最低工资标准的调整和就业:对人力资本投资的异质性影响
Lin Ling1, Hayat Khan2, Liu Qianqian1
1Guangxi University of Finance and Economics, Nanning, 530007, China.
Heliyon
|February 6, 2024
概括
根据人力资本投资,最低工资上对就业产生不同的影响. 低投资减少就业机会,而高投资增加就业机会,显示出非线性关系.
科学领域:
- 劳动经济学 劳动经济学
- 人力资本理论 人力资本理论
背景情况:
- 关于最低工资对就业的影响存在争论.
- 中国的最低工资政策是研究的一个关键领域.
研究的目的:
- 分析最低工资变化对中国就业的影响.
- 研究人力资本投资在这种关系中的作用.
主要方法:
- 使用了正规模型和回归分析.
- 运用劳动经济学理论与中国工业企业数据 (2000-2007年).
- 企业按人力资本投资水平分类.
主要成果:
- 最低工资的增加具有非线性就业效应.
- 低人力资本投资与就业减少相关.
- 高人力资本投资与就业增加相关.
结论:
- 人力资本投资影响最低工资对就业的影响.
- 由于生产率和需求,高人力资本地区出现了积极的就业效应.
- 在人力资本较低的地区观察到负面的就业影响.
更多相关视频
16:23Automated, Quantitative Cognitive/Behavioral Screening of Mice: For Genetics, Pharmacology, Animal Cognition and Undergraduate Instruction
Published on: February 26, 2014
14.3K
08:27Applying an eMASS Customization Program as a Research Tool to Evaluate Consumer Benefits
Published on: September 27, 2019
6.9K
相关概念视频
One-Way ANOVA: Equal Sample Sizes
3.3K
One-Way ANOVA can be performed on three or more samples with equal or unequal sample sizes. When one-way ANOVA is performed on two datasets with samples of equal sizes, it can be easily observed that the computed F statistic is highly sensitive to the sample mean.
Different sample means can result in different values for the variance estimate: variance between samples. This is because the variance between samples is calculated as the product of the sample size and the variance between the...
Different sample means can result in different values for the variance estimate: variance between samples. This is because the variance between samples is calculated as the product of the sample size and the variance between the...
3.3K
Two-Way ANOVA
2.6K
The two-way ANOVA is an extension of the one-way ANOVA. It is a statistical test performed on three or more samples categorized by two factors - a row factor and a column factor. Ronald Fischer mentioned it in 1925 in his book 'Statistical Methods for Researchers.'
The two-way ANOVA analysis initially begins by stating the null hypothesis that there is an interaction effect between the two factors of a dataset. This effect can be visualized using line segments formed by joining the...
The two-way ANOVA analysis initially begins by stating the null hypothesis that there is an interaction effect between the two factors of a dataset. This effect can be visualized using line segments formed by joining the...
2.6K
Testing a Claim about Standard Deviation
2.5K
A complete procedure to test a claim about population standard deviation or population variance is explained here.
The hypothesis testing for the claim of population standard deviation (or variance) requires the data and samples to be random and unbiased. The population distribution also must be normal. There is no specific requirement on the sample size as the estimation is based on the chi-square distribution.
As a first step, the hypothesis (null and alternative) concerning the claim about...
The hypothesis testing for the claim of population standard deviation (or variance) requires the data and samples to be random and unbiased. The population distribution also must be normal. There is no specific requirement on the sample size as the estimation is based on the chi-square distribution.
As a first step, the hypothesis (null and alternative) concerning the claim about...
2.5K
Regression Toward the Mean
6.3K
Regression toward the mean (“RTM”) is a phenomenon in which extremely high or low values—for example, and individual’s blood pressure at a particular moment—appear closer to a group’s average upon remeasuring. Although this statistical peculiarity is the result of random error and chance, it has been problematic across various medical, scientific, financial and psychological applications. In particular, RTM, if not taken into account, can interfere when...
6.3K
Test for Homogeneity
2.0K
The goodness–of–fit test can be used to decide whether a population fits a given distribution, but it will not suffice to decide whether two populations follow the same unknown distribution. A different test, called the test for homogeneity, can be used to conclude whether two populations have the same distribution. To calculate the test statistic for a test for homogeneity, follow the same procedure as with the test of independence. The hypotheses for the test for homogeneity can...
2.0K
One-Way ANOVA: Unequal Sample Sizes
5.8K
One-way ANOVA can be performed on three or more samples of unequal sizes. However, calculations get complicated when sample sizes are not always the same. So, while performing ANOVA with unequal samples size, the following equation is used:
5.8K
