Entrepreneurial decision-making using the knightian uncertainty approach

The article discusses the behavioral aspects that affect the entrepreneurs' decision making under the Knightian uncertainty approach. Since the profit arising from entrepreneurial activity represents the reward of an immeasurable and subjective risk, it has been hypothesized that innovative entrepreneurs have excessive optimism and confidence, which leads them to invest in high-risk activities. A behavioral model of decision making under uncertainty is used to test the hypothesis of overconfidence. This model is based on Bayesian inference, which allows us to model the assumption that these entrepreneurs are overconfident. We conclude that, under the hypothesis of overconfidence, these entrepreneurs decide to invest, despite the fact that the expected utility model indicates the contrary. This theoretical finding could explain why there are a large number of business failures in the first years of activity.

A Tool for optimum design of Waste Water Treatment Plants under uncertainty

L’objectiu principal és presentar un nou prototipus d’eina per al disseny de les plantes de tractament d’aigües residuals utilitzant models mecànics dinàmics quantificant la incertesa

Traiter l'hypertension artérielle: l'incertitude des définitions et des cibles [Managing hypertension: the uncertainty of definitions and targets].

In clinical practice, physicians are confronted with a multitude of definitions and treatment goals for arterial hypertension, depending of the diagnostic method used (e.g. office, home and ambulatory blood pressure measurement) and the underlying disease. The historical background and evidence of these different blood pressure thresholds are discussed in this article, as well as some recent treatment guidelines. Besides, the debate of the "J curve", namely the possible risks associated with an excessive blood pressure reduction, is discussed.

Fault diagnosis by refining the parameter uncertainty space of nonlinear dynamic systems

This paper deals with fault detection and isolation problems for nonlinear dynamic systems. Both problems are stated as constraint satisfaction problems (CSP) and solved using consistency techniques. The main contribution is the isolation method based on consistency techniques and uncertainty space refining of interval parameters. The major advantage of this method is that the isolation speed is fast even taking into account uncertainty in parameters, measurements, and model errors. Interval calculations bring independence from the assumption of monotony considered by several approaches for fault isolation which are based on observers. An application to a well known alcoholic fermentation process model is presented

Robust fault detection using consistency techniques for uncertainty handling

Often practical performance of analytical redundancy for fault detection and diagnosis is decreased by uncertainties prevailing not only in the system model, but also in the measurements. In this paper, the problem of fault detection is stated as a constraint satisfaction problem over continuous domains with a big number of variables and constraints. This problem can be solved using modal interval analysis and consistency techniques. Consistency techniques are then shown to be particularly efficient to check the consistency of the analytical redundancy relations (ARRs), dealing with uncertain measurements and parameters. Through the work presented in this paper, it can be observed that consistency techniques can be used to increase the performance of a robust fault detection tool, which is based on interval arithmetic. The proposed method is illustrated using a nonlinear dynamic model of a hydraulic system

BME-based uncertainty assessment of the Chernobyl fallout

The vast territories that have been radioactively contaminated during the 1986 Chernobyl accident provide a substantial data set of radioactive monitoring data, which can be used for the verification and testing of the different spatial estimation (prediction) methods involved in risk assessment studies. Using the Chernobyl data set for such a purpose is motivated by its heterogeneous spatial structure (the data are characterized by large-scale correlations, short-scale variability, spotty features, etc.). The present work is concerned with the application of the Bayesian Maximum Entropy (BME) method to estimate the extent and the magnitude of the radioactive soil contamination by 137Cs due to the Chernobyl fallout. The powerful BME method allows rigorous incorporation of a wide variety of knowledge bases into the spatial estimation procedure leading to informative contamination maps. Exact measurements (?hard? data) are combined with secondary information on local uncertainties (treated as ?soft? data) to generate science-based uncertainty assessment of soil contamination estimates at unsampled locations. BME describes uncertainty in terms of the posterior probability distributions generated across space, whereas no assumption about the underlying distribution is made and non-linear estimators are automatically incorporated. Traditional estimation variances based on the assumption of an underlying Gaussian distribution (analogous, e.g., to the kriging variance) can be derived as a special case of the BME uncertainty analysis. The BME estimates obtained using hard and soft data are compared with the BME estimates obtained using only hard data. The comparison involves both the accuracy of the estimation maps using the exact data and the assessment of the associated uncertainty using repeated measurements. Furthermore, a comparison of the spatial estimation accuracy obtained by the two methods was carried out using a validation data set of hard data. Finally, a separate uncertainty analysis was conducted that evaluated the ability of the posterior probabilities to reproduce the distribution of the raw repeated measurements available in certain populated sites. The analysis provides an illustration of the improvement in mapping accuracy obtained by adding soft data to the existing hard data and, in general, demonstrates that the BME method performs well both in terms of estimation accuracy as well as in terms estimation error assessment, which are both useful features for the Chernobyl fallout study.

The role of role uncertainty in modified dictator games

We compare behavior in modified dictator games with and without role uncertainty. Subjectschoose between a selfish action, a costly surplus creating action (altruistic behavior) and acostly surplus destroying action (spiteful behavior). While costly surplus creating actions are themost frequent under role uncertainty (64%), selfish actions become the most frequent withoutrole uncertainty (69%). Also, the frequency of surplus destroying choices is negligible with roleuncertainty (1%) but not so without it (11%). A classification of subjects into four differenttypes of interdependent preferences (Selfish, Social Welfare maximizing, Inequity Averse andCompetitive) shows that the use of role uncertainty overestimates the prevalence of SocialWelfare maximizing preferences in the subject population (from 74% with role uncertainty to21% without it) and underestimates Selfish and Inequity Averse preferences. An additionaltreatment, in which subjects undertake an understanding test before participating in theexperiment with role uncertainty, shows that the vast majority of subjects (93%) correctlyunderstand the payoff mechanism with role uncertainty, but yet surplus creating actions weremost frequent. Our results warn against the use of role uncertainty in experiments that aim tomeasure the prevalence of interdependent preferences.

The effects of employment uncertainty and wealth shocks on the labor supply and claiming behavior of older American workers

Unemployment rates in developed countries have recently reached levels not seenin a generation, and workers of all ages are facing increasing probabilities of losingtheir jobs and considerable losses in accumulated assets. These events likely increasethe reliance that most older workers will have on public social insurance programs,exactly at a time that public finances are suffering from a large drop in contributions.Our paper explicitly accounts for employment uncertainty and unexpectedwealth shocks, something that has been relatively overlooked in the literature, butthat has grown in importance in recent years. Using administrative and householdlevel data we empirically characterize a life-cycle model of retirement and claimingdecisions in terms of the employment, wage, health, and mortality uncertainty facedby individuals. Our benchmark model explains with great accuracy the strikinglyhigh proportion of individuals who claim benefits exactly at the Early RetirementAge, while still explaining the increased claiming hazard at the Normal RetirementAge. We also discuss some policy experiments and their interplay with employmentuncertainty. Additionally, we analyze the effects of negative wealth shocks on thelabor supply and claiming decisions of older Americans. Our results can explainwhy early claiming has remained very high in the last years even as the early retirementpenalties have increased substantially compared with previous periods, andwhy labor force participation has remained quite high for older workers even in themidst of the worse employment crisis in decades.

Measuring strategic uncertainty in coordination games

This paper explores three aspects of strategic uncertainty: its relation to risk, predictability of behavior and subjective beliefs of players. In a laboratory experiment we measure subjects certainty equivalents for three coordination games and one lottery. Behavior in coordination games is related to risk aversion, experience seeking, and age.From the distribution of certainty equivalents we estimate probabilities for successful coordination in a wide range of games. For many games, success of coordination is predictable with a reasonable error rate. The best response to observed behavior is close to the global-game solution. Comparing choices in coordination games with revealed risk aversion, we estimate subjective probabilities for successful coordination. In games with a low coordination requirement, most subjects underestimate the probability of success. In games with a high coordination requirement, most subjects overestimate this probability. Estimating probabilistic decision models, we show that the quality of predictions can be improved when individual characteristics are taken into account. Subjects behavior is consistent with probabilistic beliefs about the aggregate outcome, but inconsistent with probabilistic beliefs about individual behavior.

The effects of uncertainty avoidance on brand performance: Marketing creativity, product innovation and the brand duration

This paper investigates the link between brand performance and cultural primes in high-risk,innovation-based sectors. In theory section, we propose that the level of cultural uncertaintyavoidance embedded in a firm determine its marketing creativity by increasing the complexityand the broadness of a brand. It determines also the rate of firm product innovations.Marketing creativity and product innovation influence finally the firm marketingperformance. Empirically, we study trademarked promotion in the Software Security Industry(SSI). Our sample consists of 87 firms that are active in SSI from 11 countries in the period1993-2000. We use the data coming from SSI-related trademarks registered by these firms,ending up with 2,911 SSI-related trademarks and a panel of 18,213 observations. We estimatea two stage model in which first we predict the complexity and the broadness of a trademarkas a measure of marketing creativity and the rate of product innovations. Among severalcontrol variables, our variable of theoretical interest is the Hofstede s uncertainty avoidancecultural index. Then, we estimate the trademark duration with a hazard model using thepredicted complexity and broadness as well as the rate of product innovations, along with thesame control variables. Our evidence confirms that the cultural avoidance affects the durationof the trademarks through the firm marketing creativity and product innovation.

Minimax regret and strategic uncertainty

This paper introduces a new solution concept, a minimax regret equilibrium, which allows for the possibility that players are uncertain about the rationality and conjectures of their opponents. We provide several applications of our concept. In particular, we consider pricesetting environments and show that optimal pricing policy follows a non-degenerate distribution. The induced price dispersion is consistent with experimental and empirical observations (Baye and Morgan (2004)).