CRRC 23-Nov-05 1 The effects of The effects of men’s labor migration men’s labor migration on rural women’s on rural women’s socioeconomic conditions, socioeconomic conditions, social networks, and social networks, and reproductive behavior reproductive behavior in Armenia in Armenia (preliminary results of a (preliminary results of a sociological study) sociological study)
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CRRC 23-Nov-051 The effects of men’s labor migration on rural women’s socioeconomic conditions, social networks, and reproductive behavior in Armenia (preliminary.
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CRRC 23-Nov-05 1
The effects of The effects of men’s labor migration men’s labor migration
on rural women’s on rural women’s socioeconomic conditions, socioeconomic conditions,
social networks, and social networks, and reproductive behavior reproductive behavior
in Armeniain Armenia (preliminary results of a sociological study)(preliminary results of a sociological study)
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Prepared by:
Victor Agadjanian, PhDVictor Agadjanian, PhD
Cecilia Menjívar, PhDCecilia Menjívar, PhDArizona State University, USAArizona State University, USA
Gohar Shahnazaryan, PhDGohar Shahnazaryan, PhD
Sociology Master’s studentsSociology Master’s students
Yerevan State UniversityYerevan State University
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Conceptual framework and research questions
How does husband’s migration affect…• Household’s material conditions?• Women’s economic activities?• Marriage and family dynamics?• Women’s social ties?• Women’s health, reproductive behavior and
plans?• Women’s gender roles and attitudes?• Psychological issues and religion?
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The study design
• Funded by a grant from Arizona State University Institute for Social Science Research and the School of Social and Family Dynamics
• Conducted as part of a Master’s level “Sociological Practicum” course
• Students involved in all stages of the project (including this presentation!)
• It is a pilot study which (hopefully) will lead to a larger study
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The Study Design (cont.)The study was conducted in rural areas of two marzes—Tavush
and AraratTavush—a poorer, more economically depressed marz, with a
high level of out-migration.Ararat—a more affluent and economically dynamic marz, closer
to Yerevan, less out-migration
Data collection:• Carried out in late September-October 2005, i.e. just before
most seasonal migrants return home• A probability survey of 1040 married women in 52 villages• A community (village) survey• Qualitative in-depth interviews with 27 women whose
husbands are current migrants or were in migration in 2005• All participants received a symbolic gift (coffee + chocolate)
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AraratArarat
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TavushTavush
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AraratArarat
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TavushTavush
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The Survey: Sampling• 26 villages in each marz (52 in total) were selected with the probability proportional to estimated population size• Within each village, the goal was to interview 20 married women aged 18-45: 10 whose husbands are current/recent migrants and 10 whose husbands are not current/recent migrants• In each village, 10 interviewers, 2 interviews per interviewer• In each village, 10 first addresses were selected randomly from the village household lists• The remaining 10 (or more if prior non-response) addresses were selected using a random walking algorithm.
Important: the survey was not meant to produce a representative migration profile of the rural population but to compare women whose husbands are migrants and those whose husbands are not migrants.
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Sampling (cont.)
Locating second respondent:•If the first respondent is married to a non-migrant, the second should be one married to a migrant (and vice versa)
•If no respondent of desired migration status is found at fifth house, the residents are asked where the nearest woman with a migrant husband lives. That woman is interviewed.
•If in the fifth visited residence no one knows where a woman with desired characteristics lives, the interviewer goes to a next residence following the same algorithm to interview a married woman regardless of her migration status.
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Sampling (cont.)
Challenges:Challenges:• Availability of household rosters: if not available, we Availability of household rosters: if not available, we
selected starting points in different parts of the villageselected starting points in different parts of the village• Availability of people (many are busy in the fields, Availability of people (many are busy in the fields,
working, attending events, etc.)working, attending events, etc.)• Availability of “migrants,” especially in Tavush:Availability of “migrants,” especially in Tavush:
– Migration as a family or by unmarried menMigration as a family or by unmarried men– Խոպան Խոպան by married men relatively uncommonby married men relatively uncommon– ““Migrant” households are spatially clusteredMigrant” households are spatially clustered
Resulting sample:Resulting sample:62% Non-migrants; 38% Migrants62% Non-migrants; 38% MigrantsLower percentage of migrants in Tavush than in AraratLower percentage of migrants in Tavush than in AraratWhy? A different pattern of migrationWhy? A different pattern of migration
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Survey instrument
Five parts:
A. Respondent’s demographic characteristics
B. Marriage and husband’s characteristics (including husband’s migration)
C. Health and reproduction
D. Social ties and community
E. Gender attitudes
F. Household characteristics and time-use
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Fieldwork: Challenges and solutions• Timing of fieldwork: Weekends—to maximize availability
of both respondents and interviewers, but… – In rural areas weekends are no less busy that weekdays,
especially during the harvest time Whenever possible, the selected households were revisited until the respondent is available
– Elections in some villages and related village politics We emphasized that our study had nothing to do with politics
– Unavailability of community leaders on weekends We notified them in advance about our study. In a few cases, no advance contact could be established and no residential lists could be obtained.
• Interviewer-Respondent Age difference: no apparent effect
• Interviewer-Respondent cultural background differences: no apparent effects
• Some respondents thought we represent the health services
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Fieldwork: Challenges and solutions (cont.)
• Some thought we represented social assistance agencies and expected assistance (or saw threat to assistance they were already receiving) underreporting of wealth, income?
• Some women suspected that we represented religious organizations: We emphasized that we don’t
• Yet, overall the refusal rate was very low• Questionnaire content:
– Some items were “culturally” difficult:• Abstract questions• Notions of “work” and “working”• Questions dealing with social interactions and ties• Question on sexual violence
– Recall problems: age, year/month of events, number of repeated events
– Underreporting: income, help from/to others, cooperation
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Community survey
• Collected by supervisors from գյուղապետ or secretary
• General demographic characteristics
• Economic characteristics
• Living conditions and services
• Assessment of labor out-migration
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Survey data processing
CSPro software– Designed by the US Census Bureau and Micro
International– Widely used for survey data processing (including in
Armenia)– Convenient interface, supports Armenian fonts– Elaborate system of filters and checks– Available free of charge on the Internet – Regularly updated– On-line technical support is free and efficient
Double-entry to ensure quality
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Qualitative (in-depth) interviews
• 27 women married to migrants in both marzes (two villages in Tavush and one in Ararat)
• The interview guide followed the themes and topics of the survey but explored them in greater depth
• Most interviews were tape-recorded and transcribed verbatim
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Qualitative (in-depth) interviews (cont.)
Interview guide – to complement and expand on the survey
Main themes: Marriage Children Work Religion Social networks
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Qualitative (in-depth) interviews: Challenges and solutions
• Content issue• Women tend to answer “yes” and “no”• Women want to please the interviewers• Women were afraid of tape-recording of
interviews• Second visit • Cultural differences• Building rapport with respondents
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Data analysis: survey• Descriptive and bivariate explorations
“Migrants” vs. “Non-Migrants” comparison“Migrants”: Definitions of migrants:
1. Husband was in migration 3 months or more, or2. Husband is current migrant or return less than a month ago
Ararat vs. Tavush comparison Separate analyses for “migrants” only
• Multivariate analyses—to establish net effect of husband’s migration on outcomes of interest: OLS regression, Poisson regression, and logistic regression
• Analyses are done using SPSS and SAS
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Data analysis: survey (cont.)
• Demographics
• Economic conditions
• Health
• Reproduction
• Social ties
• Migration attitudes and prospects
• Decision-making and gender attitudes
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Migrants vs. non-Migrants: DemographicsMigrant Non-
Migrant
Woman’s age (mean) 36.6 33.0
Age difference (husband-wife) 4.4 4.6
Age at first marriage (mean) 19.7 20.0
Officially registered marriage (%) 93.1 85.0
Woman’s educational level (%)
Incomplete secondary 5.3 7.3
Complete secondary 42.2 47.4
Secondary special 44.2 35.6
Incomplete or complete higher 8.3 9.8
Educational differences husb-wife (%)
Wife more educated 26.4 30.4
Equally educated 51.4 45.0
Husband more educated 22.1 24.6
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Migrants vs. non-Migrants: DemographicsEducational level, by Marz
0% 20% 40% 60% 80% 100%
Migrant (Tavush)
Non-migrant (Tavush)
Migrant (Ararat)
Non-migrant (Ararat)
Migrant (all)
Non-migrant (all)
Incomp. sec. Complete sec. Sec. spec. Incomp. or comp. higher
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Income and economic activitiesMigrant Non-
migrantHH total income (D/month) (mean) 78200 55200
In Ararat 89500 66200In Tavush 58800 46200
HH income per head (mean) 14900 10200In Ararat 17200 12600In Tavush 11200 8230
Woman works for income (%) 14.7 16.6Woman’s monthly earnings (mean) 28500 24000
(n=152)Took loan from a bank(%) 26.1 22.4
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HH material characteristicsMigrant Non-
migrant
Rooms used for sleeping (mean) 2.4 2.3
Residents per room (mean) 2.7 2.7
Household owns a car (%) 28.5 41.4
HH owns a refrigerator (%) 74.4 74.9
HH owns a color TV (%) 87.4 78.1
HH owns a video or DVD (%) 46.8 33.7
HH owns gas or elect. stove (%) 76.2 69.6
Woman owns a cell phone (%) 18.7 9.6
Woman ate meat in past wk (%) 50.0 56.3
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Agricultural possessionsMigrant Non-
migrant
Household owns agr. land (%) 90.8 87.8
Size of own land, in ha (mean) .54 .74
Household rents agr. land (%) 10.4 13.9
HH sells/exchanges produce (%) 36.9 39.0
Household owns cows (%) 29.9 38.4
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Perceptions of economic conditionsMigrant Non-
Migrant
Perceived HH wealth relative to
most HH in village (%)
Most other are wealthier 23.2 21.4
Most other are poorer 15.7 17.0
Most are about the same 61.2 61.6
HH econ. conditions will improve
in a year (%) 45.0 37.5
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Migrants vs. Non-migrants: HealthMigrant Non-
MigrantAssessment of own health
Good 16.0 23.2Average 58.9 58.4Bad 25.1 18.4
Has a serious health problem ordisability (%) 47.8 39.6
Health worsened in past yr (%) 41.7 35.4Was sick in bed at least once in
past year (%) 54.3 43.4Had to see doctor in past yr (%) 35.1 33.0Youngest child was sick in past 44.6 45.7
3 months
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Migrants vs. non-Migrants: Reproduction
Migrant Non-Migrant
Number of children ever born (mean) 2.7 2.3Explained by differences in age
Wants to have more children (%) 14.5 25.9Explained by differences in age and number of children
Husband wants more children (%) 32.0 40.3Largely explained by differences in age and number of children
Currently uses family planning (%) 18.4 47.8
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Migrants vs. non-Migrants: Social Capital
Migrant Non-MigrantKnows half or more villagers
by name (%) 50.0 53.7Has own relatives in village (%) 51.3 57.0Has in-laws in village (%) 83.8 87.0Visited in-laws in past week (%) 60.1 56.8Visited non-relatives in past wk (%)
Never 22.5 30.81-2 times 34.1 30.13 or more times 43.4 38.4
Attended one or more weddingsin village in past year (%) 66.4 72.3
Attended one or more funeralsin village in past year (%) 66.7 58.2
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Migrants vs. non-Migrants: Social Capital
Migrant Non-Migrant
Socialized w/others last Wed. (%) 79.6 74.0Socialized w/others last Sun. (%) 78.2 75.9
Cooperated with other women in past 3 months (%):In agricultural work 17.7 16.2In buying and selling 8.1 6.7Making preserves for winter 29.0 26.7In any type of cooperation 41.2 36.5
Participated in community projects (%) 11.1 10.7
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Migrants vs. non-Migrants: Social Capital
Migrant Non-Migrant
Got money from relatives as …
Interest-free loan 8.6 10.4
Loan with interest 4.0 4.4
Gift 13.4 11.7
Got money from in-laws as …
Interest-free loan 11.1 13.4
Loan with interest 4.1 3.6
Gift 8.1 11.0
Got money from others as …
Interest-free loan 10.4 15.4
Loan with interest 9.6 7.5
Gift 2.5 3.7
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Migration intentions and expectationsMigrant Non-Migrant
Would like to move from village (%) 59.5 53.5
Would like to move abroad (%)7.6 5.6
Husband will likely to work away 54.8 18.0
She is likely to go with husband 30.0 53.1(% of those whose husbandsare likely to go)
Watched Russian-language TVin past week 66.7 58.4
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Decision-making and gender attitudes
Migrant Non-migrant
Respondent is head of HH 11.8 3.3
Who made the decision on a major purchase*:
Mainly respondent 34.4 12.9
Mainly husband 33.0 44.7
Respondent and husband 17.6 24.6
Others 15.0 17.8
* Only those who reported having made a major purchase recently
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Insights From Qualitative Interviews Marriage and Family