Multiple regression problems (restricted regression, dummy variables)

Marisol Rivers 2022-07-18 Answered
Multiple regression problems (restricted regression, dummy variables)
Q1.
Model 1: Y = X 1 β 1 + ε
Model 2: Y = X 1 β 1 + X 2 β 2 + ε
(a) Suppose that Model 1 is true. If we estimates OLS estrimator b 1 for β 1 in Model 2, what will happen to the size and power properties of the test?
(b) Suppose that Model 2 is true. If we estimates OLS estrimator b 1 for β 1 in Model 1, what will happen to the size and power properties of the test?
-> Here is my guess.
(a) b 1 is unbiased, inefficient estimator. (I calculated it using formula for "inclusion of irrelevant variable" and b 1 = ( X 1 M 2 X 1 ) 1 X 1 M 2 Y where M 2 is symmetric and idempotent matrix) Inefficient means that it has larger variance thus size increases and power increases too.
(b) b 1 is biased, efficient estimator. (I use formular for "exclusion of relevant variable" and b 1 = ( X 1 X 1 ) 1 X 1 Y) Um... I stuck here. What should I say using that information?
Q2.
Let Q and P be the quantity and price. Relation between them is different across reions of east, west, south and north, and as well, for different 4 seasons. Construct a model.
-> Actually, I don't know well about dummy variables. So any please solve this problem to help me.
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Answers (1)

Hassan Watkins
Answered 2022-07-19 Author has 18 answers
For Q1-b), take that formula b 1 = ( X 1 X 1 ) 1 ( X 1 Y ) and now plug in the true value for Y using model 2 and look what happens in the limit. You should end up with something like:
E [ b 1 ] = β 1 + β 2 b 12 where b 12 is the coefficient a regression of X 2 on X 1 (Note, I'm taking that formula from memory, so it might not be exactly correct, but it's the general idea). That will give you cases of bias.
Q2:
I don't know how advanced the class is, but usually in cases of quantity and price, we're worried about endogeneity and simultaneity. However, it seems like in this case that is not the main point of the question. If we wanted the relation between quantity and price, one option is to simply regress quantity on price. Q = β 1 P + ϵ. However, here you're told that relationship differs across regions. One way to think about this model is as follows:
Suppose there were only 2 regions North and South, and I showed you a model:
Q = β 1 P + β 2 ( P N ) + ϵ where N is a dummy variable equal to 1 in the north. In this case, β 1 could be interpreted as the effect of price on quantity when N=0, i.e. in the south and β 1 + β 2 is the effect of price on quantity when N=1; i.e. in the North. The case with 4 regions is similarly defined.
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New questions

The Porsche Club of America sponsors driver education events that provide high-performance driving instruction on actual racetracks. Because safety is a primary consideration at such events, many owners elect to install roll bars in their cars. Deegan Industries manufactures two types of roll bars for Porsches. Model DRB is bolted to the car using existing holes in the car's frame. Model DRW is a heavier roll bar that must be welded to the car's frame. Model DRB requires 20 pounds of a special high alloy steel, 40 minutes of manufacturing time, and 60 minutes of assembly time. Model DRW requires 25 pounds of the special high alloy steel, 100 minutes of manufacturing time, and 40 minutes of assembly time. Deegan's steel supplier indicated that at most 40,000 pounds of the high-alloy steel will be available next quarter. In addition, Deegan estimates that 2000 hours of manufacturing time and 1600 hours of assembly time will be available next quarter. The pro?t contributions are $200 per unit for model DRB and $280 per unit for model DRW. The linear programming model for this problem is as follows:
Max 200DRB + 280DRW
s.t.
20DRB + 25DRW 40,000 Steel Available
40DRB + 100DRW ? 120,000 Manufacturing minutes
60DRB + 40DRW ? 96,000 Assembly minutes
DRB, DRW ? 0
Optimal Objective Value = 424000.00000
Variable Value blackuced Cost
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
DRB 1000.00000 0.00000
DRW 800.00000 0.00000
Constraint Slack/ Surplus Dual Value
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
1 0.00000 8.80000
2 0.00000 0.60000
3 4000.00000 0.00000
Objective Allowable Allowable
Variable Coef?cient Increase Decrease
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
DRB 200.00000 24.00000 88.00000
DRW 280.00000 220.00000 30.00000
RHS Allowable Allowable
Constraint Value Increase Decrease
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
1 40000.00000 909.09091 10000.00000
2 120000.00000 40000.00000 5714.28571
3 96000.00000 Infnite 4000.00000
a. What are the optimal solution and the total profit contribution?
b. Another supplier offeblack to provide Deegan Industries with an additional 500 pounds of the steel alloy at $2 per pound. Should Deegan purchase the additional pounds of the steel alloy? Explain.
c. Deegan is considering using overtime to increase the available assembly time. What would you advise Deegan to do regarding this option? Explain.
d. Because of increased competition, Deegan is considering blackucing the price of model DRB such that the new contribution to profit is $175 per unit. How would this change in price affect the optimal solution? Explain.
e. If the available manufacturing time is increased by 500 hours, will the dual value for the manufacturing time constraint change? Explain.