nataliia cherkas phd, associate professor lviv academy of ... · nataliia cherkas phd, associate...

NATALIIA CHERKAS PhD, Associate Professor

Lviv Academy of Commerce, Department of International Economic Relations

e-mail: natsanex@yahoo.com

The 7th Professor Aleksander ZeliasInternational Conference on Modellingand Forecasting of Socio-Economic PhenomenaMay 7-10, 2013, Zakopane, Poland

1.Background2.Data overview3.2SLS model 4.Vector autoregression (VAR) estimations5.Kalman filter approach6.Conclusions

Key words: export structure, industrial production, exchange rate, import elasticity

2

Domination of export mainly by commoditieswith low value added

Critical dependence on imported natural gas and oil

Maintenance of depreciated exchange rate Direct and indirect budget support for

primary sector Growing inflation Limited possibilities of industrial production Economic populism

3

4

Currency devaluation

Obstructions for investment imports

Limited possibilities of production

Retraction of credit resources

Budget support for primary sector

Insufficiency of infrastructure

Maintenance of depreciated exchange

rateDecreased demand

on technologiesLow salaries

Political mobilization

Corporatism

Economic populism

Growing inflation

Influence on budget

decisions

Prim

ary

expo

rt

Man

ufac

ture

d ex

port

The economic development is stimulated by intensification of structural changes in industrial production, exports and imports structure (Xu 2010, Saygılı, Saygılı, 2011; Parteka А. Tamberi М., 2013)

The functional relations of foreign trade structure and economic growth were empirically investigated for many countries (Chen, Jefferson and Zhang, 2011, Patnaik et al. 2011, Sato and Fukushige 2011, Cimoli, Fleitas & Porcile, 2013)

Leamer and Maul 1999, showed the negative impact of natural resources abundance on economic development for Latin American panel data, in particularly through increasing the income inequality

5

Notes: I – Live animals and livestock products; II – Plant products; III – Animal or plant fats and oils; IV – Finished food industry products; V – Mineral Products; VI – Products of chemical industry; VII – Polymeric materials, plastics and articles of them; X – Paper bulk from wood or other vegetable fibers; XI – Textiles materials; XV – Base metals and articles thereof; XVI – Machines, equipment and mechanisms; XVII – Ground, air and water transport facilities.

Data from Ukrainian statistical committee

1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 20121 XV XV XV XV XV XV XV XV XV XV XV XV XV XV XV2 VI V VI V V V V V V XVI V II V V II3 XVI VI V XVI XVI XVI XVI VI VI V XVI XVI XVI XVI V4 V XVI XVI VI. VI. VI. VI. XVI XVI VI II V. II II XVI5 II II ХI II II XVII XVII II XVII XVII VI VI VI VI XVII6 XVII ХI XVII ХI XVII IV IV XVII II IV XVII IV XVII XVII VI7 ХI XVII IV XVII ХI ХI II IV IV II IV III III III III8 VII IV II IV IV II ХI ХI III III III XVII IV IV IV9 IV I I I I III I I ХI ХI VII Х Х Х Х

10 I IX VII X III I XVIII III VII VII. ХI ХI ХI ХI ХI

6

Data from Ukrainian statistical committee

0

5

10

15

20

25

3019

98

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

Bill

ion

dolla

rs

II. Plant products

V. Mineral Products

VI. Chemical industry products

XV. Base metals

XVI. Machines, equipment and mechanisms

7

Data from Ukrainian statistical committee

0

5

10

15

20

25

30

35

40

45

5019

99

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

II. Plant products

V. Mineral Products

VI. Chemical industry products

XV. Base metals

XVI. Machines, equipment and mechanisms

8

65

70

75

80

85

90

95

1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

Top 10

Top 5

9

10

Ext is specific export group (XV, V, XVI, II, VI) (in $ millions); Imt is specific import group (in $ millions);Indukrsat is industrial production (index, 1994=100); cpit is consumer price index (1994 =100) and rert is real exchange rate of hryvna per $ (index, 2000=100).

Data sources: the IFS database and State Statistics Committee of Ukraine.

Statistical package EViews 5 was used for data processing.

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2SLS VAR Kalman

filter 1. The differences between long- and short-term influences + + -

2. The dynamics of functional relationships in time - - +

3. Time development of initial functional impulse - + -4. Identification of mutual influence of dependent variables + + +

5. Consideration of cointegration + + -6. Determination of the share of dependent variables in their dynamics - + -

ttttareraExaaEx Imlnlnlnln

32110

ttttIndukrsabcpibExbbEx lnlnlnln

32110

(1b)

,,

(1a)

12

аdj.R2 DW

)875.8(Im527.0

)381.2()402.1(383.015134.0

)363.6(131.515

***11

*tttt portRERExEx 0.96 1.52

)237.6(207.1

)063.2()868.4(160.015435.0

)768.4(722.215

****1

*tttt IndukrsaCPIExEx 0.94 1.88

13

)445.4(Im481.0

)832.1()228.6(534.05574.0

)502.2(564.25

*****11

**tttt portRERExEx

)299.3(865.0

)249.2()870.4(286.05529.0

)551.1(918.05

***1 tttt IndukrsaCPIExEx

аdj.R2 DW

0.91 1.75

0.90 1.66

14

аdj.R2 DW

0.93 1.73

0.93 2.08

)992.5(Im450.0

)853.1()372.6(518.016515.0

)093.1(941.016

*****1

*tttt portRERExEx

)114.4(893.0

)247.4()572.2(621.016314.0

)734.1(844.016

****1

***tttt IndukrsaCPIExEx

15

)667.2(Im338.0

)689.1()764.5(269.12634.0

)828.1(614.32

******11 tttt portRERExEx

)887.1(871.0

)452.3()228.3(960.02383.0

)476.2(021.32

***4

**31

**

tttt IndukrsaCPIExEx

аdj.R2 DW

0.91 1.75

0.90 1.66

16

аdj.R2 DW

0.92 2.04

0.92 1.71

)065.2(Im141.0

)448.3()909.6(752.06747.0

)290.0(227.06

*1

***21

tttt portRERExEx

)377.4(076.1

)911.1()576.3(149.06425.0

)995.3(537.26

*1

****1

* tttt IndukrsaCPIExEx

17

,1

tt

n

iitit BxyAy

(2)

Kalman filter approach

,tttt

uBFEx t

u

tindukrsatimtrerFt

1 ttttBt 3210

(3)~ ііd N(0,1)

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Null Hypothesis Lags

1 2 3 4 10

RER does not Granger Cause EX15

EX15 does not Granger Cause RER

2.02084 (0.16124) 6.24668

(0.01570**)

3.56570 (0.03599**)

3.98901 (0.02497**)

1.61004 (0.20029) 2.40657

(0.07965***)

2.70281 (0.04317**)

1.54227 (0.20752)

0.64594 (0.76073) 1.55208

(0.18177) IM15 does not Granger EX15

EX15does not Granger Cause IM15

0.37291 (0.54394) 5.79421

(0.01946**)

1.70081 (0.19253) 4.79308

(0.01229**)

2.28273 (0.09069***)

4.53891 (0.00694*)

1.14450 (0.34763) 5.33294

(0.00130*)

0.59163 (0.80698) 2.02615

(0.06891***) INDUKRSA does not Granger Cause EX15 EX15 does not Granger Cause INDUKRSA

24.1055 (1.0E-05*) 8.46285

(0.00540*)

13.7136 (2.0E-05*) 2.20564

(0.12146)

9.44416 (6.2E-05*) 2.63278

(0.06168***)

9.42969 (1.7E-05*) 1.82486

(0.14251)

4.00091 (0.00288*) 2.44506

(0.03695**) Note: (* - 1%, ** - 5%, *** - 10%)

19

20

SVEC modes specifications

lags The quantity of equations

1 2 3 4

Ех15t, RERt, Im15t та Indukrsat

1 64.084** 26.745 7.682 2.789 2 44.372 23.193 5.533 1.112 3 45.508 21.633 8.485 0.001

Ех5t, RERt, Im5t та Indukrsat

1 46.581 19.179 6.889 1.268 2 43.861 16.954 6.769 0.018 3 41.696 18.668 5.478 1.238

Ех16t, RERt, Im16t та Indukrsat

1 53.870* 25.237 9.494 1.835 2 39.533 21.210 5.501 1.983 3 30.881 17.425 8.010 0.572

Ех2t, RERt, Im2t та Indukrsat

1 60.435** 30.445* 8.561 2.460 2 45.501 26.009 7.736 1.271 3 32.719 16.925 5.908 0.849

Ех6t, RERt, Im6t та Indukrsat

1 48.831* 26.397 9.373 1.333 2 40.779 21.991 7.664 1.310 3 51.875* 23.101 7.0224 0.481

Critical values 5% 47.21 29.68 15.41 3.76 1% 54.46 35.65 20.04 6.65

Note: The test assumptions is linear trend (**- 1%, *- 5%)

-0,15

-0,1

-0,05

0

0,05

0,1

0,15

1 2 3 4 5 6 7 8 9 10

0

5

10

15

20

25

30

1 2 3 4 5 6 7 8 9 10

ex5 ex16 ex15

ex2 ex6

21

-.04

-.03

-.02

-.01

.00

.01

.02

.03

.04

.05

1 2 3 4 5 6 7 8 9 100

5

10

15

20

25

30

35

40

45

50

1 2 3 4 5 6 7 8 9 10

RER

22

-0,15

-0,1

-0,05

0

0,05

0,1

0,15

0,2

0,25

1 2 3 4 5 6 7 8 9 10

0

5

10

15

20

25

30

1 2 3 4 5 6 7 8 9 10

ex5 ex16 ex15

ex2 ex6

23

0

0,02

0,04

0,06

0,08

0,1

0,12

0,14

0,16

0,18

0,2

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

RER

0

0,05

0,1

0,15

0,2

0,25

0,3

0,35

0,4

0,45

0,5

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

RER

-0,3

-0,25

-0,2

-0,15

-0,1

-0,05

0

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

RER

4.а. Factors of ЕХ15t 4.b. Factors of ЕХ5t 4.c. Factors of ЕХ16t

24

0

0,1

0,2

0,3

0,4

0,5

0,6

0,7

0,8

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

Import15

0

0,1

0,2

0,3

0,4

0,5

0,6

0,7

0,8

0,9

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

Import5

0

0,1

0,2

0,3

0,4

0,5

0,6

0,7

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

Import16

4.а. Factors of ЕХ15t 4.b. Factors of ЕХ5t 4.c. Factors of ЕХ16t

25

-7

-6

-5

-4

-3

-2

-1

0

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

RER

-0,1

0,4

0,9

1,4

1,9

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

RER

-0,5

-0,3

-0,1

0,1

0,3

0,5

0,7

0,9

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

Import2

-0,1

0

0,1

0,2

0,3

0,4

0,5

0,6

0,7

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

Import6

4.а. Factors of ЕХ2t 4.b. Factors of ЕХ6t

26

It was proved that commodity exports groups with low valueadded are significantly dependent on the exchange ratefluctuations.

Simultaneously the dependence on imports was observedthat most applies to group XVI.

The negative impact of currency depreciation on industrialproduction was revealed.

Estimates of Kalman filter generally correspond to 2SLS andVAR, confirming the robustness of the results.

The RER effects confirm previous results concerning theasymmetric impact of exchange rate on technological(machineries) and primary (metals, chemicals, plant andmineral products) sectors.

27

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