Modelling the participation decision and duration of sporting activity in Scotland

Motivating individuals to actively engage in physical activity due to its beneficial health effects has been an integral part of Scotland's health policy agenda. The current Scottish guidelines recommend individuals participate in physical activity of moderate vigour for 30 min at least five times per week. For an individual contemplating the recommendation, decisions have to be made in regard of participation, intensity, duration and multiplicity. For the policy maker, understanding the determinants of each decision will assist in designing an intervention to effect the recommended policy. With secondary data sourced from the 2003 Scottish Health Survey (SHeS) we statistically model the combined decisions process, employing a copula approach to model specification. In taking this approach the model flexibly accounts for any statistical associations that may exist between the component decisions. Thus, we model the endogenous relationship between the decision of individuals to participate in sporting activities and, amongst those who participate, the duration of time spent undertaking their chosen activities. The main focus is to establish whether dependence exists between the two random variables assuming the vigour with which sporting activity is performed to be independent of the participation and duration decision. We allow for a variety of controls including demographic factors such as age and gender, economic factors such as income and educational attainment, lifestyle factors such as smoking, alcohol consumption, healthy eating and medical history. We use the model to compare the effect of interventions designed to increase the vigour with which individuals undertake their sport, relating it to obesity as a health outcome.     

REGIONAL INFORMATION DESIGN FOR PUBLIC DECISIONS*

Regional information designs are tools for decision makers at subnational levels; their principal purpose is to improve the dialogue between the decision maker and the analyst as a means of improving the quality of policy decisions. This paper first examines key characteristics of regional accounts and regional information systems of relevance primarily at the state or province level. Then the nature and scope of regional decisions are reviewed with a view of delineating the problems encountered in developing systematic regional information to help make those decisions. Both policy and program decisions are considered in terms of scanning the horizon for potential opportunities and problems and of identifying preferred solutions to the problems. Finally, one regional information design is sketched out which classifies in an orderly fashion the environmental and program information useful in regional decision making.     

Emotional Temperature,Probabilistic Choice and the Optimal Power of Incentives*

From the time of Plato it has been assumed that emotions cloud rational thinking. Fully rational individuals were supposed to be completely free of emotions. Modern psychological research challenged this paradigm. One of the insights of this research is that though emotions indeed interfere with the ability to evaluate the objective consequences of choices, they also allow the decision maker to feel the difference in utility arising from those choices. In this article, I formalise this intuition by introducing the concept of emotional temperature. I show that there exists a positive optimal emotional temperature, which leads to an irreducible probability of suboptimal choice. I apply the model to characterise the optimal contracts under moral hazard, assuming that the emotional temperature of the decision maker increases when the contract provides more powerful incentives. A more general point the article makes is that a mechanism designer needs to be aware that the mechanism will not only affect incentives but also the degree of rationality of the agents.     

Recursive robust estimation and control without commitment

In a Markov decision problem with hidden state variables, a posterior distribution serves as a state variable and Bayes’ law under an approximating model gives its law of motion. A decision maker expresses fear that his model is misspecified by surrounding it with a set of alternatives that are nearby when measured by their expected log likelihood ratios (entropies). Martingales represent alternative models. A decision maker constructs a sequence of robust decision rules by pretending that a sequence of minimizing players choose increments to martingales and distortions to the prior over the hidden state. A risk sensitivity operator induces robustness to perturbations of the approximating model conditioned on the hidden state. Another risk sensitivity operator induces robustness to the prior distribution over the hidden state. We use these operators to extend the approach of Hansen and Sargent [Discounted linear exponential quadratic Gaussian control, IEEE Trans. Automat. Control 40(5) (1995) 968-971] to problems that contain hidden states.     

New product launch: herd seeking or herd preventing?

A decision maker offers a new product to a number of potential adopers. He does not know the value of the product, but adopers receive some private information about it. We study how the decision maker may influence learning among adopers by manipulaing the launch sequence when both the decision maker and adopers can learn about the value of the product from previous adoption decisions. The conditions under which the decision maker prefers a sequential launch to a simultaneous launch depend on adopers?? prior beliefs about the value of the product and adoption costs. We derive the decision maker??s optimal launch sequence and study how it endogenizes informational herding.     

PARTISAN ADVOCATES

This paper studies the problem of an uninformed decision maker who acquires expert advice prior to making a decision. I show that it is less costly to hire partisan agents than impartial agents, especially under advocacy, and that the decision maker prefers partisan advocacy to other forms of institutions. I also extend the literature, originating with Dewatripont and Tirole ( 1999 ), to a setting with contracts that condition on information provided and not just the decision made.     

The value of a stochastic information structure

Upon observing a signal, a Bayesian decision maker updates her probability distribution over the state space, chooses an action, and receives a payoff that depends on the state and the action taken. An information structure determines the set of possible signals and the probability of each signal given a state. For a fixed decision problem, the value of an information structure is the maximal expected utility that the decision maker can get when the observed signals are governed by this structure. Thus, every decision problem induces a preference order over information structures according to their value. We characterize preference orders that can be obtained in this way. We also characterize the functions defined over information structures that measure their value.     

Subjective random discounting and intertemporal choice

This paper provides an axiomatic foundation for a particular type of preference shock model called the random discounting representation where a decision maker believes that her discount factors change randomly over time. For this purpose, we formulate an infinite horizon extension of [E. Dekel, B. Lipman, A. Rustichini, Representing preferences with a unique subjective state space, Econometrica 69 (2001) 891-934], and identify the behavior that reduces all subjective uncertainties to those about future discount factors. We also show uniqueness of subjective belief about discount factors. Moreover, a behavioral comparison about preference for flexibility characterizes the condition that one's subjective belief second-order stochastically dominates the other. Finally, the resulting model is applied to a consumption-savings problem.     

Minimax regret with imperfect ex-post knowledge of the state

We consider decision problems under complete ignorance and extend the minimax regret principle to situations where, after taking an action, the decision maker does not necessarily learn the state of the world. For example, if the decision maker only learns what the outcome is, then all she knows is that the actual state is one of the (possibly several) states that yield the observed outcome under the chosen action. We refer to this situation as imperfect ex-post information. We show that, given a choice between more information and less information, the decision maker prefers the latter. We also extend the framework to encompass the possibility of less than the extreme degree of pessimism that characterizes the minimax regret criterion.     

Confidence and decision

Many real-life decisions have to be taken on the basis of probability judgements of which the decision maker is not entirely sure. This paper develops a decision rule for taking such decisions, which incorporates the decision makerʼs confidence in his probability judgements according to the following maxim: the larger the stakes involved in a decision, the more confidence is required in a probability judgement for it to play a role in the decision. A formal representation of the decision makerʼs confidence is proposed and used to formulate a family of decision models conforming to this maxim. A natural member of this family is studied in detail. It is structurally simpler than other recent models of decision under uncertainty, which may make it easier to apply to practical decisions, whilst being axiomatically sound, permitting the separation of beliefs and tastes, and allowing comparative statics analysis of attitudes to choosing in the absence of confidence.     

Real and financial effects of insider trading with correlated signals

Summary. In this paper we study the real and financial effects of insider trading in a Static, Kyle-type model. In our model the insider is also the manager of the firm. Hence the insider chooses both the amount of the real output to be produced and the amount of the stock of the firm to trade. The aim of the paper is to study the relationship between financial decisions and real decisions. In particular, we examine how insider trading on the stock market affects the real output and price and how the real decision making affects the financial variables, such as the extent of insider trading, stock prices, and the stock pricing rule of the market maker. In the model, the market maker observes two correlated signals: the total order flow and the market price of the real good. We study the informativeness of the stock price and the effects on insider's profits. We also construct a compensation scheme that aligns the interests of the insider and the firm. Finally, we generalize the pricing rule set up by a competitive market maker and analyze the comparative statics of the model. Received: October 3, 1999: revised version: December 1, 1999     

Subjective probability over a subjective decision tree

A state space has been assumed as a primitive for modeling uncertainty, which presumes that the analyst knows all the uncertainties a decision maker (DM) perceives. This is problematic because states are private information of the DM, and hence are not directly observable to the analyst. Dekel et al. [Representing preferences with a unique subjective state space, Econometrica 69 (2001) 891-934] derive, rather than assume, the subjective state space from preference over suitable choice objects.In a dynamic setting, a decision tree, that is, a pair consisting of a state space and a filtration, has been taken as a primitive. This assumption is also problematic—a decision tree should be derived rather than assumed as a primitive. We formulate a three-stage extension of the above literature in order to model a DM who anticipates subjective uncertainty to be resolved gradually over time. We identify also subjective beliefs on the subjective state space.     

Aggregation of expert opinions

Conflicts of interest arise between a decision maker and agents who have information pertinent to the problem because of differences in their preferences over outcomes. We investigate how the decision maker can extract the information by distorting the decisions that will be taken. We show that only slight distortions will be necessary when agents' signals are sufficiently accurate or when the number of informed agents becomes large. We argue that the particular mechanisms analyzed are substantially less demanding informationally than those typically employed in implementation and virtual implementation. Further, the mechanisms are immune to manipulation by small groups of agents.     

On the Composition of Committees

This article is concerned with the role of committees in collectivedecision making processes in a world where agents must be motivatedto collect information. Committees improve the quality of decisionmaking by providing information and by coordinating the collectionof information. We address two types of questions. First, howdoes the composition of a committee affect final decisions?Second, what is the optimal composition of a committee fromthe decision maker's point of view? As to the latter question,we show that the cost of information collection plays an importantrole. If this cost is low, then the preferences of the committeemembers should be aligned to those of the decision maker. Memberswith similar preferences as the decision maker collect the properpieces of information. Moreover, manipulation of informationdoes not occur if the preferences of the decision maker andthe members are consonant. If the cost of searching is high,then the committee should be composed of members with polarizedpreferences. Outliers have a strong incentive to search forinformation.     

Financial Decision Making and Cognition in a Family Context

In this paper, we studied the association of cognitive traits and in particular numeracy of both spouses on financial outcomes of the family. We found significant effects, particularly for numeracy for financial and non-financial respondents alike, but much larger effects for the financial decision maker in the family. We also examined who makes these financial decisions in the family and why. Once again, cognitive traits such as numeracy were an important component of that decision with larger effects of numeracy for husbands compared to wives.     

Monetary policy committees and interest rate setting

This paper shows that it is preferable for monetary policy to be conducted by a committee instead of a single policy maker if there is uncertainty about potential output. We examine three decision procedures - an optimal procedure, averaging and voting - and find that the latter is the appropriate way to reach decisions if policy makers are not equally skilled. Finally, we demonstrate that efficient decision procedures reduce the persistence of shocks.     

Inter-temporal choices with temporal reference dependence

I develop an intertemporal choice model for rational deviators whose preferences depend not only on their actual consumption but also on comparison to their beliefs about the optimal consumption. The standard decision maker is loss averse with respect to this belief-dependent reference point. When psychologically weighted loss aversion is low, a decision maker deviates from the standard intertemporal choice behavior and over-consumption, as well as the alternative possibility of under-consumption can be rationalized. When the decision maker has time-varying degrees of loss aversion, he re-optimizes the consumption plan through adjusted beliefs as subsequent selves realize that past decision for the present period is no longer optimal. In the dynamic model, I solve for consistent intertemporal optimization rules by which a dynamic deviator should meet rational intertemporal consistency at each point in time. Finally, I demonstrate that the dynamic reference dependent model can solve a puzzling feature in lifecycle consumption data.     

Multiple Criteria Decision Making: A Case Study of the Columbia River Salmon Recovery Plan

A common problem faced by decision makers is choosing the best alternative from among many. Traditionally, such decisions in the public arena were made using benefit-cost analysis, which involves the conversion of all costs and benefits associated with a project into monetary terms. But public projects often have a variety of economic, ecological, social and political objectives, many of which cannot or perhaps should not be converted to monetary terms. In such projects decisions must be made based on multiple, even conflicting objectives. Multiple criteria decision making (MCDM) methods are widely used for such decisions. However, a common disadvantage among many such methods available in the literature is that they require input from a real decision maker. This paper presents the development and application of an expert system based on fuzzy set theory and IF-THEN rules. The system mimics a real decision maker. Along with two conventional MCDM methods the developed expert system was applied on a data set from the Columbia River Basin salmon recovery plan to assess its potential usefulness as a decision-making tool for natural resource projects. The results suggest that the fuzzy expert system is easy to develop and makes better decisions than the other two conventional MCDM methods used.     

Contributing for Myself,but Free riding for My Group?

Many real‐world decisions are made by individuals as representatives of groups. Most research, however, studies either individuals or groups as decision‐makers. This paper explores whether there is a general difference between a decision made as an individual and as a representative of a group in the context of a public good game. We conducted a series of experiments to test this question and to understand mechanisms contributing to potential differences. We found that representatives contributed less than individuals when they could not communicate with their constituency. However, when they could discuss their strategy before playing, they contributed at least as much as individual decision‐makers. Furthermore, when they could justify their decision after playing, they contributed even more than individual decision‐makers. We discuss potential reasons for this and directions for future research.     

Robust estimation and control under commitment

In a Markov decision problem with hidden state variables, a decision maker expresses fear that his model is misspecified by surrounding it with a set of alternatives that are nearby as measured by their expected log likelihood ratios (entropies). Sets of martingales represent alternative models. Within a two-player zero-sum game under commitment, a minimizing player chooses a martingale at time 0. Probability distributions that solve distorted filtering problems serve as state variables, much like the posterior in problems without concerns about misspecification. We state conditions under which an equilibrium of the zero-sum game with commitment has a recursive representation that can be cast in terms of two risk-sensitivity operators. We apply our results to a linear quadratic example that makes contact with findings of T. Ba?ar and P. Bernhard [H^∞-Optimal Control and Related Minimax Design Problems, second ed., Birkhauser, Basel, 1995] and P. Whittle [Risk-sensitive Optimal Control, Wiley, New York, 1990].