Task 1
Using the dataset below and with data from the Labor Force Participation sheet, create a frequency table for each of the ten variables—i.e., all variables except age2, lfaminc, and lhours.
For example:
Variable (labforce)
Frequency Relative Frequency Percentage
Create graphs describing each variable using percentages.
You should create ten figures.
Watch the tutorial video or attend the live tutorial session for assistance. To create frequency tables, use the ‘countif’ function in excel.
Graphs must be well-labeled to earn full points in this assignment section.
Each figure must have a title, axes must be labeled with intuitive labels, check the codebook for variable labels.
For example, use “white” and “non-white” instead of “1” and “0”
Be creative with font size, colors, and types of graphs. Just ensure to use the appropriate graphs for categorical variables. Please see the graphs I created in the pdf file labeled graphs, as a guide.
You must submit your Excel file with all calculations. You will receive partial points if you submit a pdf with your graphs with no description.
Task 2
Write at least two sentences but no more than three describing each figure.
Task 3
Use Excel to run two regression models: one for labor force participation rate (labforce) and another for log(hours per week – lhours). That is labforce and lhours are the dependent variables.
In each model, the independent variables should be age, age-squared, the white dummy, dummies for high school and college graduation status, number of children under 6, number of children aged 6-18, the non-married dummy, and unearned income.
(If you have experience running regressions with different software like R, feel free to use this software.)
Your regression models will take the following form:
Using data from the Labor Force Participation sheet, run Equation 1
Using data from Hours Worked sheet, run Equation 2
Note that the sample on each sheet is different.
Task 4
In your pdf document, include the regression results in a table format with numbers represented using four decimal places. You should have two tables.
For example
The dependent variable is the labor force participation rate for women 18 to 65 years as of March 2023, and the following table provides the regression estimates.
Coefficients
Standard Error
t Stat
P-value
Intercept
0.2774
0.0139
19.8959
0.0000
age
-0.0023
0.0007
-3.1090
0.0019
age2
0.0000
0.0000
-0.3780
0.7055
child6
-0.0132
0.0028
-4.7033
0.0000
Task 5
Re-write Equations 1 and 2 with the estimates for each equation with numbers represented using two/three decimal places, for example:
Task 6
Write two paragraphs but no more than one page with an interpretation of each estimated coefficient from Equations 1 and 2.
Summarize by saying whether the results of these regressions are roughly consistent with the time-allocation model discussed in Chapter 2.
Note: the regression estimates represent percentage point changes and not percent changes.
