nataliia cherkas phd, associate professor lviv academy of ... · nataliia cherkas phd, associate...
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NATALIIA CHERKAS PhD, Associate Professor
Lviv Academy of Commerce, Department of International Economic Relations
e-mail: [email protected]
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.
11
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
28