Policy Analysis: A Checklist of Concerns

In September 1978 Howard Raiffa gave a talk to the Young Scientists Summer Program at the International Institute for Applied Systems Analysis that was recorded. Since it contains much sage advice for systems analysts, we have obtained his permission to reproduce it as a IIASA Professional Paper so that it will be available to a wider audience

Conflicting Objectives in Decisions

This book deals with quantitative approaches in making decisions when conflicting objectives are present. This problem is central to many applications of decision analysis, policy analysis, operational research, etc. in a wide range of fields, for example, business, economics, engineering, psychology, and planning. The book surveys different approaches to the same problem area and each approach is discussed in considerable detail so that the coverage of the book is both broad and deep. The problem of conflicting objectives is of paramount importance, both in planned and market economies, and this book represents a cross-cultural mixture of approaches from many countries to the same class of problem

Long-Range Policy Options for IIASA

Later this month the Council of IIASA will meet to consider many issues of which the most critical will be resolution of the long-term strategy for the Institute. Determination of the optimal strategy will depend upon our judgement of many factors -- the appropriate nature of our scientific program, our constraints of money and of space, the opportunities for IIASA in the world of the late 1970's. These are inherently interrelated: the research we will be able to perform will depend upon available resources, while more resources will be forthcoming for the scientific program of greater promise. This document shall present briefly these issues, the policy choices arising from them, and my personal thoughts about our options

Estimating the Expected Value of Partial Perfect Information in Health Economic Evaluations using Integrated Nested Laplace Approximation

The Expected Value of Perfect Partial Information (EVPPI) is a decision-theoretic measure of the "cost" of parametric uncertainty in decision making used principally in health economic decision making. Despite this decision-theoretic grounding, the uptake of EVPPI calculations in practice has been slow. This is in part due to the prohibitive computational time required to estimate the EVPPI via Monte Carlo simulations. However, recent developments have demonstrated that the EVPPI can be estimated by non-parametric regression methods, which have significantly decreased the computation time required to approximate the EVPPI. Under certain circumstances, high-dimensional Gaussian Process regression is suggested, but this can still be prohibitively expensive. Applying fast computation methods developed in spatial statistics using Integrated Nested Laplace Approximations (INLA) and projecting from a high-dimensional into a low-dimensional input space allows us to decrease the computation time for fitting these high-dimensional Gaussian Processes, often substantially. We demonstrate that the EVPPI calculated using our method for Gaussian Process regression is in line with the standard Gaussian Process regression method and that despite the apparent methodological complexity of this new method, R functions are available in the package BCEA to implement it simply and efficiently

Decision Analysis with Multiple Conflicting Objectives, Preferences and Value Tradeoffs

This working paper is the manuscript for a book titled "Decision Analysis with Multiple Conflicting Objectives: Preferences and Value Tradeoffs" being published by John Wiley and Sons, New York. It is being distributed now in very limited number prior to formal publication both (1) to facilitate the use of these results within the IIASA projects, and (2) to elicit comments on their content. The work reported here began over five years ago when Ralph L. Keeney was affiliated with the Massachusetts Institute of Technology and Howard Raiffa was at Harvard University. The finalization of this work has taken place at IIASA where our interactions with various members of the applied projects has helped to make the presentation more useful to potential practitioners. Efforts are now beginning to utilize the theories and procedures outlined in this book on the problems being addressed by the applied projects of IIASA. We plan to report on these developments in the various IIASA publications in the near future

But Is It Myopia? Risk Aversion and the Efficiency of Stock-Based Managerial Incentives

This paper points out that stock incentives do not lead to myopia unless they result in more emphasis on the short-term than would occur under an optimal contract. It shows that myopia findings relative to the standard used throughout the literature (first-best efficiency) are often reversed when evaluated relative to the relevant standard of optimal contracting. Results reported by the previous literature to be myopia often in fact have excessive emphasis on the long-term. The paper solves in closed-form for the region in parameter space which gives rise to these reversals and shows that it can be arbitrarily largehttp://deepblue.lib.umich.edu/bitstream/2027.42/49369/5/2008Jan16JCarmel.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/49369/1/Visiting-Carmel.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/49369/4/Visiting-Carmel.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/49369/7/1108_2008Jan16JCarmel.pd

General rules for environmental management to prioritise social ecological systems research based on a value of information approach

This is the final version. Available on open access from Wiley via the DOI in this record1. Globally, billions of dollars are invested each year to help understand the dynamics of social ecological systems (SES) in bettering both social and environmental outcomes. However, there is no scientific consensus on which aspect of an SES is most important and urgent to understand; particularly given the realities of limited time and money. 2. Here we use a simulation‐based “value of information” approach to examine where research will deliver the most important information for environmental management in four SESs representing a range of real‐life environmental issues. 3. We find that neither social nor ecological information is consistently the most important: instead, researchers should focus on understanding the primary effects of their management actions. 4. Thus, when managers are undertaking social actions the highest research priority should be understanding the dynamics of social groups. Alternatively, when manipulating ecological systems it will be most important to quantify ecological population dynamics. 5. Synthesis and applications. Our results provide a standard assessment to determine the uncertain social ecological systems (SES) component with the highest expected impact for management outcomes. First, managers should determine the structure of their SES by identifying social and ecological nodes. Second, managers should identify the qualitative nature of the network, by determining which nodes are linked, but not the strength of those interactions. Finally, managers should identify the actions available to them to intervene in the SES. From these steps, managers will be able to identify the SES components that are closest to the management action(s), and it is these nodes and interactions that should receivepriority research attention to achieve effective environmental decision making.Centre of Excellence for Environmental Decisions, Australian Research Counc

Herbert Simon's decision-making approach: Investigation of cognitive processes in experts

This is a post print version of the article. The official published can be obtained from the links below - PsycINFO Database Record (c) 2010 APA, all rights reserved.Herbert Simon's research endeavor aimed to understand the processes that participate in human decision making. However, despite his effort to investigate this question, his work did not have the impact in the “decision making” community that it had in other fields. His rejection of the assumption of perfect rationality, made in mainstream economics, led him to develop the concept of bounded rationality. Simon's approach also emphasized the limitations of the cognitive system, the change of processes due to expertise, and the direct empirical study of cognitive processes involved in decision making. In this article, we argue that his subsequent research program in problem solving and expertise offered critical tools for studying decision-making processes that took into account his original notion of bounded rationality. Unfortunately, these tools were ignored by the main research paradigms in decision making, such as Tversky and Kahneman's biased rationality approach (also known as the heuristics and biases approach) and the ecological approach advanced by Gigerenzer and others. We make a proposal of how to integrate Simon's approach with the main current approaches to decision making. We argue that this would lead to better models of decision making that are more generalizable, have higher ecological validity, include specification of cognitive processes, and provide a better understanding of the interaction between the characteristics of the cognitive system and the contingencies of the environment