This paper explores the sustainability of the Romanian current account. For this purpose we test the stationarity and cointegration of the monthly credit and debit transactions of the current account. It results these time series have unit roots for levelRomanian Current Account, Sustainability, Cointegration

DUMITRIU RAMONA

STEFANESCU RAZVAN

English

Research Papers in Economics

163 
 
ANALYSIS OF THE ROMANIAN CURRENT ACCOUNT SUSTAINABILITY 
 
Dumitriu Ramona,  
“Dunarea de Jos” University Galati, Faculty of Economic Sciences,  59-61 Nicolae Balcescu 
Street, 800001, Galati rdumitriu@ugal.ro 0748 - 917 045 
Stefanescu Razvan,  
“Dunarea de Jos” University Galati, Faculty of Economic Sciences,  59-61 Nicolae Balcescu 
Street, 800001, Galati rzvn_stefanescu@yahoo.com 0741 - 731 937 
 
This paper explores the sustainability of the Romanian current account. For this purpose we test  the 
stationarity and cointegration of the monthly credit and debit transactions of the current account. It results 
these time series have unit roots for levels values, but they are stationary for their first differences. We find 
that the debit and the credit transactions are not cointegrated so the current account deficit could not be 
considered as sustainable. 
 
Keywords: Romanian Current Account, Sustainability, Cointegration  
 
JEL Classification: F40, C22, C32 
 
Introduction 
This paper approaches the perspectives of the Romanian current account sustainability. In the 
recent  years  Romania  experienced  significant  deficits  of  the  current  account  and  their 
perpetuation could become a serious constraint for the macroeconomic policies. 
In  the  last  decades  the  problem  of  external  disequilibrium  was  largely  approached  in  the 
specialized literature. A clear distinction between sustainable and unsustainable foreign trade 
disequilibrium was made by Mann (2002). A sustainable disequilibrium occurs when the exports 
and the imports converge on a long-run. In that case significant changes in the macroeconomic 
policy are not necessary. An unsustainable disequilibrium occurs when exports and imports don’t 
converge on a long-run. In the absence of an active implication of the government this situation 
could lead to significant increases of the interest rates in order to attract foreign capitals.  
For the analysis of the current account sustainability we used several methods. The most reliable 
seemed to be the cointegration techniques which allow analyzing if exports and imports are 
moving together on a long-run. A simple model proposed by Husted (1992) could be used in 
studying  the  cointegration  between  exports  and  imports.  Arize  (2002)  provided  a  similar 
framework based on the equation: 
 
Mt= a + b Xt + et                                                                                                                              (1) 
where: Mt refers to the imports of goods and services;  
            Xt refers to the exports of goods and services;              
  et is a stationary process.  
A  current  account  is  considered  as  sustainable  if  Mt  and  Xt  are  cointegrated  and  the  slope 
coefficient b is statistically equal to 1. 
The  cointegration  techniques  were  applied  in  the  current  account  sustainability  analyze  for 
several countries. Bahmani - Oskooee (1994) proved that Australian exports and imports will 
converge in the long-run. Hollauer and Mendonça (2006) tested the cointegration of Brazilian 
exports and imports using monthly data and we found the balance of accounts was sustainable. 
Verma  and  Perera  (2008)  found  that  Sri  Lanka  current  account  deficits  are  unsustainable. 
Erbaykal and Karaca (2008) examined the foreign deficit of Turkey and concluded that, although 
exports and imports are cointegrated, the slope coefficient of their regression is not statistically 
equal to 1. 164 
 
The analysis of the Romanian current account sustainability has some particularities. First, the 
importance of the current account components other than exports and imports has to be taken into 
consideration. Second, it has to be adapted to the significant changes that occurred in the last 
decades. In this paper we analyze the cointegration between the credit transactions of the current 
account instead of the exports and the debit transactions of the current account instead of the 
imports. We apply tests of stationarity that allow taking into account the structural breaks.  
The remaining part of this paper is set out as follows. The second part approaches the data and 
methodology we used. The results of the analyses are presented in the third part and the fourth 
part concludes. 
 
Data and Methodology 
In this analysis we employ monthly data of credit and debit transactions of the Romanian current 
account provided by the National Bank of Romania. Our sample covers the period from January 
2005 to February 2009. Because of the significant seasonality of these values we apply ARIMA 
(Autoregressive Integrated Moving Average) technique to obtain seasonally adjusted values. We 
use four variables: 
  -X for natural logarithms of seasonally adjusted values of credit transactions from the 
  current account; 
  -M for natural logarithms of seasonally adjusted values of debit transactions from the 
  current account; 
  -d_X for first differences of X; 
  -d_M for first differences of M. 
 
We  use two  unit root  tests  for  analyzing  the  stationarity  of the four  time  series: the  classic 
Augmented Dickey Fuller (ADF) and a test proposed by Saikkonen and Lutkepohl (2002) and 
Lanne et al (2002) which allows taking into account the structural breaks. For selecting the 
numbers  of  lagged  differences  we  apply  four  criteria:  Akaike  Info  Criterion  (AIC),  Final 
Prediction Error (FPE), Hannan-Quinn Criterion (HQC) and Schwarz Criterion (SC). 
After we drew conclusions about the stationarity of the four variables we study the cointegration 
between credit and debit transactions. We start with the classical Engle-Granger method (1987) 
which consists in performing a regression between the two variables and testing the stationarity 
of the resulted residuals. We continue with much powerful lambda-max and trace cointegration 
tests proposed by Johansen (1995) and then with the nonparametric test developed by Breitung 
(2002).  
 
Empirical Results 
We begin to test the stationarity for levels values of the debit and credit transactions   taking into 
consideration, as Figure 1 suggests, intercept and time trend as deterministic terms. The results of 
the ADF test are presented in the Table 1. It suggests that we cannot reject, for both time series, 
the null hypothesis of a unit root. 
 
Table 1 - Augmented Dickey Fuller Unit Root Test for levels values of the two  
      variables (with intercept and time trend as deterministic terms) 
 
Variable  Lagged differences  Test statistics 
X  AIC, FPE, HQC, SC: 4  -0.7034 
M  AIC, FPE: 4  1.2819 
HQC, SC: 1  0.8484 
 165 
 
We also apply the unit root tests with structural breaks with two kind of shift function for the 
structural breaks: with impulse dummy and with shift dummy.  The results confirm that debit and 
credit transactions are not stationary (see Table 2).  
 
 
Table 2 - Unit root tests with structural breaks for levels values of the  
two variables (with intercept and time trend as deterministic terms) 
 
Variabl
e 
Shift Function  Break Date  Lagged differences  Test statistics 
X  Impulse dummy  2007 M8  AIC, FPE, HQC, SC: 1  -1.3678 
Shift dummy  2007 M8  AIC, FPE, HQC, SC: 1  -1.2776 
M  Impulse dummy  2007 M5  AIC, FPE: 4  -1.6431 
2007 M5  HQC: 1  -1.1041 
2007 M5  SC: 0  -1.3690 
Shift dummy  2007 M11  AIC, FPE, HQC: 1  -1.3072 
2007 M10  SC: 0  -1.4052 
 
 
 
Figure 1 - Evolution of the debit and credit transactions for level values  
and for their first differences 
 
We test the stationarity of the first differences of the debit and credit transactions using only 
intercept as deterministic term (see Figure 1). 
The results of the ADF tests indicate that we can reject the null hypothesis of a unit root for the 
two variables (Table 3).  
 
Table 3 - Augmented Dickey Fuller Unit Root Test for the first differences values  
of the two variables (with intercept as deterministic term) 
 
 7.7
 7.8
 7.9
 8
 8.1
 8.2
 8.3
 8.4
 8.5
 2005  2007  2009
X
 7.9
 8
 8.1
 8.2
 8.3
 8.4
 8.5
 8.6
 8.7
 8.8
 2005  2007  2009
M
-0.2
-0.15
-0.1
-0.05
 0
 0.05
 0.1
 0.15
 2007  2009
d_X
-0.15
-0.1
-0.05
 0
 0.05
 0.1
 0.15
 2007  2009
d_M166 
 
Variable  Lagged differences  Test statistics 
d_ X  AIC, FPE, HQC, SC: 0  -10.7925*** 
d_ M  AIC, FPE: 2  -2.5786* 
HQC, SC: 0  -8.0202*** 
       * Indicates that results are significant at 10% level; 
       *** Indicates that results are significant at 1% level of significance. 
 
We continue the analysis of the stationarity performing the unit root tests with structural breaks 
for the first differences of the debit and credit transactions. It resulted that both time series are 
stationary (Table 4).  
 
Table 4 - Unit root tests with structural breaks for the first differences values of the  
two variables (with intercept as deterministic term) 
 
Variable  Shift Function  Break 
Date 
Lagged differences  Test statistics 
d_ X  Impulse dummy  2007 M8  AIC, FPE, HQC, SC: 0  -9.2245*** 
Shift dummy  2007 M8  AIC, FPE, HQC, SC: 0  -2.7008* 
d_ M  Impulse dummy  2007 M10  AIC, FPE, HQC: 1  -4.5583*** 
2007 M5  SC: 0  -6.9244*** 
Shift dummy  2007 M6  AIC, FPE, HQC, SC: 0  -2.8939* 
 * Indicates that results are significant at 10% level; 
 *** Indicates that results are significant at 1% level of significance. 
 
We  apply  the  Engle-Granger  cointegration  technique  starting  with  a  regression  with  M  as 
dependent variable. A slope coefficient of 1.155 resulted (Table 5).  
 
Table 5 - Cointegration regression (Dependent variable: M) 
Variable  Coefficient  Std. Error  t-statistic  p-value 
const  -1.01697  0.314551  -3.2331  0.00222*** 
X  1.15522  0.0385731  29.9488  <0.00001*** 
R
2  0.949203   
Durbin-Watson 
statistic 
1.3789 
*** Indicates that results are significant at 1% level of significance. 
 
We analyze the stationarity of the residuals with ADF tests. The graphical representation cannot 
indicate a single form of the deterministic terms so we use two variants: with only intercept and 
with  intercept  and  time  trend  (see  Figure  2).  The  results  indicate  that  the  residuals  are  not 
stationary, so we find no evidence of the cointegration relation between the two series.  
 
Table 6 - Augmented Dickey Fuller Unit Root Test for the residuals of cointegration regression 
Deterministic terms  Lagged differences  Test statistics 
Intercept  AIC, FPE, HQC, SC:1  -1.9684 
Intercept and time trend  AIC, FPE, HQC:3  -0.6495 
SC:1  -1.9206 
 167 
 
 
 
Figure 2 - Residuals of the cointegration regression 
 
We continue the cointegration analysis with the two lags Johansen tests with no restriction on 
intercept.  In  Table  7  there  are  presented  the  results  of  lambda-max  test  that  suggest  a 
cointegration rank of 0. 
 
Table 7 - Johansen lambda-max test for cointegration between the two variables  
(with no restriction on intercept) 
 
r  Test statistic  Critical values 
20%  10%  5% 
0  11.5  10.1  12.1  14.0 
1  2.4  1.7  2.8  4.0 
 
The results of trace test, presented in Table 8, indicate also a cointegration rank of zero. In these 
circumstances we reject the hypothesis of cointegration between debit and credit transactions. 
   
Table 8 - Johansen trace test for cointegration between the two variables  
(with no restriction on intercept) 
r  Test statistic  Critical values 
20%  10%  5% 
1  2.4  1.7  2.8  4.0 
0  13.9  11.2  13.3  15.2 
 
We apply the non parametric Breitung test for the case with no drift. The results indicate a 
cointegration rank of zero, so we reject the hypothesis of cointegration between the two variables. 
 
Table 9 - Breitung test for cointegration between the two variables (case with no drift) 
H0  H1  Test statistic  Critical value 
10%  5% 
r = 0  r > 0  143.75  261.00  329.90 
r = 1  r > 1  11.37  67.89  95.60 
 
-0.15
-0.1
-0.05
 0
 0.05
 0.1
 0.15
 2005  2006  2007  2008  2009168 
 
Conclusions 
In  this  paper  we  analyzed  the  Romanian  current  account  sustainability.  We  investigated  the 
stationarity of debit and credit transactions and we found that the two time series had unit roots 
for level values, but are stationary for the first differences. We proved, using several techniques, 
that debit and credit transactions were not cointegrated so the Romanian current account deficit 
was unsustainable.     
The research over the Romanian current account could be extended by using other foreign trade 
variables with nominal and real values. It could be also continued by studying the global crisis 
implication in the external equilibrium. 
 
References 
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Econometrics 108, pp. 343 – 363; 
4.  Erbaykal  E.,  Karaca  O.  (2008),  Is  Turkey’s  Foreign  Deficit  Sustainable?  Cointegration 
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ANALYSIS OF THE ROMANIAN CURRENT ACCOUNT SUSTAINABILITY

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ANALYSIS OF THE ROMANIAN CURRENT ACCOUNT SUSTAINABILITY

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