Dissertation Paper Real effective exchange rates and their

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Transcript Dissertation Paper Real effective exchange rates and their

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

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 provide an 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 * )

RER

E

P

*

P

ln(

RER

) 

e

p

* 

p

 REER= multilateral real exchange rate

REER

i n

  1 (

E i

P i

*)

w i P

ln

(REER)

i n

  1 ln(

RER

) 

w

i

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) preaccession countries”  „Estimates of Fundamental real effective exchange rate for the five EU 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, Bala sz (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

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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

VAR Lag Order Selection Criteria Endogenous variables: E XPORT, REE R_CPI Exogenous variables: C Sample: 1990:1 2003:4 Included observations: 44 Lag LogL LR FPE 0 1 2 3 4 18.64299 140.5235 197.2145 218.7088 227.7022 NA 227.1409 100.4977 36.14953 14.30762 0.001609 7.58E-06 6.92E-07 3.14E-07 2.51E-07 5 6 7 8 237.7466 239.8403 242.0719 243.5213 15.06670* 2.950117 2.941641 1.778921 1.93E-07* 2.14E-07 2.36E-07 2.73E-07 9 10 11 12 245.6951 246.6142 248.3471 255.1624 2.470124 0.960939 1.654083 5.885988 3.07E-07 3.71E-07 4.37E-07 4.15E-07 * indicates lag order selected by the criterion VAR Lag Order Selection Criteria Endogenous variables: IMP ORT, REE R_CPI Exogenous variables: C Sample: 1990:1 2003:4 Included observations: 44 Lag LogL LR FPE 0 1 2 3 4 5 6 7 35.60992 157.4382 192.4339 225.4138 229.3502 240.4575 245.1842 253.8275 NA 227.0436 62.03789 55.46624 6.262357 16.66095 6.660372 11.39348 0.000744 3.51E-06 8.60E-07 2.31E-07 2.33E-07 1.71E-07 1.67E-07 1.38E-07 8 9 10 11 255.9610 257.5618 260.4494 273.2037 2.618347 1.819084 3.018900 12.17457* 1.55E-07 1.79E-07 1.98E-07 1.41E-07 12 283.4469 8.846322 1.15E-07* * indicates lag order selected by the criterion AIC -0.756500 -6.114703 -8.509749 -9.304945 -9.531916 -9.806665* -9.720012 -9.639630 -9.523697 -9.440684 -9.300646 -9.197594 -9.325564 SC -0.675400 -5.871404 -8.104252 -8.737249 -8.802021 -8.914570* -8.665718 -8.423137 -8.145005 -7.899793 -7.597556 -7.332304 -7.298076 HQ -0.726424 -6.024476 -8.359371 -9.094416 -9.261236 -9.475833* -9.329029 -9.188495 -9.012412 -8.869247 -8.669058 -8.505854 -8.573674 AIC -1.527724 -6.883554 -8.292451 -9.609720 -9.606827 -9.929886 -9.962918 -10.17398 -10.08914 -9.980081 -9.929520 -10.32744 -10.61122* SC -1.446624 -6.640255 -7.886953 -9.042024* -8.876931 -9.037791 -8.908624 -8.957486 -8.710444 -8.439190 -8.226430 -8.462154 -8.583732 HQ -1.497648 -6.793327 -8.142073 -9.399191 -9.336146 -9.599054 -9.571935 -9.722844 -9.577851 -9.408645 -9.297932 -9.635704 -9.859330* VAR Lag Order Selection Criteria Endogenous variables: E XPORT, REE R_PP I Exogenous variables: C Sample: 1990:1 2003:4 Included observations: 44 Lag LogL LR FPE 0 1 2 3 4 22.33651 142.5551 201.3957 221.0981 230.6090 NA 224.0438 104.3083 33.13589 15.13092 0.001360 6.91E-06 5.72E-07 2.81E-07 2.20E-07 5 6 7 8 237.9007 240.5912 243.1992 245.8116 10.93761* 3.791085 3.437847 3.206170 1.92E-07* 2.06E-07 2.24E-07 2.46E-07 9 10 11 12 248.1479 249.0865 250.8831 260.2801 2.654817 0.981315 1.714890 8.115579 2.75E-07 3.31E-07 3.89E-07 3.29E-07 * indicates lag order selected by the criterion VAR Lag Order Selection Criteria Endogenous variables: IMP ORT, REE R_PP I Exogenous variables: C Sample: 1990:1 2003:4 Included observations: 44 Lag LogL LR FPE 0 1 2 3 4 5 6 7 37.80223 159.2074 195.9572 226.9968 231.2568 240.1207 245.3190 254.2628 NA 226.2552 65.14738 52.20287 6.777246 13.29596 7.324769 11.78962 0.000673 3.24E-06 7.33E-07 2.15E-07 2.14E-07 1.73E-07 1.66E-07 1.36E-07 8 9 10 11 256.6843 259.4509 263.1227 275.4063 2.971868 3.143793 3.838718 11.72523* 1.50E-07 1.64E-07 1.75E-07 1.28E-07 12 285.1218 8.390666 1.06E-07* * indicates lag order selected by the criterion AIC -0.924387 -6.207051 -8.699805 -9.413551 -9.664045 -9.813670* -9.754144 -9.690873 -9.627802 -9.552176 -9.413024 -9.312867 -9.558185 SC -0.843287 -5.963752 -8.294307 -8.845855 -8.934149* -8.921575 -8.699851 -8.474380 -8.249110 -8.011285 -7.709934 -7.447578 -7.530696 HQ -0.894311 -6.116824 -8.549427 -9.203022 -9.393365 -9.482838* -9.363161 -9.239738 -9.116516 -8.980739 -8.781436 -8.621128 -8.806294 AIC -1.627374 -6.963975 -8.452602 -9.681672 -9.693490 -9.914579 -9.969044 -10.19376 -10.12202 -10.06595 -10.05103 -10.42756 -10.68735* SC -1.546274 -6.720676 -8.047105 -9.113976* -8.963594 -9.022485 -8.914750 -8.977272 -8.743324 -8.525058 -8.347942 -8.562269 -8.659866 HQ -1.597298 -6.793327 -8.142073 -9.399191 -9.336146 -9.599054 -9.571935 -9.722844 -9.577851 -9.408645 -9.297932 -9.635704 -9.859330* 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 Lags interval (in first differences): 1 to 5 Unrestricted Cointegration Rank Test Hypothesized No. of CE(s) Eigenvalue Trace Statistic 5 Percent Critical Value 1 Percent Critical Value None ** At most 1 0.278567 0.053139 19.05595 2.730156 15.41 3.76 *(**) denotes rejection of the hypothesis at the 5%(1%) level Trace test indicates 1 cointegrating equation(s) at the 5% level Hypothesized No. of CE(s) Eigenvalue Trace Statistic 5 Percent Critical Value 20.04 6.65 1 Percent Critical Value None ** 0.305608 21.80719 15.41 20.04 At most 1 0.068935 3.571283 3.76 6.65 *(**) denotes rejection of the hypothesis at the 5%(1%) level Trace test indicates 1 cointegrating equation(s) at bot h 5% and 1%level Import and REER_CPI and REER_PPI Hypothesized No. of CE(s) Eigenvalue Trace Statistic 5 Percent Critical Value None ** At most 1 0.220942 0.129856 19.43829 6.954482 15.41 3.76 *(**) denotes rejection of the hypothesis at the 5%(1%) level Trace test indicates 2 cointegrating equation(s) at the 5% level 1 Percent Critical Value 20.04 6.65 Hypothesized No. of CE(s) Eigenvalue Trace Statistic 5 Percent Critical Value 1 Percent Critical Value None ** 0.254476 21.91039 15.41 20.04 At most 1 0.134579 7.226983 3.76 6.65 *(**) denotes rejection of the hypothesis at the 5%(1%) level Trace test indicates 2 cointegrating equation(s) at bot h 5% and 1%levels

Pairwise Granger Causality Tests

Sample: 1990:1 2003:4 Lags: 1 Null Hypothesis: REER_CPI does not Granger Cause EXPORT EXPORT does not Granger Cause REER_CPI Lags: 2 REER_CPI does not Granger Cause EXPORT EXPORT does not Granger Cause REER_CPI Lags:3 REER_CPI does not Granger Cause EXPORT Obs 55 54 F-Statistic 12.7740

1.37356

30.6393

1.05514

Probability 0.00077

0.24654

2.3E-09 0.35592

53 3.82998

0.01571

EXPORT does not Granger Cause REER_CPI Lags:4 REER_CPI does not Granger Cause EXPORT EXPORT does not Granger Cause REER_CPI Lags:5 REER_CPI does not Granger Cause EXPORT EXPORT does not Granger Cause REER_CPI Lags:6 52 51 0.79001

3.96543

1.92690

2.03730

1.74625

0.50570

0.00795

0.12323

0.09400

0.14634

REER_CPI does not Granger Cause EXPORT EXPORT does not Granger Cause REER_CPI 50 2.45737

1.28232

0.04225

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

Pairwise Granger Causality Tests

Sample: 1990:1 2003:4 Lags: 1 Null Hypothesis: REER_CPI does not Granger Cause IMPORT IMPORT does not Granger Cause REER_CPI Lags: 2 REER_CPI does not Granger Cause IMPORT IMPORT does not Granger Cause REER_CPI Lags: 3 REER_CPI does not Granger Cause IMPORT IMPORT does not Granger Cause REER_CPI Lags: 4 Null Hypothesis: REER_CPI does not Granger Cause IMPORT IMPORT does not Granger Cause REER_CPI Lags: 5 Null Hypothesis: REER_CPI does not Granger Cause IMPORT IMPORT does not Granger Cause REER_CPI Obs 55 54 53 Obs 52 Obs 51 F-Statistic 6.71508

3.99534

6.02671

1.28449

3.03152

0.72388

F-Statistic 2.33387

0.37474

F-Statistic 0.97039

1.43388

Probability 0.01238

0.05087

0.00457

0.28595

0.03866

0.54292

Probability 0.07077

0.82536

Probability 0.44750

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

Responses of Export and Import to REER_CPI and REER_PPI impulses

Response of EXPORT to Cholesky One S.D. REER_CPI Innovation Response of EXPORT to Cholesky One S.D. REER_PPI Innovation .16

.16

.12

.12

.08

.08

.04

.04

.00

.00

-.04

-.04

25 50 75 100 125 150 175 200 25 50 75 100 125 150 175 200 Response of IMPORT to Cholesky One S.D. REER_CPI Innovation .04

.02

.00

-.02

.14

.12

.10

.08

.06

25 50 75 100 125 150 175 200 Response of IMPORT to Cholesky One S.D. REER_PPI Innovation .04

.02

.00

-.02

.12

.10

.08

.06

25 50 75 100 125 150 175 200

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]

    1.07

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

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Error Correction: CointEq1 D(EXPORT(-1)) D(EXPORT(-2)) D(EXPORT(-3)) D(EXPORT(-4)) D(EXPORT(-5)) D(REER_CPI(-1)) D(REER_CPI(-2)) D(REER_CPI(-3)) D(REER_CPI(-4)) D(REER_CPI(-5)) C R-squared Adj. R-squared D(EXPORT) -0.026831 -0.00796 [-3.37139] 1.739403 -0.14054 [ 12.3764] -0.995528 -0.24651 [-4.03844] 0.011508 -0.194 [ 0.05932] 0.135763 -0.17803 [ 0.76259] 0.034147 -0.10317 [ 0.33098] -0.028347 -0.04203 [-0.67439] -0.015701 -0.03904 [-0.40218] -0.003189 -0.03615 [-0.08820] 0.008532 -0.03446 [ 0.24760] -0.022911 -0.03963 [-0.57809] 0.003103 -0.00252 [ 1.23355] 0.977714 0.971262 D(REER_CPI) 0.037366 -0.03473 [ 1.07602] 0.396493 -0.61324 [ 0.64655] -1.626568 -1.07564 [-1.51219] 1.097897 0.396493 -0.8465 0.663789 -0.77681 [ 0.85451] -0.751968 -0.45017 [-1.67041] -0.031705 -0.18341 [-0.17286] -0.032804 -0.17034 [-0.19258] -0.071179 -0.15774 [-0.45123] 0.661299 -0.15035 [ 4.39840] -0.034658 -0.17293 [-0.20041] 0.010857 -0.01097 [ 0.98929] 0.599403 0.483441 Error Correction: CointEq1 D(E XPORT(-1)) D(E XPORT(-2)) D(E XPORT(-3)) D(E XPORT(-4)) D(E XPORT(-5)) D(REER_PPI(-1)) D(REER_PPI(-2)) D(REER_PPI(-3)) D(REER_PPI(-4)) D(REER_PPI(-5)) C R-squared Adj. R-squared Export and REER D(EXPORT) -0.028198 -0.00748 [-3.76757] 1.686887 -0.14096 [ 11.9670] -0.929841 -0.24379 [-3.81409] -0.015874 -0.18797 [-0.08445] 0.103608 -0.17251 [ 0.60060] 0.067053 -0.10082 [ 0.66506] -0.050379 -0.04334 [-1.16241] -0.035705 -0.04212 [-0.84768] -0.018617 -0.03819 [-0.48748] -0.00479 -0.03568 [-0.13423] -0.027285 -0.03782 [-0.72145] 0.004179 -0.0025 [ 1.66879] 0.979022 0.972949 D(REER_PPI) 0.018593 -0.03499 [ 0.53144] 0.188421 -0.65892 [ 0.28595] -1.221119 -1.1396 [-1.07153] 0.872541 -0.87866 [ 0.99304] 0.435582 -0.80639 [ 0.54016] -0.576815 -0.47129 [-1.22390] -0.074302 -0.20259 [-0.36676] -0.143763 -0.1969 [-0.73015] -0.188018 -0.17852 [-1.05320] 0.522877 -0.1668 [ 3.13484] -0.130857 -0.17679 [-0.74019] 0.018002 -0.01171 [ 1.53771] 0.545854 0.414391

Error Correction: CointEq1 D(IMPORT(-1)) D(IMPORT(-2)) D(IMPORT(-3)) D(IMPORT(-4)) D(IMPORT(-5)) D(REER_CPI(-1)) D(REER_CPI(-2)) D(REER_CPI(-3)) D(REER_CPI(-4)) D(REER_CPI(-5)) C R-squared Adj. R-squared D(IMPORT) -0.032755 -0.01028 [-3.18586] 0.745684 -0.14289 [ 5.21865] 0.074828 -0.15227 [ 0.49141] 0.09975 -0.12756 [ 0.78200] -0.559474 -0.13069 [-4.28104] 0.182278 -0.11005 [ 1.65636] -0.048302 -0.06324 [-0.76377] -0.022826 -0.05791 [-0.39415] -0.025285 -0.05557 [-0.45499] 0.0006 -0.05446 [ 0.01101] 0.009193 -0.06222 [ 0.14774] 0.017404 -0.00452 [ 3.84629] 0.878063 0.842766 D(REER_CPI) -0.027104 -0.02632 [-1.02964] -0.30989 -0.36585 [-0.84704] 0.009553 -0.38988 [ 0.02450] 0.415445 -0.3266 [ 1.27203] 0.080728 -0.33461 [ 0.24126] -0.344243 -0.28177 [-1.22173] -0.068509 -0.16192 [-0.42310] -0.207774 -0.14828 [-1.40123] -0.2286 -0.14229 [-1.60661] 0.508509 -0.13944 [ 3.64678] -0.252885 -0.15932 [-1.58731] 0.018448 -0.01159 [ 1.59233] 0.546659 0.415429 Error Correction: CointEq1 D(IMPORT(-1)) D(IMPORT(-2)) D(IMPORT(-3)) D(IMPORT(-4)) D(IMPORT(-5)) D(REER_PPI(-1)) D(REER_PPI(-2)) D(REER_PPI(-3)) D(REER_PPI(-4)) D(REER_PPI(-5)) C R-squared Adj. R-squared Import and REER D(IMPORT) -0.026887 -0.00817 [-3.28986] 0.755633 -0.14285 [ 5.28964] 0.06916 -0.15294 [ 0.45221] 0.088999 -0.12843 [ 0.69299] -0.562758 -0.13091 [-4.29894] 0.196872 -0.10993 [ 1.79094] -0.048784 -0.06184 [-0.78887] -0.035428 -0.05779 [-0.61305] -0.028545 -0.05585 [-0.51108] -0.023677 -0.05541 [-0.42732] 0.004645 -0.06083 [ 0.07636] 0.017544 -0.00448 [ 3.91921] 0.876274 0.840458 D(REER_PPI) -0.032249 -0.02089 [-1.54376] -0.492515 -0.36514 [-1.34885] 0.175768 -0.39092 [ 0.44963] 0.336445 -0.32827 [ 1.02491] 0.140002 -0.3346 [ 0.41841] -0.354086 -0.28098 [-1.26018] -0.088648 -0.15807 [-0.56082] -0.252976 -0.14771 [-1.71261] -0.287974 -0.14276 [-2.01717] 0.429441 -0.14163 [ 3.03218] -0.284672 -0.15548 [-1.83089] 0.020442 -0.01144 [ 1.78657] 0.518917 0.379657

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) - 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-squared Adjusted R-squared S.E. of regression Durbin-Watson stat 0.977714

0.971262

0.008929

2.013430

Mean dependent var S.D. dependent var Sum squared resid 0.032526

0.052673

0.003030

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 R-squared Adjusted R-squared S.E. of regression C(1)=-0.028198 t-Statistic =-3.767567 Prob =0.0003

0.979022

0.972949

0.008663

Mean dependent var S.D. dependent var Sum squared resid 0.032526

0.052673

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 Adjusted R-squared S.E. of regression Durbin-Watson stat 0.878063

0.842766

0.016188

1.664252

Mean dependent var S.D. dependent var Sum squared resid 0.035058

0.040824

0.009958

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 Adjusted R-squared S.E. of regression Durbin-Watson stat 0.876274

0.840458

0.016306

1.675513

Mean dependent var S.D. dependent var Sum squared resid 0.035058

0.040824

0.010104

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 VAR Lag Order Selection Criteria Endogenous variables: TB, REER_CP I Exogenous variables: C Sample: 1990:1 2003:4 Included observations: 44 Lag LogL LR FPE 0 1 2 3 4 17.70244 88.67878 91.89628 94.40193 104.8354 NA 132.2741 5.703744 4.214051 16.59863 0.001679 8.00E-05 8.30E-05 8.92E-05 6.70E-05 5 6 7 8 9 131.8029 141.2231 151.3592 154.7967 157.2011 40.45131 13.27391 13.36123* 4.218743 2.73231 2.38E-05 1.89E-05 1.46E-05 1.54E-05 1.72E-05 10 11 161.4021 167.3322 4.391939 5.660496 1.78E-05 1.74E-05 12 177.3208 8.626542 1.4E-05* * indicates lag order selected by the criterion AIC SC -0.713747 -3.758126 -3.722558 -3.654633 -3.947062 -4.991041 -5.237413 -5.516327 -5.490759 -5.418233 -5.427369 -5.515098 -5.787308* HQ -0.632648 -3.514828 -3.317061 -3.086937 -3.217166 -4.098946 -4.183119 -4.299834* -4.112067 -3.877342 -3.724278 -3.649809 -3.75982 -0.683672 -3.6679 -3.57218 -3.444104 -3.676381 -4.660209 -4.84643 -5.065193* -4.979473 -4.846796 -4.795781 -4.823359 -5.035418 VAR Lag Order Selection Criteria Endogenous variables: TB, REER_PP I Exogenous variables: C Sample: 1990:1 2003:4 Included observations: 44 Lag LogL LR FPE AIC SC HQ 0 1 2 3 4 5 6 25.93637 NA 90.80959 93.2591 95.20509 120.9001 4.342315 3.272803 104.053 127.3334 137.2678 14.07614 34.92065 13.9985 0.001155 7.26E-05 7.80E-05 8.60E-05 6.94E-05 2.92E-05 2.26E-05 -1.088017 -3.854981 -3.784505 -3.691141 -3.911498 -4.787881 -5.057627 -1.006918 -3.611683 -3.379007 -3.123444 -3.181602 -3.895786 -4.003333 -1.057941 -3.764755 -3.634127 -3.480611 -3.640817 -4.457049 -4.666644 7 8 9 10 11 12 147.7789 151.4471 154.1415 157.5464 169.0374 172.6375 13.85551 4.501931 3.061851 3.55959 1.72E-05 1.79E-05 1.97E-05 2.12E-05 -5.353585 -4.137092* -4.902451* -5.338505 -5.279161 -5.252108 10.96870* 1.61E-05* -5.592609* 3.10918 1.77E-05 -5.574431 * indicates lag order selected by the criterion -3.959813 -3.73827 -3.549018 -3.727319 -3.546943 -4.82722 -4.707725 -4.62052 -4.900869 -4.822541

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 Hypothesized No. of CE(s) Eigenvalue Max-Eigen Statistic 5 Percent Critical Value 1 Percent Critical Value None ** At most 1 0.316328 0.053405 19.01385 2.744201 18.96 12.25 23.65 16.26 *(**) denotes rejection of the hypothesis at the 5%(1%) level Max-eigenvalue test indicates 1 cointegrating equation(s) at the 5% level Hypothesized No. of CE(s) Eigenvalue Trace Statistic 5 Percent Critical Value None ** 0.241673 14.01937 12.53 At most 1 0.015312 0.740640 3.84 *(**) denotes rejection of the hypothesis at the 5%(1%) level Trace test indicates 1 cointegrating equation(s) at 5% level 1 Percent Critical Value 16.31 6.51

Pairwise Granger Causality Tests: Sample: 1990:1 2003:4

Lags: 1

Null Hypothesis: REER_CPI does not Granger Cause TB TB does not Granger Cause REER_CPI

Lags: 2

Null Hypothesis: REER_CPI does not Granger Cause TB TB does not Granger Cause REER_CPI Obs 55 Obs 54

Lags: 1

Null Hypothesis: REER_PPI does not Granger Cause TB TB does not Granger Cause REER_PPI Obs 55

Lags: 2

Null Hypothesis: REER_PPI does not Granger Cause TB TB does not Granger Cause REER_PPI Obs 54 F-Statistic 9.52595

0.02620

Probability 0.00324

0.87203

F-Statistic 2.32283

0.02812

Probability 0.10869

0.97229

F-Statistic 9.19004

0.01979

Probability 0.00379

0.88866

F-Statistic 2.31398

0.02818

Probability 0.10958

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]

  1.07

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)

Error Correction Model

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) ) 0.1036032247*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)) –0.07424238375*D(TB(-1)) + –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)

C(1) C(2) C(3) C(4) C(5) C(6) C(7) C(8) C(9) C(10) C(11) C(12) C(13) C(14) C(15) C(16) Coefficient 0.154977

0.772608

-0.430887

0.042718

-0.252806

-0.052952

-0.063642

-0.191026

3.421184

-0.841963

1.268492

1.716229

-3.198078

2.399025

-0.156624

-0.016135

Std. Error 0.087303

0.225150

0.253643

0.140261

0.076088

0.085477

0.080023

0.071940

0.646882

0.769861

0.664479

0.449494

0.704544

0.873477

0.839850

0.026257

t-Statistic 1.775161

3.431524

-1.698796

0.304563

-3.322545

-0.619482

-0.795298

-2.655359

5.288729

-1.093657

1.909003

3.818133

-4.539218

2.746522

-0.186491

-0.614526

Prob. 0.0854

0.0017

0.0991

0.7627

0.0022

0.5400

0.4323

0.0122

0.0000

0.2823

0.0653

0.0006

0.0001

0.0098

0.8532

0.5432

R-squared Adjusted R-squared S.E. of regression Sum squared resid Log likelihood 0.705076

0.566830

0.111433

0.397356

46.94995

Mean dependent var S.D. dependent var Akaike info criterion Schwarz criterion Durbin-Watson stat 0.022440

0.169311

-1.289581

-0.665848

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)

C(1) C(2) C(3) C(4) C(5) C(6) C(7) C(8) C(9) C(10) C(11) C(12) C(13) C(14) C(15) C(16)

R-squared Adjusted R-squared S.E. of regression Sum squared resid Log likelihood

Coefficient 0.146502

0.645211

-0.472682

0.098739

-0.265859

-0.022232

-0.076169

-0.156350

2.884267

-0.906927

1.541538

1.775626

-2.656261

2.369020

-0.509762

-0.006860

Std. Error 0.074730

0.208309

0.226722

0.133076

0.073777

0.084235

0.077014

0.068061

0.560499

0.690607

0.586483

0.459297

0.619329

0.781475

0.766876

0.024101

0.704920

0.566601

0.111463

0.397566

46.93725

t-Statistic 1.960429

3.097381

-2.084853

0.741979

-3.603558

-0.263930

-0.989016

-2.297198

5.145893

-1.313232

2.628445

3.865960

-4.288936

3.031472

-0.664725

-0.284647

Prob. 0.0587

0.0040

0.0451

0.4635

0.0011

0.7935

0.3301

0.0283

0.0000

0.1984

0.0131

0.0005

0.0002

0.0048

0.5110

0.7777

Mean dependent var S.D. dependent var Akaike info criterion Schwarz criterion Durbin-Watson stat 0.022440

0.169311

-1.289052

-0.665318

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 Openness” to GDP ratio

86.0% 84.0% 82.0% 80.0% 78.0% 76.0% 74.0% 72.0% 70.0% 68.0% 2001 2002

period

2003 Weight in GDP Romanian Trade volumes 14000 12000 10000 8000 6000 4000 2000 0 export with EU export with Europe Total export

period

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Source: Romanian External Trade Department