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148 results for “Inequality”
Dataset for paper submission: "Revisiting the Long-Run Relationship Between Inward/Outward FDI and Income Inequality: New Evidence from the OECD"
<p>The relatively small panel cointegration literature on the dynamics between FDI and income inequality predominantly finds that FDI will reduce income inequality in the long-run in developed countries. However, we point out an important technical oversight in the literature. Not accounting for cross-section dependence in panel data methodologies may yield unreliable results. Expanding on the work of @herzer/nunnenkamp:13, who pioneered the use of panel cointegration in the European context, we obtain different results when we account for cross-section dependence and employ economic procedures robust to it. Using a panel containing 16 OECD countries (1979-2017), 2 income inequality measures, and 4 FDI measures, we begin by showing strong evidence for the existence of cross-section dependence. Then, using second-generation econometric procedures, we do not find any evidence for a cointegrating relationship between inward FDI and income inequality. We do find evidence that outward FDI is cointegrated with income inequality; however, contrary to the main results of the literature, we find that it widens the income gap in the long-run. Additionally, our results support the view that fiscal policy is an important tool to reduce income inequality.</p>
The French Covid-19 vaccination policy did not solve vaccination inequities a nationwide study on 64.5 million people
<p>Data and code to reproduce the analysis of our article.</p> <p> </p> <p># Contents</p> <p>`code/`: Analysis code. <br> The main analysis file is `vaccination-indicators.Rmd`. <br> Some results are exported in `out*.RData` files. </p> <p>`data/`: Data used for the analysis. <br> The data are treated by the `code/0_INSEE_predictors.R` script, and saved as `code/data_indicators.RData`, which is the file used for analysis.</p> <p>`ms/`: Manuscript files; they are outdated (the ms was later modified with Word), but `ms.Rmd` contains code to reproduce the figures and some numerical values given in the text. </p> <p># Data Sources</p> <p>- Vaccination data from Assurance Maladie: <br> - EPCI: <https://datavaccin-covid.ameli.fr/explore/dataset/donnees-devaccination-par-epci/><br> - Paris, Marseille, Lyon: <https://datavaccin-covid.ameli.fr/explore/dataset/donnees-de-vaccination-parcommune/information/></p> <p>- Geographic information:<br> - EPCI: <https://datavaccin-covid.ameli.fr/explore/dataset/georef-france-epci/><br> - Paris, Marseille, Lyon: <https://datavaccin-covid.ameli.fr/explore/dataset/georef-france-commune-arrondissement-municipal/></p> <p>- Socio-economic indicators from INSEE: <https://www.insee.fr/fr/statistiques/5359146#consulter></p> <p>- 2017 Presidential election:<br> - <https://www.data.gouv.fr/fr/datasets/election-presidentielle-des-23-avril-et-7-mai-2017-resultats-definitifs-du-1er-tour-par-communes/#resource-d282e53a-d273-425d-95bb-8a0d7632c79a-header> <br> https://www.data.gouv.fr/fr/datasets/election-presidentielle-des-23-avril-et-7-mai-2017-resultats-du-2eme-tour-2/<br> - Paris: <https://opendata.paris.fr/explore/dataset/elections-presidentielles-2017-1ertour/export/?disjunctive.id_bvote&disjunctive.num_circ&disjunctive.num_quartier&disjunctive.num_arrond&sort=-num_arrond> <br> - Marseille: <https://trouver.datasud.fr/dataset/82a6d91c-c81d-423c-9a4a-3f76d121c8ce/resource/03e2ef07-c2d0-41dd-b503-26910ecb15c3/download/marseille_presidentielles2017_tour1.csv> <br> - Lyon: <https://www.interieur.gouv.fr/Elections/Les-resultats/Presidentielles/elecresult__presidentielle-2017/(path)/presidentielle-2017/084/069/069L.html></p>
Supplementary Material for "Do you think there is no gender inequality in Software Engineering?"
<p><strong>README</strong></p> <p>This repository contains supplementary materials for the paper titled "<em>Do you see what happens around you? Men's Perceptions of Gender Inequality in Software Engineering".</em></p> <p>The data in this repository originates from a survey conducted with men technology practitioners, focusing on their experiences within the industry and their perceptions of gender inequality within their teams and workplaces.</p> <p>The survey was administered using Microsoft Forms, allowing practitioners to respond to the questionnaire asynchronously, anonymously, and without supervision.</p> <p>The organization of this repository is as follows:</p> <ol> <li><code>Phase 1:</code> <ol> <li><em><code>charts.Rmd</code>:</em> This file contains R scripts used to generate the figures that present quantitative data in the manuscript.</li> <li><em><code>Q<strong>x</strong>.png</code></em>: These images are the figures generated by the <code>charts.Rmd</code> script.</li> <li><em><code>responses.csv</code></em>: This file contains complete and detailed responses to the questionnaire submitted by participants.</li> <li><em><code>responses_coding.xlsx</code></em>: Within this sheet, you will find the results of the coding process conducted using the Grounded Theory methodology.</li> <li><em><code>survey_questions_english.pdf</code></em>: This document contains a faithful translation of the questionnaire sent to the participants.</li> </ol> </li> <li>Phase 2 <ol> <li><em>brazilian_responses.csv: </em>focus group responses from brazilian participants.</li> <li><em>european_responses.csv:</em> focus group responses from european participants.</li> </ol> </li> </ol> <p> </p>
Replication package for: Stock Market Participation, Inequality, and Monetary Policy
<p>This package contains replication files for the paper "Stock Market Participation, Inequality, and Monetary Policy", by Davide Melcangi and Vincent Sterk, to be published in the <em>Review of Economic Studies</em>.</p>
Assessing inequities in electrification via heat pumps across the U.S.
<p>This repository contains code and publicly available data to reproduce the results of <em>Assessing inequities in electrification via heat pumps across the U.S.</em> published in Joule.</p>
China's Greener Production Reduces East-to-West Pollution Transfers and Alleviates Environmental-Economic Inequalities
<p>The data contains 1. Pro-andCon-base_APE_Value added (the production- and consumption-based APE and value added in 2007, 2012, 2017, and the change); 2. f_d (the production- and consumption-based emission intensity (<em>f</em>) and value added intensity (<em>d</em>) in 2007, 2012, 2017); 3. REI_REIC (the REI index in 2007 and 2017, and REIC index); 4. ape_flow2007 (the APE flows in 2007); 5. ape_flow2012 (the APE flows in 2012); 6. ape_flow2017 (the APE flows in 2017); 7. ape_flowchange (the change of the APE flows from 2007 to 2017); 8. va_flow2007 (the value added flows in 2007); 9. va_flow2012 (the value added flows in 2012); 10. va_flow2017 (the value added flows in 2017); 11. va_flowchange (the change of the value added flows from 2007 to 2017);</p>
Data from: Comparing measures of breeding inequality and opportunity for selection with sexual selection on a quantitative character in bighorn rams
The reliability and consistency of the many measures proposed to quantify sexual selection have been questioned for decades. Realized selection on quantitative characters measured by the selection differential i was approximated by metrics based on variance in breeding success, using either the opportunity for sexual selection Is or indices of inequality. There is no consensus about which metric best approximates realized selection on sexual characters. Recently, the opportunity for selection on character mean OSM was proposed to quantify the maximum potential selection on characters. Using 21 years of data on bighorn sheep (Ovis canadensis), we investigated the correlations between seven indices of inequality, Is, OSM and i on horn length of males. Bighorn sheep are ideal for this comparison because they are highly polygynous, sexually dimorphic, ram horn length is under strong sexual selection, and we have detailed knowledge of individual breeding success. Different metrics provided conflicting information, potentially leading to spurious conclusions about selection patterns. Iδ, an index of breeding inequality, and to a lesser extent Is, showed the highest correlation with i on horn length, suggesting that these indices document breeding inequality in a selection context. OSM on horn length was strongly correlated with i, Is, and indices of inequality. By integrating information on both realized sexual selection and breeding inequality, OSM appeared to be the best proxy of sexual selection and may be best suited to explore its ecological bases.
Migrant health inequalities or unequal measurements? Online Appendix
<p>Online Appendix for Article: </p> <p><strong>Migrant health inequalities or unequal measurements? On the intercultural and longitudinal measurement invariance of physical and mental health. </strong> </p> <p>Files:</p> <p>- analysis.R: measurement invariance tests, calculation of latent means, estimation with FIML; robustness with MLR</p> <p>- robustness_check.R: robustness with WLSMV estimator , parameterized scales</p> <p>- robustness_outputs.html: fit measures, factor loadings, latent means of robustness check</p>
Dataset Content Analysis Framing Inequality in Spanish Online Media
<p>Dataset Content Analysis Framing Inequality in Spanish Online Media. Project: News, networks and users in the<br> Hybrid Media System (Newsnet)</p>
Exploring the effect of industrial agglomeration on income inequality in China
<p><span>Income inequality is a good indicator reflecting the quality of people's livelihood. There are many studies on the determinants of income inequality. However, few have studied the impacts of industrial agglomeration on income inequality, and even fewer have studied the spatial correlation of income inequality. The goal of this paper is to investigate the impact of China's industrial agglomeration on income inequality from a spatial perspective. Using data on China's 31 provinces from 2003 to 2020 and the spatial panel Durbin model, our results show that industrial agglomeration and income inequality present an inverted "U-shape" relationship, proving that they are non-linear changes. As the degree of industrial agglomeration increases, income inequality will rise; after it reaches a certain value, income inequality will drop. Therefore, the Chinese government and enterprises had better pay attention to the spatial distribution of industrial agglomeration, thereby reducing China's regional income inequality.</span></p>
Replication package for "Skill heterogeneity and market labour income inequality"
<p>Medrano-Adan, L., Salas-Fumás, V. and Sánchez-Asín, J. (2023) “Skill heterogeneity and market labour income inequality”. <em>SERIEs-Journal of the Spanish Economic Association</em>.</p>
Socioeconomic Inequalities in the Diagnosis and Treatment of Colon and Ovarian Cancer in England Between 2016-2017
ClinicalTrials.gov study NCT05185388. IPD Sharing: NO. Countries: 1. Publications: 1.
Study of Patient Navigation to Reduce Social Inequalities
ClinicalTrials.gov study NCT01555450. IPD Sharing: Not stated. Countries: 1. Publications: 3.
Health, Perception, Practices, Relations and Social Inequalities in the General Population During the Covid-19 Crisis
ClinicalTrials.gov study NCT04392388. IPD Sharing: UNDECIDED. Countries: 1. Publications: 13.
Overweight Management and Social Inequalities
ClinicalTrials.gov study NCT01688453. IPD Sharing: Not stated. Countries: 1. Publications: 7.
Reducing Structural Inequities in Heart Failure Management: An Approach to Improve the Quality of Heart Failure Care on the General Medicine Service: Longitudinal Equity Action Plan (LEAP)
ClinicalTrials.gov study NCT03942978. IPD Sharing: NO. Countries: 1. Publications: 10.
Community Care Intervention to Decrease COVID-19 Vaccination Inequities
ClinicalTrials.gov study NCT06156254. IPD Sharing: YES. Countries: 1. Publications: 1.
Best Practice Advisories to Reduce Inequities in Technology Use for People With Type 1 Diabetes
ClinicalTrials.gov study NCT06931275. IPD Sharing: NO. Countries: 1. Publications: 4.
Socioeconomic Inequalities Exacerbated by Mitigation Measures to COVID-19 and Differences in Prematurity Prevalence
ClinicalTrials.gov study NCT05087160. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Comorbidities And Reducing inEquitieS
ClinicalTrials.gov study NCT04836221. IPD Sharing: Not stated. Countries: 1. Publications: 0.
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.