Chapter 3

Question 1

is the study of the relationships between a dependent variable (Y) and one or more independent or explanatory variables (X1, X2,..).

Answer 1

Regression

Question 2

is Population Regression Function (PRF) or Population Regression (PR).

Answer 2

• E(Y|X=Xi) = f(Xi)

Question 3

• It states merely that the expected value of the distribution of Y given Xi is functionally related to Xi.

Answer 3

Population Regression Function (PRF) or Population Regression (PR).

Question 4

In simple terms, it tells how the mean or average response of Y varies with X

Answer 4

Population Regression Function (PRF) or Population Regression (PR).

Question 5

Linearity in variable

The conditional mean of the dependent variable is a linear function of the independent variables. A function Y = f(X) is linear if

Answer 5

 X appears with a power of 1 only (no X2 or √X)
 X is not multiplied or divided by another variable

Question 6

Linearity in parameters

• • The conditional mean of the dependent variable is a linear function of the parameters. if A function is linear in the parameter β1,

Answer 6

if β2 appears with a power of 1 only.

Question 7

Stochastic disturbance or stochastic error term.

Answer 7

Ui

Question 8

It is nonsystematic component

Answer 8

• Ui = Stochastic disturbance or stochastic error term

Question 9

is systematic or deterministic. It is the mean consumption expenditure of all the families with the same level of income

Answer 9

• Component E(Y|X=Xi )

Question 10

• The assumption that the regression line passes through the conditional means of Y implies that

Answer 10

E(Ui|Xi) = 0

Question 11

This is a surrogate for all variables that are omitted from the model but they collectively affect Y

Answer 11

Ui

Question 12

Why not include as many as variable into the model (or the reasons for using ui )

Answer 12

 Vagueness of theory
 Unavailability of Data
 Core Variables vs. Peripheral Variables
 Intrinsic randomness in human behavior
 Poor proxy variables
 Principle of parsimony
 Wrong functional form

Question 13

A particular numerical value obtained by the estimator in an application

Answer 13

Estimate

Question 15

SRF in stochastic form

Answer 15

Yi= B^1 +B^2X1+ U^i or Y^i + U^1

Question 16

Primary objective in regression analysis

Answer 16

Estimate the PRF on the Basis of SRF. And how to construct B^1 close to B1 and B^2 close to B2 as much as possible