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001 978-1-4614-1665-4
003 DE-He213
005 20140220083243.0
007 cr nn 008mamaa
008 120611s2012 xxu| s |||| 0|eng d
020 _a9781461416654
_9978-1-4614-1665-4
024 7 _a10.1007/978-1-4614-1665-4
_2doi
050 4 _aJA1-92
072 7 _aJPA
_2bicssc
072 7 _aPOL000000
_2bisacsh
082 0 4 _a320
_223
100 1 _aDesai, Anand.
_eeditor.
245 1 0 _aSimulation for Policy Inquiry
_h[electronic resource] /
_cedited by Anand Desai.
264 1 _aNew York, NY :
_bSpringer New York :
_bImprint: Springer,
_c2012.
300 _aXV, 229 p. 46 illus., 35 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
505 0 _aPART I -- 1.Simulation Design for Policy Audiences: Informing Decision in the Face of Uncertainty -- 2.Using Simulation as a Scenario Builder for Decision Making – A Case Study Using the Nurse-Family Partnership Program in Louisiana -- 3.The Utility of Multilevel Modeling vs. Agent-Based Modeling in Examining Spatial Disparities in Diet and Health: The Case of Food Deserts -- PART II -- 4.Urban Renaissance or Invasion: Planning the Development of a Simulation Model of Gentrification -- 5.Simulating Life Cycle Costs for Nuclear Facilities -- 6.Simulating a Fraud Mechanism in Public Service Delivery -- 7. Exploring Assumptions through Possible Worlds: The Case of Homeownership -- PART III -- 8.Simulating the Multiple Impacts of Deferred Maintenance -- 9.Pandemic Influenza Simulation with Public Avoidance Behavior -- 10.Iterative Storytelling in Public Policy: A Systems Thinking Approach Hightower.  .
520 _aPublic policy and management problems have been described as poorly defined, messy, squishy, unstructured, intractable, and wicked. In a word, they are complex. This book illustrates the development and use of simulation models designed to capture some of the complexity inherent in the formulation, management, and implementation of policies aimed at addressing such problems. Simulation models have long existed at the fringes of policy inquiry but are not yet considered an essential component of the policy analyst’s toolkit. However, this situation is likely to change because with improvements in computational power and software, simulation is now easier to include in the standard repertoire of research tools available for discovery and decision support. This volume provides both a conceptual rationale for using simulations to inform public policy and a practical introduction to how such models might be constructed and employed. The focus of these papers is on the uses of simulation to gain understanding and inform policy decisions and action. Techniques represented in this volume include Monte Carlo simulation, system dynamics and agent based modeling.
650 0 _aSocial sciences.
650 0 _aStatistics.
650 1 4 _aSocial Sciences.
650 2 4 _aPolitical Science, general.
650 2 4 _aStatistics for Social Science, Behavorial Science, Education, Public Policy, and Law.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9781461416647
856 4 0 _uhttp://dx.doi.org/10.1007/978-1-4614-1665-4
912 _aZDB-2-SHU
999 _c101112
_d101112