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2020/07/16

Econometrics I’s Homework

Deadline: July 22, 2020, PM23:59:59

The answer should be written in English or Japanese.

Your name and student ID number should be included in your answer sheet.

Send your answer to the email address: tanizaki@econ.osaka-u.ac.jp.

The subject should be Econome 1 or

計量

1. Otherwise, your mail may go to the trash box.

Using annual data from 1982 to 2004, we estimate a demand function of bread. The notations are as follows:

Q

1t:

Purchase volume of bread at time t (1g)

Y

t

Income at time t (Japanese yen, and 2000 base year)

P

1t

Price of bread at time t (Japanese yen per 100g, and 2000 base year) P

2t:

Price of rice at time t (Japanese yen per 1kg, and 2000 base year) We have estimated the following demand function:

log Q

1t

= 5.899

(2.90)

+ 0.644

(4.132)

log Y

t

1.205

(13.19)

log P

1t

+ 0.00756

(0.242)

log P

2t

, (1)

R

2

= 0.925, R

2

= 0.913, σ ˆ

2

= 0.016564

2

, DW = 1.212, log L = 63.87, Estimation period: 1982 to 2004,

where the values in the parentheses denote the t-values, R

2

represents the coefficient of determination, R

2

indicates the adjusted coefficient of determination, ˆ σ is the standard error in the regression equation, DW denotes the Durbin-Watson statistic, and log L represents the estimate of the log-likelihood function.

Using the residuals in Eq. (1), denoted by b u

t

, we have estimated the following.

b

u

t

= 0.366

(1.79)

b u

t−1

, (2)

R

2

= 0.131, R

2

= 0.131, σ ˆ

2

= 0.014363

2

, DW = 1.793, log L = 62.64,

Estimation period: 1983 to 2004.

(2)

Moreover, assuming that the error term in Eq. (1) is the first-order autocorrelated and using the maximum likelihood method, we have obtained the following estimation results:

log Q

1t

= 6.33

(2.62)

+ 0.613

(3.38)

log Y

t

1.223

(12.7)

log P

1t

+ 0.0263

(0.615)

log P

2t

(3)

R

2

= 0.936, R

2

= 0.922, σ ˆ

2

= 0.015769

2

, DW = 1.739, log L = 65.58, ˆ

ρ = 0.402

(1.90)

, Estimation period: 1982 to 2004,

where ˆ ρ denotes the first-order autocorrelation coefficient estimate in the error term, and the value in the parenthesis of ˆ ρ indicates its t-value.

(1) Using the Lagrange multiplier test, explain how to test the first-order autocorrelation in the error term.

(2) Using the likelihood ratio test, explain how to test the first-order autocorrelation in the error term.

(3) Using the Wald test, explain how to test the first-order autocorrelation in the error term.

参照

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