In: Statistics and Probability
Problem 2 (25 %)
Use multiple regression to estimate a model for the share of the
shadow economy of the
form:
SHADOWi = β0 + β1INCOMEi + β2UNABLEi + εi
i = 1, …, 28
List the assumptions for the regression model, and explain the
output provided by Excel.
Provide a nice and easy to read output.
How is the R2 and the standard error calculated what is the
interpretation?
What signs are found for the estimated coefficients of the
included variables and what do
you think should be expected?
How many of the variables are significant and what is the
interpretation of the p-value?
Finally, inspect the plots of residual. Is white noise
observed?
Estimate now a new multiple regression model of the form:
SHADOWi = β0 + β1INCOMEi + β2UNABLEi + β3UNEMPi + εi
i = 1, …, 28
Again set up a nice presentation of your Excel output.
Compare the two models estimated with regard to R2, the standard
error, the significance
of the estimated coefficients, and the plots of residuals
Which of the two models performs best?
DATA TABLE
Share of the shadow economy, % | GDP per capita, (1,000) € | Unable to afford life expenses, % | Long term unemployment rate, % | Life satisfaction (1 to 10) | Income quintile share ratio (S80/S20) | Location: W = West, E = East, M = Mediterranian | |
Country | SHADOW | INCOME | UNABLE | UNEMP | SATISFACTION | RATIO | LOCATION |
Belgium | 16,8 | 30,7 | 25,4 | 3,4 | 7,4 | 3,9 | W |
Bulgaria | 31,9 | 12,0 | 68,6 | 6,8 | 5,5 | 6,1 | E |
Czech Republic | 16,0 | 20,7 | 42,4 | 3,0 | 6,4 | 3,5 | E |
Denmark | 13,4 | 32,1 | 28,2 | 2,1 | 8,4 | 4,5 | W |
Germany | 13,3 | 31,5 | 33,4 | 2,5 | 7,2 | 4,3 | W |
Estonia | 28,2 | 18,2 | 44,7 | 5,5 | 6,3 | 5,4 | E |
Ireland | 12,7 | 32,9 | 31,2 | 9,1 | 7,4 | 5,2 | W |
Greece | 24,0 | 19,2 | 40,5 | 14,4 | 6,2 | 6,6 | M |
Spain | 19,2 | 24,4 | 42,1 | 11,1 | 7,5 | 7,2 | M |
France | 10,8 | 27,7 | 33,0 | 4,1 | 7,2 | 4,5 | W |
Croatia | 29,0 | 15,7 | 67,3 | 10,3 | 6,8 | 5,4 | E |
Italy | 21,6 | 25,6 | 42,5 | 5,7 | 6,9 | 5,5 | M |
Cyprus | 25,6 | 23,6 | 50,5 | 3,6 | 7,2 | 4,7 | M |
Latvia | 26,1 | 16,4 | 73,6 | 7,8 | 6,2 | 6,5 | E |
Lithuania | 28,5 | 18,3 | 60,4 | 6,6 | 6,7 | 5,3 | E |
Luxembourg | 8,2 | 67,1 | 24,8 | 1,6 | 7,8 | 4,1 | W |
Hungary | 22,5 | 17,0 | 74,3 | 4,9 | 5,8 | 4,0 | E |
Malta | 25,3 | 21,9 | 25,0 | 3,0 | 7,2 | 3,9 | M |
Netherlands | 9,5 | 32,6 | 22,0 | 1,8 | 7,7 | 3,6 | W |
Austria | 7,6 | 33,1 | 22,2 | 1,1 | 7,7 | 4,2 | W |
Poland | 24,4 | 17,1 | 54,1 | 4,1 | 7,1 | 4,9 | E |
Portugal | 19,4 | 19,4 | 35,9 | 7,7 | 6,8 | 5,8 | M |
Romania | 29,1 | 12,8 | 53,1 | 3,2 | 6,7 | 6,3 | E |
Slovenia | 23,6 | 21,4 | 45,7 | 4,3 | 7,0 | 3,4 | E |
Slovakia | 15,5 | 19,4 | 36,1 | 9,4 | 6,4 | 3,7 | E |
Finland | 13,3 | 29,4 | 27,9 | 1,6 | 8,1 | 3,7 | W |
Sweden | 14,3 | 32,2 | 17,6 | 1,5 | 8,0 | 3,7 | W |
United Kingdom | 10,1 | 26,8 | 42,9 | 2,7 | 7,3 | 5,4 | W |
Source: Eurostat | |||||||
Source: On the black economy: Friedich Schneider (2013): "The Shadow Economy in Europe 2013" Universität Linz, ATKearney and VISA. |
List the assumptions for the regression model
1) Normality distributed .
2) Variance constant
3) relationship between two or more variable must be linear .
4) independence .
For Model 1
Model1 is given by
SHADOW=182.8353 -0.30515 *INCOME + 0.207074*UNABLE
model 1 R-square = 0.6705
Adjusted R-square =0.6441
FOr Model 2
Model1 is given by
SHADOW=174.63 -0.2912*INCOME + 0.1997*UNABLE +0.1529*UNEMP
model 1 R-square = 0.6744
Adjusted R-square =0.6337
Comment - Using both the model we say that Model1 is better than model 2 becuse Adjusted R-square is better than model 2.