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A joint dataset of official COVID-19 reports and the governance, trade and competitiveness indicators of World Bank group platforms

机译:官方Covid-19报告的联合数据集和世界银行集团平台的治理,贸易和竞争力指标

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摘要

The presented cross-sectional dataset can be employed to analyze the governmental, trade, and competitiveness relationships of official COVID-19 reports. It contains 18 COVID-19 variables generated based on the official reports of 138 countries (European Centre for Disease Prevention and Control, 2020 [1] and Beltekian et al. [2]), as well as an additional 2203 governance, trade, and competitiveness indicators from the World Bank GroupGovData360(World Bank Group, 2020 [3]) andTCdata360(World Bank Group, 2020 [4]) platforms. From these platforms, only annual indicators from 2015 and later were collected, and their missing values were replaced with previous annual values, in descending order by year, until 2015. During preprocessing, indicators (columns) were filtered out when the ratio of missing values exceeded 50%. Then, the same filtration was applied for the ratio of missing values above 25% in the case of countries (rows). Finally, duplicated variables were removed from the dataset. As a result of these steps, the missing value rate of the employed indicators was reduced to 4.25% on average. In addition to the database, the Kendall rank correlation matrix is provided to facilitate subsequent analysis. The dataset and the correlation matrix can be updated and customized with an R Notebook file, which is also available publicly in Mendeley Data (Kurbucz, 2020 ).
机译:提供的横断面数据集可用于分析官方Covid-19报告的政府,贸易和竞争力关系。它包含基于138个国家的官方报告生成的18个Covid-19变量(欧洲疾病预防和控制中心,2020 [1]和Beltekian等人[2]),以及额外的2203年治理,贸易和来自世界银行GroupGovdata360的竞争力指标(世界银行集团,2020年[3])和TCDATA360(世界银行集团,2020年[4])平台。从这些平台上,只收集来自2015年及以后的年度指标,并将其缺失的值替换为以前的年度值,按年下降到2015年。在预处理期间,当缺失值的比率时,滤除指标(列)超过50%。然后,在国家(行)的情况下,申请相同的过滤以高于25%的缺失值比率。最后,从数据集中删除重复的变量。由于这些步骤,所用指标的缺失值率平均降至4.25%。除了数据库之外,提供了KendAll秩相关矩阵,以便于后续分析。可以使用R Notebook文件更新和自定义数据集和相关矩阵,该文件也可公开在Mendeley数据(Kurbucz,2020)中可用。

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