1. 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 ACADEMY OF ECONOMIC STUDIES, BUCHAREST DOCTORAL SCHOOL OF FINANCE AND BANKING DOFIN

2. Topics Objectives Introduction Review of the literature Theoretical models & formulas Empirical analysis Conclusions

3. Objectives To determine REER based on CPI and PPI indices weighted by the export volume of Romania to European Union countries To provide an empirical investigation on the Romania’s REER influence on its trade with European Union countries Export Import Trade balance graph

4. 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

5. 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

6. 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

7. 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

8. Empirical analysis Data series Results

9. 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

10. 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

11. 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

12. Export and REER_CPI and REER_PPI Import and REER_CPI and REER_PPI Lags interval (in first differences): 1 to 5 Unrestricted Cointegration Rank Test

13. Pairwise Granger Causality Tests Sample: 1990:1 2003:4 Lags: 1 Null Hypothesis:ObsF-StatisticProbability REER_CPI does not Granger Cause EXPORT55 12.7740 0.00077 EXPORT does not Granger Cause REER_CPI 1.37356 0.24654 Lags: 2 REER_CPI does not Granger Cause EXPORT54 30.6393 2.3E-09 EXPORT does not Granger Cause REER_CPI 1.05514 0.35592 Lags:3 REER_CPI does not Granger Cause EXPORT53 3.82998 0.01571 EXPORT does not Granger Cause REER_CPI 0.79001 0.50570 Lags:4 REER_CPI does not Granger Cause EXPORT52 3.96543 0.00795 EXPORT does not Granger Cause REER_CPI 1.92690 0.12323 Lags:5 REER_CPI does not Granger Cause EXPORT51 2.03730 0.09400 EXPORT does not Granger Cause REER_CPI 1.74625 0.14634 Lags:6 REER_CPI does not Granger Cause EXPORT50 2.45737 0.04225 EXPORT does not Granger Cause REER_CPI 1.28232 0.28922 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

14. Pairwise Granger Causality Tests Sample: 1990:1 2003:4 Lags: 1 Null Hypothesis:ObsF-StatisticProbability REER_CPI does not Granger Cause IMPORT55 6.71508 0.01238 IMPORT does not Granger Cause REER_CPI 3.99534 0.05087 Lags: 2 REER_CPI does not Granger Cause IMPORT54 6.02671 0.00457 IMPORT does not Granger Cause REER_CPI 1.28449 0.28595 Lags: 3 REER_CPI does not Granger Cause IMPORT53 3.03152 0.03866 IMPORT does not Granger Cause REER_CPI 0.72388 0.54292 Lags: 4 Null Hypothesis:ObsF-StatisticProbability REER_CPI does not Granger Cause IMPORT52 2.33387 0.07077 IMPORT does not Granger Cause REER_CPI 0.37474 0.82536 Lags: 5 Null Hypothesis:ObsF-StatisticProbability REER_CPI does not Granger Cause IMPORT51 0.97039 0.44750 IMPORT does not Granger Cause REER_CPI 1.43388 0.23320 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

15. Responses of Export and Import to REER_CPI and REER_PPI impulses

16. Results of regression for the two types of REER back 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] 1.07 2.714627 =1.2016 ≈20.16% and 1.04 3.058773 =1.1274 ≈12,74 % respectively the volume of Export 1.07 2.726184 =1.2025 ≈ 20.25 % and 1.04 3.121839 =1.13025≈13% the volume of Import 0.93 2.714627 =0.8211 ≈ 17% and 0.96 3.058773 =0.8826 ≈11% respectively the volume of Export 0.93 2.726184 = 0.82050≈ 18% and 0.96 3.121839 = 0.8803≈ 12% the volume of Import

17. Export and REER

18. Import and REER

19. Error correction equations : Equation: D(EXPORT) = C(1)*( EXPORT(-1) - 3.505269075*REER_CPI(-1) + 17.52164625 ) + 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_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)=-0.026831 t-Statistic =-3.37139 Prob =0.0012 R-squared0.977714 Mean dependent var0.032526 Adjusted R-squared0.971262 S.D. dependent var0.052673 S.E. of regression0.008929 Sum squared resid0.003030 Durbin-Watson stat2.013430 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-squared0.979022 Mean dependent var0.032526 Adjusted R-squared0.972949 S.D. dependent var0.052673 S.E. of regression0.008663 Sum squared resid0.002852 Durbin-Watson stat2.047369

20. 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-squared0.878063 Mean dependent var0.035058 Adjusted R-squared0.842766 S.D. dependent var0.040824 S.E. of regression0.016188 Sum squared resid0.009958 Durbin-Watson stat1.664252 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-squared0.876274 Mean dependent var0.035058 Adjusted R-squared0.840458 S.D. dependent var0.040824 S.E. of regression0.016306 Sum squared resid0.010104 Durbin-Watson stat1.675513

21. 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]

22. 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

23. 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

24. Pairwise Granger Causality Tests: Sample: 1990:1 2003:4 Lags: 1 Null Hypothesis:Obs F-StatisticProbability 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:ObsF-StatisticProbability REER_CPI does not Granger Cause TB54 2.32283 0.10869 TB does not Granger Cause REER_CPI 0.02812 0.97229 Lags: 1 Null Hypothesis:ObsF-StatisticProbability REER_PPI does not Granger Cause TB55 9.19004 0.00379 TB does not Granger Cause REER_PPI 0.01979 0.88866 Lags: 2 Null Hypothesis:ObsF-StatisticProbability REER_PPI does not Granger Cause TB54 2.31398 0.10958 TB does not Granger Cause REER_PPI 0.02818 0.97223

25. Results of regressions for the two types of REER TB=REER_CPI*1.65779 -8.692956 R-squared0.441621, D-W=0.79 [3.6841] [-3.8573] TB=REER_PPI*1.92424 -9.293298 R-squared0.431312, D-W=0.78 [3.6981] [-3.8518] 1.07 1.65 =1.118 ≈11.8 % and 1.04 1.92 =1.078 ≈7.8 % 0.93 1.65 =0.887 ≈ 12 % and 0.96 1.92 =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)

26. TB and REER_CPI (7 lags): 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 Error Correction Model

27. 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) CoefficientStd. Errort-StatisticProb. C(1)0.1549770.0873031.7751610.0854 C(2)0.7726080.2251503.4315240.0017 C(3)-0.4308870.253643-1.6987960.0991 C(4)0.0427180.1402610.3045630.7627 C(5)-0.2528060.076088-3.3225450.0022 C(6)-0.0529520.085477-0.6194820.5400 C(7)-0.0636420.080023-0.7952980.4323 C(8)-0.1910260.071940-2.6553590.0122 C(9)3.4211840.6468825.2887290.0000 C(10)-0.8419630.769861-1.0936570.2823 C(11)1.2684920.6644791.9090030.0653 C(12)1.7162290.4494943.8181330.0006 C(13)-3.1980780.704544-4.5392180.0001 C(14)2.3990250.8734772.7465220.0098 C(15)-0.1566240.839850-0.1864910.8532 C(16)-0.0161350.026257-0.6145260.5432 R-squared0.705076 Mean dependent var0.022440 Adjusted R-squared0.566830 S.D. dependent var0.169311 S.E. of regression0.111433 Akaike info criterion-1.289581 Sum squared resid0.397356 Schwarz criterion-0.665848 Log likelihood46.94995 Durbin-Watson stat2.087974 White Heteroskedasticity Test: F-statistic 1.788021 Probability 0.116205 Jarque-Bera normality Test: Statistic 2.391790 Probability 0.302433

28. 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) CoefficientStd. Errort-StatisticProb. C(1)0.1465020.0747301.9604290.0587 C(2)0.6452110.2083093.0973810.0040 C(3)-0.4726820.226722-2.0848530.0451 C(4)0.0987390.1330760.7419790.4635 C(5)-0.2658590.073777-3.6035580.0011 C(6)-0.0222320.084235-0.2639300.7935 C(7)-0.0761690.077014-0.9890160.3301 C(8)-0.1563500.068061-2.2971980.0283 C(9)2.8842670.5604995.1458930.0000 C(10)-0.9069270.690607-1.3132320.1984 C(11)1.5415380.5864832.6284450.0131 C(12)1.7756260.4592973.8659600.0005 C(13)-2.6562610.619329-4.2889360.0002 C(14)2.3690200.7814753.0314720.0048 C(15)-0.5097620.766876-0.6647250.5110 C(16)-0.0068600.024101-0.2846470.7777 R-squared0.704920 Mean dependent var0.022440 Adjusted R-squared0.566601 S.D. dependent var0.169311 S.E. of regression0.111463 Akaike info criterion -1.289052 Sum squared resid0.397566 Schwarz criterion-0.665318 Log likelihood46.93725 Durbin-Watson stat2.215315 White Heteroskedasticity Test : F-statistic 1.687595 Probability 0.141207 Jarque-Bera normality Test: Statistic 6.482801 Probability 0.039109

29. 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

30. Romanian “ Trade Openness” to GDP ratio 68.0% 70.0% 72.0% 74.0% 76.0% 78.0% 80.0% 82.0% 84.0% 86.0% 200120022003 period Weight in GDP Romanian Trade volumes 0 2000 4000 6000 8000 10000 12000 14000 1990199219941996199820002002 period mil USD export with EU export with Europe Total export back Source: Romanian External Trade Department