Risk Measures and Attitudes

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An Implicit Association Test IAT was constructed to measure implicit risk-taking and compared to an explicit risk questionnaire in its influence on several management decisions.

Results Results showed that the chance that managers take the risk is significantly higher when the IAT classified them as risk-seeking. This, however, was only found if the decision was framed as a loss situation.

Measuring Attitudes

Under a gain framing, the IAT was not a significant predictor, but the explicit measure significantly differentiated between managers choosing the risk versus not. Implicit attitudes may assess impulsive risk-decisions in loss situations better than explicit attitudes.

About Risk Attitudes, Risk Propensity, and Risk Types

It would be worthwhile to further develop indirect measures to assess managerial decision making. Thus, implicit attitudes may predict risky decision making in loss situations better than explicit attitudes. AB - Purpose We examined the contribution of implicit and explicit risk-attitudes to the prediction of risky management decisions.

BT - Imagine the future world: How do we want to work tomorrow? Managers' implicit and explicit risk-attitudes in managerial decision making Jenny Bittner, Julia Landwehr.

Risk Measures and Attitudes

Faculty of Behavioural, Management and Social Sciences. Abstract Purpose We examined the contribution of implicit and explicit risk-attitudes to the prediction of risky management decisions. Original language English Title of host publication Imagine the future world: How do we want to work tomorrow? Fingerprint Managerial decision making. Risk attitude.

Risk Attitudes Profiler: The Concept

Management decisions. Field experiment. The genetic association tests used are F-tests of the difference in the distribution of the risk attitude measure across subjects in different genotype categories; we implement both a dominant and a recessive model for each polymorphism and phenotype considered. The p-value is corrected for multiple testing using the false discovery rate FDR p-value [45]. FDR is an alternative that controls the number of false positives that is equivalent to the Bonferroni method when there are no truly significant results; otherwise it is less conservative and therefore a more powerful test [46].

It is also possible that these SNPs are not the functional polymorphisms but are linked to a functional polymorphism elsewhere in the gene. The rs SNP has not been previously associated with a phenotype while the rs SNP has been associated with cigarette smoking among schizophrenics [47]. The minor allele of rs is associated with a higher HA score Table 4 and the minor allele of rs is associated with a lower HA score Table 5.

Specifically the rs genotypes AA and AG are associated with low scores, while the GG genotype is associated with high scores. The rs genotypes TT and CT are associated with low scores while the CC genotype is associated with high scores. A few individuals had genotypes that gave conflicting predictions of their HA score; specifically individuals that are CT at the rs locus while being GG at rs locus.

If these individuals are removed from the analysis, the FDR p-values become more robust two individuals with incomplete data were also eliminated, for a total of 7 persons removed from the analysis. These two SNPs were not significantly associated with any other phenotypes. Our study was small for a genetic association study. Realizing this limitation, however, we report on several polymorphisms that showed significant unadjusted associations with one or more of the phenotypes we measured. ESRa rs was the only SNP associated with risk attitudes from both economic and psychology literature.

Each of these associations survives correction for multiple comparison testing. Neuronal nicotinic cholinergic receptors, including CHRNA4 , are of general interest because they modulate the release of several neurotransmitters, including dopamine, serotonin, gamma-amino butyric acid GABA and glutamate in the ventral tegmental area [48]. CHRNA4 is highly expressed in the central nervous system and is, in particular, important in modulation of mesolimbic dopamine function [49] , which suggests it is an appropriate target for studies concerning reward processing and risk attitudes [49].

Furthermore, polymorphisms in CHRNA4 have been associated previously with response inhibition as measured using cognitive tests such as the Stroop Test, Matching Familiar Figures Test, Tower of London Test and the Continuous Performance Test [50] and as measured by success in smoking cessation programs [49]. Harm Avoidance is also associated with inhibitory response; respondents scoring low on HA have been characterized as having underdeveloped inhibitory responses [51].


  • Flatness of Bernoulli jets;
  • 1. Introduction.
  • Risk Attitudes Profiler: Test Results?
  • The English Wool Market, c.1230-1327.
  • About Risk Attitudes, Risk Propensity, and Risk Types!
  • Excitation Control;

Inability to inhibit response is a classic issue with impulse control disorders such as pathological gambling PG and previous work has revealed significant associations between HA and PG [4] , [5] , [6]. These results may also hold relevance for understanding the incidence of impulse control disorders in Parkinson's patients treated with dopamine agonists [10] in light of the role that CHRNA4 plays in dopamine regulation and in light of the data suggesting pre-morbid risk taking behavior is associated with the risk in developing impulse control disorders with treatment of Parkinson's [52] , as well as the prevalence of tobacco use among PD populations.

Research by Takeuchi et al. One of the SNPs from Hutchison et al. We note that the SNPs found significant by Rigbi et al.

Risk Attitudes and Measures of Value for Risky Lotteries

The relevance of these findings can be resolved only after the underlying molecular mechanisms are known. Sadee, unpublished results ; if confirmed, this would further support a possible role for marker SNPs in this region. Furthermore, Voon et al. The significant association between economic risk attitudes and VMAT2 SNPs is novel in the literature, though we must caution that the statistical significance of this finding does not survive adjustment for multiple comparisons. The rs SNP has been previously implicated in alcohol dependence [59] though our search of the literature revealed no previous behavioral associations for the rs SNP.

Previous research involving VMAT2 and inherent genetic variation has indicated the gene as a region of interest with respect to risk attitudes. For example, cocaine users lose VMAT2 protein compared to non-cocaine users [60]. This is of interest as substance addicted individuals have poorer ability to control impulses toward high risk choices in the Iowa Gambling Task [61] , [62].

Other work also links genetic variation in VMAT2 to impulse control issues. For example, Lin et al. Previous research has associated novelty seeking personality traits with PG outcomes [4] , [6]. Given the small sample size involved in this study, independent replication of these results with larger sample sizes is necessary to further refine the genetic basis for risk attitude measures.

Our exploratory results suggest that employing several risk attitude measures drawn from distinct disciplinary literatures can be important to refining the understanding of any genetic basis as the degree of correlation found between economic and psychological measures of risk attitude in this and other samples tends to be low. Furthermore, while most research on the genetic basis of risk attitudes have focused directly on dopamine receptors and the dopamine and serotonin transporter genes, we find that genetic variation in a broad array of genes with ties to the regulation of dopamine and serotonin might be important for understanding individual risk attitudes.

For future directions for genetic studies, the present results set the stage for estimating the cohort size needed to address and replicate the associations identified here. Moreover, consideration of the interaction between the various risk genes, each individually with some potential impact on risk behavior, has the potential to reveal more accurately the impact of genetic factors on risk taking behavior. Analyzed the data: MRT. Secured seed funding and managed all human subjects elements: BER.

Handled the biological samples: HRG. Browse Subject Areas? Click through the PLOS taxonomy to find articles in your field.

Background

Abstract With recent advances in understanding of the neuroscience of risk taking, attention is now turning to genetic factors that may contribute to individual heterogeneity in risk attitudes. Introduction Risk attitudes have been correlated to a broad array of financial, employment, health, safety and social decisions made by humans, including financial investments, insurance coverage, smoking, drinking, sport participation, migration and self-employment status [1] , [2] , [3]. Download: PPT.

Genotypes Genotyping focused on 98 polymorphisms in genes thought to affect catecholamine function, or previously implicated in impulse control issues or associated with risk attitudes. Statistical Methods The genetic association tests used are F-tests of the difference in the distribution of the risk attitude measure across subjects in different genotype categories; we implement both a dominant and a recessive model for each polymorphism and phenotype considered. Table 4.

Table 5. Associations with Other Polymorphisms Our study was small for a genetic association study. References 1. Quarterly Journal of Economics — View Article Google Scholar 2. IZA Discussion Paper. Bonn, Germany. Labour Economics — View Article Google Scholar 4. Cns Spectrums — View Article Google Scholar 5.

Comprehensive Psychiatry — View Article Google Scholar 6. Journal of Gambling Studies — View Article Google Scholar 7.

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