Suppose that the general fertility rate, g f rt , is following an AR(1) process shown in the image belowA) if y1<1, what is the expression for the mean and variance of g f t rt showing any assumptions that were made .b) suppose that Var (€|gfrt-1)= as shown in the image below.explain why you may not obtain a best linear unbiased estimator of y0 and y1 by estimating (3) using OLS. 2. Suppose that the general fertility rate, gf re, is following an AR(1) process as shown in(3) below.(3)gfrt=yo+Vigfrt-1 + €t.(a) Suppose that ₁ < 1. Obtain an expression for the mean and variance of gf rt.State any assumptions you have to make and show all the steps you followed.(b) Suppose now that Var(e|gfrt) = o²gfr²_1.Briefly explain why you may not be able to obtain a Best Linear UnbiasedEstimator (BLUE) of yo and y₁ by estimating (3) using OLS. Briefly outline howyou can transform the model specification in (3) to obtain a BLUE estimator of theparameters in (3).

In this question, we are given an autoregressive (AR) model for the general fertility rate, denoted…

Answered: 2. Suppose that the general fertility…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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Suppose that the general fertility rate, g f rt , is following an AR(1) process shown in the image below

A) if y1<1, what is the expression for the mean and variance of g f t rt showing any assumptions that were made .

b) suppose that Var (€|gfrt-1)= as shown in the image below.

explain why you may not obtain a best linear unbiased estimator of y0 and y1 by estimating (3) using OLS.

2. Suppose that the general fertility rate, gf re, is following an AR(1) process as shown in
(3) below.
(3)
gfrt=yo+Vigfrt-1 + €t.
(a) Suppose that ₁ < 1. Obtain an expression for the mean and variance of gf rt.
State any assumptions you have to make and show all the steps you followed.
(b) Suppose now that Var(e|gfrt) = o²gfr²_1.
Briefly explain why you may not be able to obtain a Best Linear Unbiased
Estimator (BLUE) of yo and y₁ by estimating (3) using OLS. Briefly outline how
you can transform the model specification in (3) to obtain a BLUE estimator of the
parameters in (3).

Definition Definition Measure of central tendency that is the average of a given data set. The mean value is evaluated as the quotient of the sum of all observations by the sample size. The mean, in contrast to a median, is affected by extreme values. Very large or very small values can distract the mean from the center of the data. Arithmetic mean: The most common type of mean is the arithmetic mean. It is evaluated using the formula: μ = 1 N ∑ i = 1 N x i Other types of means are the geometric mean, logarithmic mean, and harmonic mean. Geometric mean: The nth root of the product of n observations from a data set is defined as the geometric mean of the set: G = x 1 x 2 ... x n n Logarithmic mean: The difference of the natural logarithms of the two numbers, divided by the difference between the numbers is the logarithmic mean of the two numbers. The logarithmic mean is used particularly in heat transfer and mass transfer. ln x 2 − ln x 1 x 2 − x 1 Harmonic mean: The inverse of the arithmetic mean of the inverses of all the numbers in a data set is the harmonic mean of the data. 1 1 x 1 + 1 x 2 + ...

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