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A study on
Relationship
between
RBI Rupee Dollar Rates
and
Trade Deficit, CAD & Net FII
Niraj Shrivastava
Ravi Sondhi
Focus of Presentation
Rupee Dollar fluctuation- Graphical
Relationship of Rupee-Dollar rate with FII, CAD , Trade balance and Foreign
Reserves- Graphical Analysis/ Surface level
Performing Correlation on Rupee Dollar rate with FII, Trade balance and
Foreign reserves variables.Foreign reserves variables.
Understand & identifying Co-movement or long term relationship of Rupee
Dollar rate with FII, Trade balance
Indentifying the Short term casual relationship between Rupee Dollar rate , FII
, CAD and trade balance.
Framework & Tools Used
Data Source from Indianstat.com and RBI website
Graphical Comparison- Primary Analysis
Co-integration & VAR FrameworkCo-integration & VAR Framework
Regression/ Correlation
Eviews software.
Historical Movement of Rupee
Focus Area
Dynamic movement on Rupee post Global Financial Crisis affecting
Indian Economy
Rupee Dollar Rate & FII, CAD- Graphical Representation
2,00,000
1,50,000
1,00,000
50,000
0
50,000
1,00,000
1,50,000
61.00
61.50
62.00
62.50
63.00
63.50
64.00
Rupee Dollar rate - CAD , FII , Trade balance and Foreign Ex. Reserves
3,50,000
3,00,000
2,50,000
60.00
60.50
61.00
Jun-99
Nov-99
Apr-00
Sep-00
Feb-01
Jul-01
Dec-01
May-02
Oct-02
Mar-03
Aug-03
Jan-04
Jun-04
Nov-04
Apr-05
Sep-05
Feb-06
Jul-06
Dec-06
May-07
Oct-07
Mar-08
Aug-08
Jan-09
Jun-09
Nov-09
Apr-10
Sep-10
Feb-11
Jul-11
Dec-11
May-12
Oct-12
Mar-13
Aug-13
Jan-14
Jun-14
Nov-14
Rupee Dollar FII Trade Balance CAD Reserves
Primary Analysis:-
Trade balance and CAD are moving in tandem / parallel.
FII and Foreign Exchange reserves are moving in opposite direction not relationship with Trade
balance & CAD.
• Variation shows the increasing/widening trend from 2000 to 2014.
Source: Indiastat.com
Correlation of Indian Rupee Dollar – FII, CAD, Trade Balance
& Foreign Ex. Reserves
Analysis Results - Eviews
Ind. Variables t- stat prob. Acceptance prob. Co-efficient t- stat prob. Acceptance prob. Co-efficient
C 0.00 <=0.05 62.14 C 0.00 <=0.05 62.15
CAD 0.55 <=0.05 -1.85E-06 CAD 0.00 <=0.05 9.06E-06
Trade balance 0.02 <=0.05 8.42E-06 Trade balance 0.00 <=0.05 -3.40E-06
FII 0.02 <=0.05 -3.45E-06
Foreign Ex. Reserves 0.70 <=0.05 -8.36E-07
Dep. Variable ( Indian Rupee Dollar Rate)- Removing FII & Foreign Ex. ReservesDep. Variable ( Indian Rupee Dollar Rate)
Rupee Dollar Rate t = c + β1 FII + β2 CAD + β3 Trade balance + β4 Foreign ex. Reserves
where :-Probability of t-stat - x1, x2, x3, x4 <= 5%
There exist the Correlation of Indian Rupee dollar rate with CAD and Trade
balance.
F-stat, DW shows model is relevant & okay.
There seems the problem of Multi-Collinearity in Trade Balance.
R-square is less due to less data points which can be overcome if time span is
increased.
Interpretation
Foreign Ex. Reserves 0.70 <=0.05 -8.36E-07
F -stat 0.047 <=0.05 F -stat 0.01 <=0.05
DW 0.361 <=2 DW 0.361 <=2
Model OK Model OK
Co-integration
Cointegration can be defined as a systemic co-movement among two or more
variables over the long run
The desire to evaluate models which combine both long tern as well as short
term properties and which at the same time, maintain stationary in all the
variables has prompted a consideration of the problem of regression using
variables measured in their levels
The focus of attention was data series which although non-stationary, can be
combined together through a linear combination into a single series which is
itself stationary
Series which exhibit such property called co-integrated series
Co-integration Modelling Strategy
CO-INTEGRATION MODEL..Cntd
T-stat T-critical T-stat T-critical
1 Rupee Dollar rate -1.67 -3.48 -6.79 -2.91
2 FII -4.54 -3.48 -7.32 -2.91
3 CAD -3.88 4.11 -9.062 -3.54
4 Trade balance -1.449 -3.48 -4.04 -2.91
RESULTS OF UNIT ROOT TEST - ADF
Level First difference
VariablesSr. No. Results
I(1) series
4 Trade balance -1.449 -3.48 -4.04 -2.91
All variable series is I(1) series – Stationary at 1st difference.
Co-integration Framework can be applied to analyse this variables
CO-INTEGRATION MODEL…Cntd
JOHANSEN CO-INTEGRATION TEST
1 Trace None 84.42 47.86
2 Trace at Most 1 43.33 29.79
3 Trace at Most 2 18.11 15.49
t-stat > t-critical.
Sr. No. Test Type
Hypotheised
no of CE(s)
Stat value Critical value (5%) Remarks
)1log( *
1max +−−= rT λλ )1log(
1
*
∑+=
−−=
n
ri
iTTrace λ
Max Eigenvalue Trace Statistics
Ho : Null Hypothesis = No Co-integration, if t-stat > t-critical then Ho is
rejected.
There exist long term Co-integration India – Rupee Dollar exchange rate
with FII , CAD and Trade balance.
Means there is co-movement of this variables.
3 Trace at Most 2 18.11 15.49
4 Trace at Most 3 6.11 3.84
5 Max-Eigen None 41.09 27.58
6 Max-Eigen at Most 1 25.22 21.13
7 Max-Eigen at Most 2 11.99 14.26
8 Max-Eigen at Most 3 6.11 3.84
t-stat > t-critical.
Co-integration
exists
Co-integration – Long Term Causality
If two variables are non-stationary, but they become stationary after first-
differencing, and co-integrated, the ECMs for the Granger-causality test
can be specified accordingly as follows:
Co-integration – Long Term Causality
varibale coefficient Coefficient Std. Error t-Statistic Prob. Remarks
C(1) -4.29E-05 0.048765 -0.000879 0.9993
C(2) 2.97E-07 1.83E-06 0.162596 0.871
C(3) -7.78E-06 1.97E-06 -3.937794 0.0001 Significant
C(4) -0.101338 0.168383 -0.601828 0.548
C(5) -0.049988 0.156791 -0.318818 0.7502
C(6) 1.27E-06 1.46E-06 0.873925 0.3832
C(7) 1.28E-07 1.32E-06 0.09694 0.9229
C(8) 3.73E-06 3.00E-06 1.246466 0.2141
C(9) 4.25E-06 3.02E-06 1.407851 0.1608
C(10) 1.36E-06 2.83E-06 0.479364 0.6322
C(11) -1.26E-06 2.93E-06 -0.430408 0.6674
C(12) 0.009095 0.029368 0.309684 0.7571
C(13) 12375 6942.128 1.782595 0.0762
C(14) -0.74099 0.260266 -2.847046 0.0049 Significant
C(15) 0.509928 0.281111 1.813975 0.0712
C(16) -8293.938 23970.94 -0.346 0.7297
C(17) -6353.466 22320.75 -0.284644 0.7762
C(18) 0.016026 0.207264 0.077324 0.9384
C(19) -0.097469 0.187906 -0.518713 0.6045
C(20) -0.54121 0.426456 -1.269086 0.2059
C(21) -0.660404 0.429316 -1.538269 0.1256
Error Correction Model - Long term causality
C(25) -403.7109 6350.689 -0.06357 0.9494
C(26) -0.370169 0.238093 -1.554727 0.1216
C(27) -0.75324 0.257162 -2.929053 0.0038 Significant
C(28) 1165.343 21928.72 0.053142 0.9577
C(29) 20120.03 20419.12 0.985353 0.3257
C(30) 0.240448 0.189606 1.268147 0.2062
C(31) 0.468417 0.171897 2.724988 0.007 Significant
C(32) -0.024003 0.390124 -0.061526 0.951
C(33) 0.095062 0.39274 0.242047 0.809
C(34) 0.06535 0.368265 0.177452 0.8593
C(35) 0.128169 0.382209 0.335337 0.7377
C(36) -2764.595 3824.673 -0.722832 0.4706
C(37) -27156.98 13126.49 -2.068868 0.0399 Significant
C(38) -1.169569 0.492123 -2.376577 0.0184 Significant
C(39) -1.096725 0.531538 -2.063306 0.0404 Significant
C(40) 18257.29 45325.36 0.402805 0.6875
C(41) 39061.67 42205.09 0.92552 0.3558
C(42) 1.0339 0.391904 2.638142 0.009
C(43) 1.163749 0.355301 3.275392 0.0012 Significant
C(44) -0.272479 0.806363 -0.337911 0.7358
C(45) 0.001242 0.81177 0.00153 0.9988
C(46) 0.576672 0.761182 0.757601 0.4496
varibale coefficient Coefficient Std. Error t-Statistic Prob. Remarks
Error Correction Model - Long term causality
C(22) 0.382195 0.402562 0.949407 0.3436
C(23) 0.474239 0.417804 1.135074 0.2577
C(24) 5253.318 4180.864 1.256515 0.2104
C(46) 0.576672 0.761182 0.757601 0.4496
C(47) 0.668755 0.790004 0.846521 0.3983
C(48) -9292.987 7905.369 -1.175529 0.2412
Co-integration – Long Term Causality
Results & Interpretations
1st Eqn D( RD) – Long term causality flows from independent variable CAD(-1) to
Rupee Dollar Ex. RateRupee Dollar Ex. Rate
2nd Eqn D(FII) – Long term causality flows from or is dependent upon its own past
value FII (-1) and FII(-2)
3rd Eqn D(CAD)- Long term causality flows from or is dependent upon its own past
value CAD (-1) and FII(-2)
4th Eqn D(Trade Balance) – Long term causality flows from or is dependent upon its
own past value RD (-1), TB(-1), FII(-1), CAD(-1), FII(-2)
Co-integration – Granger Causality ( Short term)
d(RD) d(FII) d(CAD) d(TB)
d(RD) 0.94 0.15 0.82
d(FII) 0.59 0.03 0.00
d(CAD) 0.96 0.79 0.38
d(TB) 0.81 0.70 0.84
Note: - All are probability values, Accepted if it is <0.05
Independent
Variable
Dependent Variable
Granger Causality - CASUALITY DIRECTION
Note: - All are probability values, Accepted if it is <0.05
Uni-directional causal relationship flowing from FII ( Foreign
Institutional Investors ) to CAD ( Current Account Deficit)
Uni-directional casual relation flowing from FII (Foreign Institutional
Investors to TB ( Trade balance )
Analysis/ Interpretation
Conclusion & Recommendation
Co-integrating /Co-movement / Long term relationship exists between
Rupee Dollar rate, Current Account Deficit & Trade balance.
There exist the granger causality in short term flowing from FII to CAD and
Trade Balance.
Long term causality – 3 Co-integrating equations flowing from
FII depends upon its own past value of t-1 & t-2;
Uni-directional flow from CAD t-1 to Rupee Dollar Ex. Rate;
Causality flowing from CAD t-1 and FII t-2 to CAD; RD (t-1), TB(t-
1), FII(t-1), CAD(t-1), FII(t-2) flowing to Trade balance.
THAN
K YOUK YOU

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ICF Presentation 1

  • 1. A study on Relationship between RBI Rupee Dollar Rates and Trade Deficit, CAD & Net FII Niraj Shrivastava Ravi Sondhi
  • 2. Focus of Presentation Rupee Dollar fluctuation- Graphical Relationship of Rupee-Dollar rate with FII, CAD , Trade balance and Foreign Reserves- Graphical Analysis/ Surface level Performing Correlation on Rupee Dollar rate with FII, Trade balance and Foreign reserves variables.Foreign reserves variables. Understand & identifying Co-movement or long term relationship of Rupee Dollar rate with FII, Trade balance Indentifying the Short term casual relationship between Rupee Dollar rate , FII , CAD and trade balance.
  • 3. Framework & Tools Used Data Source from Indianstat.com and RBI website Graphical Comparison- Primary Analysis Co-integration & VAR FrameworkCo-integration & VAR Framework Regression/ Correlation Eviews software.
  • 4. Historical Movement of Rupee Focus Area Dynamic movement on Rupee post Global Financial Crisis affecting Indian Economy
  • 5. Rupee Dollar Rate & FII, CAD- Graphical Representation 2,00,000 1,50,000 1,00,000 50,000 0 50,000 1,00,000 1,50,000 61.00 61.50 62.00 62.50 63.00 63.50 64.00 Rupee Dollar rate - CAD , FII , Trade balance and Foreign Ex. Reserves 3,50,000 3,00,000 2,50,000 60.00 60.50 61.00 Jun-99 Nov-99 Apr-00 Sep-00 Feb-01 Jul-01 Dec-01 May-02 Oct-02 Mar-03 Aug-03 Jan-04 Jun-04 Nov-04 Apr-05 Sep-05 Feb-06 Jul-06 Dec-06 May-07 Oct-07 Mar-08 Aug-08 Jan-09 Jun-09 Nov-09 Apr-10 Sep-10 Feb-11 Jul-11 Dec-11 May-12 Oct-12 Mar-13 Aug-13 Jan-14 Jun-14 Nov-14 Rupee Dollar FII Trade Balance CAD Reserves Primary Analysis:- Trade balance and CAD are moving in tandem / parallel. FII and Foreign Exchange reserves are moving in opposite direction not relationship with Trade balance & CAD. • Variation shows the increasing/widening trend from 2000 to 2014. Source: Indiastat.com
  • 6. Correlation of Indian Rupee Dollar – FII, CAD, Trade Balance & Foreign Ex. Reserves Analysis Results - Eviews Ind. Variables t- stat prob. Acceptance prob. Co-efficient t- stat prob. Acceptance prob. Co-efficient C 0.00 <=0.05 62.14 C 0.00 <=0.05 62.15 CAD 0.55 <=0.05 -1.85E-06 CAD 0.00 <=0.05 9.06E-06 Trade balance 0.02 <=0.05 8.42E-06 Trade balance 0.00 <=0.05 -3.40E-06 FII 0.02 <=0.05 -3.45E-06 Foreign Ex. Reserves 0.70 <=0.05 -8.36E-07 Dep. Variable ( Indian Rupee Dollar Rate)- Removing FII & Foreign Ex. ReservesDep. Variable ( Indian Rupee Dollar Rate) Rupee Dollar Rate t = c + β1 FII + β2 CAD + β3 Trade balance + β4 Foreign ex. Reserves where :-Probability of t-stat - x1, x2, x3, x4 <= 5% There exist the Correlation of Indian Rupee dollar rate with CAD and Trade balance. F-stat, DW shows model is relevant & okay. There seems the problem of Multi-Collinearity in Trade Balance. R-square is less due to less data points which can be overcome if time span is increased. Interpretation Foreign Ex. Reserves 0.70 <=0.05 -8.36E-07 F -stat 0.047 <=0.05 F -stat 0.01 <=0.05 DW 0.361 <=2 DW 0.361 <=2 Model OK Model OK
  • 7. Co-integration Cointegration can be defined as a systemic co-movement among two or more variables over the long run The desire to evaluate models which combine both long tern as well as short term properties and which at the same time, maintain stationary in all the variables has prompted a consideration of the problem of regression using variables measured in their levels The focus of attention was data series which although non-stationary, can be combined together through a linear combination into a single series which is itself stationary Series which exhibit such property called co-integrated series
  • 9. CO-INTEGRATION MODEL..Cntd T-stat T-critical T-stat T-critical 1 Rupee Dollar rate -1.67 -3.48 -6.79 -2.91 2 FII -4.54 -3.48 -7.32 -2.91 3 CAD -3.88 4.11 -9.062 -3.54 4 Trade balance -1.449 -3.48 -4.04 -2.91 RESULTS OF UNIT ROOT TEST - ADF Level First difference VariablesSr. No. Results I(1) series 4 Trade balance -1.449 -3.48 -4.04 -2.91 All variable series is I(1) series – Stationary at 1st difference. Co-integration Framework can be applied to analyse this variables
  • 10. CO-INTEGRATION MODEL…Cntd JOHANSEN CO-INTEGRATION TEST 1 Trace None 84.42 47.86 2 Trace at Most 1 43.33 29.79 3 Trace at Most 2 18.11 15.49 t-stat > t-critical. Sr. No. Test Type Hypotheised no of CE(s) Stat value Critical value (5%) Remarks )1log( * 1max +−−= rT λλ )1log( 1 * ∑+= −−= n ri iTTrace λ Max Eigenvalue Trace Statistics Ho : Null Hypothesis = No Co-integration, if t-stat > t-critical then Ho is rejected. There exist long term Co-integration India – Rupee Dollar exchange rate with FII , CAD and Trade balance. Means there is co-movement of this variables. 3 Trace at Most 2 18.11 15.49 4 Trace at Most 3 6.11 3.84 5 Max-Eigen None 41.09 27.58 6 Max-Eigen at Most 1 25.22 21.13 7 Max-Eigen at Most 2 11.99 14.26 8 Max-Eigen at Most 3 6.11 3.84 t-stat > t-critical. Co-integration exists
  • 11. Co-integration – Long Term Causality If two variables are non-stationary, but they become stationary after first- differencing, and co-integrated, the ECMs for the Granger-causality test can be specified accordingly as follows:
  • 12. Co-integration – Long Term Causality varibale coefficient Coefficient Std. Error t-Statistic Prob. Remarks C(1) -4.29E-05 0.048765 -0.000879 0.9993 C(2) 2.97E-07 1.83E-06 0.162596 0.871 C(3) -7.78E-06 1.97E-06 -3.937794 0.0001 Significant C(4) -0.101338 0.168383 -0.601828 0.548 C(5) -0.049988 0.156791 -0.318818 0.7502 C(6) 1.27E-06 1.46E-06 0.873925 0.3832 C(7) 1.28E-07 1.32E-06 0.09694 0.9229 C(8) 3.73E-06 3.00E-06 1.246466 0.2141 C(9) 4.25E-06 3.02E-06 1.407851 0.1608 C(10) 1.36E-06 2.83E-06 0.479364 0.6322 C(11) -1.26E-06 2.93E-06 -0.430408 0.6674 C(12) 0.009095 0.029368 0.309684 0.7571 C(13) 12375 6942.128 1.782595 0.0762 C(14) -0.74099 0.260266 -2.847046 0.0049 Significant C(15) 0.509928 0.281111 1.813975 0.0712 C(16) -8293.938 23970.94 -0.346 0.7297 C(17) -6353.466 22320.75 -0.284644 0.7762 C(18) 0.016026 0.207264 0.077324 0.9384 C(19) -0.097469 0.187906 -0.518713 0.6045 C(20) -0.54121 0.426456 -1.269086 0.2059 C(21) -0.660404 0.429316 -1.538269 0.1256 Error Correction Model - Long term causality C(25) -403.7109 6350.689 -0.06357 0.9494 C(26) -0.370169 0.238093 -1.554727 0.1216 C(27) -0.75324 0.257162 -2.929053 0.0038 Significant C(28) 1165.343 21928.72 0.053142 0.9577 C(29) 20120.03 20419.12 0.985353 0.3257 C(30) 0.240448 0.189606 1.268147 0.2062 C(31) 0.468417 0.171897 2.724988 0.007 Significant C(32) -0.024003 0.390124 -0.061526 0.951 C(33) 0.095062 0.39274 0.242047 0.809 C(34) 0.06535 0.368265 0.177452 0.8593 C(35) 0.128169 0.382209 0.335337 0.7377 C(36) -2764.595 3824.673 -0.722832 0.4706 C(37) -27156.98 13126.49 -2.068868 0.0399 Significant C(38) -1.169569 0.492123 -2.376577 0.0184 Significant C(39) -1.096725 0.531538 -2.063306 0.0404 Significant C(40) 18257.29 45325.36 0.402805 0.6875 C(41) 39061.67 42205.09 0.92552 0.3558 C(42) 1.0339 0.391904 2.638142 0.009 C(43) 1.163749 0.355301 3.275392 0.0012 Significant C(44) -0.272479 0.806363 -0.337911 0.7358 C(45) 0.001242 0.81177 0.00153 0.9988 C(46) 0.576672 0.761182 0.757601 0.4496 varibale coefficient Coefficient Std. Error t-Statistic Prob. Remarks Error Correction Model - Long term causality C(22) 0.382195 0.402562 0.949407 0.3436 C(23) 0.474239 0.417804 1.135074 0.2577 C(24) 5253.318 4180.864 1.256515 0.2104 C(46) 0.576672 0.761182 0.757601 0.4496 C(47) 0.668755 0.790004 0.846521 0.3983 C(48) -9292.987 7905.369 -1.175529 0.2412
  • 13. Co-integration – Long Term Causality Results & Interpretations 1st Eqn D( RD) – Long term causality flows from independent variable CAD(-1) to Rupee Dollar Ex. RateRupee Dollar Ex. Rate 2nd Eqn D(FII) – Long term causality flows from or is dependent upon its own past value FII (-1) and FII(-2) 3rd Eqn D(CAD)- Long term causality flows from or is dependent upon its own past value CAD (-1) and FII(-2) 4th Eqn D(Trade Balance) – Long term causality flows from or is dependent upon its own past value RD (-1), TB(-1), FII(-1), CAD(-1), FII(-2)
  • 14. Co-integration – Granger Causality ( Short term) d(RD) d(FII) d(CAD) d(TB) d(RD) 0.94 0.15 0.82 d(FII) 0.59 0.03 0.00 d(CAD) 0.96 0.79 0.38 d(TB) 0.81 0.70 0.84 Note: - All are probability values, Accepted if it is <0.05 Independent Variable Dependent Variable Granger Causality - CASUALITY DIRECTION Note: - All are probability values, Accepted if it is <0.05 Uni-directional causal relationship flowing from FII ( Foreign Institutional Investors ) to CAD ( Current Account Deficit) Uni-directional casual relation flowing from FII (Foreign Institutional Investors to TB ( Trade balance ) Analysis/ Interpretation
  • 15. Conclusion & Recommendation Co-integrating /Co-movement / Long term relationship exists between Rupee Dollar rate, Current Account Deficit & Trade balance. There exist the granger causality in short term flowing from FII to CAD and Trade Balance. Long term causality – 3 Co-integrating equations flowing from FII depends upon its own past value of t-1 & t-2; Uni-directional flow from CAD t-1 to Rupee Dollar Ex. Rate; Causality flowing from CAD t-1 and FII t-2 to CAD; RD (t-1), TB(t- 1), FII(t-1), CAD(t-1), FII(t-2) flowing to Trade balance.