1,2Assistant Professor at Sociology Department, Social Science Faculty, Bamyan University
3Assistant Professor at Banking and Commerce Department, Economic Faculty, Bamyan University
DOI: 10.55559/sjahss.v2i01.78 | Received: 08.02.2023 | Accepted: 21.02.2023 | Published: 25.02.2023
ABSTRACT
Due to job prospects, widespread violence, general instability, poverty, and natural disasters, the rate of internal migration has risen in recent years. The goal of this study is to gain a better understanding of the factors that influence internal migration in Afghanistan. The data were collected from various regions of Kabul during the period July-August 2019. Study data were gathered from 895 rural-urban migrants in the city of Kabul. This study applied logistic regression to examine the push and pull factors affecting internal migration. The results show that those who migrated between 2010 and 2018 are more likely pulled to migrate due to security problems in their last area of residence and more likely to be affected by the push-pull of social, economic, educational, health and safety factors. The results of this study suggest that rural-urban migration in Afghanistan must be slowed down and rural development programs ought to be implemented in order to create employment opportunities and to pay attention to rural-urban equal development. Otherwise, the rural-urban migrants who are dissatisfied with their quality of life in Kabul will prefer not to return to their villages, so seeking ways for international migration. Besides that, the country should take action plans in order to remove security issues in urban areas.
Keywords: Internal Migration, Pushing and pulling factor, Kabul, Afghanistan
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Electronic reference (Cite this article): AKBARY, M. F., TAQADDAUSI, M. T., & MAREFAT, M. B. (2023). Causes of Internal Migration in Afghanistan: The Case of Kabul City. Sprin Journal of Arts, Humanities and Social Sciences, 2(01), 69–77. https://doi.org/10.55559/sjahss.v2i01.78 Copyright Notice: © 2023 Author(s). This is an Open Access article distributed under the terms of the Creative Commons Attribution 4.0 International License (CC-BY 4.0: https://creativecommons.org/licenses/by/4.0/), allowing third parties to copy and redistribute the material in any medium or format and to remix, transform, and build upon the material for any purpose, even commercially, provided the original work is properly cited and states its license. |
Introduction
Generally, migration is the moving of a person or household from one geographical location or region to another, if it happens inside the country and from one province or city to another called internal migration, and if crossing the border and moving to another country called international migration (Borjas, 2015; Swee-Hock, 2016). The phenomenon of migration is gaining importance day by day because of the complexity of human life, changing the socioeconomic condition and factors that influenced the mobility of persons and households (Gutkar, 2015; Otoiu et al., 2014; Stark, 1991). It is also a matter of host society and culture, population, resources, and variation of economic and cultural developments (Bromandzada & Nawbakht, 2011; Gould, 2008; Gutkar, 2015).
Globally, there are economic, sociocultural, demographic, political, and miscellaneous categories of important factors that push and pull individuals, households, and groups to migrate whether internally or internationally (Brauw & Lee, 2013; Dorigo et al., 2016; Hoffmann et al., 2019; Oda, 2007; Stanford, 2015; Thet, 2014; Todaro, 1980).
However, the migration situation in Afghanistan is a complex phenomenon (Qasimi, 2018; the World bank, 2017) and mobility is an essential part of Afghan history (Marchand et al., 2014; Schetter, 2012). It has a lengthy history (admir, 2018), which has affected both the political and security sectors. (Paikar, 2018; Saramad, 2018). According to (Lopez-Lucia, 2015), 76% of Afghans had experienced displacement during their lifetime, 41% internal and 42% external displacement, and 70.2% of Afghans had experienced crossing borders (Opel, 2005). According to (Akseer et al., 2018), 38.8% of Afghans like to migrate and men than women are more likely to leave the country. Also, young adults are more likely to migrate (Opel, 2005). Permanent, seasonal, and circular forms of migration including nomadism (Koser, 2014), characterizes the pattern of migration in Afghanistan, (Ministry of Refugees and Repatriations, 2104, 2015, 2017). Additionally, migration flows are highly gender-specific and very different from those of short and long-distance migration (Katrin et al., 2014; Wickramasekara. P. et al., 2013).
There are lots of factors pushing Afghans to migrate internally and internationally the most important one is war and the situation of conflict in Afghanistan (Amiri et al., 2014; Garrote-Sanchez, 2017; Hakim & Boz, 2019; Majidi, 2011; Schetter, 2012). Insecurity, unemployment, poverty, natural disasters, inadequate agricultural lands, unproductive soils, religious extremism, homelessness, and less freedom also pushed Afghans to migrate (Akseer et al., 2017; Ghobadi et al., 2005; Hakim & Boz, 2019; Koser, 2014; Marchand et al., 2014). Less poor households who were unemployed or had fewer wages and experienced violence and conflict were more likely to migrate (Akseer et al., 2018; Ghobadi et al., 2005). However, Afghans have a perception that there are better opportunities in the city (Opel, 2005), and living in cities is more attractive for rural Afghans (Asif, 2013). Human rights, women's rights, voting right, better education, security, job opportunities, freedom of speech, better health services, access to media and internet and clean water are the factors pulling Afghans to migrate (Al-Amin, 2010; Hakim & Boz, 2019; Lopez-Lucia, 2015). Besides that, there are other inter-linked factors that affected to migration flow in Afghanistan like economic, security and political factors especially considering the history of war and tribal conflict in Afghanistan (Lopez-Lucia, 2015; Marchand et al., 2014).
Afghanistan as a conflict-impacted country is facing complex and various socio-economic challenges (UNHCR, 2018). One is unemployment which has a damaging effect on the economy, education, healthcare, and security systems. (APPRO, 2013; UNHCR, 2012). The population movement especially internal migration of households and individuals is among the major consequences of war, conflict, disasters, consecutive droughts, and economic disability (UNHCR, 2012; Osmani, et al., 2010). As we know, over 36 years of the war and conflict in Afghanistan, peace, economy social security, education, etc. have been hugely affected. Due to this situation as suggested by many official reports, many Afghans have migrated within the country and across borders. After the fall of the Taliban in 2001, national and international efforts focused on improving the post-war situation in Afghanistan. The purpose of these efforts was to bring stability and development to Afghanistan. But after nearly two decades of effort, statistics show that the living conditions of Afghans have not yet improved, but the growing trend of poverty, unemployment rate, rural-urban migration, the geography of insecurity and war are increasing, and its pressure on every Afghan’s daily life. Moreover, 80% of internal migration is from rural to urban in Afghanistan which increased after falling the Taliban in 2001(Dora & Kuschminder, 2009) and especially Kabul city population in 2001 was 1.5 million had increased to 4.5 million in 2007(Majidi, 2011).
Data and Methodology
The data were collected from various regions of Kabul -the capital of the country- during the period July-August 2019. First, the most populated areas of Kabul were established, particularly those areas where the majority of families migrated from rural areas. Study data were gathered from (N=895) rural-urban migrants including 362 females (40.45%) and 533 males (59.55%), and the respondents’ ages were among the limits of lowest of 18 years and highest of 57 years and above in the city of Kabul based on the use of a formula prepared by Krejcie and Morgan (Bukhari, 2021), from an estimated population about 2.2 million of internal migration in Kabul city (NSIA, 2018), the minimum sample size of the present study with a confidence level of 95% and considering a 5% degree of error, is 384. Here I considered using the following formula for the determination of sample size:
s = X2NP (1-P) d2 (N-1) + X2P(1-P)
A well-structured questionnaire was prepared to find out the socio-demographic characteristics of the respondents and the push and pull factors (social, educational, economic, health and safety) of migration. The independent variables are the push-pull factors to analyze the factors behind the dependent variable which is internal migration. During face-to-face informal meetings with individuals, the questionnaires were filled in. The question was a five-point Likert with a scale (5 = strongly agree, 4= agree, 3= neutral, 2= disagree, and 1= strongly disagree). The data have been analyzed using STATA version 14.1. All the respondents were asked in the following field:
1) Demographic characteristics of respondents like gender, age, Matrimonial status, ethnicity, residency, number of family members, profession and expertise, etc.
2) The socio-economic features, like education level (the year of completed education), employment status, daily income, of respondents…etc.
3) Causes of migration, the pull-push factors that affected decision-making on migration, which factors forced them to the origin, and which ones in the destination encourage them to decide to migrate. All respondents were asked if it was a factor in origin that forced a person to decide for looking and move to other places with better conditions (a. Ethnic violence, b. violations of human rights, c. lack of proper educational services, d. Lack of proper health services, e. Tribal conflict, f. Armed Conflict/War, violence and persecution, g. Oppressed by irresponsible armed groups, h. Disasters (climate change, floods, earthquakes, avalanches, and droughts), I. Continuous unemployment, j. Existence and continuation of extreme poverty, k. Not having a home and land). And if it was the factors in the destination that attracted a person to decide to move there (a. access to urban facilities, b. access to urban transportation services, c. Access to better education services, d. Access to job opportunities, e. Access to better health services, f. Access to food security, g. Access to drinking water and electricity, h. Access to better security, i. wage difference in rural and urban).
Result
The outcome variable is binary describing the period of migration from 2002-2009 and 2010-2018. Those who migrated from 2002-2009 were assigned 0 and from 2010 to 2018 were assigned number 1. And then all five predictor variables were coded as dummy variables (social, educational, economical, health and safety factors) developed based on push and pull factors with four categories (0=no reason, 1=pull, 2= push, and 3=pull-push).
Table.1 presented the association between push-pull factors and internal migration in Afghanistan. The results show that those who migrated between 2010-2018 compared to the reference group (2002-2009) are more likely to be affected by the social push-pull factors (odds ratio [OR] = 2.43, 99% confidence interval [CI] = 1.63 – 3.62), economics push-pull factors (OR = 2.25, 99% CI = 1.50 – 3.37), educational push-pull factors (OR = 2.27, 99% CI = 1.53 – 3.38), health push-pull factors (OR = 1.65, 99% CI = 1.13 – 2.42), and security pull factor (OR = 3.75, 99% CI = 1.76 - 8.87 and push factor OR = 2.57, 95% CI = 1.12-5.90 ) whereas it’s shown that the economic pull factor (OR = 1.44, 90% CI = 0.95 - 2.20) and the security push-pull factors (OR = 2.11, 90% CI = 0.93 - 4.78) with 90% confidence interval have put an impact on the migration.
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Table 1: The Causes of migration predict by Pushing and Pulling factors |
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|
(1) |
(2) |
(3) |
(4) |
(5) |
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VARIABLES |
Social factors |
Educational factors |
Economic factors |
Health factors |
Security factors |
|
Social factors (Ref = no reason) |
|||||
|
Pulling factor |
1.94*** |
||||
|
(1.31 - 2.86) |
|||||
|
Pushing factor |
0.95 |
||||
|
(0.66 - 1.37) |
|||||
|
Pulling-pushing factors |
2.43*** |
||||
|
(1.63 - 3.62) |
|||||
|
Educational factors (Ref = no reason) |
|||||
|
Pulling factor |
1.26 |
||||
|
(0.85 - 1.85) |
|||||
|
Pushing factor |
1.17 |
||||
|
(0.79 - 1.73) |
|||||
|
Pulling-pushing factors |
2.25*** |
||||
|
(1.50 - 3.37) |
|||||
|
Economic factors (Ref = no reason) |
|||||
|
Pulling factor |
1.44* |
||||
|
(0.95 - 2.20) |
|||||
|
Pushing factor |
1.31 |
||||
|
(0.87 - 1.97) |
|||||
|
Pulling-pushing factors |
2.27*** |
||||
|
(1.53 - 3.38) |
|||||
|
Health factors (Ref = no reason) |
|||||
|
Pulling factor |
1.40* |
||||
|
(0.95 - 2.07) |
|||||
|
Pushing factor |
1.36 |
||||
|
(0.91 - 2.03) |
|||||
|
Pulling-pushing factors |
1.65*** |
||||
|
(1.13 - 2.42) |
|||||
|
Security factors (Ref = no reason) |
|||||
|
Pulling factor |
3.95*** |
||||
|
(1.76 - 8.87) |
|||||
|
Pushing factor |
2.57** |
||||
|
(1.12 - 5.90) |
|||||
|
Pulling-pushing factors |
2.11* |
||||
|
(0.93 - 4.78) |
|||||
|
Marital status (Ref = single) |
|||||
|
Married |
0.40** |
0.41** |
0.43** |
0.46* |
0.40** |
|
(0.17 - 0.92) |
(0.18 - 0.96) |
(0.19 - 1.00) |
(0.20 - 1.06) |
(0.17 - 0.92) |
|
|
Widow/widower |
0.50 |
0.53 |
0.88 |
0.64 |
0.76 |
|
(0.03 - 8.20) |
(0.03 - 8.47) |
(0.06 - 13.93) |
(0.04 - 10.00) |
(0.05 - 11.80) |
|
|
Respondents' Education level (Ref = Illiterate) |
|||||
|
Primary |
2.63*** |
2.71*** |
2.56*** |
2.70*** |
2.42*** |
|
(1.48 - 4.66) |
(1.53 - 4.78) |
(1.45 - 4.52) |
(1.54 - 4.75) |
(1.37 - 4.28) |
|
|
Secondary |
1.95*** |
1.87** |
1.99*** |
1.92*** |
1.77** |
|
(1.19 - 3.19) |
(1.15 - 3.05) |
(1.22 - 3.24) |
(1.19 - 3.12) |
(1.09 - 2.87) |
|
|
High School |
1.35 |
1.32 |
1.26 |
1.25 |
1.18 |
|
(0.72 - 2.55) |
(0.71 - 2.47) |
(0.67 - 2.35) |
(0.67 - 2.33) |
(0.63 - 2.22) |
|
|
Higher education |
1.66* |
1.52 |
1.62* |
1.49 |
1.41 |
|
(0.98 - 2.82) |
(0.90 - 2.56) |
(0.96 - 2.73) |
(0.89 - 2.51) |
(0.84 - 2.37) |
|
|
Respondents Profession (Ref = No profession) |
|||||
|
Handcraft/ professional |
0.64 |
0.67 |
0.69 |
0.70 |
0.72 |
|
(0.36 - 1.15) |
(0.38 - 1.20) |
(0.39 - 1.23) |
(0.40 - 1.25) |
(0.40 - 1.28) |
|
|
Construction area |
0.51** |
0.54** |
0.57* |
0.57* |
0.60* |
|
(0.28 - 0.94) |
(0.30 - 0.99) |
(0.31 - 1.04) |
(0.31 - 1.04) |
(0.33 - 1.10) |
|
|
Free trade |
0.75 |
0.79 |
0.83 |
0.83 |
0.84 |
|
(0.39 - 1.45) |
(0.41 - 1.51) |
(0.43 - 1.59) |
(0.44 - 1.59) |
(0.44 - 1.60) |
|
|
Agricultural and farming |
0.60* |
0.59* |
0.63 |
0.66 |
0.65 |
|
(0.34 - 1.05) |
(0.34 - 1.04) |
(0.36 - 1.11) |
(0.38 - 1.15) |
(0.37 - 1.14) |
|
|
Modern science teachers, engineers… |
0.67 |
0.76 |
0.75 |
0.76 |
0.79 |
|
(0.33 - 1.38) |
(0.37 - 1.54) |
(0.37 - 1.52) |
(0.37 - 1.53) |
(0.39 - 1.61) |
|
|
Observations |
894 |
894 |
894 |
894 |
894 |
|
ciEform in parentheses |
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*** p<0.01, ** p<0.05, * p<0.1 |
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Ref= Reference Group |
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Among demographic characteristics and socio-economic features, respondents who had secondary education are above 90 percent more likely associated with social, economic, and health factors, with a level of confidence of (0.001) and associated 87 percent with educational and 77 percent with security factors in the confidence level of 0.05 to migrate than the reference group who were illiterate. However, respondents who had primary education are more than two times more likely to be associated with all factors with a confidence level of (0.001) compared to those who were illiterate.
Conclusion and discussions
Among pulling factors of migration to Kabul city, social factors 94 percent, economic factors 44 percent, health factors 40 percent, and security factors were more than three times associated with taking decision to migrate compared to those with no reasons. However, the result shows that respondents migrated to Kabul city due to better security and social services that Kabul city has more than other factors. Respondents answered that they were pulled due to security problems in their last area of residency more than two times compared to those with no reasons. Among pulling-pushing factors together, social, educational, and economic factors more than two times have pulled-pushed respondents to migrate to Kabul city with a confidence level of (0.001) but in security factors with confidence level of (0.005) compared to whom answered no reason. Health factors 65% more than those who answered no reason have pulled-pushed to migrate to Kabul city.
However, the result of the study matched with the literature studies on pulling factors of social, economic, educational, health and safety, whether a person or household decides to migrate(Al-Amin, 2010; Hakim & Boz, 2019; Lopez-Lucia, 2015; Opel, 2005) and it is because of the huge level of difference that city and village have in Afghanistan, especially in case of delivering social, economic, health, education and development services that rural Afghans are attracted to migrate into cities.
Another important finding which is different from studies (Akseer et al., 2017; Ghobadi et al., 2005; Marchand et al., 2014) is in case of pushing factors that only security problems have pushed respondents to migrate and it is reasonable because continuous war and conflict in Afghanistan (Amiri et al., 2014; Garrote-Sanchez, 2017; Hakim & Boz, 2019; Majidi, 2011; Schetter, 2012). Also, in the condition of war and conflict, what is the priority of the person and household is safety, not their socio-economic conditions. Additionally, the finding shows that rural-urban migration in Afghanistan mostly happens because of security problems and shows the level of respondents’ tolerance against social, educational, economic, and health obstacles.
The results of this study suggest that rural-urban migration in Afghanistan must be slowed down and rural development programs ought to be implemented in order to create employment opportunities and to pay attention to rural-urban equal development. Otherwise, the rural-urban migrants who are dissatisfied with their quality of life in Kabul will prefer not to return to their villages, so seeking ways for international migration. Besides that, the country should take action plans in order to remove security issues in urban areas.
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