) methods for policy and decisionmaking.
RAND Europe is expanding the original traffic model it developed for Copenhagen to include time-of-day choice for car drivers. Doing so will allow city planners to assess the effectiveness of different charging policies aimed at reducing congestion levels.
Policymakers are facing new challenges as they implement the Patient Protection and Affordable Care Act (ACA). RAND COMPARE is a modeling tool that simulates the impact of implementation decisions on insurance coverage, premiums, and health care spending.
The RAND Roybal Center for Health Policy Simulation developed better models to understand the consequences of biomedical developments and social forces for health, health spending, and health care delivery, particularly for the elderly.