Durbin–Watson - Regression on the Transformed Data - Econometrics Assignment Help

Assignment Task:

1.         (a) A model was constructed to study the spending behaviour of 240 Malaysian consumers. Total spending (S) was regressed on income (I) and financial literacy rate (L). The following estimation was obtained in the survey (standard errors are in parentheses):

Si   = 263.6416 + 0.0056 Ii  – 2.2316 Li        Model 3.1

Se = (11.5932)            (0.0019)           (0.2099)

R2 = 0.7077    Adjusted R2 = 0.6981

Now suppose an additional variable, wealth (W) is included in the model. From previous studies, it is found that wealth and income are highly correlated variables. The following regression results are obtained

Si   = 168.3067 + 0.0055 Ii – 1.7680 Li + 12.8686 Wi          Model 3.2

se = (32.8916) (0.0018) (0.2480) (4.1905)

R2 = 0.7473    Adjusted R2 = 0.7347

(i)         Compare the regression results obtained from Model 3.1 and Model 3.2, what changes can you observe? What can you say about the collinearity problem in Model 3.2?     

(ii)        Is it worth adding the variable W to the model? Why?        

(b)        The data on research and development (R&D) expenditure and sales for 31 industry groupings were collected in 2019, to examine the impact of sales on R&D expenditure. All data were measured in RM millions.

(i)         Formulate the econometrics model.  

(ii)       Using the data given by R&D.xlsx, estimate your model as stated in b (i) and interpret your regression results.        

(iii)       What problem may exist in your estimation in b (ii)? Use an appropriate test to test whether the problem exists in the model, at 5% level of significance? 

(iv)       How would you rectify the problem as stated in (iii)? Show the results of the test for the problem and the regression output which is free from the problem.

2.         (a) Consider the following model for a sample size, n = 65

Yi  = 132.809 – 0.001X1i + 2.794X2i + 0.796X3i + 0.017X4i

t = [2.720]       [-0.402]           [1.051] [1.282] [0.556]

R2 = 0.9478    Model 4.1

(i)         What problem(s) may exist in Model 4.1?  

(ii)        Discuss three possible solutions to the problem.        

(b)  (i)  Refer to the data given in Sales.xlsx, estimate the following regression model and interpret the regression result.  (4 marks)

Yt = β1 + β2 Xt + ut

Where  Y = Inventories (RM) X = Sales (RM)

(ii)        Check the Durbin–Watson d statistic and comment on the nature of autocorrelation in the data (Si = 0.01).          

(iii)       Estimate ρ, and transform the data to run the regression on the transformed data. Show the regression output of the transformed model.     

(iv)       Check for the existence of autocorrelation in the transformed model (Si = 0.01).

This Econometrics Assignment has been solved by our Econometrics Experts at My Uni Paper. Our Assignment Writing Experts are efficient to provide a fresh solution to this question. We are serving more than 10000+ Students in Australia, UK & US by helping them to score HD in their academics. Our Experts are well trained to follow all marking rubrics & referencing style.

Be it a used or new solution, the quality of the work submitted by our assignment experts remains unhampered. You may continue to expect the same or even better quality with the used and new assignment solution files respectively. There’s one thing to be noticed that you could choose one between the two and acquire an HD either way. You could choose a new assignment solution file to get yourself an exclusive, plagiarism (with free Turnitin file), expert quality assignment or order an old solution file that was considered worthy of the highest distinction.