Lag length criteria, Macroeconomics

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Lag Length criteria

VAR Lag Order Selection Criteria

 

 

 

 

Endogenous variables: OIL EXCH R RPI LUNEMP GDP 

 

 

 

Exogenous variables: C 

 

 

 

 

Date: 04/10/12   Time: 09:40

 

 

 

 

Sample: 1980Q1 2011Q4

 

 

 

 

Included observations: 90

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 Lag

LogL

LR

FPE

AIC

SC

HQ

 

 

 

 

 

 

 

 

 

 

 

 

 

 

0

-1297.398

NA 

 152838.1

 28.96439

 29.13105

 29.03160

1

-629.2589

 1232.345

 0.121419

 14.91686

 16.08344

 15.38730

2

-546.9702

 140.8050

 0.043857

 13.88823

  16.05473*

  14.76189*

3

-502.2073

 70.62590

 0.037065

 13.69350

 16.85992

 14.97039

4

-469.5335

 47.19560

 0.042007

 13.76741

 17.93376

 15.44753

5

-424.0268

 59.66430

 0.037071

 13.55615

 18.72242

 15.63950

6

-377.6019

 54.67826

 0.033616

 13.32449

 19.49068

 15.81106

7

-312.0832

 68.43057

 0.021261

 12.66852

 19.83464

 15.55832

8

-247.3143

  59.01173*

  0.014906*

  12.02921*

 20.19525

 15.32223

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 * indicates lag order selected by the criterion

 

 

 

 LR: sequential modified LR test statistic (each test at 5% level)

 

 

 FPE: Final prediction error

 

 

 

 

 AIC: Akaike information criterion

 

 

 

 

 SC: Schwarz information criterion

 

 

 

 

 HQ: Hannan-Quinn information criterion

 

 

 

 

 

 

 

 

 

 

Fig - Table of Lag Order Selection Criteria from Eviews

From Fig it can be seen that the AIC statistic minimises at a lag length of 8. Therefore, according to Akaike, this should be the lag length which is used in the VAR model. However it can also be seen that the SC and HQC both minimise at the lag length 2. As the lag length 2 satisfies more than one criterion, and therefore the majority of criteria assessed in this paper, this length will be chosen.This length should produce the best goodness of fit for the VAR model.


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