COVID-19和收入不平等:来自每月人口登记册的证据
Nikolay Angelov1,2, Daniel Waldenström3,4
1The Swedish Tax Agency, Sundbyberg, Sweden.
概括
随着COVID-19的流行,瑞典的收入不平等增加了,主要是由于低薪工人的损失. 政府的支持有所缓解,但并没有消除这种不平等的增加.
科学领域:
- 流行病的社会经济影响.
- 劳动力经济学 劳动力经济学
- 公共政策分析 公共政策分析
背景情况:
- 在全球范围内,COVID-19大流行带来了深刻的社会经济后果.
- 了解经济冲击的分布效应对于有效的政策反应至关重要.
研究的目的:
- 测量COVID-19大流行对瑞典收入不平等的分布影响.
- 在疫情期间确定收入不平等变化的关键驱动因素.
- 评估政府支持政策在缓解不平等方面的有效性.
主要方法:
- 利用新发布的瑞典人口登记册数据进行月度和年度收入分析.
- 分析了收入不平等,就业影响和条件收入.
- 检查了政府COVID-19支持计划的个人采用数据.
主要成果:
- 疫情期间,每月收入不平等显著增加,原因是低收入人群的收入损失.
- 疫情在就业和收入方面不成比例地影响了私营部门的工人和妇女.
- 政府的COVID-19支持政策大大减轻了不平等的增加,但并没有完全抵消它.
- 年度总市场收入不平等也呈现出与月收入不平等相似的增长趋势.
结论:
- COVID-19大流行加剧了瑞典的收入不平等,低收入收入者承受了经济影响的最大负担.
- 虽然政府干预在缓解不平等方面发挥了至关重要的作用,但可能需要采取进一步措施才能获得充分的补偿.
- 调查结果突出了经济危机对不同人口和就业群体的影响.
更多相关视频
07:13Swabbing the Urban Environment - A Pipeline for Sampling and Detection of SARS-CoV-2 From Environmental Reservoirs
Published on: April 9, 2021
4.3K
09:33Visualizing Field Data Collection Procedures of Exposure and Biomarker Assessments for the Household Air Pollution Intervention Network Trial in India
Published on: December 23, 2022
2.3K
相关概念视频
Pareto Chart
6.8K
A Pareto chart is a bar graph or a combination of both line and bar graphs. The bar lengths represent the individual values or the frequency, while the lines represent the cumulative total values. In this chart, the longest bars are arranged on the left and the shortest bars on the right, which makes it easier to read and interpret the data. It can also be called a Pareto diagram or Pareto analysis.
The Pareto chart is named after the Italian economist Vilfredo Pareto, who described the Pareto...
The Pareto chart is named after the Italian economist Vilfredo Pareto, who described the Pareto...
6.8K
Bias in Epidemiological Studies
375
Biases can arise at various stages of research, from study design and data collection to analysis and interpretation. Recognizing and addressing these biases is essential to ensure the validity and reliability of epidemiological findings.Broadly speaking, biases in epidemiology fall into three main categories: selection bias, information bias, and confounding. A more detailed description of possible biases is:
375
Statistical Methods for Analyzing Epidemiological Data
426
Epidemiological data primarily involves information on specific populations' occurrence, distribution, and determinants of health and diseases. This data is crucial for understanding disease patterns and impacts, aiding public health decision-making and disease prevention strategies. The analysis of epidemiological data employs various statistical methods to interpret health-related data effectively. Here are some commonly used methods:
426
Pie Chart
14.2K
A pie chart (or a pie graph) is a circular graphical chart or a pictorial representation of categorical data. It is divided into slices of pie each indicating numerical proportions. It is also used to show the relative sizes of data in a single chart.
In a pie chart, the central angle, the arc length of each slice, and the area are directly proportional to the quantity or percentage it represents. Some real-world examples that can be depicted using pie charts include marks obtained by students...
In a pie chart, the central angle, the arc length of each slice, and the area are directly proportional to the quantity or percentage it represents. Some real-world examples that can be depicted using pie charts include marks obtained by students...
14.2K
Population Growth
25.3K
Population size is dynamic, increasing with birth rates and immigration, and decreasing with death rates and emigration. In ideal conditions with unlimited resources, populations can increase exponentially, which plots as a J-shaped growth rate curve of population size against time. This type of curve is characteristic of newly-introduced invasive species, or populations that have suffered catastrophic declines and are rebounding.
25.3K
Wilcoxon Signed-Ranks Test for Median of Single Population
177
The Wilcoxon signed-rank test for the median of a single population is a nonparametric test used to evaluate whether the median of a population differs from a specified value. Unlike parametric tests, it does not require data to follow a normal distribution, making it suitable for non-normal or small samples. The test begins by calculating the difference (d) between each observation and the hypothesized median. The absolute values of these differences are ranked in ascending order, with ties...
177
