Quantitative Research

Since 1967, the median household income in the United States has risen modestly, fluctuating several times. Even though personal income has risen substantially and large percentage of all household now has two income earners, the median household income has increased only slightly. According to the US Census Bureau, this inconsistent set of trends is due to the changing structure of American households (Household income in the United States, 2006).

Purpose Statement and Model

The dependent variable, household income, is determined by independent variables education of the household members, race and age of the household members. The beginning assumption in the relationship of these variables is that the three independent variables affect the household income. The most important independent variable in this correlation is the level of education obtained by each household member who has an income, over the age of 18. Without an education, your chance of making income is relatively slim. Advanced education beyond the level of high school increases the opportunities available to an individual in the workplace, thereby increasing your income. The general multiple regression equation is Y = a + b1X1 + b2X2 - b3X3. (Lind, 2008). In this multiple regression equation "a" is the coefficient of the dependent variable of household income and X1, X2 and X3 are the independent variables of education level, household size and age of household members. The general multiple regression equation in this scenario is: Y = household income + education + household size + age.

Definition of Variable

Household Income is a measure commonly used by the United States government and private institutions, that counts the income of all residents over the age of 18 in each household, including not only all wages and salaries, but such items as unemployment insurance, disability payments, child support payments, regular rental receipts, as well as any personal business, investment, or other kinds of income received routinely (Household income in the United States, 2006). The total of the income figures reported for all individuals at the same address is constituted as household income. Most commonly used income measures deal with values at the household or family level rather than for individuals. This reflects the role of the household/family as a fundamental economic unit (Missouri Census Data Ctr). With today's economic downturn, we have to determine what is needed to adapt and overcome our economic struggles. With this in mind, we need to examine what factors come into play when determining our household income. Have we reached our highest income capabilities and/or is it just a matter of unchangeable circumstances?

Primary Independent Variable

The primary independent variable for household income is education. This variable is basically decided by the education level of the household members, such as high school, or colleges. A study conducted by the Bureau of Labor Statistics in 2009 revealed that the differences in weekly earnings registered by the individuals with just a high school diploma and individuals bachelor degrees can total up to $399. Also, the differences are undoubtedly evident between consecutive levels. For instance, an individual who has finished high school but did not go to college will make about $626 per week, whereas the individual who only acquired an Associate degree will only make $761 per week. The genuine figures are revealed in the chart below:

In the Median income as displayed, education is the main factor in the increasing income variance between households that are ran by a person with a 4-year college degree and those households that are ran by individuals with the basic high school diploma. A positive coefficient is expected for this independent variable.

Independent Variables

The size or number of members in the household represents the second independent variable influencing the household income. The household is defined as an individual or a group of individuals either related to each other or otherwise who share accommodation and one aspect or more of living arrangements and who sleep, in the night of conducting the census, in one home, according to the definition used in Census 2003. (6 Average Household Size, n.d.). The coefficient for size of household will be positive due to the fact that the number of members in the household has significant amount of effect on the amount of income that is generated within the household.

The age of the household members is another independent variable that influences the household income. The Census Bureau conducted several studies along the years and have generally categorized the ages into seven age groups: 15 - 24, 25 - 34, 35 - 44, 45 - 54, 55 - 64, 65 - 74 and 75 - over (U.S. Census Bureau, 2008-9). Nevertheless, various results can occur within the studies at various times. The coefficient of age is positive, because the age level in the household can signify experience, which influences the amount of household income members can create.

Data Description

Several sources of data have been documented in this paper. The primary dependent variable is taken from Figure 1 of the U.S. Census Bureau: Household Income for States:

2008 and 2009. The data is from the years 2008-2009. The primary independent variable of education is taken from the Table 1, All Races, U.S. Census Bureau: Educational Attainment. The data is from the year 2009. The independent variable of race is taken from Figure 1 of the U.S. Census Bureau Income, Poverty, and Health Insurance Coverage in the United States: 2009. The limits of this data include the difference in the years for which information was obtainable and the tendency for household incomes and other variables to be traditionally underreported.

Presentation and Interpretation of Results

The estimated prediction equation is Y = a + b1X1 + b2X2 - b3X3. The results of the multiple regression analyses are summarized below: