ECO-315 - Econometrics - Economics Assignment Help

Assignment Task

Introduction
The assignment makes use of the 2014 ‘General Household Survey’ which was conducted by
Statistics South Africa. For more information about this dataset in general or its variables in particular, please consult the ‘Metadata’ file and the questionnaire. However, note that some of the variables provided were derived by your lecturers to make your lives a bit easier, so you will not find them mentioned in the Metadata file. (Also note that the dataset provided to you consists of only a small subset (n=2,416 households) of GHS’s variables and observations.) The assignment dataset is available on RUConnected (see the ‘practice datasets’ folder) as both an Excel and STATA file. The name of the file you want to open is ‘GHS_2014 for ECO 315 Assignment.xls’ or ‘GHS_2014 for ECO 315 Assignment.dta’.

Preparatory steps
Before you jump in and start analysing the data, you need to look at some of the variables. For the present assignment, an important variable is ‘totmhinc’, which stands for total monthly household income. The variable for total per capita household income, (PCINC) is simply the total monthly household income divided by household size. The other variables of interest are as follows:
Variable name Description
hholdsz Total household size
head_yrschool Years of education attained by the household head
mean_yrschool Average years of education for adults (over 18) in the household

Your models
You want to test the proposition that household income is a function of education, but
generally bearing in mind that other variables may also be important. Consider four ways of testing this relationship using regression analysis:.totmhinc = ? + ?(head_yrschool) + ?
PCINC = ? + ?(head_yrschool) + ?
totmhinc = ? + ?1(mean_yrschool) + ?2(hholdsz) + ?
PCINC = ? + ?1(mean_yrschool) + ?2(hholdsz) + ?
NB: Run each of these models and present your results in tables (similar to those from the lecture slides)

Questions
For regression (a), report the results and, using your own words, interpret the results.
For regression (b), report the results and using your own words, interpret the results.
For regression (c), report the results/output and, using your own words, interpret the results.
Explain in your own words why the results for regressions (c) and (d) might be so different.
Based on regression (d) calculate the predicted per capita household income for a household with four members and an average of 11 years of education (among adults in the household).
For regression (c) run the normality test for residuals and interpret the output.
For regression (a) explain whether the model is a good fit with the data. Be specific and use at least two statistics to support your evaluation of the model.
Interpret the R2 for model (d)? Use precise language to describe what we can say about the model from this statistic.

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