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ACADEMY OF ECONOMIC STUDIES, BUCHAREST DOCTORAL SCHOOL OF FINANCE AND BANKING DOFIN. Dissertation Paper Real effective exchange rates and their influence on Romania’s trade with European Union Countries. MSc Student :Grigorescu Madalina Supervisor : Professor Moisa Altar. Topics. Objectives
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ACADEMY OF ECONOMIC STUDIES, BUCHAREST DOCTORAL SCHOOL OF FINANCE AND BANKING DOFIN Dissertation PaperReal effective exchange rates and their influence on Romania’s trade with European Union Countries MSc Student :Grigorescu Madalina Supervisor : Professor Moisa Altar
Topics • Objectives • Introduction • Review of the literature • Theoretical models & formulas • Empirical analysis • Conclusions
Objectives • To determine REER based on CPI and PPI indices weighted by the export volume of Romania to European Union countries • To providean empirical investigation on the Romania’s REER influence on its trade with European Union countries • Export • Import • Trade balance graph
Introduction: Real Effective Exchange Rate • Useful indicator of one country’s competitiveness • The appropriate definition and calculation of REER depend upon the economic issue to be demonstrated and data availability • The “effective” aspect of REER is referring to the weights to be put upon each interacting partner country • Import-weighted indices • Exports-weighted indices • Total direct trade (export and imports) • Multilateral export-weight • Indices to be included in REER’s measurement formula • CPI • PPI • GDP deflators • ULC each having its advantages and disadvantages
Theoretical models and formulas • RER = nominal exchange rate adjusted for price level differences between countries (domestic P and abroad P* ) • REER= multilateral real exchange rate REER is usually presented in several context including: 1) relating real exchange rates to productivity differencials 2) estimating the relative price responsiveness of the trade flow 3) assessing its impact on country’s competitiveness
Review of the literature:Studies on EU accession countries • Barell,Dawn, Smidkova (2002)„Estimates of Fundamental real effective exchange rate for the five EU preaccession countries” • Stability of REER will not automatically be in line with economic developments • De Broeck, Slok (2001) „Interpreting real exchange rate movements in transition countries” • EU accession countries can expect to experience further productivity –driven REER appreciations • Egart, Balasz (2002) „Investigating the Balassa-Samuelson hypothesis in transition :do we understand what we see?” • Continuous capital inflows will upward pressure on nominal exchange rate and provoke exchange rate to appreciate to unsustainable levels • Egart, Balasz and Drine , Imed and Rault, Cristophe (2002), „On the Balassa-Samuleson effect in the transition countries : a panel study” • Evidence for Romania : cointegration very unstable • Stucka, Tihomi (2004) „The effect of exchange rate change in the trade balance in Croatia” • It is questionable weather permanent depreciation is desirable to improve the trade balance • Kim,Korhonen (2002),”Equilibrium exchange rates in transition countries: evidence from dynamic panel models” • Serious challenges for the exchange rates policies in EU accession countries as joining Euro at the current level of exchange rate risks undermining exports to EU countries
Theoretical implications: • When REER rises (REER depreciates) -> each unit of domestic output purchases fewer units of foreign output; • Foreign consumers demand more of our products-> the volume of exports will rise • Domestic consumers purchase fewer units of expensive foreign products -> imports decreases measured in foreign output units but increases measured in domestic output units • When REER decrease (REER appreciates) -> the opposite situation • The evolution of the exports is obvious while the evolution of imports is ambiguous • All things equal, the volume effect of REER changes outweighs the value effect , and a depreciation of REER improves the trade balance and an appreciation worsens the trade balance
Empirical analysis • Data series • Results
Data series • Period : 1990-2003 • Frequency : quarterly data • Log of REER_CPI index calculated as a geometric average using CPI index and weights as bilateral exports of Romania with EU countries • Log of REER_PPI index calculated as a geometric average using PPI index and weights as bilateral exports of Romania with EU countries • Log of Exports and Imports series of Romania with EU countries • Log of Trade Balance of Romania with EU countries back
Results • Unit root tests on series • Augmented Dickey Fuller tests: Given the I(1) nature of the series, the cointegration analysis is employed to explore the long-run relationship among the variables • Cointegration analysis • Vector Error Correction Models • To observe short-run deviations of variables from long-run equilibrium path • To see the speed of adjustment of the variables to shocks from long-run equilibrium
Cointegration analysis For the obtained number of lags I found cointegration equation for Export and REER and for Import and REER both for the 5% level of significance
Export and REER_CPI and REER_PPI Import and REER_CPI and REER_PPI
The hypothesis that REER_CPI and REER_PPI do not Granger cause the volume of export are rejected while the hypothesis that EXPORT do not Granger cause REER_CPI and REER_PPI are not rejected
The hypothesis that REER_CPI and REER_PPI do not Granger cause the volume of Import are rejected while the hypothesis that IMPORT do not Granger cause REER_CPI and REER_PPI are not rejected
Responses of Export and Import to REER_CPI and REER_PPIimpulses
Results of regression for the two types of REER Newey-West HAC Standard Errors & Covariance (lag truncation=3) Export= REER_CPI*2.714627-13.4857 R-squared 0.735833 D-W=0.25 [7.37] [-7.15] Export= REER_PPI*3.058773-15.33536 R-squared 0.677775 D-W=0.24 [6.98] [-6.83] Import =REER_CPI*2.726184-13.44575 R-squared 0.863549 D-W=0.47 [10.88] [-10.57] Import =REER_PPI*3.121839-15.55607 R-squared 0.821542 D-W=0.45 [10.22] [-9.97] 1.072.714627 =1.2016 ≈20.16% and 1.043.058773 =1.1274 ≈12,74 % respectively the volume of Export 1.072.726184 =1.2025 ≈ 20.25 % and 1.043.121839 =1.13025≈13% the volume of Import 0.932.714627 =0.8211 ≈ 17% and 0.963.058773 =0.8826 ≈11% respectively the volume of Export 0.932.726184 = 0.82050≈ 18% and 0.963.121839 = 0.8803≈ 12% the volume of Import back
Error correction equations: Estimation Method: Least Squares Sample: 1991:3 2003:4 Included observations: 50 Total system (balanced) observations 100 Equation:D(EXPORT) = C(1)*( EXPORT(-1) - 4.165968926*REER_PPI( -1) + 21.01019822 ) + C(2)*D(EXPORT(-1)) + C(3)*D(EXPORT(-2)) + C(4)*D(EXPORT(-3)) + C(5)*D(EXPORT(-4)) + C(6)*D(EXPORT(-5)) + C(7)*D(REER_PPI(-1)) + C(8)*D(REER_PPI(-2)) + C(9) *D(REER_PPI(-3)) + C(10)*D(REER_PPI(-4)) + C(11) *D(REER_PPI(-5)) + C(12) Observations: 50 C(1)=-0.028198 t-Statistic =-3.767567 Prob =0.0003 R-squared 0.979022 Mean dependent var 0.032526 Adjusted R-squared 0.972949 S.D. dependent var 0.052673 S.E. of regression 0.008663 Sum squared resid 0.002852 Durbin-Watson stat 2.047369
Equation:D(IMPORT) = C(1)*( IMPORT(-1) - 1.568281763*REER_CPI(-1) + 7.625304795 ) + C(2)*D(IMPORT(-1)) + C(3)*D(IMPORT(-2)) + C(4)*D(IMPORT(-3)) + C(5)*D(IMPORT(-4)) + C(6)*D(IMPORT( -5)) + C(7)*D(REER_CPI(-1)) + C(8)*D(REER_CPI(-2)) + C(9) *D(REER_CPI(-3)) + C(10)*D(REER_CPI(-4)) + C(11) *D(REER_CPI(-5)) + C(12) Observations: 50 C(1)=-0.026887 t-Statistic =-3.289858 Prob =0.0015 R-squared 0.878063 Mean dependent var 0.035058 Adjusted R-squared 0.842766 S.D. dependent var 0.040824 S.E. of regression 0.016188 Sum squared resid 0.009958 Durbin-Watson stat 1.664252 Equation:D(IMPORT) = C(1)*( IMPORT(-1) - 1.300769017*REER_PPI(-1) + 6.323013095 ) + C(2)*D(IMPORT(-1)) + C(3)*D(IMPORT(-2)) + C(4)*D(IMPORT(-3)) + C(5)*D(IMPORT(-4)) + C(6)*D(IMPORT(-5)) + C(7)*D(REER_PPI(-1)) + C(8)*D(REER_PPI(-2)) + C(9) *D(REER_PPI(-3)) + C(10)*D(REER_PPI(-4)) + C(11) *D(REER_PPI(-5)) + C(12) Observations: 50 C(1)=-0.032755 t-Statistic =-3.185857 Prob =0.0021 R-squared 0.876274 Mean dependent var 0.035058 Adjusted R-squared 0.840458 S.D. dependent var 0.040824 S.E. of regression 0.016306 Sum squared resid 0.010104 Durbin-Watson stat 1.675513
Results of regressions: EXPORT =REER_CPI *0.565837+GDP_EU*0.390866 -0.971709 R-squared 0.691239 , D-W=0.54 [3.57] [2.71] [- 1.26] EXPORT =REER_PPI *0.441380+GDP_EU*0.507131 -0.887198 R-squared 0.608194 , D-W=0.38 [3.16] [3.26] [-1.11] IMPORT=REER_CPI*-0.095769+EXPORT*0.802969+AGR_DEMAND*0.048147+ 1.078879 R-squared 0.961766 , D-W=0.28 [-1.59] [16.92] [1.33] [3.66] IMPORT=REER_PPI*-0.007240+EXPORT*0.793771+AGR_DEMAND*0.023037+ 1.078879 R-squared 0.969995 , D-W=0.25 [-0.137] [15.98] [0.48] [2.42]
REER influence on Trade Balance Romania has negative Trade Balance (TB) with EU countries VAR lag length criteria : 7 lags for both REER_CPI and REER_PPI relationship with TB
REER influence on Trade Balance • cointegration equation for 5% level of significance for the two cases TB and REER_CPI and TB and REER_PPI Lags interval (in first differences): 1 to 7 Unrestricted Cointegration Rank Test
Pairwise Granger Causality Tests: Sample: 1990:1 2003:4 Lags: 1 Null Hypothesis: Obs F-Statistic Probability REER_CPI does not Granger Cause TB 55 9.52595 0.00324 TB does not Granger Cause REER_CPI 0.02620 0.87203 Lags: 2 Null Hypothesis: Obs F-Statistic Probability REER_CPI does not Granger Cause TB 54 2.32283 0.10869 TB does not Granger Cause REER_CPI 0.02812 0.97229 Lags: 1 Null Hypothesis: Obs F-Statistic Probability REER_PPI does not Granger Cause TB 55 9.19004 0.00379 TB does not Granger Cause REER_PPI 0.01979 0.88866 Lags: 2 Null Hypothesis: Obs F-Statistic Probability REER_PPI does not Granger Cause TB 54 2.31398 0.10958 TB does not Granger Cause REER_PPI 0.02818 0.97223
Results of regressions for the two types of REER TB=REER_CPI*1.65779 -8.692956 R-squared 0.441621 , D-W=0.79 [3.6841] [-3.8573] TB=REER_PPI*1.92424 -9.293298 R-squared 0.431312 , D-W=0.78 [3.6981] [-3.8518] • 1.071.65 =1.118 ≈11.8 % and 1.041.92 =1.078 ≈7.8 % • 0.931.65 =0.887 ≈ 12 % and 0.961.92 =0.92 ≈8 % • TB does not have the expected sign and consequently it initially worsens at REER depreciations and then it improves (starting with lag 4 it has the expected negative sign)
TB and REER_CPI (7 lags): Error Correction Model D(TB) = 0.1370008082*( TB(-1) + 0.01767896916*REER_CPI_LOG(-1) ) + 0.7865814588*D(TB(-1)) - 0.3968784339*D(TB(-2)) + 0.03360259529*D(TB(-3)) - 0.2447805494*D(TB(-4)) -0.04381380141*D(TB(-5)) - 0.04652583436*D(TB(-6)) - 0.1803369447*D(TB(-7)) +3.425845879*D(REER_CPI (-1)) – 0.8003956003*D(REER_CPI (-2)) +1.207371803*D(REER_CPI (-3)) +1.756795848*D(REER_CPI (-4)) - 3.157573105*D(REER_CPI (-5)) + 2.403071583*D(REER_CPI (-6)) - 0.01985208971*D(REER_CPI (-7)) D(REER_CPI) = - 0.06954231854*( TB(-1) + 0.01767896916*REER_CPI(-1) ) –0.07424238375*D(TB(-1)) + 0.1036032247*D(TB(-2)) +0.005701677302*D(TB(-3)) +0.03426812401*D(TB(-4)) + 0.01956357912*D(TB(-5)) + 0.05240118994*D(TB(-6)) +0.04620054128*D(TB(-7)) - 0.5301569997*D(REER_CPI(-1)) + 0.02040601877*D(REER_CPI(-2)) –0.4077126554*D(REER_CPI(-3)) + 0.3907634519*D(REER_CPI(-4)) +0.1055090966*D(REER_CPI(-5)) - 0.5415890667*D(REER_CPI(-6)) +0.03241797129*D(REER_CPI(-7)) TB and REER_PPI (7 lags): D(TB) = 0.1453655075*( TB(-1) + 0.2806808741*REER_PPI(-1) - 1.039744678 ) + 0.7616830328*D(TB(-1)) - 0.5830842106*D(TB(-2)) + 0.1383830284*D(TB(-3)) - 0.2598415963*D(TB(-4)) - 0.006246235075*D(TB(-5)) - 0.08143625724*D(TB(-6)) - 0.1648990411*D(TB(-7)) + 3.078886096*D(REER_PPI(-1)) - 1.223630924*D(REER_PPI(-2)) + 1.706903517*D(REER_PPI(-3)) + 1.682785129*D(REER_PPI(-4)) - 2.927038695*D(REER_PPI(-5)) + 2.73469155*D(REER_PPI(-6)) - 0.8225060185*D(REER_PPI(-7)) - 0.00491755967 D(REER_PPI) = - 0.07763000086*( TB(-1) + 0.2806808741*REER_PPI(-1) - 1.039744678 ) - 0.04419584655*D(TB(-1)) + 0.1514702121*D(TB(-2)) - 0.01653847494*D(TB(-3)) + 0.03061622078*D(TB(-4)) + 0.01204721762*D(TB(-5)) + 0.05570758654*D(TB(-6)) + 0.04820989632*D(TB(-7)) - 0.4477123584*D(REER_PPI(-1)) + 0.03722262183*D(REER_PPI(-2)) - 0.5756806286*D(REER_PPI(-3)) + 0.2824755348*D(REER_PPI(-4)) - 0.0615261533*D(REER_PPI(-5)) - 0.6419286947*D(REER_PPI(-6)) + 0.161200314*D(REER_PPI(-7)) + 0.01206296165
Dependent Variable: D(TB) Method: Least Squares Sample(adjusted): 1992:1 2003:4 Included observations: 48 after adjusting endpoints D(TB) = C(1)*( TB(-1) + 0.01069773101*REER_CPI(-1) + 0.2191682532 ) + C(2)*D(TB(-1)) + C(3)*D(TB(-2)) + C(4)*D(TB(-3)) + C(5)*D(TB( -4)) + C(6)*D(TB(-5)) + C(7)*D(TB(-6)) + C(8)*D(TB(-7)) + C(9) *D(REER_CPI(-1)) + C(10)*D(REER_CPI(-2)) + C(11)*D(REER_CPI(-3)) + C(12)*D(REER_CPI(-4)) + C(13) *D(REER_CPI(-5)) + C(14)*D(REER_CPI(-6)) + C(15) *D(REER_CPI(-7)) + C(16) Coefficient Std. Error t-Statistic Prob. C(1) 0.154977 0.087303 1.775161 0.0854 C(2) 0.772608 0.225150 3.431524 0.0017 C(3) -0.430887 0.253643 -1.698796 0.0991 C(4) 0.042718 0.140261 0.304563 0.7627 C(5) -0.252806 0.076088 -3.322545 0.0022 C(6) -0.052952 0.085477 -0.619482 0.5400 C(7) -0.063642 0.080023 -0.795298 0.4323 C(8) -0.191026 0.071940 -2.655359 0.0122 C(9) 3.421184 0.646882 5.288729 0.0000 C(10) -0.841963 0.769861 -1.093657 0.2823 C(11) 1.268492 0.664479 1.909003 0.0653 C(12) 1.716229 0.449494 3.818133 0.0006 C(13) -3.198078 0.704544 -4.539218 0.0001 C(14) 2.399025 0.873477 2.746522 0.0098 C(15) -0.156624 0.839850 -0.186491 0.8532 C(16) -0.016135 0.026257 -0.614526 0.5432 R-squared 0.705076 Mean dependent var 0.022440 Adjusted R-squared 0.566830 S.D. dependent var 0.169311 S.E. of regression 0.111433 Akaike info criterion -1.289581 Sum squared resid 0.397356 Schwarz criterion -0.665848 Log likelihood 46.94995 Durbin-Watson stat 2.087974 White Heteroskedasticity Test: F-statistic 1.788021 Probability 0.116205 Jarque-Bera normality Test: Statistic 2.391790 Probability 0.302433
Dependent Variable: D(TB) Method: Least Squares Sample(adjusted): 1992:1 2003:4 Included observations: 48 after adjusting endpoints D(TB) = C(1)*( TB(-1) + 0.3370609842*REER_PPI(-1) - 1.444550447 ) + C(2)*D(TB(-1)) + C(3)*D(TB(-2)) + C(4)*D(TB(-3)) + C(5)*D(TB(-4)+ C(6)*D(TB(-5)) + C(7)*D(TB(-6)) + C(8)*D(TB(-7)) + C(9) *D(REER_PPI(-1)) + C(10)*D(REER_PPI(-2)) + C(11 ) *D(REER_PPI(-3)) + C(12)*D(REER_PPI(-4)) + C(13) *D(REER_PPI(-5)) + C(14)*D(REER_PPI(-6)) + C(15) *D(REER_PPI(-7)) + C(16) Coefficient Std. Error t-Statistic Prob. C(1) 0.146502 0.074730 1.960429 0.0587 C(2) 0.645211 0.208309 3.097381 0.0040 C(3) -0.472682 0.226722 -2.084853 0.0451 C(4) 0.098739 0.133076 0.741979 0.4635 C(5) -0.265859 0.073777 -3.603558 0.0011 C(6) -0.022232 0.084235 -0.263930 0.7935 C(7) -0.076169 0.077014 -0.989016 0.3301 C(8) -0.156350 0.068061 -2.297198 0.0283 C(9) 2.884267 0.560499 5.145893 0.0000 C(10) -0.906927 0.690607 -1.313232 0.1984 C(11) 1.541538 0.586483 2.628445 0.0131 C(12) 1.775626 0.459297 3.865960 0.0005 C(13) -2.656261 0.619329 -4.288936 0.0002 C(14) 2.369020 0.781475 3.031472 0.0048 C(15) -0.509762 0.766876 -0.664725 0.5110 C(16) -0.006860 0.024101 -0.284647 0.7777 R-squared 0.704920 Mean dependent var 0.022440 Adjusted R-squared 0.566601 S.D. dependent var 0.169311 S.E. of regression 0.111463 Akaike info criterion -1.289052 Sum squared resid 0.397566 Schwarz criterion -0.665318 Log likelihood 46.93725 Durbin-Watson stat 2.215315 White Heteroskedasticity Test : F-statistic 1.687595 Probability 0.141207 Jarque-Bera normality Test: Statistic 6.482801 Probability 0.039109
Conclusions • Results show that is possible to start building a quantitative background for discussion about REER in Romania during the accession process • REER is a useful summary indicator of essential economic information • REER can be a good indicator for monetary and exchange rate policies in order to forecast trade balance in a country (R-squared ≈ 70%) • Exports and Imports have the expected reaction to REER movements • Trade Balance initially worsens after a REER depreciation and then it improves • It is questionable whether permanent depreciation is desirable to improve trade balance
Romanian Trade volumes Romanian “ Trade Openness” to GDP ratio mil USD 86.0% 14000 84.0% 12000 82.0% 10000 80.0% 8000 78.0% Weight in GDP export with EU 6000 76.0% export with Europe 4000 74.0% 2000 72.0% Total export 70.0% 0 68.0% 1990 1992 1994 1996 1998 2000 2002 2001 2002 2003 period period Source: Romanian External Trade Department back