(2 rânduri libere, 11p)


Studies and Scientific Researches. Economics Edition, No 19, 2014  http://sceco.ub.ro 

 
STATISTICAL ANALYSIS OF THE SEASONAL VARIATION 
OF MOLDOVAN MIGRANTS’REMITTANCES DURING THE 

PERIOD 2003-2013 
  

 Christiana Balan 
“Alexandru Ioan Cuza” University of Iasi  

  christiana.balan@uaic.ro  
Elisabeta Jaba  

“Alexandru Ioan Cuza” University of Iasi  
ejaba@uaic.ro  
Ion Pârţachi 

Academy of Economic Studies of Moldova 
ipartachi@ase.md 
Boris Chistrugă 

Academy of Economic Studies of Moldova 
bchistruga@ase.md 

 
 
Abstract 
As a consequence of the increased number of Moldovan migrants, the volume of remittances 
inflows to Moldova raised steadily. Previous studies on labor migration and remittances in 
Republic of Moldova underline both the role of remittances in generating increased 
consumption of the population and its impact on the economic development of the country. In 
this paper, we aim to analyze the variation of money transfers of Moldovan migrants in order 
to estimate the trend of the remittances inflows and the seasonal variations under the impact of 
the global crisis. The data on remittances are available from the National Bank of Moldova, on 
a monthly basis, for the time span 2003-2013. The study’s results highlight an upward trend 
and the seasonal variation of money transfer of Moldovan migrants for the considered time 
span. 
  
Keywords  
migration; remittances; economic growth; Moldova; trend; seasonal variation 
 
JEL Classification  
F22; F24; O15; C22 
 
 
 
Introduction 
International migration of labor force is a key issue of the European and global labor 
markets. A very important feature of the migration process is the money that migrants 
transfer to their families. Workers’ remittances represent an important source of 
external development finance. The literature on migration underlined the positive and 
negative sides of remittances.  
In developing countries, remittances represent a stable financial flow and have a 
counter-cyclical effect during the economic crisis (OECD, 2005). In some developing 
countries, the remittances flows are larger than public and private capital flows 
(OECD, 2005; Mushtaq, 2007). Remittances play a major role in reducing poverty 
and increasing economic growth (Pantiru et al., 2007; Goschin et al., 2011). The 
positive effect of remittances is highlighted either when they are used for supporting 
children’s education or finance health expenses or when they are used for 
consumption or buying houses or other investments. Remittances stimulate demand 

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Balan, Jaba, Pârțachi, Chistrugă 

for other goods and services thus having a positive effect on the economy and have 
multiplier effects, especially in countries with high unemployment (OECD, 2005). 
Furthermore, remittance receipts imply foreign currency inflows that allow a country 
to pay for imports and repay foreign debt. 
On the other side, Chami et al. (2008) argue that, despite their role in increasing 
households’ disposable income, remittances do not lead automatically to higher 
investments and output growth. Remittances may also have some negative effects on 
a country’s economy. They may reduce recipients’ motivation to work, and thus slow 
down growth. Moreover, remittances may increase income inequality in the recipient 
country.  
In the paper we aim to estimate the trend of the remittances inflows and the seasonal 
variations, for Republic of Moldova, during the period 2003-2013. The rest of the 
paper is structured as follows. Section 2 presents the characteristics of the remittance 
inflows and their importance for Republic of Moldova as described in previous 
studies on this topic. Section 3 explains both the data used in the analysis and the 
techniques applied for the decomposition of seasonal time series considering an 
additive model. Section 4 illustrates the main results of time variation analysis on 
remittances, underlying the seasonal pattern of transfers’ inflows. Final section draws 
the main conclusions of the study. 
  
 
Labor migrants’ money transfers in Republic of Moldova 
The migration flows of Moldovan citizens increased in the last years due to the 
economic unfavorable situation in their own country. The economy of the Republic of 
Moldova faced important changes during the transition process that affected 
population in a negative way. The structural transformations implied by the market 
economy generated inflation, unemployment, economic crisis and, thus, determined a 
part of the population to look for better living and working conditions abroad 
(Cebotari et al., 2012).Estimations about the number of Moldovan migrants presented 
in IOM (2008a) and in Lücke et al. (2007) show that in mid-2006 approximately 
345,000 individuals are migrant workers (25.4% of the economically active 
population in Moldova). However, IOM (2008a) show that other studies such as 
Schwartz (2007) estimates that the number of Moldovans abroad may exceed 800,000 
persons. The Moldovan migrants are mainly qualified workers with secondary 
education or incomplete higher education (Moşneaga, 2000).The principal destination 
country for Moldovan migrants is Russia (65.8%), followed by Italy (8.1%), as shown 
by the results of the survey carried out by CBS-AXA in 2008 and presented in IOM 
(2008b).An important characteristic of the Moldovan migrant workers is the 
seasonality of the migration process especially for the workers in the construction 
sector, for example in Russia (Ghencea & Gudumac, 2004). 
Due to the intensity of the migration phenomenon and the domestic economic 
situation, Republic of Moldova is one of the world countries with a very high 
dependence on remittances. The money transfers sustain consumption as they increase 
the disposable income of the labor migrants’ families in the home country. The 
money transfers often surpass both the foreign direct investment and the development 
assistance (Kring, 2008, Siegel and Lücke, 2009).The money remitted is used mainly 
for daily needs or for buying apartments, used cars, housing or land (Sander et al., 
2005).There are different methods to transfer money, either through formal channel 
(express transfer services and services offered by banks) or by informal channels. The 
formal channel is preferred by the majority of the migrants (75.8%) as shown in the 
report of IOM (2009). However, banks are attracting more of the volume of transfers 
in order to increase the banks’ available capital for loans for entrepreneurs. The 
migrants’ preference for the methods of remittances transfer is assessed by several 

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Studies and Scientific Researches. Economics Edition, No 19, 2014  http://sceco.ub.ro 

studies, such as Siegel and Lücke (2013), Lücke et al. (2009), Lücke et al. (2007), 
Kring (2008), Sander et al. (2005). 
Pantiru et al. (2007) present both the economic and social effects of migration and 
highlight their positive and negative impact on the country’s development. They 
argue that remittances have led to an increase of imports and stimulated inflation. The 
perception of the Moldovan population regarding the impact of remittances is mainly 
positive. More than half (51.6%) of the people surveyed on the issue of migration in 
Moldova in 2008 believe that migrants can contribute to Moldova’s development by 
sending money home, thus ensuring subsistence incomes for families. However this 
positive consequence is limited only to consumption increase (IOM, 2009). In the 
same time, more than a quarter of the respondents (26.9%) consider that Moldovans’ 
remittances may represent a source for the economic development through 
investments in business. The negative consequences of remittances are perceived less 
significant, as only 1% of the surveyed population believe that remittances have 
negative impact on inflation (IOM, 2009).  
 
 
Data and method 

Data 
The data represent the money transfers from abroad in favor of individuals made via 
the national banking system of Republic of Moldova. The data are available from the 
National Bank of Moldova 1.  
The data on remittances sent home by migrants are available on a monthly basis for 
the period January 2003 – September 2013. The original currency amounts are 
expressed in US dollars at the official exchange rate of the National Bank of Moldova 
at the date of transfer. Data include settlements with banks from the Republic of 
Moldova, excluding the banks located in the Transnistrian region (National Bank of 
Moldova, 2013). 
The persons that send/receive money can be of any nationality. The data on money 
transfers include both the money transferred by Moldovan migrants and other foreign 
exchange transfers. 
The data concerns both the total inflows (US$ millions) and the currency structure of 
inflows via international money transfer systems. The currency structure of inflows is 
presented according to the three currencies used to remit the money (US Dollar, Euro 
and Russian Ruble). 
The most important international money transfer operators in Republic of Moldova, in 
2013, are: Allure, Anelik, Avers, Blizko, Coinstar Money Transfer, Contact, 
InterExpress, Leader, Migom, MoneyGram, Poşta Rapidă, Privat Money, RIA Money 
Transfer, Smith&Smith, Strada Italia, Unistream, Western Union, Xpress Money, 
Zolotaya Korona, etc. (National Bank of Moldova, 2013). 

 
Method 

The classical statistical analysis of time series implies the study of the changes in time 
in the evolution of a phenomenon due to the influence of specific factors. Thus, we 
can identify the time series’ components, which are: the long term tendency, the 
seasonal component, the cycle component and the residual component. In order to 

1The authors would like to thank the Department of Balance of Payments from the National Bank of 
Moldova for making available the data on money transfers from January 2003 to September 2013 for this 
study. Data on Money Transfers from Abroad in Favor of Individuals from January 2007 to September 
2009 are available on BNM webpage, in the Statistics section, The International accounts of the Republic of 
Moldova subsection at http://www.bnm.md/en/external_operations_via_banc_system 
 

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Balan, Jaba, Pârțachi, Chistrugă 

study the different components, the time series concerning the remittances inflows 
can be decomposed using an additive model (the appropriate model was chose after 
the graphical analysis of the data), such as: 

                                tttt S)t(fCy ε+++= ,t = 1, …, n. 
where: 
Ct– cyclical component; f(t) – trend component; St– seasonal component; εt–error 
component. The seasonal component (St) is characterized by constant periodicity, 

n,...,t,SS dtt 1)( =∀= + , where d is the period of the seasonal component (Jaba, 
2002; Cormier, 2009). 
The trend component represents the long term tendency of a time series, the law of 
evolution of a phenomenon and it is noted by f(t)The trend component assesses the 
effect of factors with long term influence. The trend analysis implies the elimination 
of seasonal, cyclical and irregular variations from the time series (Pârţachi & 
Caraivanova, 2007).The trend is estimated by applying a moving average filter 
specially used to eliminate the seasonal component and to reduce the noise (Jaba, 
2002; Brockwell & Davis, 2002).The moving average has the following expression, 
in the case of even period (d=2p): 

d/yy...yyy...yyy ptpttttptptt )2
1

2
1

( 1111 +−++−+−− ++++++++=
,      p<t ≤ n–p 

The moving averages are used to estimate the seasonal component, by calculating first 

the differences: tt yy − (for the additive model). Then, the seasonal indices (ik) are 
computed as the average of the differences, using observations only for period k, 
where k = 1, …, d. By adjusting the seasonal indices, the seasonal factors are 
obtained, for the additive model, as the difference between the seasonal index and the 

average of all seasonal indices: 
d,...,k,i

d
iŜ

d

k
kkk 1

1

1

=−= ∑
= .  

The sum of the seasonal factors equals 0(
d,...,k,Ŝ

d

k
k 10

1

==∑
= ).   

The seasonal component is removed from the original series in order to produce the 

deseasonalized time series (seasonally adjusted series): n,...,t,Ŝyd ttt 1=−= . 
The trend is re-estimated from the deseasonalized data in order to have a parametric 

form of the trend, such as the linear trend: n,...,t,tbbŷt 110 =+= ., where the time 
variable t is the exogenous variable.  
The cyclical component (Ct) reflects the long term cyclical influence that is 
nonrandom.  

The random component ( t
ε

) represent the residual or the noise component and it is 
stationary. It reflects the deviations from the ideal non-stochastic model. The 
expectation of the error variable equals 0. The residual component is estimated by: 

n,...,t,Ŝŷy kttt 1=−−=ε . 
The estimation of the seasonal component of the time series on remittances and the 
generation of the deseasonalized series are accomplished using the Seasonal 
Decomposition procedure in SPSS. The Sequence procedure is used to plot the 
original and the seasonal adjusted time series. In order to estimate the trend from the 
seasonally adjusted series, the Curve estimation procedure was applied. The results of 
the data treatment are presented in the following section. 
 

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Studies and Scientific Researches. Economics Edition, No 19, 2014  http://sceco.ub.ro 

Results 
The evolution of transfers’ inflows shows that the time series present an upward trend 
over the considered time span and that there is a strong seasonal variation of the 
transfer inflows (Figure 1). A number of peaks are evident, the increases and 
decreases in the transfers’ inflows repeat almost in the same month every year, thus 
showing clear evidence of an annual pattern. Moreover, it can be noticed a break in 
the time series at the end of 2008. The sudden drop in money transfers of Moldovan 
migrants can be explained by the economic and financial crisis that had a negative 
impact on the remittances. Due to the break in series, the overall time span is split in 
two periods: before the crisis (January 2003 – December 2008) and after the crisis 
(January 2009 – September 2013). The data show that the magnitude of the time 
series is not increasing with the level of the series, therefore the decomposition model 
is considered to be additive. 
 

 
 
Figure 1 The evolution of monthly transfer inflows (US$ millions) of Moldovan 

migrants during the period 2003 – 2013 
Source: Authors’ results with SPSS package 

 
In order to measure the variations due to seasonality in contrast with trend and cycle 
effects, we determine the seasonal component by removing other effects. The moving 
average filter is applied and the seasonal factors are obtained (Table 1). For both time 
spans, January is the month with minimum values of remittances along each year. 
January follows December which is a month with more important money transfers as 
compared to the previous months or the next following it. The reason for this seasonal 
pattern is that December is the period of winter holidays when persons have high 
expenses for the traditional winter celebrations; therefore, migrants send more money 
to their home families during this month. 
 
Table 1 Seasonal factors estimated for the two time spans: before the crisis and 

after the crisis 
 

Month Before the crisis After the crisis 
January -19.89 -37.43 
February -15.89 -27.34 
March -3.99 -7.27 
April 1.12 -7.57 
May -3.18 -1.14 

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June 5.19 6.26 
July 7.39 16.90 
August 11.04 10.81 
September 6.30 17.80 
October 5.28 12.57 
November 0.41 3.99 
December 6.23 12.41 

Source: Authors’ results with SPSS package 
 
Before the crisis, the highest transfers’ inflows are registered in August, followed by 
July and September. After the crisis, the money transfers become quite high in July 
each year and they reach a peak in September, while in August the transfers drop 
considerably, compared to the previous month. This may be explained by the fact that 
August is the period of summer holidays and the temporary employees are working 
less during this month. Therefore, we can notice a change in the seasonal pattern of 
transfers, before and after the crisis, regarding the months with peak amounts of 
money sent back home. The influence of the seasonal factors becomes more important 
during the after the crisis time span. 
If the seasonal variations are removed from the periodic time series, the seasonally 
adjusted series or the deseasonalized series is obtained. The original series for the 
remittances inflows, the seasonally adjusted series and the smoothed trend-cycle 
component are plotted against the periods in Figure 2.  
 

 
(a) 

 
(b) 

 
Figure 2 The original series for remittances inflows, the deseasonalized series 

and the trend-cycle series before the crisis (a) and after the crisis (b) 
Source: Authors’ results with SPSS package 

 
Comparing the real transfers level and the seasonally adjusted level, we can notice 
that the adjustment process correct the variations due to seasonality within the years. 
The seasonally adjusted data are smoother than the actual data but it is still presents 
the same trend and cycle general effects as the original data. 
For both time spans, the graph of the deseasonalized data shows a clear upward trend 
and suggests the presence of a linear trend function. The seasonally adjusted series 
allows isolating the trend component and analyzing it independently of the seasonal 
component. Thus, the deseasonalized series is used for re-estimating the trend that can 
be extrapolated in order to make predictions or simulations. 

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Studies and Scientific Researches. Economics Edition, No 19, 2014  http://sceco.ub.ro 

The trend is re-estimated by a linear regression model and the intercept and the slope 
are estimated using the least squares method. The deseasonalized series and the linear 
trend are plotted in Figure 3 and the estimated coefficients are presented in Table 2. 
 

 
(a) 

 
(b) 

 
Figure 3The seasonally adjusted series and estimated linear trend before the 

crisis (a) and after the crisis (b) 
Source: Authors’ results with SPSS package 

 
For both time spans, the linear trend models are statistically significant. The slope is 
significant for both models, while the intercept is significant only for the model 
corresponding to the years after the crisis. The slope is higher for the before the crisis 
model, showing a more important increase in monthly remittances during the time 
span prior to the crisis. After the crisis, the monthly increase in money transfers is still 
significant but it is smaller compared to the period before 2009. 
 
Table 2 The regression coefficients for the two time spans: before the crisis and 

after the crisis 
 

 Before the crisis After the crisis 
Intercept 5.019 

(3.220) 
93.173*** 
(1.728) 

Slope 1.824*** 
(0.077) 

0.752*** 
(0.052) 

Adjusted R Square 88.8% 78.9% 
Note: *** (Sig. < 0.1%) 

Source: Authors’ results with SPSS package 
 
The crisis impact on remittances is highlighted by the reduced pace of the increase of 
the money transfers. The global crisis had impact on trade, construction and 
manufacture sectors, thus Moldovan migrants experienced declining employment 
opportunities and wages beginning with2009 (Lücke et al., 2009). Indeed, the 
remitted amounts during the period 2009-2013 are smaller than the remitted amounts 
in 2008.  
The monthly transfers via international money transfer operators represent, on 
average, approximately 78% of the total monthly transfers. The maximum value is 
observed in October 2012 (90.45%) while the minimum value (46.88%) is noticed in 
March 2004. The share of money transfers via international money transfer operators 
increased persistently during the period January 2007 – September 2013. 

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The structure of the inflows via international money transfer operators shows different 
trend patterns according to the three currencies: US Dollar, Euro, and Russian Ruble 
(Figure 4).  
 

 
 

Figure 4 The currency structure of inflows via international money transfer 
systems 

Source: Authors’ results with SPSS package 
 
The money remitted in US Dollars shows a declining trend, while the inflows in 
Russian Ruble follow an upward trend. The trend for the inflows in Euro is constant 
though it is declining in the last three years. The divergence in the inflows’ evolution 
by currency highlights the variation in the dynamics of the transfers’ inflows and of 
the labor migration patterns. 
 
 
Conclusion 
The paper aimed to analyze the money transfers of Moldovan migrants during the 
period 2003-2013 using monthly data. The remittances sent by labor migrants to 
important especially for sustaining consumption income of their families in the home 
country.  
The global crisis had impact on sectors employing low-to-medium-skilled jobs, thus 
affecting Moldovan migrants. During the observed time span, the impact of the 
economic crisis on transfers’ inflows is obvious. The trend pattern is similar before 
and after the crisis, but the slope is different between the two periods. 
The remittances seasonality is shown by increases and decreases that repeat every 
year. The lowest level is registered in January each year, while the highest level of 
money transfers is registered in the summer months. The seasonal pattern of the time 
series changes under the impact of the crisis with respect to the amplitude of the 
seasonal variations. Therefore, after the crisis, the trend slowed down, while the 
seasonal variations increased. 
The structural variation of the transfers’ inflows by currency underlines important 
trend changes, the money transfers in Russian Ruble have raised, while the transfers 
in Euros and US Dollar have decreased. 

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Studies and Scientific Researches. Economics Edition, No 19, 2014  http://sceco.ub.ro 

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Acknowledgement 
This work was co-financed from the Erasmus Mundus Action 2 – Strand 1 2009–2013 
EMERGE Project postdoctoral grant at the Academy of Economic Studies of 
Moldova, Republic of Moldova, 1st of September 2013 – 1st of March 2014. 
 

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