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How much does intelligence predict lifetime income? A Meta-Analysis
Nguyenová, Van Anh ; Havránková, Zuzana (advisor) ; Bortnikova, Kseniya (referee)
Despite growing interest and extensive empirical research in economic returns to ability, a consensus regarding the true impact of intelligence on financial outcomes remains elusive. While psychology literature has made e orts to unify divergent findings, economics is yet to produce a comprehensive meta- analysis addressing this issue. Addressing this gap, our thesis utilizes cutting- edge meta-analytic techniques to analyze a unique dataset of 765 estimates drawn from 38 studies, providing a clearer picture of intelligence's impact on income. We uncover a notable positive publication bias, which, after correction, yields a diminished yet statistically significant e ect. Specifically, our results indicate that a standard deviation increase in cognitive ability results in a less than 10% increase in financial outcomes. Leveraging over 30 variables in our Bayesian and frequentist averaging models, we identify key determinants of this e ect, including the data collection year, outcome specifications, methodologi- cal choices, country-specific factors, and the number of estimates reported per study. Additionally, when adjusting for factors such as gender, residential loca- tion, work experience, and family attributes, we observe substantial variations in e ect size. JEL Classification J24, J31, D31, C11...
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Do Money Rewards Motivate People? A Meta-Analysis
Čala, Petr ; Havránková, Zuzana (advisor) ; Bortnikova, Kseniya (referee)
Do financial incentives motivate people to work better? A plethora of re- search papers in psychology have long tried to answer this question, together with more recent papers from behavioral economics. We take a stock of emerging research in economics and conduct a quantitative analysis from a strictly economic point of view. We collect a total of 1568 estimates from 44 different studies and codify over 30 variables to capture the underlying nature of the effect money has on motivation and performance. A range of statistical tests suggests the overall effect to be virtually zero, which we confirm using a specific design check. We then employ Bayesian and fre- quentist model averaging to identify the most prominent determinants of the effect. Among these, publication bias pushes this effect upwards the most, along with laboratory setting and positive framing in the task. Six variables then pull the effect in the opposite direction - school setting, charitable giv- ing, cross-sectional data, self-reward, quantitative performance, and students subgroup. 1
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Beauty and Productivity: A Meta-Analysis
Bortnikova, Kseniya ; Havránek, Tomáš (advisor) ; Pertold-Gebicka, Barbara (referee)
This thesis conducts a quantitative synthesis of 418 estimates of the effect of beauty on productivity as reported in 37 studies. We test the estimates of beauty effect for publication selection, using informal testing of the funnel plot as well as formal testing methods. We find solid evidence of selective reporting: positive estimates of the beauty effect are preferred in literature. To determine the sources of heterogeneity in the reported estimates, we collect the set of 21 explanatory variables. We take the model uncertainty into account and employ the Bayesian model averaging; the Frequentist model averaging is used as a robustness check. The results indicate that differences in the reported estimates appear to be driven by choice of study design and sources of real heterogeneity, such as geographical regions and individual characteristics of respondents (age, education and cognitive skills). The type of occupation and gender of respondents have no impact on the estimates of beauty effect in relation to productivity. The average beauty effect is probably much lower than commonly believed based on the available empirical literature. JEL Classification C83, J3,J7, M51 Keywords meta-analysis, beauty bias, productivity, dis- crimination, publication bias Author's e-mail xenia.bortnikova@gmail.com...
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