Econometrics Assignment Example | Topics and Well Written Essays - 500 words

Econometrics - Assignment ExampleFor RM (average number of rooms in the owner occupied lodgement in the census tract), in the first variant, a 1 pct change in RM causes 0.329 % change in MV (the median housing price). In the second variant, a 1 percent change in RM causes a 0.0306 % change in the median housing price (MV). Eventually, a 1 percent changes in RM causes a 0.294 % change in the median housing price in the third variant.In the second variable, the weighted distance to five major(ip) employment centers in the Boston region (DIS), the order of coefficients 0.028, 0.027, and 0.027 in absolute values. In the criteria of absolutism, a one percent change in DIS causes a reducing of median housing price by 0.028 in the first variant, a reduction of 0.027 in the second variant, and a reduction of 0.027 in the third variant.In the third variable, nitrogen oxide concentrations in parts per hundred million (NOX), the coefficients are 1.479 and 1.529 in the second and third variants respectively. These figures suggest that 1 percent change in nitrogen oxide concentration increases the medium housing price by 1.479 in the second variant and by 1.529 in the third variant.Beta coefficient is the measure of the esthesia of the estimates in influencing the median housing price. In the estimates, the beta coefficient is the slope of the model summarized into 0, 1, 4, 3, and 2.Normally, the coefficients would imply 1 percentage change in the estimate 1 and 2 would cause an increase of 0.566 and 0.0261. However, using the beta approach, the two coefficients are below, suggesting that they are below the median housing price.6. Suppose in model (3) I added in the variable NOX DCHAS, resulting in ln(MVi) = 0 + 1RMi + 2 ln(DISi) +3NOXi + 4DCHASi + 5 NOX DCHAS +i . How would the interpretation of 3 change in model (3) after the inclusion of this variable? What is the interpretation of 5 in this model?9. Given