WOW !! MUCH LOVE ! SO WORLD PEACE !
Fond bitcoin pour l'amélioration du site: 1memzGeKS7CB3ECNkzSn2qHwxU6NZoJ8o
  Dogecoin (tips/pourboires): DCLoo9Dd4qECqpMLurdgGnaoqbftj16Nvp


Home | Publier un mémoire | Une page au hasard

 > 

The role of National Bank of Rwanda from 1995 to 2010

( Télécharger le fichier original )
par Paterne RUKUNDO
National University of Rwanda - A0 2011
  

précédent sommaire

Bitcoin is a swarm of cyber hornets serving the goddess of wisdom, feeding on the fire of truth, exponentially growing ever smarter, faster, and stronger behind a wall of encrypted energy

APPENDICES

1. ORGINAL DATA OF USED VARIABLE IN TAYLOR RULE

years

GDPt

EXCHt

Mt

INFt

GDP tar

INF tar

1995

337.2

297.69

62.9

48.249

324.897

38.386

1996

431.4

304.16

75.6

13.434

411.751

8.736

1997

562.4

304.67

92.5

11.689

546.526

16.615

1998

632.1

330.72

97.8

6.842

605.629

-5.958

1999

677

349.53

104.2

-2.423

606.991

2.057

2000

732.2

430.49

119.5

3.901

676.099

5.832

2001

799.4

443.74

130.7

3.366

741.872

-0.219

2002

872.7

471.93

144.3

1.975

797.439

6.165

2003

993

516.07

167.5

7.445

992.597

7.677

2004

1,206

577.52

187.4

11.951

1,206.23

10.236

2005

1,440

557.81

218.4

9.122

1,439.83

5.608

2006

1,716

551.8

286

8.831

1,716.32

12.138

2007

2,046

547

375.1

9.081

2,049.26

6.579

2008

2,577

546.8

384.1

15.436

2,565.29

22.323

2009

2,990

568.27

402

10.4

2,964.07

5.737

2010

3,282

813

516.7

6.4

3,278.26

0.227

Source: NBR, NISR, MINECOFIN AND http://www.economywatch.com/economic-statistics/Rwanda/General Government Total Expenditure Percentage GDP/

1. VALUES OF ALL USED VARIABLES IN TAYLOR RULE

obs

MT

M1

IG

IG1

YG

YG1

DEXCH

DEXCH1

1995

62.9

NA

-9.863

NA

12.303

NA

NA

NA

1996

75.6

62.9

-4.698

-9.863

19.649

12.303

6.47

NA

1997

92.5

75.6

4.926

-4.698

15.874

19.649

0.51

6.47

1998

97.8

92.5

-12.8

4.926

26.471

15.874

26.05

0.51

1999

104.2

97.8

4.48

-12.8

70.009

26.471

18.81

26.05

2000

119.5

104.2

1.931

4.48

56.101

70.009

80.96

18.81

2001

130.7

119.5

-3.585

1.931

57.528

56.101

13.25

80.96

2002

144.3

130.7

4.19

-3.585

75.261

57.528

28.19

13.25

2003

167.5

144.3

0.232

4.19

0.403

75.261

44.14

28.19

2004

187.4

167.5

-1.715

0.232

-0.23

0.403

61.45

44.14

2005

218.4

187.4

-3.514

-1.715

0.17

-0.23

-19.71

61.45

2006

286

218.4

3.307

-3.514

-0.32

0.17

-6.01

-19.71

2007

375.1

286

-2.502

3.307

-3.26

-0.32

-4.8

-6.01

2008

384.1

375.1

6.887

-2.502

11.71

-3.26

-0.2

-4.8

2009

402

384.1

-4.663

6.887

25.93

11.71

21.47

-0.2

2010

516.7

402

-6.173

-4.663

3.74

25.93

244.73

21.47

Source of basic data: NBR, NISR, MINECOFIN and are done in E-VIEWS 3.1

Where: MT = Current money stock

M1= Previous money stock

IG= Current inflation gap

IG1= Previous inflation gap

YG= Current output gap

YG1= Previous output gap

DEXCH= Current variation of exchange

DEXCH1= Previous variation of exchange

2. AIC AND SIC FOR FINDING USED LAGS

 

 

 

AIC

 

SIC

 

 

CHOOSEN LAG

 

LAG

INT

INT AND TRE

NONE

INT

INT AND TRE

NONE

 

MT

0

9.641715

9.688929

9.50839

9.736122

9.830539

9.555593

LAG IS 0

 

1

9.866872

9.887956

9.724115

10.00381

10.07054

9.815408

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

M1

0

9.296327

9.208122

9.206107

9.387621

9.345063

9.251754

LAG IS 0

 

1

9.458962

9.25416

9.374977

9.589335

9.427991

9.461892

 

 

 

 

 

 

 

 

 

 

IG

0

6.206957

6.322018

6.14714

6.301364

6.463628

6.194343

 

 

1

6.064265

6.142289

6.01912

6.201206

6.324877

6.110414

LAG IS 1

 

 

 

 

 

 

 

 

 

IG1

0

6.143109

6.098601

6.039519

6.234403

6.235541

6.085166

 

 

1

6.097979

5.82158

5.845228

6.097979

5.99541

5.932143

LAG IS 1

 

 

 

 

 

 

 

 

 

YG

0

9.560466

9.683185

9.419062

9.65176

9.820126

9.464709

LAG IS 1

 

1

9.790076

9.907057

9.637297

9.920449

10.08089

9.724212

 

 

 

 

 

 

 

 

 

 

YG1

0

9.612163

9.763314

9.458669

9.699078

9.893687

9.502127

 

 

1

9.872514

10.02692

9.706344

9.993741

10.18856

9.787161

LAG IS 0

 

 

 

 

 

 

 

 

 

DEXCH

0

11.61242

11.63065

11.53175

11.69933

11.76102

11.57521

 

 

1

11.88346

11.84749

11.78135

12.00469

12.00912

11.86217

LAG IS 0

 

 

 

 

 

 

 

 

 

DEXCH1

0

9.755819

9.832075

9.856065

9.842734

9.962448

9.899522

 

 

1

9.988968

9.93752

10.04704

10.11019

10.09916

10.12786

LAG IS 0

 

 

 

 

 

 

 

 

 

R

0

10.02276

10.10345

9.930729

10.09511

10.21197

9.966901

 

 

1

10.31132

10.20734

10.22258

10.40209

10.32838

10.2831

LAG IS 0

 

 

 

 

 

 

 

 

 

R1

0

10.1346

10.10586

9.995851

10.19512

10.19663

10.02611

 

 

1

10.46616

9.93182

10.32152

10.53191

10.01948

10.36535

LAG IS 1

Source of basic data: NBR, NISR and MINECOFIN

2(100/n)0.25 = 1.8, this shows that we stop at lag 1.

3. ERROR CORRECTION MODEL

DMT=B0+ B1DM1 +B2DIG +B3DIG1 +B4DYG +B5DYG1 + B6DDEXCH + B7DDEXCH1 + DR

Dependent Variable: MT-MT(-1)

Method: Least Squares

Date: 09/19/11 Time: 10:01

Sample(adjusted): 1998 2010

Included observations: 13 after adjusting endpoints

Variable

Coefficient

Std. Error

t-Statistic

Prob.

C

28.09017

8.530250

3.293007

0.0110

IG-IG(-1)

0.499831

0.999226

0.500218

0.6304

YG-YG(-1)

-0.317961

0.348275

-0.912961

0.3879

DEXCH-DEXCH(-1)

0.222279

0.125268

1.774425

0.1139

RESID-RESID(-1)

0.515337

0.312843

1.647271

0.1381

R-squared

0.527088

Mean dependent var

32.63077

Adjusted R-squared

0.290633

S.D. dependent var

35.03913

S.E. of regression

29.51134

Akaike info criterion

9.891149

Sum squared resid

6967.352

Schwarz criterion

10.10844

Log likelihood

-59.29247

F-statistic

2.229121

Durbin-Watson stat

1.000899

Prob(F-statistic)

0.155471

Source: Done in E-VIEWS 3.1

After estimating the error correction model, it is found that all probabilities are greater than 5% this verifies that each explanatory variable has an effect on explained variable (MT).

4. RAMSEY RESET TEST FOR MODEL SPECIFICATION

Ramsey RESET Test:

F-statistic

31.08468

Probability

0.061410

Log likelihood ratio

58.04147

Probability

0.072100

 
 
 
 
 

Test Equation:

Dependent Variable: MT

Method: Least Squares

Date: 09/19/11 Time: 09:53

Sample: 1997 2010

Included observations: 14

Variable

Coefficient

Std. Error

t-Statistic

Prob.

C

4.001070

197.2238

0.020287

0.9857

MT(-1)

4.339922

7.446307

0.582829

0.6190

IG

-5.797933

12.89962

-0.449465

0.6971

IG(-1)

-8.277322

19.41283

-0.426384

0.7113

YG

-1.842925

4.348232

-0.423833

0.7129

YG(-1)

1.287048

2.608869

0.493336

0.6706

DEXCH

0.255345

0.632645

0.403615

0.7256

DEXCH(-1)

-0.784084

1.650993

-0.474917

0.6817

FITTED^2

-0.046524

0.054793

-0.849073

0.4853

FITTED^3

0.000276

0.000205

1.347810

0.3101

FITTED^4

-6.66E-07

3.58E-07

-1.858988

0.2041

FITTED^5

5.56E-10

2.38E-10

2.338133

0.1443

R-squared

0.999651

Mean dependent var

230.4429

Adjusted R-squared

0.997732

S.D. dependent var

137.8947

S.E. of regression

6.567172

Akaike info criterion

6.370419

Sum squared resid

86.25550

Schwarz criterion

6.918183

Log likelihood

-32.59293

F-statistic

520.8801

Durbin-Watson stat

2.655976

Prob(F-statistic)

0.001918

Source: Done in E-VIEWS 3.1

Ramsey RESET Test, as all probabilities are greater than 5%, this shows that the model is well specified.

5. AUTOCORRELATION TEST OF DARBIN WATSON (DW)

DW TABLE

0 4

2

(1.177) (1.732) (2.268) (2.823)

dL du 4-du 4-dL

Source: statistical tables

DW =2.461915 =where the DW is placed on table.

DW is in the indecision zone near no autocorrelation zone, so DW is associated in the zone of no autocorrelation.

6. TEST FOR COINTEGRATION

In econometric literature, it is not clear whether cointegration should be applied to only series integrated of the same order. Though Verbeck (2004) noted that the concept of cointegration can be applied to (nonstationary) integrated time series only and Dickey et al, quoted by Gujarati (2004), stipulated that Cointegration deals with the relationship among a group of variables, where (unconditionally) each has a unit root, however Brooks (2004) stressed that it is also possible to combine levels and first differenced terms in a VECM. The later therefore illustrates that cointegration can exist among variables not integrated of the same order.

Heij et al (2004) stated by gujarati (2009) developed the mathematical proof of this view where they asserted that a cointegration relationship exists between stationary and nonstationary variables. If their mathematical proof is put in simple terms, there are three possibilities in VAR with many variables: If m: the number of variables, r = rank of the matrix of coefficients and also the number of cointegration relations, therefore:

· If all variables are stationary, r = m and all roots lie outside the unit cycle

· If all variables are not stationary, r = 0, there are m unit roots or m stochastic trends.

· If some variables are stationary and others not stationary, r = 0< r < m, there are m-r unit roots, the polynomial have m-r common stochastic trends and there are r cointegrating relations.

As all variables are stationary, Johansen cointegration test has been used to determine whether there exist a long-run relationship between these variables. This test was preferred to Engle-Granger approach because in case of six variables we may have more than one cointegrating relationship (Brooks, 2004).

précédent sommaire






Bitcoin is a swarm of cyber hornets serving the goddess of wisdom, feeding on the fire of truth, exponentially growing ever smarter, faster, and stronger behind a wall of encrypted energy








"Et il n'est rien de plus beau que l'instant qui précède le voyage, l'instant ou l'horizon de demain vient nous rendre visite et nous dire ses promesses"   Milan Kundera