Uncertain information structures and backward induction

In everyday economic interactions, it is not clear whether each agent’s sequential choices are visible to other participants or not: agents might be deluded about others’ ability to acquire, interpret or keep track of data. Following this idea, this paper introduces uncertainty about players’ ability to observe each others’ past choices in extensive-form games. In this context, we show that monitoring opponents’ choices does not affect the outcome of the interaction when every player expects their opponents indeed to be monitoring. Specifically, we prove that if players are rational and there is common strong belief in opponents being rational, having perfect information and believing in their own perfect information, then, the backward induction outcome is obtained regardless of which of her opponents’ choices each player observes. The paper examines the constraints on the rationalization process under which reasoning according to Battigalli’s (1996) best rationalization principle yields the same outcome irrespective of whether players observe their opponents’ choices or not. To this respect we find that the obtention of the backward induction outcome crucially depends on tight higher-order restrictions on beliefs about opponents’ perfect information. The analysis provides a new framework for the study of uncertainty about information structures and generalizes the work by Battigalli and Siniscalchi (2002) in this direction.     

Exploring the capability to reason backwards: An experimental study with children,adolescents, and young adults

This is the first study investigating the development of the capability to reason backwards in children, adolescents, and young adults aged 6 to 23 under controlled laboratory conditions. The experimental design employs a modified version of the race game. As in the original game, subjects need to apply backward analysis in order to solve the games. We find that subjects’ capability to reason backwards improves with age, but that this process systematically differs across genders. Our repetition of the games indicates that differences exist also in learning between age groups and across genders.     

Backward simulation methods for pricing American options under the CIR process

In this paper, we focus on backward simulation of the CIR process. The purpose is to solve the memory requirement issue of the Least Squares Monte Carlo method when pricing American options by simulation. The concept of backward simulation is presented and it is classified into two types. Under the framework of the second type backward simulation, we seek the solutions for the existing CIR schemes. Specifically, we propose forward–backward simulation approaches for Alfonsi’s two implicit schemes, the fixed Euler schemes and the exact scheme. The proposed schemes are numerically tested and compared in pricing American options under the Heston model and the stochastic interest rate model. Some numerical properties such as the convergence order of the explicit–implicit Euler schemes, the storage requirement estimation of the forward–backward exact scheme and its computing time comparison with the squared Bessel bridge are also tested. Finally, the pros and cons of the related backward simulation schemes are summarized.     

Belief in the opponentsʼ future rationality

For dynamic games we consider the idea that a player, at every stage of the game, will always believe that his opponents will choose rationally in the future. This is the basis for the concept of common belief in future rationality, which we formalize within an epistemic model. We present an iterative procedure, backward dominance, that proceeds by eliminating strategies from the game, based on strict dominance arguments. We show that the backward dominance procedure selects precisely those strategies that can rationally be chosen under common belief in future rationality if we would not impose (common belief in) Bayesian updating.     

Solving the incomplete markets model with aggregate uncertainty by backward induction

This paper describes a method to solve models with a continuum of agents, incomplete markets and aggregate uncertainty. I use backward induction on a finite grid of points in the aggregate state space. The aggregate state includes a small number of statistics (moments) of the cross-sectional distribution of capital. For any given set of moments, agents use a specific cross-sectional distribution, called “proxy distribution”, to compute the equilibrium. Information from the steady state distribution as well as from simulations can be used to chose a suitable proxy distribution.     

Do people plan?

We report the results of an experimental investigation of a key axiom of economic theories of dynamic decision making—namely, that agents plan. Inferences from previous investigations have been confounded with issues concerning the preference functionals of the agents. Here, we present an innovative experimental design which is driven purely by dominance: if preferences satisfy dominance, we can infer whether subjects are planning or not. We implement three sets of experiments: the first two (the Individual Treatments) in which the same player takes decisions both in the present and the future; and the third (the Pairs Treatment) in which different players take decisions at different times. The two Individual treatments differed in that, in one, the subjects played sequentially, while, in the other, the subjects had to pre-commit to their future move. In all contexts, according to economic theory, the players in the present should anticipate the decision of the player in the future. We find that over half the participants in all three experimental treatments do not appear to be planning ahead; moreover, their ability to plan ahead does not improve with experience, except possibly when we force subjects to pre-commit to their future decision. These findings identify an important lacuna in economic theories, both for individual behaviour and for behaviour in games.

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Electronic Supplementary Material  The online version of this article () contains supplementary material, which is available to authorized users.      

The impact of forecasting on companies’ performance: Analysis in a multivariate setting

Over the years, practitioners and researchers have devoted their attention to forecasting techniques and methods that can be adopted to improve companies’ performance. However, forecasting techniques alone are not enough since companies should also consider several other issues associated with forecasting process management, e.g. how companies collect and use information on the market, or how the forecast is used in different decision-making processes. It is also important to understand the existence of interaction effects between these different forecasting variables, as they could determine a positive additional synergistic effect on companies’ performance. This paper aims to investigate what relevant forecasting variables should be considered to improve companies’ performance, and whether some forecasting variables can interact and influence performance with a synergistic effect. Analyses are conducted by means of data collected by the Global Manufacturing Research Group (GMRG). Data from a sample of 343 manufacturing companies in 6 different countries demonstrate that when companies intend to improve cost and delivery performances, they should devote their attention to all the different forecasting variables. In addition, the results found reveal the existence of positive interaction effects between the collection and use of information on the market and the other forecasting variables, as well as the existence of a negative interaction effect between the adoption of forecasting techniques and the use of forecasts in several decision-making processes. These results have important implications for managers as they provide guidance on how to lever on the different forecasting variables to maximize companies’ performance.     

中国房地产业关联度高、带动力强吗——兼论房地产业的定位

在辨析房地产和房地产业的基础上,本文运用1997、2000、2002、2005、2007年的投入产出表,计算房地产业的影响力系数和感应度系数,发现房地产业的影响力系数远低于平均水平,且该系数从2000年起逐次降低,说明房地产业的带动作用较弱且这种带动作用呈现不断下降的态势;房地产业的感应度系数也远低于各行业平均水平,意味着房地产业对国民经济的推动作用比较小,难以通过房地产业有效推动整体国民经济的增长。因此,所谓"房地产业关联度高,带动力强"的说法没有依据;与其他产业相比,房地产业的带动和推动作用是逐渐降低的。这些发现的政策意义是,国民经济的各个产业都是重要产业,政府不必先入为主地认定房地产业在过去、现在或将来肯定是关联度高、带动力强的产业,也不必为此而出台倾斜性的培育政策以促进该产业成为所谓的支柱产业。     

基金收益率排名与计算的比较研究

目前各种财经媒体推出的基金收益率排名存在较大差异,向前复权或向后复权均不能反映基金的实际收益情况。基于定点复权的思想,本文提出新的实际收益率计算方法,重点关注分红对基金收益的影响,并构建分析模板分别对开放式基金和封闭式基金进行研究。针对封闭式基金实际收益率构建的三因子模型,发现封基的实际收益率除了和其自身盈利能力有关之外,对折价率变动、分红再投资收益等因素更加敏感。     

Use of forward versus backward reasoning during audit analytical procedures: evidence from a computerised-process-tracing field study

Audit judgement research has widely assumed that auditors rely primarily on backward reasoning during analytical procedures but the relative use of forward reasoning has not been directly examined. The present study explains how auditors use backward and forward reasoning during analytical procedures, discusses evidence from other research suggesting that forward reasoning could be more prevalent, and examines the relative use of forward reasoning during analytical procedures with data from a computerised process‐tracing field study. Results suggest that auditors rely extensively on forward reasoning when using analytical procedures. Findings motivate future research that examines when forward and backward reasoning are most effective.