General Mental Ability and pay: Nonlinear effects

Ganzach, Yoav; Gotlibobski, Chemi; Greenberg, Doron; Pazy, Asya

doi:10.1016/j.intell.2013.07.015

Cited by 12 publications

(8 citation statements)

References 28 publications

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“…Beyond the six U-shaped effects that we found using the Two-Lines test, we detected nonlinear effects for cognitive ability on annual income for participants in the NLSY97. These effects were similar to the nonlinear effects reported by Ganzach et al (2013) but nonlinear effects on income could not be replicated in any of the remaining cohorts (Figure 5). We also detected a nonlinear effect of ability on educational attainment within the BCS70 cohort.…”

Section: Polynomial Regressionsupporting

confidence: 78%

“…More recently, T. R. Coyle (2015) observed similar results when investigating the relationships between cognitive ability and grade point average (GPA) across two different cohort samples (National Longitudinal Survey of Youth 1997 [NLSY97], N = 1,950; the College Board Validity study, N = 160,670). In addition, Ganzach et al (2013) found that cognitive ability was positively related to pay and that nonlinear effects could be detected but only after controlling for the interaction between ability and job complexity. Likewise, Ganzach (1998) also observed practically no nonlinear effect of cognitive ability on self-reported job satisfaction within the National Longitudinal Survey of Youth 1979 (NLSY79) cohort study.…”

Section: Existing Literature On Nonlinear Effectsmentioning

confidence: 97%

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Can You Ever Be Too Smart for Your Own Good? Comparing Linear and Nonlinear Effects of Cognitive Ability on Life Outcomes

Brown

Wai

Chabris

2021

Perspect Psychol Sci

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Despite a long-standing expert consensus about the importance of cognitive ability for life outcomes, contrary views continue to proliferate in scholarly and popular literature. This divergence of beliefs presents an obstacle for evidence-based policymaking and decision-making in a variety of settings. One commonly held idea is that greater cognitive ability does not matter or is actually harmful beyond a certain point (sometimes stated as > 100 or 120 IQ points). We empirically tested these notions using data from four longitudinal, representative cohort studies comprising 48,558 participants in the United States and United Kingdom from 1957 to the present. We found that ability measured in youth has a positive association with most occupational, educational, health, and social outcomes later in life. Most effects were characterized by a moderate to strong linear trend or a practically null effect (mean R2 range = .002–.256). Nearly all nonlinear effects were practically insignificant in magnitude (mean incremental R2 = .001) or were not replicated across cohorts or survey waves. We found no support for any downside to higher ability and no evidence for a threshold beyond which greater scores cease to be beneficial. Thus, greater cognitive ability is generally advantageous—and virtually never detrimental.

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Section: Polynomial Regressionsupporting

confidence: 78%

Section: Existing Literature On Nonlinear Effectsmentioning

confidence: 97%

Can You Ever Be Too Smart for Your Own Good? Comparing Linear and Nonlinear Effects of Cognitive Ability on Life Outcomes

Brown

Wai

Chabris

2021

Perspect Psychol Sci

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“…Previous research has shown both positive (e.g., Judge et al, 1999) and negative (e.g., Lounsbury, Gibson, Steel, Sundstrom, & Loveland, 2004) correlations between the two variables. Researchers also proposed that this relationship may even be nonlinear (Ganzach, Gotlibobski, Greenberg, & Pazy, 2013). Future research should tackle this question in greater depth.…”

Section: Discussionmentioning

confidence: 99%

Are genetic and environmental influences on job satisfaction stable over time? A three-wave longitudinal twin study.

Li¹,

Stanek²,

Zhang³

et al. 2016

Journal of Applied Psychology

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Job satisfaction research has unfolded as an exemplary manifestation of the “person versus environment” debate in applied psychology. With the increasing recognition of the importance of time, it is informative to examine a question critical to the dispositional view of job satisfaction: Are genetic influences on job satisfaction stable across different time points? Drawing upon dispositional and situational perspectives on job satisfaction and recent research in developmental behavioral genetics, we examined whether the relative potency of genetic (i.e., the person) and environmental influences on job satisfaction changed over time in a 3-wave longitudinal twin study. Biometric behavioral genetics analyses showed that genetic influences accounted for 31.2% of the variance in job satisfaction measured at approximately Age 21, which was markedly greater than the 18.7% and 19.8% of variance explained by genetic factors at Age 25 and Age 30. Such genetic influences were mediated via positive affectivity and negative affectivity, but not via general mental ability. After partialing out genetic influences, environmental influences on job satisfaction were related to interpersonal conflict at work and occupational status, and these influences were relatively stable across the 3 time points. These results offer important implications for organizations and employees to better understand and implement practices to enhance job satisfaction.

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“…It is clear that conventional wisdom assumes and tests that the effect of intelligence on performance (in a general sense) is linear (Coward & Sackett, 1990). However, in a recent largescale study, Ganzach, Gotlibobski, Greenberg, and Pazy (2013) theorized and demonstrated otherwise with respect to the effect of intelligence on pay; these authors suggested that the studies that failed to detect nonlinear effects may have been underpowered. We agree, but the problem is more complex in other aspects too, particularly because a prevailing problem in our field is the failure to correct for endogeneity-related issues like measurement error as well as not dealing correctly with the problem of omitted variables, which reduces statistical power and also biases coefficients (Antonakis, Bendahan, Jacquart, & Lalive, 2010); these issues will be exacerbated when attempting to detect nonlinear effects (McClelland & Judd, 1993).…”

Section: The Curvilinear Effect Of Intelligence On Leader Behaviormentioning

confidence: 99%

Can super smart leaders suffer from too much of a good thing? The curvilinear effect of intelligence on perceived leadership behavior.

Antonakis

House

Simonton

2017

Journal of Applied Psychology

102

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Although researchers predominately test for linear relationships between variables, at times there may be theoretical and even empirical reasons for expecting nonlinear functions. We examined if the relation between intelligence (IQ) and perceived leadership might be more accurately described by a curvilinear single-peaked function. Following Simonton's (1985) theory, we tested a specific model, indicating that the optimal IQ for perceived leadership will appear at about 1.2 standard deviations above the mean IQ of the group membership. The sample consisted of midlevel leaders from multinational private-sector companies. We used the leaders' scores on the Wonderlic Personnel Test (WPT)-a measure of IQ-to predict how they would be perceived on prototypically effective leadership (i.e., transformational and instrumental leadership). Accounting for the effects of leader personality, gender, age, as well as company, country, and time fixed effects, analyses indicated that perceptions of leadership followed a curvilinear inverted-U function of intelligence. The peak of this function was at an IQ score of about 120, which did not depart significantly from the value predicted by the theory. As the first direct empirical test of a precise curvilinear model of the intelligence-leadership relation, the results have important implications for future research on how leaders are perceived in the workplace. (PsycINFO Database Record

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General Mental Ability and pay: Nonlinear effects

Cited by 12 publications

References 28 publications

Can You Ever Be Too Smart for Your Own Good? Comparing Linear and Nonlinear Effects of Cognitive Ability on Life Outcomes

Can You Ever Be Too Smart for Your Own Good? Comparing Linear and Nonlinear Effects of Cognitive Ability on Life Outcomes

Are genetic and environmental influences on job satisfaction stable over time? A three-wave longitudinal twin study.

Can super smart leaders suffer from too much of a good thing? The curvilinear effect of intelligence on perceived leadership behavior.

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