Page 124 - IJPS-11-6

International Journal of
Population Studies Internal migration in Indonesia

condition. It emphasizes spatial fluidity, relational and reside in a new district or city for at least 1 year. We
connections across locales, and the ongoing negotiation of focused on rural migrants to explore the prevalence of the
belonging. This is extended by Translocal Migration Theory rural-urban migration pattern in Indonesia. Based on the
(Brickell & Datta, 2016), which conceptualizes migrants sample criterion, we kept 3221 observations.
as being embedded in multiple places simultaneously,
socially, economically, and symbolically. 2.2. Variables
Crucially, each of these perspectives addresses different The variables used in this study are broadly categorized
but complementary dimensions of migration. The Mobility into two main groups. The first is the key variable:
Turn and Translocal perspectives illuminate fluid spatial the individual’s migration status, which serves as the
ties but tend to overlook the sequencing of moves over primary outcome of interest. The second group comprises
the life course and their economic rationales. Life Cycle explanatory variables, which are primarily employed to
and Livelihood theories incorporate timing and strategic examine who migrates and how individual characteristics
considerations but give less attention to structural and vary across different migration types.
institutional constraints. Institutional Theory provides These explanatory variables include a range of
this structural lens but does not fully capture the temporal sociodemographic attributes, geographic conditions, and
fluidity of migration. migration-related information. The conceptual basis for
By integrating these five perspectives, this study including these variables is inspired by E. Lee’s (1966)
conceptualizes migration as recursive (Mobility Turn), migration theory, particularly his emphasis on migrant
multi-sited (Translocal), life-stage dependent (Life Cycle), selectivity. While E. Lee posited that migrants and non-
economically strategic (Livelihood), and institutionally migrants differ systematically in their characteristics, this
shaped (Institutional Theory). This integrative approach study extends the notion by investigating whether such
enables the analysis to move beyond binary origin- selectivity also applies across different types of migrants.
destination models, toward a framework that captures Specifically, the explanatory variables include gender,
return, circular, and multi-step migrations as adaptive marital status, level of education, age, household welfare
strategies shaped by shifting life circumstances, structural status, island of residence (included as a regional
constraints, and spatial opportunities. dummy), migration motives, and whether individuals
migrated alone or with others. These variables provide
2. Data and methods a multidimensional perspective on the factors shaping

2.1. Data source different migration trajectories, thereby allowing a more
nuanced understanding of migration selectivity within a
This research utilized five waves of data from the IFLS, the dynamic and diversified internal migration context.
largest longitudinal dataset in Indonesia. Ethical clearance
was secured through Institutional Review Boards (IRBs) 2.3. Methodology
in both the United States and Indonesia. The survey The analysis method for this study was divided into
instruments and datasets utilized in this research can be several stages. First, we defined an individual’s migration
accessed through the following website: https://www. experience starting from the age of 12 years. To achieve this,
rand.org/well-being/social-and-behavioral-policy/data/ we employed sequence analysis, a relatively new approach
Fls/iFls/access.html. The data cover the years 1993, 1997, in migration studies (Kleinepier et al., 2015). Sequence
2000, 2007, and 2014, providing a solid foundation for our analysis is a data-driven technique for mapping individual
analysis.
life trajectories by encoding each life stage as a string of
The extensive reach and detailed data of the IFLS characters that represent yearly observations (Abbott &
allow us to thoroughly examine migration patterns over Tsay, 2000; Impicciatore & Panichella, 2019). While this
time. Migration data were collected retrospectively, with method has been widely adopted in life-course research
respondents asked about their migration experiences from across various domains (Aassve et al., 2007; Billari, 2001;
the age of 12 years to the last survey period. Our analysis is Elzinga & Liefbroer, 2007; Ritschard & Oris, 2005; Vidal
based on the life cycle framework, focusing on individuals et al., 2020), its application in migration studies remains
aged 12–50. This age range ensures that participants are relatively limited (Kleinepier et al., 2015; Pollock, 2007).
aware of their initial living locations and provides consistent Sequence analysis allows us to systematically examine the
observation periods across all samples (Bernard, 2022a; order of migration events, providing a comprehensive
Chen et al., 2021). In this study, an individual is considered understanding of individuals’ migration trajectories over
a migrant if they move across district or city boundaries time.

Volume 11 Issue 6 (2025) 118 https://doi.org/10.36922/IJPS025190084