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Price Elasticity of Electricity Revisited: A Meta-Analysis
Šikl, Vojtěch ; Havránková, Zuzana (advisor) ; Petit, Mathieu (referee)
Despite a plethora of empirical research on electricity demand, results regard- ing estimated price elasticities persist to be inconclusive. Our meta-analysis synthesizes 4521 estimates from 413 studies to explore the presence of publi- cation and endogeneity bias. We code for over 100 variables to quantify the response of electricity consumers to price shifts. The price elasticity of electric- ity is inelastic and the short-run elasticity sample average of -0.231 is double (in magnitude) the short-run elasticity corrected for publication bias, which is -0.116. The long-run elasticity adjusted for publication bias is -0.303. We conclude that experimental studies, while also su ering from publication bias, report unbiased elasticities of -0.07. Our thesis also confirms a significant occur- rence of p-hacking across multiple specifications. By employing Bayesian model averaging, we explore the heterogeneity among reported elasticities, finding that factors such as decreasing tari s, demographics and fuel usage controls, daylight hours and number of citations critically influence the variability in findings. The average and marginal price of electricity and time of use tari s play a negligible role in explaining the di erences in estimated elasticities. JEL Classification D01, Q40, Q49, C11 Keywords...
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Meta-analysis of bone tumorous lesions in spinal CT data using convolutional neural networks
Nantl, Ondřej ; Jakubíček, Roman (referee) ; Chmelík, Jiří (advisor)
This bachelor thesis deals with the use of convolutional neural networks in the meta-analysis of bone tumor lesions in CT image data. The theoretical part describes the anatomy and pathology of bone tissue, machine learning, discusses the functionality of convolutional neural networks and summarizes selected existing methods for computer-aided diagnosis of vertebra bone lesions. In the practical part, various types of models using convolutional neural networks were implemented and the networks were trained on an available augmented dataset. Finally, the results of various types of models were statistically evaluated, compared with available articles and discussed.
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Standing Tall Pays Off: A Meta-Analysis of Height Premium
Juračková, Martina ; Havránková, Zuzana (advisor) ; Polák, Petr (referee)
As has been demonstrated by empirical research, height is an important physical feature impacting various aspects of the life of an individual. This thesis deals with the relationship between height and income, also referred to as height premium. With the help of modern meta-analytic methods, we aim to quantitatively summarize the empirical evidence on the impact of height on income. After introducing the topic of height premium, data collection and methodological framework, we test for publication bias. The analysis is conducted on 1084 height premium estimates collected from 67 studies. The results of publication bias testing indicate that height premium literature contains positive publication bias which persists even after we control for additional variables capturing study characteristics or, in other words, the heterogeneity of collected estimates. Based on Bayesian Model Averaging results, we conclude that geographical factors, the longitudinal nature of the dataset, restriction of the dataset with respect to gender, or adding a gender control variable into the regression are the most important factors explaining the variability of height premium effects.
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The Effect of Face Masks on Covid Transmission: A Meta-Analysis
Lušková, Martina ; Havránková, Zuzana (advisor) ; Bertoli, Paola (referee)
The effect of face masks on Covid-19 transmission is crucial for the health of populations. Nevertheless, its economic consequences cannot be overlooked. To perform a quantitative meta-analysis, 258 estimates from 44 primary studies were collected together with more than 30 variables mirroring the differences among the studies. Publication bias was examined by implementing various statistical tests resulting in mild evidence for the phenomenon. We contribute to other meta-analyses on the topic by employing the Bayesian and Frequen- tist model averaging to identify the drivers behind the heterogeneity of the estimates. The results suggest that temperature, geographical latitude, and panel data structure have a highly statistically significant and positive effect on the risk of transmission associated with mask-wearing. Moreover, a pos- itive effect was identified for healthcare set-up. In contrast, performing an aerosol-generating procedure shifts the risk in the negative direction. JEL Classification I1, I11, I19, Keywords meta-analysis, Covid-19, face masks, pan- demic, Covid-19 transmission, publication bias, Bayesian model averaging Title The Effect of Face Masks on Covid Transmis- sion: A Meta-Analysis
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Energy-Economy Nexus: a meta-analysis
Kocianová, Agáta
The aim of the thesis is to identify whether there is a consensus in the field of Energy-Economy Nexus literature. The used econometric methods serve to conduct the systematic review of empirical literature to investigate the presence of a significant evidence for any form of (Granger) causality and the prevailing type of the causality, with regard to the influence of multiple study characteristics, such as the geographic area, sample size, length of the study period, etc. Partial goal of the thesis is to review the factual relevance of the empirical literature for the policy makers. Notably whether the influential papers (as indicated by the number of citations) are also reflected, for example in the EU, US or OECD policy documents.
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The Causal Effect of Parents' Schooling on Children's Schooling: A Meta-Analysis
Pokorná, Anastasia ; Havránková, Zuzana (advisor) ; Kukačka, Jiří (referee)
One of the topics concerning education's improvement is the intergenerational transmission of education. The main goal of our study is to analyse the causal efect of parents' education on children's education. We collect 387 estimates of the causal efects from 23 studies. Using our dataset and meta-analytic methods, we test for the presence of publication bias in the literature and try to explain the heterogeneity in the results of the primary studies. After correction for publication bias, the mean becomes smaller than the mean reported in the literature and varies from 0.044 to 0.185. For exploring the heterogeneity of the estimates we use Bayesian Model Averaging and Frequentist Model Averaging. Our results suggest that there is a country heterogeneity in the estimates of the causal efect. Moreover, controlling for the size of a household in the original regression is important for the explanation of the diferences in the results of the primary studies. In addition to it, we collect 605 estimates of the non- causal associations from 39 studies and analyse the publication bias and the heterogeneity of results also using this sample. 1
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Essays in Behavioural and Experimental Economics
Matoušek, Jindřich ; Havránek, Tomáš (advisor) ; Miklánek, Tomáš (referee) ; Rachinger, Heiko (referee) ; Gechert, Sebastian (referee)
CHARLES UNIVERSITY FACULTY OF SOCIAL SCIENCES Institute of Economic Studies Essays in Behavioural and Experimental Economics Abstract for Dissertation thesis Author: Mgr. Jindřich Matoušek Study program: Economics and Finance Supervisor: prof. PhDr. Tomáš Havránek, Ph.D. Year of defense: 2022 Abstract The dissertation consists of three papers presenting applications of experimen- tal as well as statistical methods to the topics of behavioural economics. The first paper introduces a series of laboratory experiments in which I apply the experimental methods to a complex decision making problem. The second and third papers present quantitative syntheses of the literature on the classi- cal topics of behavioural economics. The general introduction connects these chapters together. Detailed abstracts for individual papers are presented at the beginning of each chapter. In the first paper, I experimentally examine two complex multi-unit auc- tion mechanisms with an opportunity to communicate and thus collude while comparing these mechanisms in terms of efficiency. Strikingly, allowing for communication increases efficiency in examined auction formats. A cheap-talk collusive agreement resulted in a better allocation compared to the treatments without communication. I hypothesize that complex auction formats makes...
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Are Women More Risk-Averse than Men? A Meta-Analysis
Černý, Patrik ; Havránek, Tomáš (advisor) ; Bauer, Michal (referee)
Are women more risk averse than men? While a large portion of economic literature confirms this phenomenon, the link between gender and risk aver- sion has not been found to be consistent. We investigate the difference in risk aversion between genders employing meta-analytic methods on 147 estimates collected from 25 primary studies, converted to partial correlation coefficients. We find positive publication bias in our dataset, suggesting that the reported estimates in primary studies are exaggerated. After adjusting for the publica- tion bias, men do not seem to be more risk-taking than women. In addition, we employ Bayesian Model Averaging to examine heterogeneity among the es- timates, controlling for additional 68 variables reflecting the design of primary studies. Based on the heterogeneity results, we find that the publication bias in our dataset is driven by 'lower quality' studies based on the RePEc ranking of economic journals. This finding also aligns with our robustness checks on sub- sets divided according to the quality of journals publishing the primary studies.
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Immigration and Wages: A Meta-Analysis
Nepivoda, Lukáš ; Havránek, Tomáš (advisor) ; Pertold-Gebicka, Barbara (referee)
Increasing number of international migrants in last decades attracts the attention of researchers who attempt to estimate the effect of immigration on the wages of native workers. Despite the extensive body of empirical literature, there is no consensus about the true effect. We employ modern techniques in the meta-analysis to address this question. Using original dataset consisting of 644 estimates from 20 primary studies which reflects the last 30 years of the research on the topic in hand we inspect the literature for the presence of publication bias and explain the heterogeneity in the estimates of primary studies. Although, there is some uncertainty about our results, findings from linear and non-linear tests for publication bias suggests the overall effect close to zero or slightly positive. Moreover, we find an evidence that immigration causes distributional effects which contribute to wealth inequality.
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The Price Elasticity of the Demand for Higher Education: A Meta-Analysis
Kiiashko, Olesia ; Havránek, Tomáš (advisor) ; Korbel, Václav (referee)
The main question of this study is whether the demand for higher education is relatively sensitive to tuition fee changes or is price inelastic. There is no definite answer in the literature. Approximately 52% of the estimates show it to be insignificant, 43% rate it as statistically negative, and approximately 5% are statistically positive. In a quantitative survey of 562 estimates reported in 48 studies, it has been found that large increases in tuition fees have a disproportionately negative impact on enrollment when potential publication bias and method heterogeneity are taken into account. The publication bias tests show that negative results are more preferable among researchers, because it is well supported by theory (when prices increase demand decreases). The results also suggest that four aspects of study design are especially effective in explaining the differences across primary studies: (1) the longer time period negatively associated with the price c of demand for higher education, (2) while the cross sectional estimations have reported more negative results, panel data estimations have reported fewer negative results, (3) controlling for endogeneity is crucial, (4) while controlling for unemployment rate has no clear conclusive impact, controlling for income is not significantly...
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