Question

Q1) answer the following

a) Omitting an important variable that is uncorrelated with the included regressors will lead to biased coefficients on the included regressors and incorrect coefficient signs.True or False

b)

Experience (EXP) is positively associated with earnings (EARN),
and years of schooling (S) is positively associated with earnings.
Also, EXP and S are negatively correlated in younger workers. If a
researcher estimates the regression :

log(EARNINGS) = β_{1} + β_{2}EXP + u, on younger
workers, the estimated coefficient on b_{2} will be

A. unbiased.

B. biased downwards and underrepresent the effect of EXP on earnings.

C. overestimate the effect of EXP on earnings.

D. None of these answers are correct.

c).

A researcher wishes to estimate a Cobb-Douglas production
function for a microprocessor company of the form

Y = β_{1} X_{2}^{β2}
X_{3}^{β3} X_{4}^{β4}u

where Y = #microprocessors; X2 = units of capital; X_{3} =
units of labour; and X_{4} = # computer science staff
involved in research and development. The researcher has n=30
observations and estimates the following unrestricted regression
with OLS:

LnY = 1.2 + 0.6ln X_{2} + 0.2ln X_{3} + 0.3ln
X_{4}
RSS=3157.2

In order to test the validity of the SINGLE linear restriction
of constant returns to scale,

Ho: β2+β3+β4 = 1, the researcher estimates a restricted regression
and find the following results:

Ln(Y/X_{4}) = 0.8 +
2.2ln(X_{2}/X_{4}) +
1.3ln(X_{3}/X_{4}) RSS=3683.4

(1.2) (1.0) (0.6)

The restriction is valid at a level of significance of
**1%**..True or False

Answer #1

a) Omitting an important variable that is uncorrelated with the included regressors will lead to biased coefficients on the included regressors and incorrect coefficient signs.

False.

(b) Experience (EXP) is positively associated with earnings
(EARN), and years of schooling (S) is positively associated with
earnings. Also, EXP and S are negatively correlated in younger
workers. If a researcher estimates the regression :

log(EARNINGS) = β1 + β2EXP + u, on younger workers, the estimated
coefficient on b2 will be

overestimate the effect of EXP on earnings.

(c) The restriction is valid at a level of significance of
**1%**

True.

A researcher wishes to estimate a Cobb-Douglas production
function for a microprocessor company of the form
Y = β1 X2β2
X3β3 X4β4u
where Y = #microprocessors; X2 = units of capital; X3 =
units of labour; and X4 = # computer science staff
involved in research and development. The researcher has n=30
observations and estimates the following unrestricted regression
with OLS:
LnY = 1.2 + 0.6ln X2 + 0.2ln X3 + 0.3ln
X4
RSS=3157.2
In order to...

The following regression output was obtained from a study of
architectural firms. The dependent variable is the total amount of
fees in millions of dollars.
Predictor
Coefficient
SE Coefficient
t
p-value
Constant
9.387
3.069
3.059
0.010
x1
0.232
0.204
1.137
0.000
x2
−
1.214
0.584
−
2.079
0.028
x3
−
0.273
0.424
−
0.644
0.114
x4
0.642
0.362
1.773
0.001
x5
−
0.060
0.028
−
2.143
0.112
Analysis of Variance
Source
DF
SS
MS
F
p-value
Regression
5
2,364.50
472.9...

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