You are trying to predict housing rent in a college town using the following mod

Question

You are trying to predict housing rent in a college town using the following model: u avginc lenroll lpop lrent

a. Suppose you want to test if “population” and “student enrollment” have identical effect on housing rent
in percentage. Write out the null and alternative hypotheses for this test.
b. Re-parameterize the above regression model in terms of a new parameter so that you can directly testthe null hypothesis in part a) using STATA regression output.
We need to create a new variable, say )

( lenroll

lpop ? and included it in the new regression.

1. (20 points). You are trying to predict housing rent in a college town using the following model: where: rent = housing rent in log; pope population in log lemol-student enrollments in logan ginc = averaged household income 4E 3, 124)= 143.53 3 3.329007 rob F R-squared d qared-7710 Root MSE Modiel 10.9148702 0.0000 Residual 3.1432444 124 -025349907 Tot1 | 14.053|34E 127-110693974 = .15921 95e Con Interall pop 1318217 .0303234.35 0.0001918403.0718031 I1690484 0382988 4.41 0.000 09324 2448524 00004 5.371993 enroll I avginc 0000418 2ll-0 19.7 0.000 000037E con ! 4.720442 .290 e 71e 15.99 0.000 4.188891 a. Suppose you want to test if population" and student enrollment have identical effect on housing rent in percentage. Write out the null and alternative hypotheses for thistest b. Re-parameterize the above regression model in terms of a new parameter so that you can directly test the nullhypothesis in part a) using STATA regression output. Weneed to create a new variable, say (lpop+lenroll) and included it in the new regression. c. Interpret the coefficient of avgino. d How much variation in the data of Irent is explained by the model?

Explanation / Answer

a)

Null Hypothesis: B0: 1 = 2

Alternative Hypothesis: B1: 1 2

b)

The new regression equation becomes:

Lnrent = 1studpop + 2avginc + u

Where, studpop is the student population

c)

It states that an increase in the average household income by $1 will increase rent by 0.0000418×100 = 0.00418%

d)

Since adjusted R-squared is 0.77, it implies that about 77% of the variation in lrent is explained by the model.

Related Questions

Navigate

• Browse (All)
• Browse Y
• Subjects

---

---

Integrity-first tutoring: explanations and feedback only — we do not complete graded work. Learn more.