Econometrics: Multicollinearity and Heteroscedastisity

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Activity 12. Multicollinearity and Heteroscedasticity INTRODUCTION TO ECONOMETRY Consider the excel file “Real_Estate” that contains the variables of the sale price of the house (in thousands of dollars), the number of bedrooms, the size of the house, if it has a pool, the distance to the city center, if it has parking, the number of bathrooms. 1.- How are these variables related? Write the econometric model to estimate and the results of the estimation of said model 2.- Analyze the individual significance of the estimators and the model. (do the analysis based on the value of p) 3.- Show 2 tests (WHITE and GODFREY) oriented to the search for Heteroscedasticity in the model. Point out: a) what test is it? b) What is the null hypothesis being worked on? c) What is the value of the statistic? d) what is the conclusion? 4.- Show 2 tests (VARIANCE INFLATION FACTOR and CONDITION INDEX) oriented to the search for multicollinearity in the model. Point out: a) what test is it? b) What is the null hypothesis being worked on? c) What is the value of the statistic? d) what is the conclusion? 5.- Final conclusions, using the results of the tests made.

Sheet1 Price Bedrooms Size Swimming Pool Distance Parking lots Bathrooms 263.1 4 2300 1 17 1 2 182.4 4 2100 0 19 0 2 242.1 3 2300 0 12 0 2 213.6 2 2200 0 16 0 2.5 139.9 2 2100 0 28 0 1.5 245.4 2 2100 1 12 1 2 327.2 6 2500 0 15 1 2 271.8 2 2100 0 9 1 2.5 221.1 3 2300 1 18 0 1.5 266.6 4 2400 0 13 1 2 292.4 4 2100 0 14 1 2 209 2 1700 0 8 1 1.5 270.8 6 2500 0 7 1 2 246.1 4 2100 0 18 1 2 194.4 2 2300 0 11 0 2 281.3 3 2100 0 16 1 2 172.7 4 2200 1 16 0 2 207.5 5 2300 1 21 0 2.5 198.9 3 2200 1 10 1 2 209.3 6 1900 1 15 1 2 252.3 4 2600 0 8 1 2 192.9 4 1900 1 14 1 2.5 209.3 5 2100 0 20 0 1.5 345.3 8 2600 0 9 1 2 326.3 6 2100 0 11 1 3 173.1 2 2200 1 21 1 1.5 187 2 1900 0 26 0 2 257.2 2 2100 0 9 1 2 233 3 2200 0 14 1 1.5 180.4 2 2000 0 11 0 2 234 2 1700 0 19 1 2 207.1 2 2000 0 11 1 2 247.7 5 2400 0 16 1 2 166.2 3 2000 1 16 1 2 177.1 2 1900 0 10 1 2 182.7 4 2000 1 14 0 2.5 216 4 2300 0 19 0 2 312.1 6 2600 0 7 1 2.5 199.8 3 2100 0 19 1 2 273.2 5 2200 0 16 1 3 206 3 2100 1 9 0 1.5 232.2 3 1900 1 16 1 1.5 198.3 4 2100 1 19 1 1.5 205.1 3 2000 1 20 0 2 175.6 4 2300 1 24 1 2 307.8 3 2400 1 21 1 3 269.2 5 2200 0 8 1 3 224.8 3 2200 0 17 1 2.5 171.6 3 2000 1 16 0 2 216.8 3 2200 0 15 1 2 192.6 6 2200 1 14 0 2 236.4 5 2200 0 20 1 2 172.4 3 2200 0 23 0 2 251.4 3 1900 0 12 1 2 246 6 2300 0 7 1 3 147.4 6 1700 1 12 0 2 176 4 2200 0 15 1 2 228.4 3 2300 0 17 1 1.5 166.5 3 1600 1 19 0 2.5 189.4 4 2200 0 24 1 2 312.1 7 2400 0 13 1 3 289.8 6 2000 0 21 1 3 269.9 5 2200 1 11 1 2.5 154.3 2 2000 0 13 0 2 222.1 2 2100 0 9 1 2 209.7 5 2200 1 13 1 2 190.9 3 2200 1 18 1 2 254.3 4 2500 1 15 1 2 207.5 3 2100 1 10 0 2 209.7 4 2200 1 19 1 2 294 2 2100 0 13 1 2.5 176.3 2 2000 1 17 0 2 294.3 7 2400 0 8 1 2 224 3 1900 1 6 1 2 125 2 1900 0 18 0 1.5 236.8 4 2600 1 17 1 2 164.1 4 2300 0 19 0 2 217.8 3 2500 0 12 0 2 192.2 2 2400 0 16 0 2.5 125.9 2 2400 0 28 0 1.5 220.9 2 2300 1 12 1 2 294.5 6 2700 0 15 1 2 244.6 2 2300 0 9 1 2.5 199 3 2500 1 18 0 1.5 240 4 2600 0 13 1 2 263.2 4 2300 0 14 1 2 188.1 2 1900 0 8 1 1.5 243.7 6 2700 0 7 1 2 221.5 4 2300 0 18 1 2 175 2 2500 0 11 0 2 253.2 3 2300 0 16 1 2 155.4 4 2400 1 16 0 2 186.7 5 2500 1 21 0 2.5 179 3 2400 1 10 1 2 188.3 6 2100 1 15 1 2 227.1 4 2900 0 8 1 2 173.6 4 2100 1 14 1 2.5 188.3 5 2300 0 20 0 1.5 310.8 8 2900 0 9 1 2 293.7 6 2400 0 11 1 3 179 3 2400 0 8 1 2 188.3 6 2100 1 14 1 2.5 227.1 4 2900 0 20 0 1.5 173.6 4 2100 0 9 1 2 188.3 5 2300 0 11 1 3

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