This research assignment aims at obtaining results from the wage gap data. It requires analysis to achieve its main objectives. The data is going to be analyzed using Stata software to be able to get depth insight of the data provided. In this section, the results obtained from the analysis are discussed.
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GENDER WAGE GAP1 Gender Wage Gap Name of Student Institution Course
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Wage Gap In Gender Introduction This research assignment aims at obtaining results from the wage gap data. It requires analysis to achieve its main objectives. The data is going to be analyzed using Stata software to be able to get depth insight of the data provided. In this section, the results obtained from the analysis are discussed. We need to run a regression analysis to estimate the average size of the gender gap pay. We will also capture other variables that might control the gender gap pay. We will also determine whether the gap shrunk after the implementation of the policy in 2007. Therefore, we will evaluate whether there is a significant change. The literature articles with the same topic of study will be reviewed to give more and detailed information on the subject of investigation. The report will enlighten our knowledge of what is already available in the group. This is of importance because it gives ideas of what to expect when doing the research. Later, real available data will be used to conduct the analysis. Appropriate analysis techniques will be applied to the objective of the research. The results obtained from the analysis will be explained in details for a more comfortable and swift understanding of the data about the objective question. The results obtained will be compared with the results obtained earlier as stated in the literature review. Finally, we will summarize our research and comment on the analysis explaining whether what was intended was achieved or not. Literature review The gender pay gap is defined as the difference between the male and female pay divided by that of the male. There has been a consistent reform for the past 20 years to encourage women to fully participate in the labor market to better their pay. There have been a persistence gender pay differences even after
the reforms. Comparing the UK to other countries, gender pay was better. The figure below summaries the gender pay gap according to their respective countries. There have been initiatives to reduce the gender pay gap over recent years. Employment and hours were the factors that were being focused on. In 1997, the government of UK introduced labor policies such that the low-income were targeted more so women. The figure below shows the employment rate for both women and men from 1994 to 2014.
The figure below shows an increase in women income form 61 % to 69 % from 1994 to 2014. Even though there was an increase in women's wages, the gap between females and males was persistent. Another initiative was introduced in 2003 by the name ‘right to request flexible working' law' gave parents who had children of ages below six more flexible working requirement which they were allowed to request. Also, working rights were strengthened when part-time employment was introduced in 2000. All these were submitted to favor the female. The impact of all these was still minimal. The figure below shows the distribution of weekly work time for both the females and the males.
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It can be observed that most men worked for 40 hours a week while that of women were sparse. This is because of the part-time employment issued to the female. In contrary, most men worked full time. The minimum wage policy introduced in 1999 aimed at reducing the pay gap. It aimed at benefiting those who had lower pay which was women. The hourly wage rate gap has been decreasing for the past years. The graph below shows the hourly wage rate from 1994 to 2014.
It can be observed that the gap has been closing from 1994 to 2014. It had reduced from 27 % in 1994 to 19 % in 2014. Comparing the wage pay with the years of experience being the defining matter, it was obtained that the wages for both female and male from the time they started working after schooling had no significant difference. The difference fluctuated as the number of years increased. The biggest gap appeared to be the biggest after 25 to 30 years. The figure below shows the gender pay difference according to experience.
Paternity leave legislation was also introduced to help reduce the pay gap. The fathers were allowed a paid two weeks paternity leave to about 26 weeks as proposed in 2011. The parents shared the leave to help them take care of their children. In March 2015, Liberal Democrats demanded transparency in the pay gap. The legislation would fine a company for failing to disclose the pay for both the females and the males a fine of up to £5,000. The main factor that explained the reason for the gender pay gap was the occupation. Only 35 % of female were involved in the highest paying occupations such as managerial and directory. 80 % of the women were engaged in low paying occupation such as tearing and leisure services. The figure below shows the relationship of the average pay according to the type of profession1. 1Azmat, G., 2015. Gender Gaps in the UK Labour Market: jobs, pay and family-friendly policies.London School of Economics and Political Science: Centre for Economic Performance.
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Focusing on part-time jobs, it was observed that almost two-thirds of the female with children worked part-time. 25 % are those women who worked part-time but had no children. The remaining 7 % were male. A study carried by Manning and Petrongolo 8)2showed that part-time employment involved a remarkable penalty. They also discovered that women who worked for part-time had a lower level of education compared to those who worked full-time. The figure below shows a summary for the payment for both the male and the female who worked part-time. 2Manning, A. and Petrongolo, B., 2008. The part‐time pay penalty for women in Britain. The Economic Journal,118(526), pp.F28-F51.
Methodology The data set was obtained from the UK government website (https://gender- pay-gap.service.gov.uk/). The data contains 854 columns and 1000 rows. Columns that contained information about the sex, the years, weekly gross pay and the number of years were selected from the initial data. Logistic analysis was conducted in order to answer the first objective. The data was transformed before conducting the analysis. The column that displayed the sex variable had input represented by 1 (male) and 2 (female). It needs to be changed to binary such that 0 represents the male and 1 represents the female. This is because logistic regression only applies to binary inputs. |In the first logistic regression, SEX variable will be used as the dependent variable and GRSSWK variable as the independent variable. In the second logistic regression, SEX will be used as the dependent variable
while the selected three control variables as the independent variable. We will conduct regression analysis for the 2018 data and compare the results with the previous years. Results The results from the logistic regression analysis aimed at understanding the gender wage gap were obtained. Formation of the hypothesis There is no significant difference in the gender pay gap. Below is the result of the logistic regression The result of the logistic equation shows that there is a significant difference in the gender pay gap. This is because the value of Probability of chi-squared is higher than 0.05. To understand the average gap, we will focus on the amount of Pseudo R-squared. In our case, the value is 0.0396. This means that the average gender gap pay is 3.96 %.
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We selected the variables EMPLEN and FORTYP15 as our control variables to understand the gender gap. The two variables signified the length of time of current employment and types of qualifications. Formulation of hypothesis The length of time of current employment and the type of qualifications has no significant effect on the gender pay gap Below is the output of the results The results obtained from the analysis rejects the hypothesis since the value of probability chi-square less than 0.05. Therefore we can deduce that the time of the current employment (experience) and the type of qualifications. To determine the level of significance from the variables, we will focus on the value of Pseudo R-squared. Only 4.17 % of the dependent variables affected the gender gap pay. The regression analysis for the same variables for the year 2018 is as below.
We can deduce from the table that there was a no significant change in the gender gap between 2017 and 2018. Discussion From the analysis, we managed to show that there was a significant gap between gender wages. The difference has been reducing each year. This is according to the research conducted by Azmat in 2015 using the previous wage gap data. The study obtained may not have been accurate because the level of error was too high. Some of the participants didn't provide the required data for specific questions. Some of them were not answering the questions appropriately. This is the main limitation of our research. The results obtained from the research has a great apparition on the gender wage up. Even though companies have been trying to succumb to this issue, they still need to do much to reduce the gender wage gap. The government should also follow up to make sure that there is insignificant gender wage gap in the companies. The study is open for future research since the information obtained has some errors. Conclusion
We have managed to discuss the objective of the study is all the aspects, we managed to analyze the data to obtain the required results which are about the purposes of the study. The finding suggests that there is a gender pay gap in the UK even in the current year (2018). The study showed that the gender wage up has been reducing relatively each and every year. There is also future expectation of the reduction of the gender wage gap. This is because of the relative decrease in the gender wage gap that has been occurring each and every year.
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References Azmat, G., 2015. Gender Gaps in the UK Labour Market: jobs, pay and family-friendly policies. London School of Economics and Political Science: Centre for Economic Performance. Manning, A. and Petrongolo, B., 2008. The part‐time pay penalty for women in Britain.The Economic Journal,118(526), pp.F28-F51.