




































AGORA International Journal of Economical Sciences, http://univagora.ro/jour/index.php/aijes 

ISSN 2067-3310, E-ISSN 2067-7669 

No. 1 (2023), pp. 126-134 

 

126 
 

THE MICROCREDIT AS A SHORT-TERMS INSTRUMENT FOR SUSTAINABLE 

DEVELOPMENT THE NORTH-WEST REGION OF ALBANIA: SHKODRA CASE 

 

M. ZENELI, A. RECI 

 

Mimoza Zeneli¹, Armalda Reci² 

¹ Business University Collage of Albania, E-mail: mzeneli2017@gmail.com  

² Credins Bank of Albania 

 

Abstract. The Sustainable Development Goals are a global call to action to end poverty, 

protect the Earth's environment and climate, and ensure that people, regardless of location, 

can enjoy peace and well-being. Recently notice that Albanians tend to move abroad. Recent 

trend show that Albanians tend to move abroad. This is characteristic especially for the 

North of Albania. Shkodra region is a northwest part of Albania that is known for its wealth 

of natural recourses, culture and traditions. It is surrounded by a lake, a sea, and a river; 

also the people of Shkoder are called “The creedal of arts and knowledge”. But the poverty 

indicators prove the opposite. The poverty in this region is nearly 15 %, and the 

unemployment level is very high. People tend to leave Shkodra. They have land and 

professions but they don't have the property legality and cash to exploit these natural 

resources.  To have a sustainable development region, the government needs to take 

measures to help people to work their lands and to create their company.  Interviewing a 

sample of 200 people in rural areas in Shkodra (borrowers/not borrowers) we notice that 

microcredit has a short-term impact in increasing their incomes and consequently 

contributes to reduction of immigration. Before and after is the method used for impact 

analysis in order to reach the above conclusion.  

Keywords: Sustainable Development, Shkodra Region, poverty indicator, microcredit 

impact, immigration. 

 

INTRODUCTION 

The Sustainable Development Goals (SDG) are a global call to action to end poverty, 

protect the earth’s environment and climate, and ensure that people everywhere can enjoy 

peace and prosperity.   

19 UN Agencies are working together to support Albania’s achievement of the SDGs, 

United Nations 

Albania (UNA,2022). One of the important objectives of the SDGs is "No poverty" which 

means "The elimination of poverty in all its forms throughout the world".  

Albania has prepared a number of strategies that address development policies in various 

fields of development, which focus on the socioeconomic improvement of Albania in the years 

2021-2030, but based on the current situation of Albania, the urgent need is to reduce inequality 

between the regions regarding main areas of development, especially in the reduction of 

poverty. This is and the first objective of SDGs 

 

mailto:mzeneli2017@gmail.com


Mimoza ZENELI, Armalda RECI 

 

127 
 

I. Problem statement 

The aim of the article is to study the assessment of the impact of microcredit on socio 

economic indicator of Shkoder region regarding the reduction of the level of poverty as a first 

objective of SDG. Access to financial services is crucial for economic development. 

Microcredit is a development model is a model that has been adopted in many countries of the 

world to provide loans to the poor who have no or little collateral. Based on the results on our 

analyses it was noticed the microcredit has an impact on family incomes as well as in improving 

health.  

 

I.1. Poverty in Albania 

The comparison of the risk of being poor for 2021, between Albania and other countries 

of the Region and the European Union show that: The highest value of relative poverty is 

recorded in Latvia (23.4%), Romania (22.6%) ), Bulgaria (22.1%) followed by Albania (22%). 

The lowest poverty rates are recorded in the Czech Republic (8.6%), Finland (10.8%), Slovenia 

(11.7%), Slovakia (12.3%) and Denmark (12.3%). The average of European Union countries 

(27 countries) is 16.8%, Institute of statistics (IS, 2021) 

According to the World Bank, from 2021 to 2023, poverty will decrease by only 1.5 % in 

total, even less than in the last seven years, which proves "The very slow trajectory that poverty 

reduction has in Albania". 

What is important to emphasize is that the level of poverty, as well as other socioeconomic 

indicators, are different in different regions. The Shkodra region is one of the regions with the 

highest poverty indicators, as it is shown in Table 1 

 

Table 1.Poverty indicators by Prefecture, 2012. 

          

              Poverty measures   

District  Headcount   Depth   Severity  

 Berat  12.3              2.3  0.7 

 Dibër  12.7              2.3  0.7 

 Durrës  16.5              3.6  1.3 

 Elbasan  11.3              2.3  0.7 

 Fier  17.1              3.4  1.0 

 Gjirokastër  10.6              2.4  1.0 

 Korçë  12.4              2.5  0.7 

 Kukës  22.5              3.8  0.9 

 Lezhë  18.4              4.7  1.8 

 Shkodër  15.5              3.7  1.6 

 Tiranë  13.9              2.7  0.8 

 Vlorë  11.1              2.4  0.8 

 Total 14.3              3.0  1.0 

Source: Living Standart Measurement Survey, LSMS 2012* INSTAT 

* After publishing the revised data for population 2001-2014 in May 

2014, the data from LSMS 2005, 2008, 2012 are revised. 



THE MICROCREDIT AS A SHORT-TERMS INSTRUMENT FOR SUSTAINABLE DEVELOPMENT 

THE NORTH-WEST REGION OF ALBANIA: SHKODRA CASE 

 

128 
 

The district of Shkodra does not have the highest level of poverty, but what makes us 

analyse this district is the fact that Shkodra is one of the districts with many natural resources, 

with an admirable geographical position on the border, with a tradition in education and culture, 

but regardless of these assets, it is ranked in the high-level poverty districts. 

 

I.2. Shkoder district and natural resources 

The district of Shkodra lies in the northern part of Albania, in a territory of 3,562 km2, 

with geographical limits with Montenegro in the north and northwest, with the district of Kukës 

in the east and with the district of Lezha in the south, while it reaches the Adriatic coast in the 

west and southwest. The favourable geographical position in terms of cross-border relations 

enables the economic and territorial connections of Shkodra with Montenegro and Kosovo, 

turning the city into a strategic point of the district; the climate is Mediterranean, with a mixture 

of continental and maritime. 

In the southeast of Shkodra lies the Rozafa castle, at a height of 130 m above sea level and 

with an area of 3.6 ha, Shkodër District Council (SDC, 2010). To the north and northeast lays 

the plain of Mbishkodra, while to the north and northwest is bordered by the Albanian Alps. In 

the opposite direction, about 30 km southeast of the city, lies Velipoja, a beach on the Adriatic 

coast. Thus, within 30 km of the city there are a number of natural attractions, ranging from 

the high mountains of northern Albania to the Mediterranean coast of the Adriatic, from the 

shores of the largest lake in the Balkans to Rozafa Castle, which stands majestically on a city, 

where a hundred years ago there was a navigable river that brought foreign ships and 

passengers to its heart. Shkodra is also one of the cities with a university. 

Thanks to the very good natural resources that the Shkodra region possesses and the 

favourable geographical position, this region has a suitable environment for the development 

of mountain and sea tourism, the development of agriculture and other economic activities. 

 

I.3. Socio-economic indicators of Shkodra district 

The population of Shkoder district has a decreasing trend. If we refer to the statistical data 

of the internal migration of the population, we will notice that the departures from the county 

are greater than the incoming flow. Compared to the general data, Shkodra is the fourth district 

in terms of population migration in the country. 

 

Table 2.Domestic movements by county by Variable, Year and County. 

   Shkoder district     

Year  2014 2015 2016 2017 2018 2019 2020 2021 

Incoming flows 1172 1338 2239 1692 1099 1682 1559 1994 

Outcoming flows 1830 2277 3409 2980 1559 2230 2367 2666 

Difference  658 939 1170 1288 460 548 808 672 

Source: IS 

 

Referring to the data on GDP or DGP per capita, we note that the trend is in decline.  The 

growth rate of Shkodra GDP in real terms is increased  by - 4.6%, being ranked as the eighth 

district (out of 12 districts) for the contribution to the overall GDP growth. 



Mimoza ZENELI, Armalda RECI 

 

129 
 

Table 3. DGP for Shkodër region. 

Indicators in region 

Measuring 

Units 2015 2016 2017 2018 2019 2020* 

Gross Domestic Product, in 

current prices Mill. Euro 554 582 596 655 699 668 

Growth Rate of Regional GDP % 1.6 3.1 -1.0 3.5 2.3 -4.6 

GDP per capita Euro 2,616 2,784 2,888 3,214 3,471 3,363 

*Evaluation for the year 2020 are based on semi-final estimation of GDP     

 

Also, the official statistics shows that starting from the 2011-2012 school year, there is a 

decrease in the number of students registered over the years in all the universities of the 

country, including the University of Shkodra. Specifically, in 2011 there are 158,963 registered 

students nationwide and 14,538 students registered at the University of Shkodra, which account 

for about 9.1% of the total number of students registered in all universities of the country. 

While in 2018, we have 113,277 students’ registered nationwide and about 8,245 students at 

the University of Shkodra, which make up 7% of the total number of students. So, there is a 

decrease of 28.7% in the total number of students in the country compared to 2011, this also 

explains the decrease in the number of students at the University of Shkodra. 

 

II. Methodology 

Theoretically, a number of econometric techniques are known for impact evaluation, but 

their use requires appropriateness of data and the fulfilment of certain conditions. 

We have considered the "Log-linear model" with an independent variable Dummy most 

appropriate model regarding to the type and volume of data collected for measuring the impact 

or effect of microcredit on the socio-economic indicators of families in rural areas, Gillespie, 

M. W. (1977). The Dummy variable consists of the state of the indicators "Before and after" 

receiving the microcredit. Dummy variable D (BEFORE-AFTER) takes the value 1 for the 

state before access to microcredit and the value 0 for the state after access to microcredit in the 

borrower group. In this way, the coefficient next to the Dummy variable shows the impact of 

microcredit on the variable of interest, Alba, R. D. (1987).  Based on above, the Log-linear 

model was estimated and the corresponding coefficients were analysed for the assessment of 

the microcredit effects on each of the socioeconomic indicators considered in this analysis.  

Through the analysis of the log linear regression coefficients it will be shown: (i) the 

impact of microcredit on the level of income in the rural areas of the Shkodër district; (ii) the 

impact of microcredit on the educational level of the inhabitants; (iii) the impact of microcredit 

on increasing the level of employment of the residents of the rural areas, McKernan SM (2002); 

(iv) the impact of Microcredit on improving the living conditions of the residents in the rural 

areas, Chliova, M., Brinckmann, J., & Rosenbusch, N. (2015). 

 

II.1. Population and Sample 

Based on the fact that the study refers to the Shkoder region, then the population will be 

the borrowers (residents of the rural areas of the Shkoder region). A sample has been chosen 

which consists of 200 families who are beneficiaries of a loan in one of the microfinance 

institutions operating in these rural areas. Data were collected before and after receiving the 

loan through the questionnaire prepared for this purpose. 



THE MICROCREDIT AS A SHORT-TERMS INSTRUMENT FOR SUSTAINABLE DEVELOPMENT 

THE NORTH-WEST REGION OF ALBANIA: SHKODRA CASE 

 

130 
 

II.2. Statistical Analysis 

As we mentioned above, the data were collected through questionnaires by interviewing 

200 borrowers. The sample consists of 80% men and 20% women. From the data analysis, it 

appears that approximately 60% of the interviewed borrowers belong to the middle level of 

education, 35% to the low level, and 5% to the high level of education. 

95% of the interviewees are self-employed and 5% are employed in the public sector. 

Regarding the profession of the respondents, 75% are workers, 15% are veterinarians and 10% 

are agronomists. 

Based on the fact that the impact of microcredit is to be evaluated, data has been collected 

for the indicators that will be analyzed in two main periods before and after obtaining the loan. 

The period of access to microcredit is marked with T. T-3, T-2, T-1 are the periods before 

access to the microcredit, and T+1, T+2, T+3 are periods after access to microcredit. If there is 

a difference between the two periods, we will conclude that access to microcredit has an impact 

on the indicator that is being analyzed. 

 

III. Results 

The following table summarizes the results of processing the data collected from the 

selection of some key socio-economic indicators in two main periods, before and after access 

to microcredit. 

Table 4. Key indicators “before and after” loan in the borrower group. 

Indicators 

Unit  

1 2 3 4 5 6 7 

Before   After  

T-3 T-2 T-1 T T+1 T+2 T+3 

Income / family / 

month 
(ALL) 

    

69,550  

    

70,012  

    

69,813  
  

    

72,020  

    

72,593  

    

72,901  

Expenses for 

education/family/month 
( %) 1.37% 1.45% 1.50%   1.87% 1.92% 1.98% 

Expenses for social 

activities / family / 

month 

( % ) 2.75% 2.75% 2.75%   2.78% 2.78% 2.78% 

Average number of 

hospital visits 

(average 

number of 

medical visits / 

family/month) 

2.6 2.4 2.3   1.95 1.8 1.75 

Average number of 

employees 

(average 

number of 

employees 

/family/month) 

2.527 2.53 2.53   2.55 2.554 2.555 

Expenses for residence  

reconstruction  
(%) 6.69% 6.03% 6.71%   11.13% 11.56% 11.58% 

 

Referring to the above table, it can be seen that all the indicators have an increasing trend, 



Mimoza ZENELI, Armalda RECI 

 

131 
 

starting from the period T-3 to the period T+3, exception for the number of visits to the hospital, 

a variable which has a negative trend. Referring to the data in Table 4, it is observed that the 

main indicators such as: "Income", "Employment", "Education", "Social activities" and 

"Living conditions" have a shift in the increasing direction after receiving the loan in 

comparison with the dynamics of the indicators in the period before receiving the loan. The 

opposite happens with the "Number of hospital visits", which moves in a decreasing direction 

after receiving the loan compared to the period before receiving the loan, which is evident due 

to the improvement of living conditions, the number of health visits is expected to decrease. 

 

III.1. The impact of microcredit on the level of income in the rural areas of the Shkodra 

district 

The following table shows the results of the "Log-linear model", where the independent 

variable is the Dummy variable itself and the dependent variable is "Income". 

 

Table 5. Income change after access to microcredit. 

Dependent Variable: LOG(TR1) 

Method: Least Squares 

Sample: 1 200 

Included observations: 200 

Variable Coefficient Std. Error t-Statistic Prob.  

C 11.32933 0.042750 265.0116 0.0000 

DPARPAS -0.195406 0.060458 -3.232085 0.0025 

R-squared 0.215628   Mean dependent var 11.23162 

Adjusted R-squared 0.194986   S.D. dependent var 0.213085 

S.E. of regression 0.191185   Akaike info criterion -

0.422442 

Sum squared resid 1.388967   Schwarz criterion -

0.337998 

Log likelihood 10.44884   F-statistic 10.44637 

Durbin-Watson stat 1.433585   Prob(F-statistic) 0.002541 

Referring to the data, it is noted that the coefficient near D is negative. This shows that 

after access to microcredit there is an increase in income by 1.16 percent points. When D has 

the value 1 (i.e. before access to microcredit), then Log (TR) = 11.33-0.195, while if D = 0, 

then Log (TR) = 11.33, a fact which shows that the impact of access to microcredit is 

approximately 1.16 percentage  

From the table, it is also observed that the p-value is 0.0025 less than the significance level 

0.05, which means that the coefficient is statistically significant. Meanwhile, based on the fact 

that R2 is around 0.22, it can be said that the model is statistically significant. Referring to the 

graph, there is a positive shift of the graph (change which is identified with a dashed line) 

through which the increase in income as a result of access to microcredit is shown. 

                                                           
1  TR  = “incomes”. 



THE MICROCREDIT AS A SHORT-TERMS INSTRUMENT FOR SUSTAINABLE DEVELOPMENT 

THE NORTH-WEST REGION OF ALBANIA: SHKODRA CASE 

 

132 
 

Figure 1. Income’s change after access to microcredit. 

 
Referring to the above analysis, at the 5% significance level, there is sufficient evidence 

to support the statement that microcredit has positive Impact on incomes. 

 

III.2. The impact of microcredit on improving the health care level of residents in 

the rural areas of Shkodra district 

The same methodology as above is used to evaluate the impact of microcredit on 

improving the health care level. Below we will present the conclusions reached from the 

analysis. The Dummy variable will be the same access to microcredit and the dependent 

variable will be the average number of visits to the hospital. 

From the processing of data, it can be observed that the the positive coefficient next to 

Dummy variable (+ 0.498) shows that access to microcredit reduces hospital expenses by 4.98 

percent points. The p-value is 0.0060 less than the 0.05 significance level, which means that 

the coefficient next to the Dummy variable is statistically significant. Meanwhile, based on the 

fact that R2 is around 0.18, it can be said that the model is statistically relativly significant. In 

conclusion, we can say that microcredit affects the improvement of the health level. 

 

III.3. The impact of microcredit on increasing the level of employment of residents 

of rural areas of Shkodra district 

The Dummy variable will be the same, access to microcredit and the dependent variable 

will be the average number of employees. 

From the data analysis, we notice that the coefficient next to the dummy variable is -

0.189000. Also from the data table it is observed that the p-value is 0.4267 greater than the 

0.05 significance level, which means that the coefficient next to the Dummy variable is not 

statistically significant. This indicates that with a significance level of 5%, there isn’t sufficient 

evidence to support the statement that microcredit has Impact on the level of employment. 

In the same way, it has been shown that microcredit has a positive impact on the 

improvement of living conditions. 

 

 

-0.6

-0.4

-0.2

0.0

0.2

0.4

10.8

11.0

11.2

11.4

11.6

11.8

5 10 15 20 25 30 35 40

Residual Actual Fitted



Mimoza ZENELI, Armalda RECI 

 

133 
 

CONCLUSIONS 

Microcredit has an important role in reducing poverty and improving the standard of living 

of families that have had access to microcredit, and therefore it is an instrument that contributes 

in the short term to sustainable development, Microcredit Summit Campaign (MSC,2009). 

Achieving the objectives of sustainable development requires comprehensive planning 

and a cross-cutting strategy to unite common policies and solve the problems that arise in the 

horizontal plane. Regardless of the existence of strategies and investment by the government 

in different areas of the economy, it is necessary to support the vulnerable population at the 

same time, since the impact of the macro economic regulations reaches this segment of the 

population later, demoralizing them.  

Hubka, Ashley, Zaidi, Rida. (2005) indicate that ““Scaling up” will require increasing the 

scope (number of individuals reached), impact (effect on the well-being of borrowers), and 

depth (ability to reach the poorest of the poor) of microfinance. The idea is to make 

microfinance available not just to the moderate poor at whom it has traditionally been targeted, 

but also to the extreme poor and the vulnerable non-poor, and to expand the set of 

microfinancial products offered (CGAP, 2003b)”  (p.6) 

Refering to the above results, it is noticed that the access in microcredit increases the 

incomes approximately by 1.16 percent points, that is a good result for poor families. Also 

reduction of the  hospital expenses by 4.98 percent points is another important impact of 

microcredit.  Also  Armalda Reci  (2021) estimated that “Access to microcredit increases 

spending on the consumption of essential food products by 2.6 percentage points” (p.98).  

But with regard to the problems that Albania has faced recently, immigration, it is 

necessary for the government to identify financial and political instruments that have an 

immediate impact in order to prevent the immigration of citizens from Albania. One of these 

instruments can be considered Exactly "Microcredit". 

The creation of microcredit financial institutions in the region of Shkodra specifically for 

crediting or guaranteeing loans to farmers who invest in agriculture, livestock and the field of 

agro-processing in accordance with agricultural development policies. 

The creation of training and advisory institutions and their financial support from the state, 

which enable counseling, training and orientation of the residents of rural areas towards 

appropriate and effective investments within the framework of the use of the resources they 

have available. 

The creation of the necessary advisory and guarantee instruments by the Shkodra local or 

central institutions, which enable residents to benefit from the EU grants applicable for making 

investments in the framework of the development of rural areas. 

These measures are very important because they create premises for poverty reduction, 

and economic development of the rural area and consequently limited the abandonment of the 

country.   

 

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THE NORTH-WEST REGION OF ALBANIA: SHKODRA CASE 

 

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