OBJETIVES
The main objective of this research is to establish and determine the factors which contribute to the increase and decrease of wages in relation to the year, ethnicity, geographical and socio-culture as per the year 2005.
DEFINITION OF TERMS
Wages- These is the money earned by a person working at a particular organization or company.
Wage Earners-These are people who work at a particular organization or company to get wages, or get paid for their service.
HYPOTHESIS
The economic downturn and meltdown that has hit the world currently has left so many families scratching beyond where their hands can reach and digging dipper into their pockets. Those coming fresh from college find it uneasy to work and those who are already working face so many challenges which affect them financially, economically and socially. Those who had already retired can no-longer stay at home but go to look for other jobs either part-time or full-time. The market for skilled professionals is flooded. Many businesses have closed down, and the number of employment opportunities reducing each and every day.
The data collected by the Wage and Wage earners in 2005 showed that the average age of workers is 39.11. This paper , will try to find out the factors that affect wage increment and decrement by use of data from the Wage and Wage Earners. Using the following data, we can draw both null and alternative hypothesis, assuming that the year, 2005 is kept constant. We can therefore summarize all those factors that affect wage increment and decrement under Geographical, Ethnicity and other socio-cultural factors as follows then we draw our null and alternative hypothesis.
Ethnicity |
Geographical Influences/ Type of Industry |
Socio-cultural factors |
Non- white |
Manufacturing |
Education |
White |
Construction |
Experience |
Non- Hispanic |
Other |
Male |
Hispanic |
|
Female |
Using the above summarized table, we can then continue with our hypothesis on how these factors affected Annual income.
Possible Outcomes
Ethnicity Factors
From the excel sheet drawn from copy of wages in the year 2005, the data shows that the mean incomes were as follows:
Whites-31517.37, Non-Whites-24678.3, Hispanic-33337 and finally, non- Hispanic-30673.66. From this data, we can then elucidate that if ethnical factors affected wages of wage earners in the year 2005, then there should be a directly observable correlation between ethnicity and wage variations. Therefore ethnicity being an independent variable, it may be defined as those uncontrollable factors that affect wage earners. To measure the level of ethnicity at a particular place, e.g. a random head count is done, like between whites and non-whites.
Geographical Factors
From the same excel sheet, we can classify Geographical factors as the employment environment or rather type of employment. The data shows that the mean income for the year 2005 was as follows:
Manufacturing- 26402.29 , Construction- 42225.67 and others 31347.88. From this set of data, we can elucidate that Geographical factors had a direct effect on wage increment and decrement for wage earners. Therefore Geographical factors become the independent variable. However, to measure such outcome, the number of employees from selected manufacturing and construction industries at their various level are interviewed about their wages though not to reveal their exact wages as this may be seen as jeopardizing their privacy, terms and conditions.
Socio-Cultural Factors
Using the same excel sheet of 2005 to draw our data, we classify socio-cultural factors as being level of education, experience, whether being male or female, hence this is the data we get that Mean wages increased with further education of up to 39395.6, reduced with experience, e.g. 31-34 years of experience was 30107.04 while 11-20 years of experience was 34387.5. Married wage earners got more while older people earned more. From this set of data, then socio-cultural factors become our independent variables, they therefore had a direct impact on wage increment and decrement. To measure this variable, like may be married and unmarried, a random headcount is done, then proper data is recorded for analysis.
Then our general hypothesis becomes that if geographical, socio-cultural and ethnicity factors affected wages of wage earners in the year 2005, then there should be a directly observable correlation between ethnicity and wage variations.
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