Reports will be in Word; single-, 1.5-, or double-spaced; 12-point type; in the

Reports will be in Word; single-, 1.5-, or double-spaced; 12-point type; in the format of a business memo with page numbers.Reports will be from three to five pages long. Please end with an appropriate executive summary.
The Effect of Language on the Incomes of Immigrants
the effect of language on the income of immigrants. It is not unusual for first-generation immigrants to have limited ability in the common or national language of the destination country; the second-generation to be bilingual, and the third-generation to be monolingual in the common or national language of the destination country. A large body of evidence indicates that mastering the common or national language of the destination country positively effects earnings and other measures of success. In assignment 3, we will utilize multiple regression to attempt to quantify this impact.
In this assignment, we will use a large numbers of x variables in the context of a cross-section model. Examples of cross-sectional units include states of the United States and stocks issued by corporations. In this assignment, we will use the human capital model to relate income to education and other factors thought to effect earning ability. Our cross-sectional unit will be individuals. Very simply,
Ln(Yi)=a+bXi +ei
Where: ln(Yi) is the natural logarithm of income of individual I
Xi is years of school of individual I, and
ei is the regression error term.
Since this equation uses the natural logarithm of income as the dependent variable, the coefficient b is interpreted as the rate of return to another year of school.1
Our equation will contain a total of 9 x variables. These will be: X1i years of school,
X2i age,
X3i age2,
X4i a dummy variable denoting unmarried men, X5i a dummy variable denoting married women,
1 The exponential of the constant term a is interpreted as the expected earnings of a person with zero years of schooling. The interpretation of the constant terms get complicated when there are additional x variables.
1
X6i a dummy variable denoting unmarried women,
X7i a dummy variable denoting blacks or African Americans,
X8i a dummy variable denoting Hispanics, and
X9i a dummy variable denoting people whose interviews were conducted in Spanish.
X2i and X3i reflect the tendency of income to rise with age and then level off or even start to decline. X4i, X5i and X6i capture systematic differences in income by household type (married men being the reference group, necessarily excluded from the regression). X7i and X8i capture systematic differences in income by race and ethnicity (whites and small numbers of “others” being the reference group).
It is important to point out that the dependent variable is household income. So, it includes labor earnings of spouses of married persons and financial earnings, as well as labor earnings of the persons being interviewed.
The samples are from a periodic survey of Texans conducted during the 1980s and available through the data archive. Each survey contains interviews with about a thousand persons.
Your assignment is to calculate a 9-x variable regression in which the natural logarithm of household income is the dependent variable, using the complete data of the survey you have been assigned. Once you calculate the multiple regression, you are to interpret the output, paying particular attention to the effect of language on income.