Positive Relationship of Wages with Multiple Variables Essay Example

wages are education (p = 2. 17x10-6), gender (p = . 0001), and experience (p = . 0083). Next, using only these three significant variables (education, gender, and experience), we performed a second multiple regression analysis, which yielded the following model: Wage (Y) = -12,227. 69 + 3,160. 29(Years of Education) – 11,149. 29(Gender) + 396. 01(Years of Experience) In the model above, one can project their approximate annual wage, depending upon their years of experience, years of education, and their gender.

Note: for the “Gender” variable, a value of one is entered if the worker is female, and a value of zero is entered if the worker is male. For example, a female worker with a bachelor’s degree (or 16 years of total schooling) and 10 years working experience can expect to earn: Wage (Y) = -12,227. 69 + 3,160. 29(16 years education) – 11,149. 29(1) + 396. 01(10 years experience) = $31,147. 66

According to this same regression model, a man with the very same education and experience will earn $42,296. 95, or $11,149. 29 more than his female counterpart. Clearly, gender plays a significant role in earning potential.