Springer Texts in Business and Economics

Using EViews, Qt+i is simply Q(1) and one can set the sample range from 1954-1976

a. The OLS regression over the period 1954-1976 yields RSt = -6.14 + 6.33 Qt+1 - 1.67 Pt

(8.53) (1.44) (1.37)

with R2 = 0.62 and D. W. = 1.07. The t-statistic for у = 0 yields

t = -1.67/1.37 = -1.21 which is insignificant with a p-value of 0.24.

Therefore, the inflation rate is insignificant in explaining real stock returns.

LS // Dependent Variable is RS Sample: 1954 1976 Included observations: 23

Variable

Coefficient

Std. Error t-Statistic

Prob.

C

-6.137282

8.528957 -0.719582

0.4801

Q(1)

6.329580

1.439842 4.396024

0.0003

P

-1.665309

1.370766 -1.214875

0.2386

R-squared

0.616110

Mean dependent var

8.900000

Adjusted R-squared

0.577721

S. D. dependent var

21.37086

S. E. of regression

13.88743

Akaike info criterion

5.383075

Sum squared resid

3857.212

Schwarz criterion

5.531183

Log likelihood

91.54095

F-statistic

16.04912

Durbin-Watson stat

1.066618

Prob(F-statistic)

0.000070

b. The D. W. = 1.07. for n = 23 and two slope coefficients, the 5% critical

values of the D. W. are dL = 1.17 and dU = 1.54. Since 1.07 < dL, this

indicates the presence of positive serial correlation.

c. The Breusch and Godfrey test for first-order serial correlation runs the regression of OLS residuals et on the regressors in the model and et_i. This yields

et = -4.95 + 1.03 Qt+1 + 0.49 Pt + 0.45 et_

(8.35) (1.44) (1.30) (0.22)

with R2 = 0.171 and n = 23. The LM statistic is nR2 which yields 3.94. This distributed as x1 under the null hypothesis and has a p-value of 0.047. This is significant at the 5% level and indicates the presence of first-order serial correlation.

Breusch-Godfrey Serial Correlation LM Test:

F-statistic 3.922666 Probability 0.062305

Obs* R-squared 3.935900 Probability 0.047266

Test Equation:

LS // Dependent Variable is RESID

Variable

Coefficient

Std. Error

t-Statistic

Prob.

C

-4.953720

8.350094

-0.593253

0.5600

Q(1)

1.030343

1.442030

0.714509

0.4836

P

0.487511

1.303845

0.373903

0.7126

RESID (-1)

0.445119

0.224743

1.980572

0.0623

d. The Cochrane-Orcutt yields the following regression RS* = - 14.19 + 7.47 Q* , - 0.92 P*

(9.34) (1.20) + 1 (1.63)

where RS* = RSt — pRSt_1, Qt*+1 = Qt+1 — pQt and Pt* = Pt — pPt_1 with

Pco = 0.387.

e. The AR(1) options on EViews yields the following results:

RSt = —7.32 + 5.91 Qt+1 — 1.25 Pt

(7.92) (1.36) (1.28)

with R2 = 0.68. The estimate of p is p = —0.027 with a standard error of 0.014 and a t-statistic for p = 0 of —1.92. This has a p-value of 0.07. Note that even after correcting for serial correlation, Pt remains insignificant while Qt+1 remains significant. The estimates as well as their standard errors are affected by the correction for serial correlation. Compare with part (a).

PRAIS-WINSTEN PROCEDURE

LS // Dependent Variable is RS Sample: 1954 1976 Included observations:23 Convergence achieved after 4 iterations

Variable

Coefficient

Std. Error

t-Statistic

Prob.

C

-7.315299

7.921839

-0.923435

0.3674

Q(1)

5.905362

1.362572

4.333981

0.0004

P

-1.246799

1.277783

-0.975752

0.3414

AR(1)

-0.027115

0.014118

-1.920591

0.0699

R-squared

0.677654

Mean dependent var

8.900000

Adjusted R-squared

0.626757

S. D. dependent var

21.37086

S. E. of regression

13.05623

Akaike info criterion

5.295301

Sum squared resid

3238.837

Schwarz criterion

5.492779

Log likelihood

-89.53155

F-statistic

13.31429

Durbin-Watson stat

1.609639

Prob (F-statistic)

0.000065

Inverted AR Roots

-.03

Добавить комментарий

Springer Texts in Business and Economics

The General Linear Model: The Basics

7.1 Invariance of the fitted values and residuals to non-singular transformations of the independent variables. The regression model in (7.1) can be written as y = XCC-1" + u where …

Regression Diagnostics and Specification Tests

8.1 Since H = PX is idempotent, it is positive semi-definite with b0H b > 0 for any arbitrary vector b. Specifically, for b0 = (1,0,.., 0/ we get hn …

Generalized Least Squares

9.1 GLS Is More Efficient than OLS. a. Equation (7.5) of Chap. 7 gives "ois = " + (X'X)-1X'u so that E("ois) = " as long as X and u …

Как с нами связаться:

Украина:
г.Александрия
тел./факс +38 05235  77193 Бухгалтерия
+38 050 512 11 94 — гл. инженер-менеджер (продажи всего оборудования)

+38 050 457 13 30 — Рашид - продажи новинок
e-mail: msd@msd.com.ua
Схема проезда к производственному офису:
Схема проезда к МСД

Партнеры МСД

Контакты для заказов шлакоблочного оборудования:

+38 096 992 9559 Инна (вайбер, вацап, телеграм)
Эл. почта: inna@msd.com.ua