Although countries with high levels of economic development generally have more personal automobile travel than less-affluent nations, income is not the only factor that determines a nation's demand for cars.
Automobility -- travel in personal vehicles -- varies between countries. This brief summarizes a study of the factors besides economic development that affect automobility and how automobility might evolve in developing countries.
The level of automobility, or travel in personal vehicles, varies among countries. By determining the factors besides economic development that have affected automobility in developed countries, researchers can predict how automobility might evolve in developing countries.
To plan the rebuilding of the Louisiana coastline, the Coastal Protection and Restoration Authority used a new analytic approach, developed in part by RAND, that incorporates results from state-of-the-art predictive models within a decision tool to formulate and compare alternatives and visualize outcomes and trade-offs for policymakers and stakeholders.
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.
A diagnostic tool maximizes the utility of security cooperation analyses and can help defense planners identify potential mismatches between security cooperation funding, priorities, and propensity for success with a given country.
Many rural agricultural areas around the world are facing severely depleted groundwater resources, which farmers rely on for irrigation. This dissertation explores the changes that would follow a move to formalize water markets and establish tradable water rights.
Mobility — the ability to travel from one location to another — may look very different in the United States in the year 2030. Three key drivers differentiate possible scenarios: the price of oil, the development of environmental regulations, and the amount of highway revenues and expenditures.
What might one expect for the future of mobility in the U.S. in 2030? A six-step scenario development process resulted in two thought-provoking scenarios that address this question, and three key drivers differentiate the scenarios: the price of oil, the development of environmental regulation, and the amount of highway revenues and expenditures.
In the past, qualitative conceptual causal models called "factor trees" were used to identify the factors that contribute to aspects of terrorism or insurgency and how the factors relate to each other. This report goes beyond the qualitative by specifying a prototype computational social-science model of public support for terrorism and insurgency.
Quantitative analysis is often indispensable to sound planning, but with deep uncertainty, predictions can lead decisionmakers astray. Robust Decision Making supports good decisions without predictions by testing plans against many futures.
The Coastal Protection and Restoration Authority of Louisiana used a new analytic approach, developed in part by RAND, that incorporates results from predictive models in a decision tool to allow formulation and comparison of alternatives.
The Coastal Louisiana Risk Assessment (CLARA) model estimates hurricane flood depths and damage and enables evaluation of potential flood risk reduction projects for inclusion in Louisiana's 2012 Coastal Master Plan.
The Coastal Louisiana Risk Assessment (CLARA) model developed by RAND estimates flood depths and damage that occurs as a result of major storms in Louisiana's coastal region and was used to evaluate potential projects for inclusion in the state's 2012 Coastal Master Plan.
A first step in dealing with uncertainty is confronting its existence, ubiquity, and magnitude. A second step is dealing with it when informing assessments and decisions. Lessons from RAND's national security work on planning under uncertainty can be applied in many other fields.