Wage inequality report in the X city of China Coursework

Wage inequality report in the X city of China - Coursework Example We find evidence that level of education, age, experience and sector of employment poses the greatest variation in determining the wage limits in the city. The presence of trade liberization and international foreign investment policy imparts varying levels of exposure to some Chinese cities more than others. While the presence international firms operating in the X city do not have a direct effect on wage equality, a major difference is evident between the majority and minority foreign-owned firms. Majority foreign-owned firms exhibit skilled-biased changes that adversely increase wage inequality. INTRODUCTION. The unequal distribution of individual or household wage across various sectors in the economy is referred as wage inequality. It can be presented as a percentage of wages to percentage of population. China has witnessed rapid growth in national income, foreign investment and export volume in the last few decades. However these economic improvement has been accompanied by inc ome inequality. The wage inequality coefficient of China has steadily increased from 0.33 in the 80s to 0.46 in the year 2000 according to government statistics. These signify a 2-3% growth rate per year, alarmingly one of the fastest in ever recorded. (Yunbo Zhou, 2012) Investigated the causes of the disparities in the wage inequality in urban and rural areas and found that, in rural areas, it is explained by an increase in the wage earning jobs in poorer regions in the end of the 20th century and decrease in regressive taxes. There are allegations of wage inequality in the X state of China. Using the provided data we investigate it basing our research on three divisions we carry out data analysis and provide the results to the Bureau of Human Resources and Social Security; Gender Affiliation and membership in Communist party Local (Hukou) and non-local workers Given the data we determine the correlation coefficients between wage rates and the various variables. This will enable us to deduce whether to use the variables in our regression analysis. Table 1 summary statistics of wage rates by sector and by gender Manufacturing sector Construction sector Others All Male Female All Male Female All Male Female Mean 2.300194 2.389804 2.082571 2.091158 2.077667 2.334 2.24447 2.385095 2.071033 S.d. 0.106617 0.129925 0.180342 0.118321 0.124271 0 0.06246 0.084603 0.090478 No. obs 72 51 21 19 18 1 268 148 120 Table 2 t-Test results for male and female workers H0: ?1-?2=0 vs HA: ?1-?2?0 Manufacturing sector Construction sector Others Assuming ?1=?2 t statistic 1.316535 -0.47321 2.525396 t critical 1.994437 2.109816 1.968922 Assuming ?12 t statistic 1.382249 -1.75867 2.535402 t critical 2.018082 - 1.969201 The research conducted examines the phenomena of nature of two variables and their degree of relatedness. Altering the level of one variable will automatically affect the other. The concept behind the t - test is to determine the difference in the statistic means of two variables relative to the spread or variability of the wage. The purpose of statistical tests is fundamentally meant to test null hypothesis. The results in the Tables 1 and 2 can be used to draw the following conclusions; The wage earned by male workers in the manufacturing sector is significantly higher than what is earned by female workers. The same is also true in the other sectors. However female workers in the manufacturing sector earn more than their male counterparts. This deviation is attributed to the less number of female workers in the construction sector. Thus we can conclude that wage inequality is evident in the X town of China based on gender.