面板协整Panel cointegration的STATA实现【xtwest】

Panel cointegration T

est

Westerlund(2007)

and

Westerlund(2008)

面板协整之误差修正技术 协整检

验，

为网友消除面板协整之痛苦，

带来迅速简洁之快乐。

源程序和说明下载见后。

运用下载包中 的数据，可以获得如下演示结果：

.

xtwest

loghex

loggdp,

westerlund

constant

trend

lags(1

3)

leads(0

3)

lrwindow(3)

Calculating Westerlund ECM panel cointegration tests..........

Results for H0: no cointegration

With 20 series and 1 covariate

Average AIC selected lag length: 2.8

Average AIC selected lead length: 1.65

Statistic

Value

Z-value

P-value

Gt

-4.082

-9.613

0.000

Ga

-27.702

-10.626

0.000

Pt

-12.969

-4.100

0.000

Pa

-22.470

-10.119

0.000

.

xtwest

loghex

loggdp,

westerlund

constant

trend

lags(1)

leads(1)

lrwindow(3) bootstrap(100)

Bootstrapping critical values under H0..........

Calculating Westerlund ECM panel cointegration tests..........

Results for H0: no cointegration

With 20 series and 1 covariate

Statistic

Value

Z-value

P-value

Robust P-value

Gt

-3.150

-4.424

0.000

0.050

Ga

-31.274

-13.027

0.000

0.000

Pt

-13.809

-5.079

0.000

0.040

Pa

-26.770

-13.339

0.000

0.000

--------------------------- -------------------------------------------------- --

---------------------------------

help for xtwest

------------ -------------------------------------------------- -----------------

---------------------- -----------

Westerlund error correction based panel cointegration tests

xtwest

depvar

varlist

[if

exp]

[in

range]

,

lags(#

[#])

leads(#

[#])

lrwindow(#) [constant trend

bootstrap(#) westerlund noisily]

xtwest

is

for

use

with

panel

data.

You

must

tsset

your

data

before

using xtwest; see help tsset.

Description

xtwest

implements

the

four

panel

cointegration

tests

developed

by

Westerlund (2007). The underlying idea

is

to

test

for

the

absence

of

cointegration

by

determining

whether

there exists error correction for

individual

panel

members

or

for

the

panel

as

a

whole.

Consider

following error correction model, where

all variables in levels are assumed to be I(1):

D.y_it = c_i + a_i1*D.y_it-1 + a_i2*D.y_it-2 + ... +

a_ip*D.y_it-p

+ b_i0*D.x_it + b_i1*D.x_it-1 + ... + b_ip*D.x_it-p

+ a_i(y_it-1 - b_i*x_it-1) + u_it

a_i provides an estimate of the speed of error-correction towards the

long run equilibrium

y_it = - (b_i/a_i) * x_it for that series i. The Ga and Gt test statistics test

H0: a_i = 0 for all i

versus

H1:

a_i

<

0

for

at

least

one

i.

These

statistics

start

from

a

weighted average of the individualy

estimated

a_i's

and

their

t-ratio's

respectively.

The

Pa

and

Pt

test

statistics pool information over all

the cross-sectional units to test H0: a_i = 0 for all i vs H1:

a_i < 0 for

all i. Rejection of H0 should