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FOOD CONSUMPTION AND NUTRITION DIVISION October 2005
FCND Discussion Paper 197
Migration and the Rural-Urban Continuum:
Evidence from the Rural Philippines
Agnes R. Quisumbing and Scott McNiven
2033 K Street, NW, Washington, DC 20006-1002 USA • Tel.: +1-202-862-5600 • Fax: +1-202-467-4439 • ifpri@cgiar.org
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ii
Abstract
Migration is an important livelihood strategy in the Philippines. In 1991, 26
percent of urban households and 13 percent of rural households received remittances
from migrant parents or children. Although international migration has received more
attention than internal migration, the latter is significant in the Philippines. Between
1980 and 1990, the number of persons over the age of five years who were not resident in
the city or municipality they resided in five years ago, increased from 2.85 to 3.24
million. Recent migration flows are interprovincial, typically in the direction of
Metropolitan Manila and surrounding areas, and are dominated by women. While the
percentage of the population classified as urban increased from 36 percent in the mid-
1970s to 52 percent in the early 1990s, roughly 80 percent of moves by a nationally
representative sample of ever-married women were to areas no more urbanized than the
migrant’s area of origin. This indicates that internal migration flows are quite
heterogeneous. This is of interest to policymakers, who are paying increasing attention to
the role of small towns and peri–urban areas as migrant destinations. For small and
intermediate-sized urban centers, in-migration from rural areas could increase local
opportunities for income diversification as well as decrease pressure on larger national
urban centers.
This paper explores the diversity of the experience of migrants to rural, peri–
urban, and urban areas using a unique longitudinal data set from the Philippines. In 2003
and 2004, the Bukidnon Panel Study followed up with 448 families in rural Mindanao
who were previously interviewed in 1984/85 by the International Food Policy Research
Institute and the Research Institute for Mindanao Culture, Xavier University, and
surveyed both a sample of their offspring living in the same area as well as a sample of
those who had moved away to different locations. Parents (original respondents) and
children who formed separate households in the same locality were interviewed in 2003;
original respondents’ offspring that migrated to different rural and urban areas were
interviewed in 2004. Thus, migration patterns were examined using the full listing of
iii
children of the original respondents as well as a special survey of 257 of their migrant
offspring who were tracked down in 2004. This migrant survey focused on differences in
the migration experience of males and females who moved to other rural areas,
poblaciones (the administrative seats of municipalities or towns), and urban areas. We
follow this with an examination of the determinants of children’s location, using the
sample of all children. In addition to migration to rural, peri–urban, and urban
destinations, we explicitly consider the case where the individual leaves his or her
parental residence, but remains in the same village, as a locational choice.
Our preliminary exploration into the migration decisions of young Filipino adults
has shown that as destinations, poblaciones, peri–urban areas, and urban areas are very
similar. Most migrants to poblaciones and urban areas have very similar reasons for
moving—initially for schooling, then subsequently to look for better jobs, except for
substantial numbers of male migrants to the closer urban locations in Bukidnon who tend
to be poorly educated and work in low-wage construction and transport jobs. If
poblaciones and peri–urban areas can offer comparable services to migrants from rural
areas, they may be able to relieve congestion in major metropolitan centers like Cagayan
de Oro and Metropolitan Manila. However, the occupational profile of migrants
indicates that females in both areas seem to do better than males—perhaps because
female migrants to urban areas are better-educated than male migrants.
Social networks are important for migrants, particularly for the first move. While
most first-time migrants move alone, they are most often financed by their parents and
live with relatives in their new community. Later on, migrants increasingly self-finance
their moves, and live with their families of procreation. Familial networks are thus very
important for helping a migrant get settled into a new community.
Lastly, we also find that rural areas, poblaciones, and urban areas systematically
attract different types of migrants. Poblaciones and urban areas generally attract better-
schooled individuals, partly because young people move to those areas to further their
education, or because better-educated individuals move to these areas to find better jobs.
Migrants to rural areas, on the other hand, move primarily to take up farming or to get
iv
married. Thus, it is no surprise that rural migrants, as well as those who opt to stay in
rural areas, are less educated than migrants to poblaciones, urban and peri–urban areas.
Does outmigration from rural areas thus constitute a “brain drain” that needs to be
stopped? Not necessarily. If migrants are able to find better jobs in urban and peri–urban
areas, and send remittances to their origin families, then migration is welfare-improving
for those who have stayed behind. However, the occupational profile of migrants to
poblaciones, urban, and peri–urban areas is quite diverse. A large proportion of male
migrants to more urbanized areas ends up in manual labor/transportation work or crafts
and trades, which are not high-earning occupations. Female migrants to poblaciones and
urban areas may fare better. A large proportion of female migrants to poblaciones ends
up working in sales occupations, while a larger proportion of female than male migrants
to urban areas has professional and managerial jobs. Clearly, many migrants are unable
to fulfill their hopes and dreams. This paper cannot answer whether migration is welfare-
improving for the migrant or the family he (or more likely she) left behind. In further
work, we will examine whether migration is a strategy that families use to escape
poverty, bearing in mind that migration and education are both individual and family
decisions.
Key words: migration, rural, urban, the Philippines
v
Contents
Acknowledgments............................................................................................................. vii
1. Introduction.................................................................................................................... 1
2. Understanding Migration Patterns in the Rural Philippines .......................................... 4
Motivation............................................................................................................... 4
The Bukidnon Panel Survey ................................................................................... 6
Characteristics of the Respondents’ Children....................................................... 10
Location .......................................................................................................... 10
Civil Status...................................................................................................... 12
Education ........................................................................................................ 13
Migration in Retrospect: Evidence from Migration Histories ............................. 17
Basic Demographic Characteristics ................................................................ 18
Occupational Characteristics .......................................................................... 19
Reasons for Moving........................................................................................ 23
Migration Support Networks .......................................................................... 27
The Job Search................................................................................................ 31
3. Modeling the Location Decision.................................................................................. 32
Empirical Specification......................................................................................... 32
Results................................................................................................................... 37
4. Conclusions.................................................................................................................. 40
References......................................................................................................................... 42
Tables
1 Distribution of children age 15 and over of original respondents,
by location, 2003......................................................................................................... 11
2 Civil status of children age 15 and over of original respondents,
by location, 2003......................................................................................................... 13
3 Percent completing educational category, children 15 and over, by sex and
location, 2003.............................................................................................................. 14
4 Basic demographic information on migrant children reinterviewed in 2004
round, by destination of first move............................................................................. 18
vi
5 Primary reason for moving, by sex and destination, first move (percent).................. 23
6 Primary reason for moving, by sex and destination, most recent move of
migrants who moved more than once ......................................................................... 25
7 Reasons for not moving to another community, migrants who do not intend to
move, 2004.................................................................................................................. 26
8 Networks and support for the first move, by destination location and
sex (percent)................................................................................................................ 27
9 Networks and support for the most recent move for migrants who moved
more than once, by location and sex (percent) ........................................................... 29
10 Characteristics of the job search after the first move, by location and
sex (percent)................................................................................................................ 30
11 Characteristics of the job search after the most recent move, by location and
sex (percent)................................................................................................................ 30
12 Means of variables used in regression analysis .......................................................... 36
13 Determinants of migration of children age 15 and over, Bukidnon ........................... 38
Figures
1 Map of the Philippines, indicating study area............................................................... 6
2 Sampled child and village household counts................................................................ 9
3 Percent of males and females completing secondary school, children 15 and
over, by destination location....................................................................................... 15
4 Occupation (on first move) of those who have moved only once, by gender ............ 20
5 Occupation (most recent move) for those who have moved more than once,
by gender..................................................................................................................... 20
6 Occupation (first move) of those who have moved only once, by location ............... 21
7 Occupation (most recent move) for those who moved more than once,
by location................................................................................................................... 22
vii
Acknowledgments
Funding for this study comes from a grant from the U. K. Department for
International Development project on rural-urban linkages to the International Food
Policy Research Institute and the Broadening Access to Input Markets and Services
Collaborative Research Support Project (BASIS-CRSP). The data were collected by the
Research Institute for Mindanao Culture, Xavier University. We thank James Garrett for
helpful discussions in conceptualizing the paper, Cecilia Tacoli and Jane Hobson for
useful comments, and Erlinda Burton and Chona Echavez for insights into the migration
experience in Mindanao. We also thank Marinella Yadao and Nelly Rose Tioco for
assistance in finalizing the manuscript.
Agnes R. Quisumbing and Scott McNiven
International Food Policy Research Institute
1
1. Introduction
Migration is an important livelihood strategy in the Philippines. In 1991, 26
percent of urban households and 13 percent of rural households received remittances
from migrant parents or children (Cox and Jimenez 1995). Although international
migration has received more attention than internal migration, the latter is also significant
in the Philippines.
1
Between 1980 and 1990, the number of persons over the age of five
years who were not resident in the city or municipality they resided in five years ago
increased from 2.85 to 3.24 million (Flieger 1995).
2
Migrants increasingly crossed
provincial boundaries: in the intercensal period, intra-provincial migration decreased by
40 percent, while interprovincial migration increased by 10 percent. Among migrants
listed in both census years, females outnumbered males; Filipinas are among the most
geographically mobile of Asian women (Lauby and Stark 1988).
Since 1970, the in-migration center of the country has shifted from Mindanao to
Metropolitan Manila and the surrounding provinces. Although Metropolitan Manila is
now the most attractive destination, and the percentage of the population classified as
urban increased from 36 percent in the mid-1970s to 52 percent in the early 1990s
(Flieger 1995), roughly 80 percent of moves by a nationally representative sample of
ever-married women were to areas no more urbanized than the migrant’s area of origin
(Jensen and Ahlburg 2000).
3
1
See, for example, Yang (2004a, 2004b). Most studies on internal migration in the Philippines examine
data from the 1970s and 1980s (Nguiagain 1985); there are relatively fewer using the 1990 census (e.g.,
Flieger 1995). Jensen and Ahlburg (2000) use the 1993 National Demographic Survey to examine the
relationship between female migration and fertility.
2
Although the number of internal migrants had increased, the proportion of the population above four years
engaged in internal migration had decreased from 7.1 percent to 6.3 percent between 1980 and 1990. In
comparison, more than 1.6 million international migrants over 15 years of age resided outside the
Philippines in 1991 (equivalent to 4 percent of the nonmigrant population of that age group residing in the
country) (Rodriguez and Horton 1996); in the 10-year period between 1990-1999, remittances from
international migrants contributed an average of 20.3 percent to the country’s export earnings and 5.2
percent of GNP (Go 2002).
3
Flieger (1995) notes that some of the increase in urbanization came from the reclassification of rural areas
to urban.
2
Understanding rural-urban migration in the Philippines, however, requires going
beyond census definitions and simple dichotomies. In the Philippines, urban areas are
defined as all settlements with at least 1,000 inhabitants, a population density of at least
500 persons per square kilometer, essential infrastructure, and where nonagricultural
occupations prevail (Philippine National Statistics Office 2003). Poblaciones are the
administrative seats of the municipality (the rural administrative district) or town (which
may be classified as urban or rural depending on certain criteria). Even though all
poblaciones are in fact population centers, only those poblaciones that have a population
density of at least 500 persons per square kilometer and essential infrastructure are
classified as urban, even if they are surrounded by predominantly rural areas. Using
census definitions, moving to a poblacion may be classified as migration to an urban
area, even if it is not very far from the individual’s rural origin. In this study, allowing
migrants to define the nature of their destination locality—whether rural, poblacion, or
urban—provides additional insights into the rural-urban continuum.
What determines the decision to migrate, and given that decision, the choice of a
migrant’s destination? The recent literature on migration in developing countries has
increasingly paid attention to the effects of familial and social factors on migration.
4
Whereas the early literature on migration typically posed the decision in terms of the
costs and benefits to the individual migrant (e.g., Sjaastad 1962), more recent studies
emphasize the role of migration as a family strategy. Policymakers are also paying more
attention to the role of small towns and peri–urban areas as migrant destinations
(Satterthwaite and Tacoli 2003). In-migration from rural areas to small and intermediate-
sized urban centers could increase local opportunities for income diversification as well
as decrease pressure on larger national urban centers.
It is obvious that rural areas, poblaciones, and urban areas offer different
opportunities to migrants. Do these various destinations systematically attract different
types of migrants? What kinds of individuals are more likely to move to rural areas, as
4
See Lucas (1997) for a review of the literature on internal migration, and Stark (1991) for a discussion of
migration as a family, rather than a purely individual, decision.
3
opposed to poblaciones or urban areas? Do migrants move for different reasons,
depending on the destination, and do their occupational profiles, job search strategies,
and support networks differ?
This paper explores the heterogeneity of the experience of migrants to rural,
poblacion, and urban areas using a unique longitudinal data set from the Philippines. The
Bukidnon Panel Study follows up 448 families in rural Mindanao who were first
interviewed in 1984/85 by the International Food Policy Research Institute and the
Research Institute for Mindanao Culture, Xavier University. The study interviewed the
original respondents and a sample of their offspring, both those who have remained in the
same area and those who have moved to a different location. Parents (original
respondents) and children who formed separate households in the same locality were
interviewed in 2003; offspring that migrated to other rural and urban areas were
interviewed in 2004.
In this paper, we examine migration patterns using the full listing of children of
the original respondents as well as a special survey including 257 of the migrant offspring
who were tracked down and interviewed in 2004. The migrant survey focuses on
differences in the migration experience of males and females who migrated to rural,
poblacion, and urban areas. We then explore the determinants of children’s location,
using the sample of all children. In addition to migration to rural, poblacion, and urban
destinations, we explicitly consider the case where the individual leaves his or her
parental residence, but remains in the same village, as a locational choice. Following a
literature that suggests that males and females migrate for different reasons (e.g., Smith
and Thomas 1998), we estimate a multinomial logit regression of locational choice
separately for males and females. The regressions allow us to control for other factors
that may be affecting the decision to migrate.
We find that rural areas, poblaciones, and urban areas systematically attract
different types of migrants. Poblaciones and urban areas generally attract better-schooled
individuals, partly because young people move to those areas to further their education,
or because better-educated individuals move to these areas to find better jobs. Migrants
4
to rural areas, on the other hand, move primarily to take up farming or to get married.
Thus, it is no surprise that, controlling for other factors, rural migrants, as well as those
who opt to stay in rural areas, are more likely to be less educated than migrants to urban
and peri–urban areas.
2. Understanding Migration Patterns in the Rural Philippines
Motivation
In contrast to early models of migration that focused on an individual’s decision
to migrate, based on a comparison of the discounted value of the mover’s expected
income in a different location and the present value of the costs of migration (e.g.,
Sjaastad 1962), a growing literature has argued that individual migration is both an
individual and a family decision. Taking family considerations into account has
considerably expanded the scope of migration models. In their study of the migration of
husbands and wives in peninsular Malaysia, Smith and Thomas (1998) discuss a number
of scenarios in which family characteristics may influence the migration decision. For
example, children and adolescents typically move with their parents, who decide where
the family goes. For these younger migrants, parental characteristics, such as father’s and
mother’s education, may be more important determinants of an individual’s location,
compared to individual characteristics. The family also matters because individuals
marry and mostly live and move with their spouses. Thus spousal characteristics may
affect an individual’s location decision, particularly for postmarital moves.
Families may also choose which of their members will migrate in order to
diversify against risk (e.g., Lucas and Stark 1985; Hoddinott 1992). If parental
investment and risk-diversification strategies are consistent, an individual's probability of
migration, and eventual location, will be a function of individual and household
characteristics. In India, Rosenzweig and Stark (1989) find that Indian farm households
with more variable profits tend to engage in longer distance marriage-cum-migration.
Similarly, Rosenzweig (1993) and Rosenzweig and Stark (1989) find that children of
5
poorer households are more likely to migrate far away. They propose that children of
households that are more vulnerable to exogenous risk tend to migrate farther afield than
other children. Likewise, children of households that are better able to self-insure against
exogenous risk—an ability that generally increases with wealth—may choose to reside
closer to the origin household. For example, children whose families live in areas that
are inherently prone to weather risk, such as drought or floods, are more likely to migrate.
In contrast, children whose families have more assets, and thus are better able to self-
insure, do not need to live so far away from the parental household. This is another way
families can use migration as insurance.
Gender may also play an important role in the family’s choice of a migrant.
Whether sons or daughters migrate depends on the family’s perception of the migrant in
its risk-diversification strategy. If, for example, daughters are socialized to be
responsible for their parents, families may invest in daughters’ migration. In the
Dominican Sierra, female migrants make remittances to their parents’ households if the
latter experience income shocks; men insure parents only if there is no other migrant in
the household (de la Brière et al. 2002). In the Philippines, the family's short-run need
for a stable source of income motivates unmarried female migrants to seek wage-earning
jobs, despite their lack of long-term stability, since parents expect remittances to decrease
after daughters marry and have their own familial obligations (Lauby and Stark 1988). In
rural India, where women migrate for marriage but men are lifetime residents in the
household and village, daughters-in-law living in the village and daughters of the
household head who have married and moved to their husbands’ village embody the
family’s insurance capital, linking families of origin and destination of married women in
mutual aid schemes (Rosenzweig 1993).
Better-educated children are also more likely to migrate in response to economic
opportunities. Because better-educated children may be able to take advantage of new
employment or entrepreneurial opportunities, they have more to gain from moving than
less-educated children.
6
The Bukidnon Panel Survey
Bukidnon is a landlocked province in Northern Mindanao, comprising 20
municipalities and two cities, Malaybalay and Valencia.
5
(See Figure 1 for a map of the
Philippines and the location of the study area.) Bukidnon has a land area of 829,378
hectares, making it the largest province in Northern Mindanao and the eighth largest in
the Philippines. The 2000 census reported Bukidnon’s population to be 1,059,355 with
an average population density of 128 people per square kilometer. An earlier census
from 1995 indicated the province’s population was split 70 percent to 30 percent between
rural and urban areas. The national highway links Bukidnon to its neighboring provinces
while the Sayre Highway links Bukidnon to Misamis Oriental and North Cotabato. The
Bukidnon-Davao road links the province to Lanao del Sur and North Cotabato.
Interprovincial travel is mainly by bus while inter-municipality and barangay travel is via
Figure 1—Map of the Philippines, indicating study area
5
This description draws from Morales (2004).
7
public utility vehicles. Since Bukidnon is landlocked, it relies on Cagayan de Oro, the
major metropolitan center in Northern Mindanao, as its nearest seaport.
The data used in this analysis draw from a survey conducted by the International
Food Policy Research Institute (IFPRI) and the Research Institute for Mindanao Culture,
Xavier University (RIMCU) of households residing in southern Bukidnon. The survey
was originally designed to investigate the effects of agricultural commercialization on the
nutrition and household welfare of these families. In 1977, the Bukidnon Sugar
Company (BUSCO) began operating a sugar mill in the area, which had previously been
dominated by subsistence corn production. The presence of the mill gave farmers the
opportunity to adopt this cash crop, depending on their proximity to the mill. The survey
was fielded in four rounds at four-month intervals from August 1984 to December 1985,
so that each round corresponded to a different agricultural season. The survey contained
information on food and nonfood consumption expenditure, agricultural production,
income, asset ownership, credit use, anthropometry and morbidity, education, and 24-
hour food consumption recall. The sample was drawn from 29 barangays (the barangay
is the smallest political unit in the Philippines)
6
and was stratified by (1) agricultural
production activities, particularly sugar (the cash crop) and corn (the food crop),
(2) proximity to the sugar mill (as a proxy for access to the new crop), and (3) access to
land, including ownership, tenancy and landlessness. The initial sample included 510
households, although 448 households were interviewed in all four rounds. Bouis and
Haddad (1990) provide a detailed description of the sample design and survey area.
The original case study (Bouis and Haddad 1990) examined the effects of the shift
from subsistence corn production to sugarcane after the construction of the BUSCO sugar
mill. The main effects of the introduction of export cropping were a significant
deterioration in access to land, as smallholder corn tenant farms using primarily family
6
The barangay is the smallest local government unit in the Philippines and is similar to a village.
Municipalities and cities are composed of barangays. Historically, barangays are relatively small
communities of 50 to 100 families. Most villages have 30 to 100 houses and the population varies from
100 to 500 persons (Wikipedia 2005, http://en.wikipedia.org/wiki/Barangay, citing Constantino 1975).
8
labor were consolidated into larger sugar farms using primarily hired labor; an increase in
incomes for households that grew sugarcane; a decline in women’s participation in own-
farm production; and very little improvement in nutritional status as a result of increased
incomes from sugarcane production, primarily because of the high levels of preschooler
sickness in the sugarcane-growing households. In 1992, 352 of the original 448
households were reinterviewed in a study focusing on adolescents (Bouis et al. 1998).
The 1992 survey included only one round of data collection and used a condensed survey
instrument.
Following qualitative studies conducted in the study communities in early 2003,
IFPRI and RIMCU returned to conduct two rounds of quantitative data collection using a
survey questionnaire that closely reflected the one used in 1984/85. In the first wave of
data collection in the fall of 2003, all original respondents still living in the survey area
were interviewed, as were two of their children (randomly selected) that formed
households in the survey area. The first wave yielded 311 original respondents (61
percent of the original respondents) and 261 households formed by non-coresident
children living in the same villages as their parents. The second wave of data collection
began in April 2004 and ended in July 2004. In this wave, the survey team interviewed
any household formed by children who no longer live in the survey area, based on
addresses and phone numbers provided by the original respondents and other family
members. This included a large group of households in three major urban areas in
Mindanao (Valencia, the commercial center of Bukidnon; Malaybalay, the provincial
capital; and Cagayan de Oro in the province of Misamis Oriental, a major port and
metropolitan area in northern Mindanao) as well as many households in poblaciones and
other rural areas of Bukidnon. The sample size from this migrant wave consisted of 257
households—about 75 percent of potential migrants to be interviewed. Figure 2 presents
a map of the survey area and the locations of original households, households formed by
children in the original barangays, and households formed by children who migrated.
While budgetary concerns did not allow all children to be followed up, the survey was
designed to obtain information on all children, regardless of location. The initial
9
interview with the parents obtained a basic set of information about all children,
including location, educational attainment, and marital status. Obtaining this information
from parents, plus assiduous follow-up of migrants and children residing in the
community, avoided the common problem of sample selection bias if interviews were
based only on residence rules (Rosenzweig 2003).
7
Figure 2—Sampled child and village household counts
7
There is evidence suggesting that panel survey rules that condition on residence provide nonrandom
subsamples of the baseline households (Thomas, Frankenberg, and Smith 2001; Foster and Rosenzweig
2002). If households do not divide randomly, residence-based sampling rules may bias estimates of
economic mobility (Rosenzweig 2003). One important source of selection bias is children’s decision to
marry and leave the parental home. Only those who remain in their original households are actually
resurveyed, making estimates biased because they are based on “stayers.” Panel surveys using residence-
based interview rules typically exclude both individuals who leave their parental residence, but remain in
the same village, as well as those who have migrated to different localities. Studies of migrants also rarely
link them back to the original household. There are, of course, exceptions, including the Malaysian Family
Life Survey, the Indonesian Family Life Survey, the INCAP-based Human Capital Study, and the
Bangladesh Nutrition Survey of 2000, to name a few.
10
It is important to note that in many residence and gender categories of the
Bukidnon survey, the sample size is quite small and thus results must be interpreted as
potentially indicative of trends—rather than final conclusions—that warrant further
scrutiny.
Characteristics of the Respondents’ Children
Tables 1, 2, and 3 present descriptive information on all children of the original
respondents, regardless of location. This information was obtained by asking the parents
to list all of their children, whether coresident, residing in the same barangay, or migrant.
In these tables, children are classified into nonmigrants, rural migrants, peri-urban
migrants, urban migrants, and overseas migrants based on the addresses given by their
parents. The classification in later tables is based on respondents’ self-reports so the
numbers in each category may differ. In addition, these tables use “peri-urban” as a
category (mostly outskirts of metropolitan areas), while surveys of the migrant offspring
use “poblacion” instead.
Location
Table 1 presents the distribution of children 15 and over of original respondents,
based on their current location.
8
About 53 percent of children 15 and over are
nonmigrants: of these, two-thirds coreside with parents and one-third live in the same
barangay but in separate households. A substantially higher proportion of males are
nonmigrants (61.8 percent versus 43.5 percent for females), consistent with national
trends. The proportion of males coresiding with parents (44.6 percent) is much higher
than the proportion of females (24.9 percent). Men have higher coresidence rates not
because women marry earlier but because women are more likely than men to migrate as
teenagers, with a high proportion of women’s migration occurring well before marriage
8
The cutoff of 15 years old could overstate the “nonmigrant” population because migration may occur
more often at an older age, but this age is consistent with other demographic studies. An older cutoff
would not change the results substantially.
11
(Lauby and Stark 1988). Roughly equal percentages of males and females—between 17
to 18 percent—have formed separate households in the same village. Many of these live
on a portion of the family farm or homestead that has been allotted to the child upon his
or her marriage.
Table 1—Distribution of children age 15 and over of original respondents, by location,
2003
Males Females
Location Number Percent Number Percent Total
Percent
distribution
Nonmigrants 510 61.8 330 43.5 840 53.1
Coresident with parents 368 44.6 189 24.9 557 35.2
Same barangay as parents 142 17.2 141 18.6 283 17.9
Rural migrants
115 13.9 127 16.8 242 15.3
Different barangay, rural 81 9.8 95 12.5 176 11.1
Rural Mindanao outside Bukidnon 27 3.3 20 2.6 47 3.0
Rural Philippines outside Mindanao 7 0.8 12 1.6 19 1.2
Peri-urban migrants
41 5.0 66 8.7 107 6.8
Different barangay, poblacion 37 4.5 59 7.8 96 6.1
Peri–urban, outside Bukidnon 4 0.5 7 0.9 11 0.7
Urban migrants
156 18.9 209 27.6 365 23.1
Urban Bukidnon 24 2.9 31 4.1 55 3.5
Cagayan de Oro 51 6.2 59 7.8 110 6.9
Other urban Mindanao 21 2.5 35 4.6 56 3.5
Urban Philippines outside Mindanao 60 7.3 84 11.1 144 9.1
Abroad
3 0.4 26 3.4 29 1.8
Total
825 100.0 758 100.0 1,583 100.0
Source: Bukidnon Panel Survey, 2003 round.
Approximately 15 percent of all children have migrated to other rural areas—a
slightly higher percentage of females than males—and roughly 7 percent have migrated
to peri–urban areas, with again, slightly more females than males. Twenty-three percent
of the children surveyed have moved to urban areas, with significantly higher migration
rates among females. Finally, only 1.8 percent of children have gone abroad, with, yet
again, more females than males represented among overseas migrants.
When considering only migrants, an interesting picture emerges. Rural migration
in this region of the Philippines is not only to large urban areas. Other rural areas and
small towns and cities are major destinations. Of the somewhat less than half who did
12
move outside their home barangay, 36 percent of male migrants and 30 percent of female
migrants (32 percent overall) went to other rural areas. Another 29 percent of migrants
went to smaller cities and towns rather than to major metropolitan areas (i.e., to peri-
urban areas, urban Bukidnon, and other urban aeras in Mindanao). About one-third of
the migrants went to the major metropolitan area in the region, Cagayan de Oro, or to
large metropolitan areas in the Philippines outside Mindanao, such as Manila or Cebu
City.
Civil Status
Since marriage may be an occasion for individuals to leave the parental home, we
examine the civil status of children in Table 2. Consistent with Table 1, the majority of
coresident males and females are single, although 18.5 percent of coresident females are
married, and living in an intergenerationally extended family.
9
Almost all children living
in separate households in the same barangay are married. The majority of children who
have migrated to rural and peri-urban areas are also married, regardless of location.
However, the pattern among migrants to urban areas is more diverse. Seventy percent of
male migrants to urban centers in Bukidnon are married, in contrast to only 48 percent of
female migrants. On the other hand, 60 percent of male migrants to urban Cagayan de
Oro are single, while 60 percent of female migrants to this same city are married (the
opposite of the male pattern). Male migrants to other cities in Mindanao are almost
equally distributed between married and single states, while female migrants are more
likely to be married. Similarly, female migrants to other urban areas outside Mindanao
are more likely to be married than single, while males are about equally likely to be
single or married. Finally, the pattern of international migration for males is opposite that
of females, with single females and married males more likely to migrate overseas.
9
This could also reflect out-of-wedlock childbearing or marital dissolution, both of which are likely to be
underestimated in the Philippines. The illegality of divorce, the importance of family cohesion and
interpersonal harmony in Philippine society, the child-centeredness of Philippine culture, and an emphasis
on the moral propriety of women may lead women without a male partner not to live alone but to reside as
a “subfamily” in larger, extended households (Chant 1998).
13
Typically, single females are likely to be employed as domestic workers, while married
males tend to migrate to the Middle East for contractual employment.
Table 2—Civil status of children age 15 and over of original respondents, by location, 2003
(percentage distribution)
Males
Females
Location Single Married
Separated/
widowed
Single Married
Separated/
widowed
Nonmigrants
Coresident with parents 91.0 7.6 1.4 78.3 18.5 3.2
Same barangay as parents 2.8 97.2 0.0 2.1 95.7 2.1
Rural migrants
Different barangay, rural 27.2 71.6 1.2 6.3 93.7 0.0
Rural Mindanao outside Bukidnon 44.4 55.6 0.0 20.0 80.0 0.0
Rural Philippines outside Mindanao 28.6 71.4 0.0 0.0 100.0 0.0
Peri-urban migrants
Different barangay, poblacion 29.7 70.3 0.0 0.0 100.0 0.0
Peri–urban, outside Bukidnon 25.0 75.0 0.0
Urban migrants
Urban Bukidnon 29.2 70.8 0.0 51.6 48.4 0.0
Cagayan de Oro 58.8 41.2 0.0 41.4 58.6 0.0
Other urban Mindanao 47.6 52.4 0.0 42.9 57.1 0.0
Urban Philippines outside Mindanao 51.7 46.7 1.7 35.7 64.3 0.0
Abroad 33.3 66.7 0.0 65.4 34.6 0.0
Total 56.6 42.5 0.9 37.4 61.5 1.2
Source: Bukidnon Panel Survey, 2003 round.
Education
With the exception of the overseas migrants and men in some rural and peri-urban
situations, females report higher elementary and high school completion rates than males
(Table 3 and Figure 3). This may reflect parental attitudes towards investing in boys’
versus girls’ schooling, as revealed by ethnographic studies in the same communities
(Bouis et al. 1998), but is also consistent with the Philippines’ national educational
statistics (Quisumbing, Estudillo, and Otsuka 2004). According to the ethnographic
studies, parents invest in the schooling of girls because they are “more studious,”
“patient,” “willing to sacrifice,” and “interested in their studies,” which are traits that
would make them succeed in school. On the other hand, boys are more prone to vices
Table 3—Percent completing educational category, children 15 and over, by sex and location, 2003
Males
Females
Location College Vocational Secondary Elementary
College Vocational Secondary Elementary
Nonmigrants
Coresident with parents 5.7 17.1 33.7 74.7 14.3 33.3 55.0 92.6
Same barangay as parents 4.9 17.6 36.6 73.9 7.9 22.9 50.0 86.4
Rural migrants
Different barangay, rural 11.1 23.5 37.0 85.2 13.7 28.4 55.8 85.3
Rural Mindanao outside Bukidnon 14.8
a
22.2 37.0 74.1 10.0 15.0 70.0 100.0
Rural Philippines outside Mindanao 28.6 42.9 42.9 71.4 8.3 41.7 66.7 100.0
Peri–Urban migrants
Different barangay, poblacion 0.0 18.9 64.9 83.8 15.3 35.6 64.4 94.9
Peri–Urban, outside Bukidnon 25.0
b
75.0 75.0 100.0 14.3 42.9 57.1 100.0
Urban migrants
Urban Bukidnon 8.3 16.7 33.3 79.2 17.2 62.1 75.9 96.6
Cagayan de Oro 21.6 49.0 78.4 92.2 37.3 67.8 88.1 98.3
Other uban Mindanao 4.8 33.3 66.7 95.2 20.0 54.3 62.9 100.0
Urban Philippines outside Mindanao 10.0 31.7 66.7 93.3 19.0 44.0 76.2 91.7
Abroad 100.0
c
100.0 100.0 100.0 42.3 73.1 100.0 100.0
Total 8.1 22.3 42.5 79.3 16.6 38.0 63.2 92.2
Source: Bukidnon Panel Survey, 2003 round.
a
Cell size: 7.
b
Cell size: 4.
c
Cell size: 3.
14
Figure 3—Percent of males and females completing secondary school, children 15 and over, by destination location
0.0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
80.0
90.0
100.0
Co
re
s
i
den
t
w
i
th
p
a
ren
t
s
S
ame baranga
y
as par
e
nts
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ifferen
t
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ra
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,
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ura
l
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ra
l
Min
da
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o
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uts
ide
B
ukid
no
n
R
u
ral Philip
p
ines
o
utside Minda
n
ao
Dif
f
er
e
nt barangay, poblacion
P
e
ri–U
rba
n,
ou
t
sid
e Bu
k
id
n
on
U
r
ban Bukidno
n
Ca
ga
y
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n de O
ro
O
ther
ub
a
n Minda
n
ao
Urb
an
P
hi
lip
pin
e
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o
uts
ide Mi
nda
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Females
Males
15
16
(such as drinking), fond of “roaming around” and “playing with their barkada” (peer
group), and have to be “reminded” and “scolded” to do their schoolwork.
Ninety-three percent of females still living with parents have completed
elementary school, whereas only 75 percent of males have done so. Fifty-five percent of
daughters living at home have completed high school, compared to only 34 percent of
sons. Among rural migrants within Bukidnon, a larger proportion of females have
completed secondary school and vocational school, and the percentage of females
completing college is slightly higher than males. Migrants to rural areas outside
Bukidnon show a similar pattern. However, among migrants to rural areas outside
Mindanao, a higher proportion of male migrants have completed college.
Female migrants to poblaciones in Bukidnon are somewhat more educated than
male migrants, with 15 percent completing college versus zero for men. However, male
migrants to poblaciones outside Bukidnon have higher secondary, vocational, and college
completion rates than females. Female migrants to urban areas are substantially more
educated than male migrants, with higher percentages completing college than men.
However, all male overseas migrants have completed college, compared to 42 percent of
female migrants, who are more likely to have completed vocational school. This reflects
the pattern of females migrating overseas to work as domestic helpers, but this result
must be taken with caution, owing to the small sample size of overseas migrants.
In sum, just over half of the respondents’ children chose to remain in their home
barangay rather than migrate to another area. However, more female offspring migrated
(56.5 percent) than male children (38.2 percent). Very few of the migrants left the
Philippines, only 3.4 percent of the daughters and 0.4 percent of the sons. Of those who
migrated, approximately half moved to urban areas. Females who moved to other rural
and peri-urban locations were usually married, but approximately half of those that went
to urban areas and two-thirds of those that left the country were still single. Female
migrants to urban and peri-urban locations were at least as well educated, if not better
educated than those females who stayed at home or in other rural areas, and, in general,
slightly better educated than male migrants.
17
Migration in Retrospect: Evidence from Migration Histories
We use the 2004 round of the survey to delve more deeply into the experience of
migrants. Migrant offspring to rural areas within Bukidnon and nearby neighboring
provinces as well as those who moved to poblaciones and urban areas were tracked and
interviewed between April and July 2004. The survey questionnaire was very similar to
that administered to their siblings who had formed separate households within the
parents’ barangay, but included a module that collected a detailed migration history,
listing all the places the individual had moved to for at least three months after leaving
the parental home. This module obtained information on the reasons for migrating and
occupation in each locality. In addition, a more detailed set of questions was asked
regarding the first move and, for those who moved more than once, the most recent
move. These focused on the type of job search, sources of support, and social networks
in the new community. Because we are interested in differences in the migration
experience by gender, and also across the rural-urban continuum, the descriptive tables
are stratified by location, and by gender within each location. We asked respondents to
report what kind of locality they moved to; the classification into rural, urban, and
poblacion is based on respondents’ assessment, not a census definition. As noted above,
because the self-classification is based on respondents’ assessments, they may not
correspond exactly to classifications based on the parents’ reports.
The following sections present descriptive statistics on basic demographic
characteristics, occupational profiles, reasons for moving, migration support networks,
and characteristics of the job search. We make comparisons between the first and most
recent moves to discern whether migrant experiences have changed through time. The
first move is important because it captures an individual’s nest-leaving decision. We note
that because the number of moves differs across individuals, when we examine
subsequent moves, we are comparing persons at different stages of their life cycle and
only those persons who have moved more than once. This group of subsequent movers,
then, may be a selected sample. We control for differences in the life-cycle stage later on
18
in the regression analysis by including age and age-squared when analyzing present
location.
Basic Demographic Characteristics
Migrants to rural areas, poblaciones, and urban areas are quite different in terms
of basic demographic characteristics (Table 4). Female migrants to rural areas and
poblaciones tend to be a few years younger than male migrants when they leave their
parents’ household, while there is no perceptible age difference between male and female
migrants to urban areas. Across all locations, females achieve higher levels of schooling
than males. The schooling gap, however, is smallest among rural migrants.
Table 4—Basic demographic information on migrant children reinterviewed in 2004 round,
by destination of first move
Rural area
Poblacion
Urban area
Characteristic Males Females Males Females Males Females
Number of observations 38 51 19 46 23 55
Age 31.0 29.1 26.4 26.9 29.9 28.9
Years of schooling 8.2 9.2 9.6 11.2 9.4 11.3
Age left parents’ household 24.5 22.4 25.5 21.0 24.1 23.7
Size of current household 4.6 4.4 2.9 3.6 3.8 4.0
Civil status
Percent single 15.8 7.8 15.8 30.4 34.8 25.5
Percent married 84.2 92.2 84.2 69.6 65.2 74.6
Migrant moves
Mean number of moves 3.0 2.0 2.7 1.9 2.8 1.6
Median number of moves 2.0 1.0 3.0 2.0 2.0 1.0
Moves by the migrant’s spouse
Mean number of moves 1.5 1.8 2.0 1.1 1.8 1.5
Median number of moves 1.0 1.0 2.0 1.0 1.0 1.0
Distance from town center (kilometer)
First move 11.7 9.0 5.5 11.4 3.4 2.9
Last move 10.0 8.7 0.7 1.6 2.7 2.6
Source: Bukidnon Panel Survey, 2004 round.
Note: Location classifications are based on respondent self- reports.
Similar to other countries, marriage is often an occasion for migration. Eighty-
four percent of male and 92 percent of female migrants to rural areas are currently
married, and 65 percent of male and 75 percent of female migrants to urban areas are
19
currently married. Not surprisingly, household sizes in the rural areas are largest,
followed by the poblacion, and lastly by urban areas.
The migrants interviewed are fairly mobile, with a median number of three moves
for males and two moves for females. Thus, while females are more likely to migrate,
conditional on migration, males seem to move more often. Spouses appear to be less
mobile than the migrants, but this could be due to recall error. Finally, distance to the
poblacion decreased between the first and last moves, indicating that migrants may be
choosing to live closer to areas where basic services are more readily accessible and jobs
more available.
To summarize:
• Female migrants migrate at younger ages and have higher schooling attainment
than male migrants;
• A high proportion of migrants to rural areas and urban areas are married; and
• Migrants who have moved more than once over time tend to choose to live closer
to areas with easier access to public services and employment opportunities.
Occupational Characteristics
Occupations of migrants vary across locations and by gender and also change
substantially between the first and most recent moves. Men tend to work in farming,
crafts and trades, and manual labor and transportation in both their first (Figure 4) and
their most recent (Figure 5) moves
10
. Although a large proportion of first-time migrants
are students, few remain in school after their first move. Aside from school, the
proportions of men in certain occupations do not change significantly after their first
move; farming, crafts and trades, and manual labor and transportation are the most
common occupations. In contrast, women who have moved at least twice are more likely
to work in housework or childcare and are less likely to be students or work in manual
labor and transportation. This change suggests that many women students and women
10
Figures 4 and 6 show data for migrants who have moved only once. Figures 5 and 7 show data for the
most recent move of migrants who have moved more than once.
20
who work in manual labor and transportation in their first move end up migrating again
and working in housework or childcare. It is possible that a subsequent move for these
women is for marriage and their husbands become the household’s income earners while
Figure 4—Occupation (on first move) of those who have moved only once, by gender
Figure 5—Occupation (most recent move) for those who have moved more than once, by
gender
0
5
10
15
20
25
30
35
Farm
i
n
g
Ho
use
work/
c
h
i
l
d
ca
re
Student
Prof
e
ss
i
on
al/
Mana
ge
r
/
Owne
r
S
a
les
Cra
f
ts/Tra
d
es
Manu
a
l La
bo
r/Tr
a
nsp
o
rtati
o
n
Unemp
l
oyed/Retir
e
d/D
isa
ble
d
Males
Females
21
the women transition to reproductive tasks. While further schooling acquired during their
first move may delay marriage, most women eventually end up getting married. For
example, Demographic and Health Survey data for the Philippines (NSO and ORC
Macro 2004) show that while only 9.4 percent of women 15-19 are ever-married, 89.2
percent are ever-married by age 30-34, and 95.5 percent are ever-married by age 45-49.
Since location along the urban-rural continuum affects a migrant’s choice of
livelihood activities, it is not surprising to see variation in the prevalence of occupations
of migrants who have moved only once (Figure 6) and the latest occupation of those who
have moved more than once (Figure 7). Farming and housework and childcare are more
prevalent in rural areas, while sales, manual labor, and getting an education are more
common in urban areas. In particular, among migrants on their first move, there are more
students in poblaciones and urban areas. However, the proportion of migrants who are
students in subsequent moves decreases while the proportion of some occupations
Figure 6—Occupation (first move) of those who have moved only once, by location
0
10
20
30
40
50
Farm
ing
H
ous
e
w
ork/childc
a
re
Student
Pro
f
es
s
i
onal/
M
a
nager/Ow
ner
S
ales
Crafts/Trades
Manual Labor/T
r
an
s
por
t
at
ion
Unemploye
d/
Ret
i
red/Dis
a
bled
Rural Area
Poblacion
Urban Area
22
Figure 7—Occupation (most recent move) for those who moved more than once, by
location
increases. In rural areas, migrants on their most recent move are farmers or do
housework and childcare. In poblaciones and urban areas, fewer migrants are students on
their subsequent move, while more engage in housework and childcare, are professionals,
managers or owners, or work in sales (in poblaciones).
In summary:
• Men tend to work in farming, crafts and trades, and manual labor and
transportation in both their first and their subsequent moves. In contrast,
occupations of female migrants become less diverse in subsequent moves, with
one in three females reporting that they are occupied in housework and childcare
after their most recent move.
• A high proportion of first-time migrants to poblaciones and urban areas are
students—particularly women. In rural areas, more migrants on their subsequent
move are farmers or do housework and childcare than migrants on their first
move. In poblaciones, more migrants on their most recent move do housework
and childcare, are professionals, managers or owners, or work in sales than
0
10
20
30
40
F
armin
g
H
o
usewor
k
/c
h
ildcar
e
St
u
dent
Professional/Manage
r
/Owne
r
Sal
es
Cra
f
t
s
/
Tr
ades
M
an
ual
Lab
or
/
Tr
ans
por
t
a
tio
n
Unemployed/Retire
d
/Disable
d
Rural Area
Poblacion
Urban Area
23
migrants on their first move. In urban areas, more migrants on their most recent
move are professionals, managers, or owners than migrants on their first move.
Reasons for Moving
Migrants’ reasons for moving differ markedly by destination and by gender
(Tables 5 and 6). While most male migrants to rural areas migrate for the first time to
start a new job (21percent), or to get married (18 percent), the predominant reason for
females to move to a rural area is marriage (35 percent), followed by starting a new job
(23 percent) (Table 5). In contrast, both male and female first-time migrants to
poblaciones and urban areas move either to start a new job or because schools are better
Table 5—Primary reason for moving, by sex and destination, first move (percent)
Rural area
Poblacion
Urban area
Reason
Males Females Males Females
Males Females
Number of observations 38 51 19 46 23 55
"Pull factors" 52.7 49.1 73.7 71.8 86.9 65.5
Better schools in destination 7.9 7.8 31.6 32.6 30.4 30.9
Schooling 2
To start new job in destination 21.1 23.5 36.8 32.6 43.5 25.5
To look for job in destination 13.2 2 5.3 13 9.1
To look for land to cultivate 7.9 9.8
Acquired property 2.6
Presence of benefactor for scholarship 2 4.4
Near current job 2
Easy access 2.2
"Push factors"
15.9 11.8 21.2 24 13.1 16.3
No school or poor school at origin 5.3 5.9 5.3 8.7 8.7 10.9
No job in origin 5.3 3.9 5.3 4.4 3.6
Poor job in origin 5.3 2 10.9 4.4 1.8
Escape war/violence 5.3
Drought/famine/disease 5.3
Life-cycle or family factors
31.5 39.7 5.3 4.4 18.1
Marriage 18.4 35.3 5.3 4.4 12.7
Moved with household head/household
member 2.6 3.9 3.6
Started living independently 2.6
Vacation
a
7.9 1.8
Source: Bukidnon Panel Survey, 2004 round.
Notes: Number of observations refer to all migrants who answered this question. Location classifications
are based on self-reports.
a
Some migrants, especially those who attend school in urban areas, return to their homes in rural areas
during the summer vacation. The migrant round was conducted during the Philippine summer vacation.
24
in the destination. Taking into account both “push” and “pull” factors related to
education, a greater share of females than males cite schooling as their primary reason for
moving to a poblacion or urban area.
Reasons for moving are more diverse for the most recent move, reflecting
different life-cycle stages as well as the effect of previous moves (Table 6). Combining
economic reasons for migration (starting a new job, looking for a job, job loss, and
looking for land to cultivate), more males (a combined total of 53 percent) migrate for
economic reasons than for life-cycle or family reasons. In contrast, more than half of
female migrants to rural areas migrate for family reasons, with marriage accounting for
54 percent of female migrants. The pattern is different in poblaciones and urban areas,
however. Most male and female migrants to poblaciones migrate for economic reasons,
such as starting a new job. The next highest percentage of male migrants move for
marriage, while schooling is the next most important motivation for female migrants.
Economic motives also dominate the most recent move by male migrants to urban areas,
while economic and life-cycle motives are equally important for female migrants—30
percent of females move to start a new job or to look for a job, while 27 percent move to
urban areas to get married.
Migrants were also asked whether they were planning to move from their present
location, and if not, why not. Among those who were not planning to move, rural males
cite a variety of reasons for not planning to move, the most important being the presence
of friends and family (42 percent), followed by a number of other reasons related to jobs
and farming (Table 7). More than 60 percent of rural females, on the other hand, say that
the presence of friends and family in the area is the most important reason for not moving
to another community—highlighting the importance of social networks for females in
rural areas. This is not surprising because females in rural areas are more likely to have
moved because of marriage rather than to pursue schooling or better employment
opportunities. Equal proportions of males in poblaciones mention having a good job and
proximity to friends and family as reasons for not moving, whereas half of females in the
25
Table 6—Primary reason for moving, by sex and destination, most recent move of
migrants who moved more than once
Rural area
Poblacion
Urban area
Reason
Males Females Males Females Males Females
Number of observations 36 65 8 27 36 59
"Pull factors" 58.3 33.8 62.5 63 75 55.9
Better schools in destination 7.4 5.6 3.4
Schooling 2.8
To start new job in destination 27.8 9.2 62.5 33.3 38.9 20.3
To look for job in destination 11.1 11.1 13.9 10.2
To look for land to cultivate 11.1 13.9
To look for cheaper rent 1.5
To look for better place to live 1.5
Acquired property 8.3 7.4 5.6 13.6
Business 1.5 3.7 5.6
Better salary 1.5
Near current job 1.5
Near home 2.8 1.7
Free housing 3.1 3.4
Easy access 3.4
"Push factors"
5.6 4.6 0.0 18.5 11.1 8.5
No school or poor school at origin 7.4 3.4
No job in origin 1.5
Poor job in origin 7.4 2.8 1.7
Lost previous job 2.8
High cost of living 1.7
Bankruptcy 2.8
Didn't like the previous place 2.8
Far from work 2.8
Far from basic services 3.7
Relocation 3.1 2.8 1.7
Life-cycle or family factors
36.1 61.5 37.5 18.5 13.9 35.6
Marriage 30.6 53.8 37.5 11.1 5.6 27.1
Moved with household head/household
member
2.8 6.2 3.7 5.6 3.4
Spouse working here 1.5
Started living independently 2.8 2.8 1.7
Domestic problems 3.7
Domestic responsibility 1.7
Vacation 1.7
Source: Bukidnon Panel Survey, 2004 round.
Notes: Number of observations differs from the previous tables because this table refers to migrants who
moved more than once and who responded to this question. The distribution across types of places
reflects subsequent moves. Location classifications are based on self-reports.
poblacion mention that their primary reason for not moving is having a good job (having
friends and family close by is mentioned by a substantially smaller 14 percent). Lastly,
both having a good job and proximity to friends and family are the most important
reasons that male and female urban migrants are planning to stay, with the order of
26
importance reversed for males and females. More males cite having a good job as a
reason to stay, while more females cite proximity to friends and family. The relative
importance accorded to economic and familial factors by males and females is consistent
with Smith and Thomas’ (1998) findings for Malaysia.
Table 7—Reasons for not moving to another community, migrants who do not intend to
move, 2004
Rural area
Poblacion
Urban area
Reason
Males Females Males Females Males Females
Number of valid responses 26 45 7 14 31 52
Positive factors
Good job here 11.5 20.0 42.9 50.0 38.7 21.2
Good business here 7.1 6.5 5.8
Good opportunities for children here 7.1 9.6
Studying here 3.2
Married 1.9
Spouse working here 4.4 1.9
Have friends and family here 42.3 62.2 14.3 19.4 30.8
Good job here and have friends and family 11.5 2.2 42.9 12.9 3.9
House/lot owned by family 4.4 7.7
Own house and lot and have friends and family 1.9
Affordable house rental 7.1
Free housing 6.5
Favorable climate for farming 3.9
Near the city 3.9 7.1
Near farm 7.7 2.2
Started planting corn in a free use land 3.2
Negative factors
Afraid of not finding job elsewhere 15.4 4.4 14.3 7.1 3.2 7.7
Don’t know anyone elsewhere 3.9 6.4 5.8
No available place to transfer 1.9
Source: Bukidnon Panel Survey, 2004 round.
Note: Locations refer to migrants’ current location; classification is based on self-reports.
To summarize:
• More males migrate to rural areas for economic reasons than for family or life-
cycle reasons; the reverse is true for females. Most male and females migrate to
poblaciones for economic reasons. While males migrate to urban areas for
economic reasons, both economic and family reasons are equally important for
females.
27
• The majority of female migrants to rural areas and a plurality of males cite the
presence of family and friends as their primary reason for not wanting to move
again; in poblaciones and urban areas, the proximity to friends and family and
having a good job are important factors for both male and female migrants who
choose to stay put.
Migration Support Networks
Support networks play different roles depending on the migrant’s destination. For
the first move (Table 8), over 50 percent of male migrants to all destinations in this
survey moved alone. About 25 percent of males moving to poblaciones moved with
Table 8—Networks and support for the first move, by destination location and sex
(percent)
Rural area
Poblacion
Urban area
Type of network/support
Males Females Males Females Males Females
Number of observations 38 51 19 46
23 55
Company in moving to new community
Alone 52.6 39.2 52.6 58.7 56.5 47.3
Parents 2.6 2.0 5.3 4.4
Siblings 5.3 2.0 13.0 4.4 12.7
Spouse/fiancé 10.5 29.4 5.3 4.4 9.1
Children 7.9 15.7 5.3 2.2 3.6
Other relative 10.5 9.8 5.3 10.9 21.7 16.4
People from place of birth 5.3 2.0 26.3 10.9 13.1 9.1
Acquaintances 5.3 1.8
Persons lived with in new community
Nobody 18.4 25.5 26.3 19.6 17.4 12.7
Parents 2.6 4.4 7.3
Siblings 2.6 5.9 5.3 10.9 30.4 3.6
Spouse/fiancé 2.6 13.7 4.4 12.7
In-laws 10.5 7.8
Other relative 47.4 25.5 47.4 37.0 43.5 41.8
People from place of birth 2.6 2.0 6.5 1.8
Other acquaintances 5.3 7.8 5.3 4.4 4.4 1.8
Employer 5.3 11.8 5.3 15.2 16.4
Stranger 2.6 10.5 2.2 1.8
Financial support for moving expenses
No one/own savings 29.0 31.4 31.6 8.7 21.7 20.0
Parents 39.5 25.5 57.9 65.2 52.2 50.9
Siblings 2.6 5.9 5.3 10.9 13.0 10.9
Spouse/fiancé 13.7 2.2 3.6
In-laws 2.6 3.9
Other relatives 23.7 7.8 5.3 4.4 13.0 3.6
People from place of birth 2.6 2.0
Employer 9.8 8.7 10.9
Source: Bukidnon Panel Survey, 2004 round.
28
people from their place of birth, and 22 percent of those moving to urban areas were
accompanied by relatives. While 39 percent of female migrants to rural areas also noted
that they moved alone, 29 percent said they moved with their spouse or fiancé, consistent
with the high proportion of women moving to rural areas because of marriage. This
number increases to 45 percent if we include the additional 16 percent that moved with
children in tow. In contrast, 59 percent of women moving to poblaciones, and 47 percent
of women moving to urban areas, moved alone. Upon arrival in the new community, a
large proportion (25 to 47 percent) of all first-time movers lived with relatives other than
immediate family members. Another 30 percent of male migrants to urban areas lived
with their siblings, probably reflecting a practice whereby children going to school rent
an apartment jointly. First-time migration, particularly to poblacion and urban areas, is
also predominantly financed by migrants’ parents.
Support patterns for subsequent moves are markedly different from the first
(Table 9). More than 70 percent of male and 85 percent of female migrants to rural areas
made this move with their spouses—many accompanied by children as well. Fifty
percent of females now moving to the poblacion moved with their spouse, with children
accompanying them half the time. Additionally, 50 percent of male and female migrants
to urban areas moved this time with spouses and often children. In contrast, about 70
percent of male migrants to poblaciones tended to make their subsequent move alone;
only 28 percent moved with their families. This could reflect men’s moving to the
poblacion for work, commuting on weekends to the nearby rural area to visit their
families. Probably reflecting accumulated wealth or experience, most migrants did not
live with other people in their most recent move, with the exception of spouses (in the
case where families moved together). About a quarter of migrants to rural areas, both
male and female, lived with their in-laws.
While first-time movers typically rely on family and friends for financial support
while looking for work in their new community, most subsequent moves tend to be self-
29
Table 9—Networks and support for the most recent move for migrants who moved more
than once, by location and sex (percent)
Rural area
Poblacion
Urban area
Type of network/support
Males Females Males Females Males Females
Number of valid responses 25 45 7 14
31 50
Company in moving to new community
Alone 24 13.3 71.4 42.7 35.5 37.2
Siblings 2
Spouse/fiancé 52 48.9 14.3 35.7 12.9 27.4
Children/spouse/fiancé 20 35.6 14.3 14.3 38.7 25.5
Other relative 4 7.1 6.4 5.9
People from place of birth 2.2 6.4 2
Persons lived with in new community
Nobody 56 35.6 42.9 35.7 41.9 25.5
Parents 2.2 3.9
Siblings 9.7 3.9
Spouse/fiancé 12 15.6 28.8 14.3 9.7 29.4
Children/spouse/fiancé 2.2 6.5
In-laws 24 26.7 7.1 6.5
Other relative 8 13.3 14.3 6.5 7.8
People from place of birth 7.1 1.7
Other acquaintances 14.3 7.1 9.7 19.6
Employer 14.3 14.3 3.2 7.8
Stranger 4.4 3.2
Financial support for moving expenses
No one/own savings 64 44.4 71.4 28.6 77.4 47.1
Parents 12 8.9 14.3 35.7 6.4 11.8
Sibling 4 8.9 5.9
Spouse 4 17.8 14.3 14.3 6.4 25.5
In-laws 12 11.1 2
Other relatives 6.7 7.1
People from place of birth 4 3.2
Employer 2.2 14.3 6.4 7.8
Source: Bukidnon Panel Survey, 2004 round.
financed. Tables 10 and 11 present information regarding the job search of migrants in
their first and most recent move, respectively. Owing to the small sample sizes in some
of the categories, these patterns are merely indicative and cannot direct us to particular
conclusions. Nonetheless, our data demonstrate that first-time migrants to rural areas and
to urban areas relied on family and friends they lived with while looking for a job, while
male migrants to the poblacion relied on their own savings. Female migrants to the
poblacion relied on family and friends from their previous place of residence, yet “own-
savings” for females in rural areas and support from “those in previous residence” is also
significant.
30
Table 10—Characteristics of the job search after the first move, by location and sex
(percent)
Rural area
Poblacion
Urban area
Males Females Males Females Males Females
Number of valid responses 27 34 11 30
16 37
Source of support while looking for a job in new
community
Own savings 18.5 26.5 27.3 10.0 18.8 8.1
Family/friends lived with 33.3 38.2 18.2 23.3 50.0 43.2
Family/friends in previous place of residence 33.3 23.5 18.2 53.3 31.3 37.8
Other family/friends 14.8 5.9 18.2 6.7 5.4
Employer (free food/house) 2.9 6.7 2.7
Own savings and lived with family/friends 2.9
Family and friends lived with and in previous
place 9.1
Menial work/begging 9.1 2.7
How did you look for a job in the new community
Own search before moving 20.0 34.5 18.2 32.1 6.7 11.5
Arranged by family 20.0 3.5 27.3 28.6 6.7 15.4
Arranged by friends 20.0 37.9 27.3 10.7 26.7 34.6
Own search after moving 36.7 17.2 9.1 17.9 53.3 34.6
Arranged by relatives 3.3 3.5 18.2 7.1 6.7 3.9
Other 3.5
Selected by employer 3.6
Source: Bukidnon Panel Survey, 2004 round.
Table 11—Characteristics of the job search after the most recent move, by location and
sex (percent)
Rural area
Poblacion
Urban area
Males Females Males Females Males Females
Number of valid responses 16 34 4 9
23 36
Source of support while looking for a job in new
community
Own savings 68.8 47.1 50.0 44.4 78.3 30.6
Family/friends lived with 31.2 38.2 50.0 33.3 8.7 55.6
Family/friends in previous place of residence 5.9 11.1 4.4 8.3
Other family/friends 5.9 11.1 8.7
Own savings and lived with family/friends 2.9
Menial work/begging 2.8
Own savings and menial work 2.8
How did you look for a job in the new community
Own search before moving 19.0 30.0 33.3 20.0 44.4 20.7
Arranged by family 4.8 10.0 20.0 14.8 24.1
Arranged by friends 23.8 20.0 33.3 20.0 7.4 3.5
Own search after moving 38.1 40.0 33.3 40.0 25.9 44.8
Arranged by relatives 9.5 3.7 3.5
Selected by employer 4.8 3.7 3.5
Source: Bukidnon Panel Survey, 2004 round.
31
In contrast to the first time they moved, subsequent migrants to all areas,
particularly males but females as well, were more likely to be able to support themselves
while looking for work (Table 11). Self-finance and being supported by coresident
family/friends are also the most important categories of support reported by female
migrants to the poblacion (44 percent and 33 percent, respectively, in their most recent
move, with 22 percent receiving support from non-coresident family and friends.
Seventy-eight percent of male migrants to urban areas who moved more than once said
that they supported themselves in their most recent move, while 56 percent of female
migrants said they received support from family and friends for their most recent move.
The Job Search
First-time male migrants to rural areas found jobs by doing their own search after
moving, while female migrants to rural areas either had jobs arranged by friends, or
looked for a job prior to moving. The majority of male and substantial numbers of
female migrants to poblaciones found jobs that were arranged by family and friends; yet
many women—more so than men—did their own search for employment. In contrast,
half of male migrants to urban areas searched for jobs after moving, and a quarter found
jobs through friends. About 35 percent of female migrants to urban areas found jobs by
themselves after moving, and an equal percentage found jobs through their friends.
For subsequent moves, migrants were less dependent on friends and relatives to
arrange for their employment in the new locale, and were in a somewhat better position to
conduct their own job search. In this case, almost 60 percent of men and 70 percent of
women heading to rural destinations did their own search (versus 29 percent and 30
percent, respectively, that had help from family and friends). Seventy percent of men and
65 percent of women did their own search for urban employment. Interestingly, on
subsequent moves to urban areas, male migrants are more much more likely to move
after they have found a new job rather than to embark on the move and then look for
work, which is usually the case on their first move.
32
To summarize the latter two sections:
• First-time moves are more likely to be financed by parents, and the migrant is
more likely to be moving alone. Subsequent moves are more likely to involve a
spouse and, possibly, children, and are more likely to be self-financed.
• Social networks can be more important for the first move than for subsequent
moves, which to some destinations are more likely now to be self-financed.
Subsequent job searches also rely less on social networks than first moves.
3. Modeling the Location Decision
Empirical Specification
We also looked at the determinants of a child’s present location, bearing in mind
that this decision was likely to have been both an individual and family decision.
Regression analysis allows us to control simultaneously for individual, household, and
locational characteristics that may influence an individual’s migration decision.
We estimate multinomial logit regressions on the following choices of location:
(1) child resides in the same barangay as the parents, but in a separate household; or (2)
child migrates to another rural area; or (3) child migrates to a poblacion, peri-urban area,
or an urban area.
11
The omitted category is coresidence with the parents. Given the
striking gender differences in migration patterns, we estimate separate regressions for
males and females. One issue in estimating migration models is the time period to which
the independent variables refer. Typically, a migrant is observed at a given point in time,
with the migration decision having been made in the past. Using current values of the
independent variables would not provide an accurate picture of the period in which the
decision was made. We therefore use variables that refer to conditions prevailing when
the individual was age 15, most of which were obtained from the 1984/85 and 1992 data.
11
Since only 5 percent of males and 9 percent of females migrated to poblaciones and peri-urban areas, it
was difficult to obtain reliable estimates when poblaciones and peri-urban locations were treated as a
separate category. Category (3) thus includes all three categories.
33
The probability of choosing location i can be expressed as
Probability (location i) = f(Individual characteristics, Parent characteristics, Sibling composition,
Household assets, Type of origin locality, Village dummies).
Individual characteristics. Individual characteristics that influence the choice of
location are the individual’s stage in the life cycle and human capital. Various studies
have shown that migration is inversely related to a person’s age (Lanzona 1998).
Younger people, who have a longer lifetime to capture the benefits of migration, are more
likely to move. We control for life-cycle effects using age and age-squared. We use
educational attainment as a proxy for individual human capital. However, because young
people are most likely to migrate to go to school, current educational attainment could
also be endogenous to the migration decision. To avoid the endogeneity of schooling to
the migration decision, we would have used educational attainment at age 15 in the
regressions. However, we only have this information for the children who were followed
up, not all children. To avoid losing observations, we use two dummy variables: (1)
whether the child completed high school; and (2) whether the child completed elementary
but not high school.
We do not include marital status in the regressions because marriage and the
decision to migrate may be codetermined, and thus marital status would be endogenous.
Individuals generally do not marry unless they have the ability to establish their own
household (Lanzona 1998) whether through their own or parental resources. Also, in
societies where extended families are common, the correlation between marriage and the
decision to leave home is low. In the rural Philippines, newlyweds may live with the
parents for a few years, moving out when they have the resources to build their own
house.
Parental characteristics. Parents’ years of schooling can affect the child’s
decision to migrate in two ways (Mincer 1978; Lanzona 1998). First, these variables
capture unobserved family background effects that can affect the child’s locational
34
decision. Households with better-educated parents are better able to acquire information
about the range of possible options in various localities and so induce greater migration.
Second, these variables can also be correlated with various assets, such as social
networks and family connections, that can lead to greater self-employment activities or
leisure, or, conversely, can facilitate job search in the new locale. Following a literature
on the collective model of the household (e.g., Thomas 1990, 1994; Schultz 1990;
Quisumbing 1994), we include both father’s and mother’s schooling in the regression,
since it is possible that mother’s and father’s schooling can have differential effects on
the migration decision.
Sibling composition. Studies of educational attainment of siblings have shown
that the gender composition of one’s siblings may affect an individual’s educational
attainment, depending on whether sibling rivalry exists (Butcher and Case 1994; Garg
and Morduch 1998a, 1998b; Morduch 2000). In Ghana, for example, the number of
brothers negatively affects one’s educational attainment, while the number of sisters has
no effect. Gender-differentiated inheritance patterns and expectations of old age support
may affect an individual’s probability of migration. In the Philippines, both sons and
daughters have equal rights to inherit owned (titled) land. Tenancy rights, however, are
typically inherited by sons, who are less likely to migrate than females. Moreover, if
parents compensate their daughters using increased educational investment, they may be
more likely to migrate in search of nonagricultural employment (Estudillo, Quisumbing,
and Otsuka 2001). Field interviews in the survey communities indicate, however, that
while parents may have preferred to give land to sons in the past, parents now give land
to whoever will use it, owing to the high outmigration rates in the study communities.
However, such land is typically not deeded over to the child; parents who own land prefer
to keep ownership in their name to prevent the children from mortgaging the land and
going into debt.
35
Asset position. We use two indicators of the household’s asset position that may
affect the probability of migration. One is the area of owned land that was cultivated by
the parents in 1984/85. Children from families owning more land per capita would be
less likely to migrate as they are more likely to inherit and farm this land in the future.
The other indicator of wealth is the value of nonland assets, which is likely to reduce the
probability of migration owing to greater self-employment activities in the parental farm
or family business. While agriculture continues to be the main activity of most of our
survey households, the survey area has witnessed the growth of many small
nonagricultural enterprises, such as farm machinery and agricultural processing.
Distance to facilities. Long distances from facilities and public services may
induce individuals to move closer to urban areas or poblaciones. To capture household
access to public services, we use three variables, defined as of 1984, when the sample
was entirely rural: (1) distance from the household to the poblacion; (2) travel time in
minutes to the nearest hospital; and (3) distance in kilometers to the BUSCO sugar mill.
Distance to the poblacion is a good proxy for access to services as well as job
opportunities because most publicly provided services and commercial establishments
would be present in the poblacion. While all of the survey barangays would have
elementary schools, for example, typically the public high school would be located in the
poblacion. Transport and communications facilities would also be present in the
poblacion, making it similar in function to a peri–urban area or small town.
Municipality dummies. Finally, the regressions contain dummy variables to
control for unobserved municipality-specific effects.
12
These include, for example,
differences in the availability of local employment conditions across municipalities.
12
We did not use village dummies because they would be highly collinear with the variables capturing
distance to facilities, even if these were measured at the household level.
36
Means
13
of the variables used in the regressions are presented in Table 12,
together with tests of differences between males and females. We can see that males are
significantly more likely to coreside with parents, whereas females are significantly more
likely to migrate to a poblacion, peri–urban area or an urban area. Males and females are
equally likely to reside in the same village as their parents or to migrate to a rural area.
Males and females are not significantly different in terms of their family background
characteristics. However, females are significantly more likely to have finished high
school.
Table 12—Means of variables used in regression analysis
Males Females Wald Test of differences
Mean Mean (p-value)
Dependent variables (0/1)
Coresiding with parents 0.42 0.29
0.00
Residing in the same village as parents 0.19 0.19 0.93
Migrating to rural area 0.15 0.18 0.14
Migrating to a peri-urban area 0.05 0.08
0.04
Migrating to urban area 0.20 0.27
0.01
Migrating to a peri-urban or urban area 0.24 0.35
0.00
Regressors
Child characteristics
Age 25.52 25.79 0.55
Elementary school completion, but not high school
a
0.37 0.32 0.19
High school completion
a
0.43 0.60
0.00
Household characteristics
Father’s education 5.34 5.30 0.81
Mother’s education 5.84 5.87 0.86
Area of owned land cultivated in 1984/85 (hectares) 1.07 1.15 0.33
Value of nonland assets in 1984/85 (thousand pesos) 457 505 0.25
Sibling composition
Number of younger brothers 1.80 1.89 0.57
Number of younger sisters 1.73 1.87 0.27
Number of older brothers 1.25 1.26 0.90
Number of older sisters 1.37 1.32 0.58
Location
Distance to poblacion (kilometers) 4.33 4.44 0.61
Time to hospital (minutes) 63.70 59.24 0.14
Distance to BUSCO Sugar Mill (kilometers) 25.04 24.15 0.22
Number of observations 863 782
Notes: Means are weighted, clustered means computed using weights described in the text. P-values in
bold are significant at 10 percent or better.
a
Dummy variable taking values 0 or 1.
13
They are computed with weights that take into account the original sample design (McNiven and Gilligan
2005); they also control for sibling effects.
37
Results
Table 13 shows marginal effects computed from weighted multinomial logit
regressions on children’s location decisions. Marginal effects are the change in the
dependent variable (the probability of being in a particular location) resulting from a one
unit change in the independent variable. Comparisons of marginal effects allow us to
discern the relative strength of the influence of the independent variables, over and above
knowing the direction of their influence. We also interpret these results taking the
Filipino cultural context into account.
Filipino children typically live at home until they marry, unless they migrate for
schooling or work to another location. Not surprisingly, for both males and females,
growing older significantly reduces the probability of living at home. For males,
completing high school significantly reduces the probability of coresiding with parents.
Males with more older brothers are also more likely to be living at home, whereas males
with more younger sisters are less likely to be living at home. Females with more older
sisters are also more likely to be living at home. This may reflect the sequential nest-
leaving decision of siblings, with the oldest moving out first, as well as the assignment of
tasks by gender, with “similar siblings” acting as substitutes (Smith and Thomas 1998).
Living farther from the poblacion reduces the probability that daughters coreside with
parents, probably because daughters would move to seek a better education or to look for
work. Distance from the sugar mill, however, increases the probability that daughters
live with their parents. Households located further from the sugar mill may be more
inaccessible, in general, than those located closer.
The next location category refers to living in the same village as parents, but in a
separate household. This transition typically occurs at the time of marriage, when parents
will allot a portion of the homestead to their newly married son or daughter. Parents also
typically provide a portion of their land for their sons to farm; if their daughter marries a
man who has no land, they may also provide land to their daughter. With married sons
38
Table 13—Determinants of migration of children age 15 and over, Bukidnon
Multinomial logit estimates, marginal effects by outcome
Regressions include correction for sampling design and attrition; standard errors account for
clustering within households.
Marginal effects on the probability of:
Coresiding with parents
Residing in the same village as
parents
Males Females Males Females
Regressors dy/dx z dy/dx z dy/dx z dy/dx z
Child characteristic
Age -0.134
-4.66
-0.149
-4.27
0.057
2.54
0.062
2.63
Age squared 0.002
3.57
0.002
3.97
-0.001
-1.81
-0.001
-2.32
Elementary school completion
a
-0.110 -1.28 0.117 0.81 0.004 0.06 -0.007 -0.11
High school completion
a
-0.344
-4.16
0.084 0.68 -0.044 -0.81 -0.119 -1.52
Household characteristics
Father’s education 0.019 1.56 0.004 0.34 -0.003 -0.38 -0.027
-3.58
Mother’s education 0.009 0.57 0.006 0.42 0.002 0.17 0.015
1.82
Area of own land cultivated in 1984/85 0.005 0.29 -0.013 -0.88 0.012 1.37 0.015 1.52
Value of nonland assets in 1984/85 0.000 -0.20 0.000
2.90
0.000
1.74
0.000 1.03
Sibling composition
Number of younger brothers -0.001 -0.03 -0.003 -0.12 -0.015 -1.13 -0.019 -1.32
Number of younger sisters -0.040
-1.86
-0.038 -1.58 0.028
1.87
0.017 1.24
Number of older brothers 0.052
2.21
-0.038 -1.57 -0.038
-2.52
-0.020 -0.94
Number of older sisters -0.011 -0.50 0.043
2.19
0.004 0.27 -0.051
-2.68
Distance from household
Distance to poblacion (kilometers) -0.005 -0.39 -0.024
-1.83
0.001 0.12 -0.003 -0.44
Travel time to nearest hospital in 1984 (minutes) -0.001 -0.82 -0.001 -0.52 0.000 -0.68 0.000 1.00
Distance to nearest sugar mill (kilometers) 0.003 0.51 0.011
2.08
0.002 0.33 0.006
1.90
Actual probability 0.51 0.43 0.16 0.15
Predicted probability 0.47 0.27 0.14 0.15
Migrating to a rural area
Migrating to a peri-urban or
urban area
Child characteristic
Age 0.018 0.03 -0.003 -0.14 0.038
1.76
0.091
2.81
Age squared 0.000 0.09 0.000 0.29 0.000 -1.38 -0.002
-2.79
Elementary school completion
a
0.051 0.64 -0.058 -0.95 0.130 1.40 -0.051 -0.50
High school completion
a
0.042 0.10 -0.052 -0.70 0.458
5.76
0.087 0.89
Household characteristics
Father’s education 0.008 0.37 0.001 0.11 -0.024
-2.38
0.022
1.85
Mother’s education 0.009 0.32 -0.038
-3.57
-0.001 -0.11 0.017 1.15
Area of own land cultivated in 1984/85 0.009 0.07 0.005 0.40 -0.033
-2.30
-0.008 -0.48
Value of nonland assets in 1984/85 0.000 0.13 0.000 -1.51 0.000 0.70 0.000 -1.28
Sibling composition
Number of younger brothers 0.014 0.13 0.018 1.10 -0.005 -0.30 0.003 0.16
Number of younger sisters 0.013 0.19 0.015 1.17 0.029 1.64 0.005 0.24
Number of older brothers 0.015 0.92 0.015 1.01 -0.015 -0.67 0.043
2.10
Number of older sisters 0.014 0.42 -0.044
-2.71
0.019 1.13 0.052
2.55
Distance from household
Distance to poblacion (kilometers) 0.007 0.15 0.017
1.99
-0.005 -0.42 0.010 0.88
Travel time to nearest hospital in 1984 (minutes) 0.000 0.21 -0.001 -0.82 0.000 0.78 0.001 1.01
Distance to nearest sugar mill (kilometers) 0.003 0.62 -0.006 -1.46 -0.003 -0.63 -0.011
-1.97
Actual probability 0.13 0.14 0.20 0.28
Predicted probability 0.14 0.19 0.25 0.39
Note: z-statistics in bold are significant at 10 percent or better.
a
Dummy variable taking values 0 or 1.
39
and daughters living on the same homestead, Filipino farm family structure can be
described as residentially nuclear, but functionally extended. Life-cycle factors (age and
age-squared) have significant effects on both sons’ and daughters’ decisions to form
separate households.
Family background characteristics affect sons and daughters in different ways. A
daughter whose father is more educated is less likely to live in the same village, while a
better-educated mother weakly increases the probability that the daughter lives in the
same village. This difference may arise from complementarity of parent-child roles: if
gender-casting is important (say, if fathers work with sons and mothers with daughters),
or if mothers’ productivity improves from having better-educated daughters nearby, the
incentive for daughters to migrate may be lower if mothers complete more schooling.
The value of non-land assets owned by parents increases the probability that sons live in
the same village, perhaps because non-land assets increase opportunities for self-
employment. The number of older brothers reduces the probability that a son will live in
the same village as the parents, probably because land will have been partitioned to older
sons first, leaving less to the younger son. Females with more older sisters are also less
likely to live in the same village. While distance to the sugar mill increases the
probability that daughters live in the same village, it does not affect sons’ decisions.
Indeed, none of the distance variables affect any of the sons’ locational decisions.
None of the explanatory variables significantly affect sons’ decisions to move to
other rural areas. In contrast, a number of factors are important in daughters’ decisions to
relocate to other rural areas. Daughters are less likely to move to other rural areas if their
mothers are better-educated. Daughters with more older sisters are also less likely to
move to other rural areas. This is consistent with mother-daughter skill complementarity
and may also suggest complementarity with sisters’ skills. Interestingly, living farther
away from the town increases girls’ probability of moving to other rural areas.
Finally, we examine the determinants of the decision to migrate to a poblacion or
an urban area. Life-cycle effects are strong for females, with marginal effects that are
thrice those for males. Surprisingly, schooling is important only in males’ decisions to
40
migrate to urban areas. Given that women already have higher levels of schooling than
males, additional schooling probably does not increase the female propensity to migrate
to urban areas. Female migrants to urban areas are employed in a variety of occupations,
not all of which require higher levels of schooling. Family composition affects women’s
decisions to move to urban areas more than men’s. Having more older brothers and
sisters increases the probability that a woman migrates to a poblacion or urban area. It is
possible that older brothers and sisters may have moved earlier to urban areas or entered
the labor force earlier, providing support networks or financial resources for a younger
sister’s move. Distance to the the poblacion or travel time to the hospital does not affect
the probability of migration, but greater distance from the sugar mill reduces daughters’
migration probabilities.
4. Conclusions
This preliminary exploration into the migration decisions of young Filipino adults
has shown that as destinations, poblaciones and urban areas are very similar. Migrants to
poblaciones and urban areas have very similar reasons for moving. If poblaciones and
peri-urban areas can offer comparable services to migrants from rural areas, they may be
able to relieve congestion in major metropolitan centers like Cagayan de Oro and
Metropolitan Manila. However, the occupational profile of migrants to both areas
indicates that females seem to fare better than males—perhaps because female migrants
to urban areas are often better-educated than male migrants. The implications of gender
differences in initial endowments and in migration streams need further investigation.
This paper has also highlighted the important role of social networks for migrants,
particularly for the first move. While most first-time migrants move alone, they are most
often financed by their parents and live with relatives in their new community. Later on,
migrants increasingly self-finance their moves, and live with their families of procreation.
Familial networks are thus very important for helping a migrant get settled into a new
community.
41
Lastly, we have found that rural areas, poblaciones, and urban areas
systematically attract different types of migrants. Poblaciones and urban areas attract
better-schooled individuals, partly because young people move to those areas to further
their education, or because better-educated individuals move to these areas to find better
jobs. Migrants to rural areas, on the other hand, move primarily to take up farming or to
get married. Thus, it is no surprise the rural migrants, as well as those who opt to stay in
rural areas, are less educated than migrants to urban areas and peri-urban areas.
Does outmigration from rural areas thus constitute a “brain drain” that needs to be
stopped? Not necessarily. If migrants are able to find better jobs in urban and peri–urban
areas or poblaciones, and send remittances to their origin families, then migration is
welfare- improving for those who have stayed behind. However, the occupational profile
of migrants to these less-rural areas is quite diverse. A large proportion of male migrants
to more urbanized areas end up in manual labor/transportation work or crafts and trades,
which are not high-earning occupations. Female migrants to poblaciones, peri–urban,
and urban areas may fare better. A large proportion of female migrants to poblaciones
end up working in sales occupations, while, compared to male migrants, a greater
proportion of female migrants to urban areas have professional and managerial jobs.
Clearly, many migrants are unable to fulfill their hopes and dreams. But this paper does
not attempt to answer whether migration is welfare-improving for the migrant or the
family he (or more likely she) left behind. In further work, we will examine this question
and look at whether migration is a strategy that families use to escape poverty, bearing in
mind that migration and education are both individual and family decisions.
42
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FCND DISCUSSION PAPERS
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194 Livelihoods, Growth, and Links to Market Towns in 15 Ethiopian Villages, Stefan Dercon and John
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193 Livelihood Diversification and Rural-Urban Linkages in Vietnam’s Red River Delta, Hoang Xuan Thanh,
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188 Coping with the “Coffee Crisis” in Central America: The Role of the Nicaraguan Red de Protección Social
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178 Community-Driven Development and Scaling Up of Microfinance Services: Case Studies from Nepal and
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177 Community Empowerment and Scaling Up in Urban Areas: The Evolution of PUSH/PROSPECT in Zambia,
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176 Why Is Child Malnutrition Lower in Urban than Rural Areas? Evidence from 36 Developing Countries, Lisa
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175 Consumption Smoothing and Vulnerability in the Zone Lacustre, Mali, Sarah Harrower and John Hoddinott,
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174
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171 Living Life: Overlooked Aspects of Urban Employment, James Garrett, January 2004
170 From Research to Program Design: Use of Formative Research in Haiti to Develop a Behavior Change
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169 Nonmarket Networks Among Migrants: Evidence from Metropolitan Bangkok, Thailand, Futoshi Yamauchi
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168 Long-Term Consequences of Early Childhood Malnutrition, Harold Alderman, John Hoddinott, and Bill
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164 Impacts of Agricultural Research on Poverty: Findings of an Integrated Economic and Social Analysis, Ruth
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163 An Integrated Economic and Social Analysis to Assess the Impact of Vegetable and Fishpond Technologies
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157 HIV/AIDS, Food Security, and Rural Livelihoods: Understanding and Responding, Michael Loevinsohn and
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156 Public Policy, Food Markets, and Household Coping Strategies in Bangladesh: Lessons from the 1998
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155 Consumption Insurance and Vulnerability to Poverty: A Synthesis of the Evidence from Bangladesh,
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154 Cultivating Nutrition: A Survey of Viewpoints on Integrating Agriculture and Nutrition, Carol E. Levin,
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153 Maquiladoras and Market Mamas: Women’s Work and Childcare in Guatemala City and Accra, Agnes R.
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152 Income Diversification in Zimbabwe: Welfare Implications From Urban and Rural Areas, Lire Ersado,
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Childcare and Work: Joint Decisions Among Women in Poor Neighborhoods of Guatemala City, Kelly
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99 Cash Transfer Programs with Income Multipliers: PROCAMPO in Mexico, Elisabeth Sadoulet, Alain de
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97 Socioeconomic Differentials in Child Stunting Are Consistently Larger in Urban Than in Rural Areas,
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91 Comparing Village Characteristics Derived From Rapid Appraisals and Household Surveys: A Tale From
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90 Empirical Measurements of Households’ Access to Credit and Credit Constraints in Developing Countries:
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89 The Role of the State in Promoting Microfinance Institutions, Cécile Lapenu, June 2000
88 The Determinants of Employment Status in Egypt, Ragui Assaad, Fatma El-Hamidi, and Akhter U. Ahmed,
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87 Changes in Intrahousehold Labor Allocation to Environmental Goods Collection: A Case Study from Rural
Nepal, Priscilla A. Cooke, May 2000
86 Women’s Assets and Intrahousehold Allocation in Rural Bangladesh: Testing Measures of Bargaining
Power, Agnes R. Quisumbing and Bénédicte de la Brière, April 2000
85 Intrahousehold Impact of Transfer of Modern Agricultural Technology: A Gender Perspective, Ruchira
Tabassum Naved, April 2000
84 Intrahousehold Allocation and Gender Relations: New Empirical Evidence from Four Developing Countries,
Agnes R. Quisumbing and John A. Maluccio, April 2000
83 Quality or Quantity? The Supply-Side Determinants of Primary Schooling in Rural Mozambique, Sudhanshu
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82 Pathways of Rural Development in Madagascar: An Empirical Investigation of the Critical Triangle of
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Bart Minten, Eliane Ralison, Désiré Randrianaivo, and Claude Randrianarisoa, March 2000
81
The Constraints to Good Child Care Practices in Accra: Implications for Programs, Margaret Armar-
Klemesu, Marie T. Ruel, Daniel G. Maxwell, Carol E. Levin, and Saul S. Morris, February 2000
80 Nontraditional Crops and Land Accumulation Among Guatemalan Smallholders: Is the Impact Sustainable?
Calogero Carletto, February 2000
79 Adult Health in the Time of Drought, John Hoddinott and Bill Kinsey, January 2000
78 Determinants of Poverty in Mozambique: 1996-97, Gaurav Datt, Kenneth Simler, Sanjukta Mukherjee, and
Gabriel Dava, January 2000
FCND DISCUSSION PAPERS
77 The Political Economy of Food Subsidy Reform in Egypt, Tammi Gutner, November 1999.
76 Raising Primary School Enrolment in Developing Countries: The Relative Importance of Supply and
Demand, Sudhanshu Handa, November 1999
75 Determinants of Poverty in Egypt, 1997, Gaurav Datt and Dean Jolliffe, October 1999
74 Can Cash Transfer Programs Work in Resource-Poor Countries? The Experience in Mozambique, Jan W.
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73 Social Roles, Human Capital, and the Intrahousehold Division of Labor: Evidence from Pakistan, Marcel
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72 Validity of Rapid Estimates of Household Wealth and Income for Health Surveys in Rural Africa, Saul S.
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71 Social Capital and Income Generation in South Africa, 1993-98, John Maluccio, Lawrence Haddad, and
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70 Child Health Care Demand in a Developing Country: Unconditional Estimates from the Philippines, Kelly
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69 Supply Response of West African Agricultural Households: Implications of Intrahousehold Preference
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68 Early Childhood Nutrition and Academic Achievement: A Longitudinal Analysis, Paul Glewwe, Hanan
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67 Determinants of Household Access to and Participation in Formal and Informal Credit Markets in Malawi,
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66 Working Women in an Urban Setting: Traders, Vendors, and Food Security in Accra, Carol E. Levin, Daniel
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65 Are Determinants of Rural and Urban Food Security and Nutritional Status Different? Some Insights from
Mozambique, James L. Garrett and Marie T. Ruel, April 1999
64 Some Urban Facts of Life: Implications for Research and Policy, Marie T. Ruel, Lawrence Haddad, and
James L. Garrett, April 1999
63 Are Urban Poverty and Undernutrition Growing? Some Newly Assembled Evidence, Lawrence Haddad,
Marie T. Ruel, and James L. Garrett, April 1999
62 Good Care Practices Can Mitigate the Negative Effects of Poverty and Low Maternal Schooling on
Children's Nutritional Status: Evidence from Accra, Marie T. Ruel, Carol E. Levin, Margaret Armar-
Klemesu, Daniel Maxwell, and Saul S. Morris, April 1999
61 Does Geographic Targeting of Nutrition Interventions Make Sense in Cities? Evidence from Abidjan and
Accra, Saul S. Morris, Carol Levin, Margaret Armar-Klemesu, Daniel Maxwell, and Marie T. Ruel, April
1999
60 Explaining Child Malnutrition in Developing Countries: A Cross-Country Analysis, Lisa C. Smith and
Lawrence Haddad, April 1999
59 Placement and Outreach of Group-Based Credit Organizations: The Cases of ASA, BRAC, and PROSHIKA
in Bangladesh, Manohar Sharma and Manfred Zeller, March 1999
58 Women's Land Rights in the Transition to Individualized Ownership: Implications for the Management of
Tree Resources in Western Ghana, Agnes Quisumbing, Ellen Payongayong, J. B. Aidoo, and Keijiro Otsuka,
February 1999
57 The Structure of Wages During the Economic Transition in Romania, Emmanuel Skoufias, February 1999
56 How Does the Human Rights Perspective Help to Shape the Food and Nutrition Policy Research Agenda?,
Lawrence Haddad and Arne Oshaug, February 1999
55 Efficiency in Intrahousehold Resource Allocation, Marcel Fafchamps, December 1998
FCND DISCUSSION PAPERS
54 Endogeneity of Schooling in the Wage Function: Evidence from the Rural Philippines, John Maluccio,
November 1998
53 Agricultural Wages and Food Prices in Egypt: A Governorate-Level Analysis for 1976-1993, Gaurav Datt
and Jennifer Olmsted, November 1998
52 Testing Nash Bargaining Household Models With Time-Series Data, John Hoddinott and Christopher Adam,
November 1998
51 Urban Challenges to Food and Nutrition Security: A Review of Food Security, Health, and Caregiving in the
Cities, Marie T. Ruel, James L. Garrett, Saul S. Morris, Daniel Maxwell, Arne Oshaug, Patrice Engle,
Purnima Menon, Alison Slack, and Lawrence Haddad, October 1998
50 Computational Tools for Poverty Measurement and Analysis, Gaurav Datt, October 1998
49 A Profile of Poverty in Egypt: 1997, Gaurav Datt, Dean Jolliffe, and Manohar Sharma, August 1998.
48 Human Capital, Productivity, and Labor Allocation in Rural Pakistan, Marcel Fafchamps and Agnes R.
Quisumbing, July 1998
47 Poverty in India and Indian States: An Update, Gaurav Datt, July 1998
46 Impact of Access to Credit on Income and Food Security in Malawi, Aliou Diagne, July 1998
45 Does Urban Agriculture Help Prevent Malnutrition? Evidence from Kampala, Daniel Maxwell, Carol Levin,
and Joanne Csete, June 1998
44 Can FAO's Measure of Chronic Undernourishment Be Strengthened?, Lisa C. Smith, with a Response by
Logan Naiken, May 1998
43 How Reliable Are Group Informant Ratings? A Test of Food Security Rating in Honduras, Gilles Bergeron,
Saul Sutkover Morris, and Juan Manuel Medina Banegas, April 1998
42 Farm Productivity and Rural Poverty in India, Gaurav Datt and Martin Ravallion, March 1998
41 The Political Economy of Urban Food Security in Sub-Saharan Africa, Dan Maxwell, February 1998
40 Can Qualitative and Quantitative Methods Serve Complementary Purposes for Policy Research? Evidence
from Accra, Dan Maxwell, January 1998
39 Whose Education Matters in the Determination of Household Income: Evidence from a Developing Country,
Dean Jolliffe, November 1997
38 Systematic Client Consultation in Development: The Case of Food Policy Research in Ghana, India, Kenya,
and Mali, Suresh Chandra Babu, Lynn R. Brown, and Bonnie McClafferty, November 1997
37 Why Do Migrants Remit? An Analysis for the Dominican Sierra, Bénédicte de la Brière, Alain de Janvry,
Sylvie Lambert, and Elisabeth Sadoulet, October 1997
36 The GAPVU Cash Transfer Program in Mozambique: An assessment, Gaurav Datt, Ellen Payongayong,
James L. Garrett, and Marie Ruel, October 1997
35
Market Access by Smallholder Farmers in Malawi: Implications for Technology Adoption, Agricultural
Productivity, and Crop Income, Manfred Zeller, Aliou Diagne, and Charles Mataya, September 1997
34 The Impact of Changes in Common Property Resource Management on Intrahousehold Allocation, Philip
Maggs and John Hoddinott, September 1997
33 Human Milk—An Invisible Food Resource, Anne Hatløy and Arne Oshaug, August 1997
32 The Determinants of Demand for Micronutrients: An Analysis of Rural Households in Bangladesh, Howarth
E. Bouis and Mary Jane G. Novenario-Reese, August 1997
31 Is There an Intrahousehold 'Flypaper Effect'? Evidence from a School Feeding Program, Hanan Jacoby,
August 1997
30 Plant Breeding: A Long-Term Strategy for the Control of Zinc Deficiency in Vulnerable Populations, Marie
T. Ruel and Howarth E. Bouis, July 1997
FCND DISCUSSION PAPERS
29 Gender, Property Rights, and Natural Resources, Ruth Meinzen-Dick, Lynn R. Brown, Hilary Sims
Feldstein, and Agnes R. Quisumbing, May 1997
28 Developing a Research and Action Agenda for Examining Urbanization and Caregiving: Examples from
Southern and Eastern Africa, Patrice L. Engle, Purnima Menon, James L. Garrett, and Alison Slack, April
1997
27 "Bargaining" and Gender Relations: Within and Beyond the Household, Bina Agarwal, March 1997
26 Why Have Some Indian States Performed Better Than Others at Reducing Rural Poverty?, Gaurav Datt and
Martin Ravallion, March 1997
25 Water, Health, and Income: A Review, John Hoddinott, February 1997
24 Child Care Practices Associated with Positive and Negative Nutritional Outcomes for Children in
Bangladesh: A Descriptive Analysis, Shubh K. Kumar Range, Ruchira Naved, and Saroj Bhattarai, February
1997
23 Better Rich, or Better There? Grandparent Wealth, Coresidence, and Intrahousehold Allocation, Agnes R.
Quisumbing, January 1997
22 Alternative Approaches to Locating the Food Insecure: Qualitative and Quantitative Evidence from South
India, Kimberly Chung, Lawrence Haddad, Jayashree Ramakrishna, and Frank Riely, January 1997
21 Livestock Income, Male/Female Animals, and Inequality in Rural Pakistan, Richard H. Adams, Jr.,
November 1996
20 Macroeconomic Crises and Poverty Monitoring: A Case Study for India, Gaurav Datt and Martin Ravallion,
November 1996
19 Food Security and Nutrition Implications of Intrahousehold Bias: A Review of Literature, Lawrence Haddad,
Christine Peña, Chizuru Nishida, Agnes Quisumbing, and Alison Slack, September 1996
18 Care and Nutrition: Concepts and Measurement, Patrice L. Engle, Purnima Menon, and Lawrence Haddad,
August 1996
17 Remittances, Income Distribution, and Rural Asset Accumulation, Richard H. Adams, Jr., August 1996
16 How Can Safety Nets Do More with Less? General Issues with Some Evidence from Southern Africa,
Lawrence Haddad and Manfred Zeller, July 1996
15 Repayment Performance in Group-Based credit Programs in Bangladesh: An Empirical Analysis, Manohar
Sharma and Manfred Zeller, July 1996
14 Demand for High-Value Secondary Crops in Developing Countries: The Case of Potatoes in Bangladesh and
Pakistan, Howarth E. Bouis and Gregory Scott, May 1996
13 Determinants of Repayment Performance in Credit Groups: The Role of Program Design, Intra-Group Risk
Pooling, and Social Cohesion in Madagascar, Manfred Zeller, May 1996
12 Child Development: Vulnerability and Resilience, Patrice L. Engle, Sarah Castle, and Purnima Menon, April
1996
11 Rural Financial Policies for Food Security of the Poor: Methodologies for a Multicountry Research Project,
Manfred Zeller, Akhter Ahmed, Suresh Babu, Sumiter Broca, Aliou Diagne, and Manohar Sharma, April
1996
10 Women's Economic Advancement Through Agricultural Change: A Review of Donor Experience, Christine
Peña, Patrick Webb, and Lawrence Haddad, February 1996
09 Gender and Poverty: New Evidence from 10 Developing Countries, Agnes R. Quisumbing, Lawrence
Haddad, and Christine Peña, December 1995
08 Measuring Food Insecurity: The Frequency and Severity of "Coping Strategies," Daniel G. Maxwell,
December 1995
07 A Food Demand System Based on Demand for Characteristics: If There Is "Curvature" in the Slutsky Matrix,
What Do the Curves Look Like and Why?, Howarth E. Bouis, December 1995
FCND DISCUSSION PAPERS
06 Gender Differentials in Farm Productivity: Implications for Household Efficiency and Agricultural Policy,
Harold Alderman, John Hoddinott, Lawrence Haddad, and Christopher Udry, August 1995
05 Gender Differences in Agricultural Productivity: A Survey of Empirical Evidence, Agnes R. Quisumbing,
July 1995
04 Market Development and Food Demand in Rural China, Jikun Huang and Scott Rozelle, June 1995
03 The Extended Family and Intrahousehold Allocation: Inheritance and Investments in Children in the Rural
Philippines, Agnes R. Quisumbing, March 1995
02 Determinants of Credit Rationing: A Study of Informal Lenders and Formal Credit Groups in Madagascar,
Manfred Zeller, October 1994
01 Agricultural Technology and Food Policy to Combat Iron Deficiency in Developing Countries, Howarth E.
Bouis, August 1994
