The value of being precise

This study investigates how individuals assess imprecise information. We focus on two essential dimensions of decision under uncertainty, outcomes and probabilities, and their respective precision. We believe the precision of information is highly relevant in the investment setting, as reflected in the well-known “home (familiarity) bias”, and the outcome and probability dimensions, separately or jointly, may affect investors’ knowledge of uncertainty and perceived risk of the investment options, and subsequently affect investors’ choices. To test this conjecture, we conducted three experiments. Our results show that 1) participants demonstrate a pattern of preference for precision and aversion of extreme vagueness and associate vagueness with higher perceived risk and lower investment (experiments one and two); 2) participants prefer vague outcome information to vague probability information (experiment two); 3) familiarity indeed positively affects the precision of estimated values, but this association is stronger for the outcome dimension than for probabilities (experiment three). Our results confirm that precision in information, especially in the outcome dimension has an impact on investors’ resource allocation choices.     

互联网深化、信息不确定性与企业出口平稳性

互联网作为信息搜寻和传播的重要渠道,有利于缓解国际市场不确定性对企业出口决策的影响,从而有助于稳定企业出口预期,保障出口企业的持续生存。本文首先基于Fernandes 和 Tang(2014)的研究框架将互联网深化程度和出口集聚同时纳入到异质性贸易企业模型,在剥离出口集聚对企业出口行为影响的基础上,从理论视角揭示了互联网深化程度提高影响企业出口行为特别是出口持续生存的内在机理与方向。研究发现,不同于出口集聚会同时影响企业的需求冲击和成本冲击,互联网深化带来的信息溢出效应会通过贝叶斯法则(Bayesian Rule)使得企业修正其对国际市场不确定性的预期,提高其对目的国市场成本冲击的估计精度,从而在互联网深化程度较高的城市,企业进入出口市场的临界生产率较低,有利于其出口参与度和出口稳定性的提高。然而互联网深化程度提高不影响企业在目的国市场产品出口的集约边际。本文使用2000-2013 年中国工业企业数据库、中国海关数据库和中国城市统计年鉴数据库的匹配数据从企业-目的国-产品层面实证检验了本文的理论命题。研究表明,我国政府应充分发挥互联网发展降低信息不确定性的微观机制,以推动外贸的平稳增长。     

Quantifying uncertainty in the biospheric carbon flux for England and Wales

Summary.  A crucial issue in the current global warming debate is the effect of vegetation and soils on carbon dioxide (CO₂) concentrations in the atmosphere. Vegetation can extract CO₂ through photosynthesis, but respiration, decay of soil organic matter and disturbance effects such as fire return it to the atmosphere. The balance of these processes is the net carbon flux. To estimate the biospheric carbon flux for England and Wales, we address the statistical problem of inference for the sum of multiple outputs from a complex deterministic computer code whose input parameters are uncertain. The code is a process model which simulates the carbon dynamics of vegetation and soils, including the amount of carbon that is stored as a result of photosynthesis and the amount that is returned to the atmosphere through respiration. The aggregation of outputs corresponding to multiple sites and types of vegetation in a region gives an estimate of the total carbon flux for that region over a period of time. Expert prior opinions are elicited for marginal uncertainty about the relevant input parameters and for correlations of inputs between sites. A Gaussian process model is used to build emulators of the multiple code outputs and Bayesian uncertainty analysis is then used to propagate uncertainty in the input parameters through to uncertainty on the aggregated output. Numerical results are presented for England and Wales in the year 2000. It is estimated that vegetation and soils in England and Wales constituted a net sink of 7.55 Mt C (1 Mt C = 10¹² g of carbon) in 2000, with standard deviation 0.56 Mt C resulting from the sources of uncertainty that are considered.     

创新活动的思维机制

创新思维是具有实践性、整合性和开创性的思维 ,创新的思维发生主要表现在 :发现导致创新的问题 ,想象可能创新的空间 ,洞察推出创新的机遇 ,反馈动态创新的信息。创新思维是在不确定、不完全信息、博弈行为中展开的。创新思维要开发隐含知识和利用软件系统     

Uncertain lies: How payoff uncertainty affects dishonesty

In this paper we experimentally explore how lying changes when its consequences are not certain. We argue that, when consequences are not certain, lying is morally less costly because the action of lying does not mechanically result in the obtainment of the benefit and this produces a lower feeling of responsibility in case the benefit is obtained. Moreover, we argue that the smaller the impact of lying on the probability to obtain the benefit the lower is the feeling of responsibility. We test our predictions using a modified die-under-the-cup task where misreporting, rather than delivering a higher payoff, increases the likelihood to get a prize. Overall we have four treatments where the reported outcome affects the probability to get a prize to a different extent. Contrary to our prediction, we do not observe any treatment difference suggesting that lying is independent to the extent to which it increases the probability to get a benefit. This result suggests that the willingness to lie to secure a benefit and the willingness to lie to marginally increase the probability to obtain a benefit are very similar.     

Replication: Revisiting Tversky and Shafir’s (1992) Disjunction Effect with an extension comparing between and within subject designs

Does uncertainty about an outcome influence decisions? The sure-thing principle (Savage, 1954) posits that it should not, but Tversky and Shafir (1992) found that people regularly violate it in hypothetical gambling and vacation decisions, a phenomenon they termed “disjunction effect”. Very close replications and extensions of Tversky and Shafir (1992) were conducted in this paper (N = 890, MTurk). The target article demonstrated the effect using two paradigms in a between-subject design: here, an extension also testing a within-subject design, with design being randomly assigned was added. These results were consistent with the original findings for the “paying to know“ problem (original: Cramer’s V = 0.22, 95% (CI) [0.14, 0.32]; replication: Cramer’s V = 0.30, 95% CI [0.24, 0.37]), yet not for the “choice under risk” problem (original: Cramer’s V = 0.26, 95% CI [0.14, 0.39]; replication: Cramer’s V = 0.11, 95% CI [−0.07, 0.20]). The within-subject extension showed very similar results. Implications for the disjunction effect and judgment and decision-making theory are discussed, and a call for improvements on the statistical understanding of comparisons of between-subject and within-subject designs is introduced. All materials, data, and code are available on https://osf.io/gu58m/.     

Optimal Digital Rights Management with Uncertain Piracy

Many firms that sell digital copies of copyrighted materials online face a common dilemma: the use of digital rights management (DRM) to impede pirates can impose restrictions on legitimate use. We introduce a two‐period model in which the use of DRM in the first period affects the probability that a consumer finds a pirated copy in the second period; the threat of legal action reduces consumers’ consumption of pirated copies; and firms choose whether to sell, and at what prices, either strongly or weakly DRM‐protected products, or both. Furthermore, we incorporate the role of uncertainty concerning future levels of piracy. Using a two‐period model with uncertainty, we investigate a firm's optimal DRM strategies and present the optimal pricing strategy as well as product launch strategy under different market conditions. We find that one important characteristic of the optimal strategy is that it is optimal to maintain the same product line configuration strategy for both periods. We also characterize the conditions under which each strategy is optimal.     

Validation of Nonparametric Two-sample Bootstrap in ROC Analysis on Large Datasets

The nonparametric two-sample bootstrap is applied to computing uncertainties of measures in receiver operating characteristic (ROC) analysis on large datasets in areas such as biometrics, speaker recognition, etc. when the analytical method cannot be used. Its validation was studied by computing the standard errors of the area under ROC curve using the well-established analytical Mann–Whitney statistic method and also using the bootstrap. The analytical result is unique. The bootstrap results are expressed as a probability distribution due to its stochastic nature. The comparisons were carried out using relative errors and hypothesis testing. These match very well. This validation provides a sound foundation for such computations.     

An integrated approach for water resources decision making under interactive and compound uncertainties

In recent years, the issue of water allocation among competing users has been of great concern for many countries due to increasing water demand from population growth and economic development. In water management systems, the inherent uncertainties and their potential interactions pose a significant challenge for water managers to identify optimal water-allocation schemes in a complex and uncertain environment. This paper thus proposes a methodology that incorporates optimization techniques and statistical experimental designs within a general framework to address the issues of uncertainty and risk as well as their correlations in a systematic manner. A water resources management problem is used to demonstrate the applicability of the proposed methodology. The results indicate that interval solutions can be generated for the objective function and decision variables, and a number of decision alternatives can be obtained under different policy scenarios. The solutions with different risk levels of constraint violation can help quantify the relationship between the economic objective and the system risk, which is meaningful for supporting risk management. The experimental data obtained from the Taguchi's orthogonal array design are useful for identifying the significant factors affecting the means of total net benefits. Then the findings from the mixed-level factorial experiment can help reveal the latent interactions between those significant factors at different levels and their effects on the modeling response.