Individual versus Household Migration Decision Rules: Gender and Marital Status Differences in Intentions to Migrate in South Africa

Individual versus HouseholdMigration Decision Rules: Genderand Marital Status Differences

in Intentions to Migratein South Africa

Bina Gubhaju and Gordon F. De Jong*

ABSTRACT

This research tests the thesis that the neoclassical microeconomic and thenew household economic theoretical assumptions on migration decision-making rules are segmented by gender, marital status, and time frame ofintention to migrate. Comparative tests of both theories within the samestudy design are relatively rare. Utilizing data from the Causes of Migrationin South Africa national migration survey, we analyse how individually held‘‘own-future’’ versus alternative ‘‘household well-being’’ migration decisionrules effect the intentions to migrate of male and female adults in SouthAfrica. Results from the gender and marital status specific logistic regres-sions models show consistent support for the different gender-marital statusdecision rule thesis. Specifically, the ‘‘maximizing one’s own future’’ neo-classical microeconomic theory proposition is more applicable for nevermarried men and women, the ‘‘maximizing household income’’ propositionfor married men with short-term migration intentions, and the ‘‘reducehousehold risk’’ proposition for longer time horizon migration intentions ofmarried men and women. Results provide new evidence on the way house-hold strategies and individual goals jointly affect intentions to move or stay.

* Bina Gubhaju, Asia Research Institute, National University of Singapore and Gordon F.

De Jong, Department of Sociology and the Population Research Institute, Pennsylvania

State University. We acknowledge the Human Sciences Research Council, Government of

South Africa, and Dr. Pieter Kok for providing access to the data used in this study. Partial

support for the analysis was provided by a centre support grant to the Pennsylvania State

University Population Research Institute from the National Institute of Child Health and

Human Development (grant No. 1R24HD41025). An earlier version of this paper was

presented at the 2005 Population Association of America.

� 2009 The AuthorsPublished by Blackwell Publishing Ltd., Journal Compilation � 2009 IOM9600 Garsington Road, Oxford OX4 2DQ, UK, International Migration Vol. 47 (1) 2009and 350 Main Street, Malden, MA 02148, USA. ISSN 0020-7985

doi:10.1111/j.1468-2435.2008.00496.x

INTRODUCTION

One of the frontiers in micro-level migration theory is to move beyondthe usual practice of imputing potential migrants’ motives to move or tostay, and rather to directly investigate the migration decision-making ofmen and women. The neoclassical microeconomic and the new house-hold economic theories of migration contrast with respect to their per-spectives on whether an individual’s decision to migrate is based onwhat is ‘‘best for one’s own future’’ or whether the decision is based onreturns for the household as a whole. The neoclassical microeconomictheory of migration decision-making posits that migration is an individ-ual choice whereby the rational actor is motivated to move to maximizeone’s own personal gains, whether in terms of monetary or human capi-tal (Todaro, 1976; Massey et al., 1998). In contrast, the new householdeconomic theory places migration decisions within the context of thehousehold and contends that the family is at the centre of migrationdecision-making. Proponents of this theory argue that migration deci-sions are rarely made by individual actors but rather by families andhouseholds (Stark and Bloom, 1985; Fischer et al., 1997). Within thisframework, an individual’s decision to migrate is not based on maximiz-ing one’s expected income but rather for the benefit of the householdand other family members. The focus thus shifts from individual inde-pendence to mutual interdependence, and it has been argued that thisperspective is particularly salient for developing countries (Stark andBloom, 1985; Lauby and Stark, 1988; Root and De Jong, 1991; Fischeret al., 1997; Massey et al., 1998).

While each one of these perspectives have established their own nicheswithin the set of available theories that attempt to explain migrationbehaviour, the question as to which is the more valid explanation formigration behaviour remains unresolved. Both theories assume that allindividuals will behave to maximize desired outcomes, but do developingcountry residents decide to move or to stay based on an individualchoice to enhance own future or for the enhancement of the well-beingof the household (Kok et al., 2003)? What needs further direct empiricalevidence is how these decisions may be different for gender and maritalstatus subgroups of the population. Are women more likely to base theirdecisions to move or to stay on household needs rather than on individ-ual attainment desires as compared to men? Or do decisions differ moreby marital status whereby married individuals concerned with householdneeds are more likely to stay and unmarried individuals concerned withtheir own future are more likely to migrate? Another important question

32 Gubhaju and De Jong

� 2009 The Authors

Journal Compilation � 2009 IOM

when looking at whether migration intentions are based on neoclassicalor new household economic arguments is the time horizon on whichmigration intentions are based. Are different migration decision perspec-tives invoked for intentions to move or to stay in the more immediateversus in the more distant future?

The main objective of this paper, therefore, is to address the above ques-tions in the context of South Africa. We use data from the Causes ofMigration in South Africa national survey to test how these two migra-tion decision-making frameworks differ in predicting both short-termand longer-term intentions to migrate for never married and marriedmen and women. We focus on South Africa because of the availabilityof unique national probability sample data on how individuals approachmigration decision-making. Past research has used several methodologiesfor testing neoclassical and new economics theories of migration. First,primarily one-time period survey data on individual human capital,employment, wages, and demographic attributes have been used to testneoclassical theory propositions, while tests of the new economics ofmigration hypothesis have focused on household size, income, social net-work ties, remittance flows, and community labour market characteris-tics as predictors of migration behaviour (cf., Massey et al., 1998, pp.69–83). However, comparative tests of both theories within the samestudy design are relatively rare (Massey et al., 1998, p. 279). Second,results from post-move ‘‘why did you move’’ survey questions (i.e. totake a job, to join family members, to get married, etc.) have been takenas evidence concerning pre-move motivations for migration, even thoughthese studies have incorrect motive-behaviour causal order and no com-parative group information from non-migrants (United Nations Secre-tariat, 1991). Third, game-theory based studies use post-move earningsgains ⁄ losses to infer pre-move motivations of households to move tomaximize income, and to infer whether the household conditioned itspre-move decision to move on post-move symmetric earning outcomeresults for both spouses (Jacobsen and Levin, 2000). We use a new anddifferent approach. Our test is based not on post-hoc inferred decisionrules but on pre-move direct self-reported decision-making rules thatrespondents themselves say they would use to decide whether to migrateor to stay.

The research focus of this study is on intentions to migrate. Based ondecades of research literature on the relationship between attitudes(intentions) and behaviour in social psychology but not in economics,we emphatically argue that intentions are an entirely appropriate

Migration decision rules 33



concept for migration scholarship, particularly for research on migrationdecision-making (Armitage and Conner, 2001). Most researchers whostudy intentions base their theoretical justification of the widely acceptedand extensively validated Theory of Planned Behaviour, formulated bysocial psychologists Ajzen and Fishbein (1980) and Ajzen (1985, 1988),in which intentions are conceptualized as the key proximate determinantof behaviour. In the application of this theory to migration scholarship(De Jong and Fawcett, 1981; De Jong, 1999), the decision to migratebecomes an option based on a person’s cost-benefit evaluation of theexpected attainment of valued goals in a new area versus remaining inthe present community.

Recently economists have also utilized migration intentions in migrationresearch (van Dalen and Henkens, 2007). In their analysis of what drivesthe pressure to emigrate out of Africa, economists van Dalen and col-leagues assess the empirical evidence on the relationship between migra-tion intentions and actual behaviour to be encouraging (2005).Supporting this conclusion, De Jong’s study in Thailand showed thatintentions to migrate were strong predictors of more permanent actualmigration behaviour two years later, controlling for numerous microeco-nomic theory factors, such as human capital, household economy, locallabour market, and demographic variables (2000). Other migrationintentions-behaviour studies support the validity of migration intentionsas an appropriate concept for migration decision-making research(Hughes and McCormick, 1985, Fawcett, 1986; Gardner et al., 1986;Gordon and Molho, 1995; Sandu and De Jong, 1996; Lu, 1999;Casimiro, 2003).

THEORETICAL FRAMEWORK

While theories at various levels of aggregation—macro, meso, andmicro- have been proposed in the migration literature to explain thedeterminants and persistence of migration (Faist, 1997; Fischer et al.,1997; Massey et al., 1998), the primary concern in this paper is to testthe propositions made by the neoclassical microeconomic theory and thenew household economic theory. Individual choice is at the centre ofdecision-making within the framework of the neoclassical microeconom-ic theory. This theory argues that individuals behave as rational actorsand decide to migrate based on cost-benefit calculations that migrationwill yield positive returns to the individual. People choose to migrate asa form of investment in human capital, moving to places where they feel




their skills can be improved and rewarded. From these perspectivesindividuals migrate based on a decision that is best for their own future(Todaro, 1976). This theory has been criticized for being individualisticand assuming that the migrant is in total control of his ⁄her decision tomove. What has been ignored, according to the critics, is the householdcontext in which an individual is making such a decision (Stark andBloom, 1985; Fischer et al., 1997; Massey et al., 1998).

The new household economics theory shifts the decision-making fromthe individual, and argues that the appropriate units of analysis formigration research are families and households (Stark and Bloom,1985). The theory is called ‘‘new’’ precisely because of the emphasis onhousehold context that had been left out of the conceptualization inmost previous migration theories. As Massey writes, ‘‘A key insight ofthis new approach is that migration decisions are not made by isolatedindividual actors, but by larger units of related people– typically familiesor households– in which people act collectively not only to maximizeexpected income, but also to minimize risks and to loosen constraintsassociated with a variety of market failures, apart from those in thelabour market’’ (1998: 436).

It has been argued that especially within the context of developingcountries, an individual is motivated to move not only for his ⁄her owngoals but also for the survival of the household (Lauby and Stark,1988). The perspective of the new household economics becomesespecially relevant in these contexts because poor families in developingcountries lack institutional mechanisms of private insurance marketsand governmental programs that minimize household risks in the moredeveloped countries. Thus, there is the incentive to self-insure by sendingone or more family members to a city or abroad to remit earnings thatguarantees family income and reduces risks incurred through cropfailures, crop price fluctuations, and unemployment (Massey et al.,1998). As Lauby and Stark conclude, ‘‘A large proportion ofrural-urban migrants in developing countries are unmarried and remit asignificant part of their earnings to their parents, thereby reducing theincome variance associated with work in agriculture’’ (1988: 474). ForSouth Africa, Kok et al. contend that the assumption of the newhousehold economic theory that all individuals in a household have sim-ilar motivations is perhaps simplistic (2003). They write, ‘‘Debatesregarding the household as the migration decision-making unit are there-fore nowhere near a resolution in the African context, as elsewhere’’(2003: 15).




In his summary evaluation of scholarship on internal migration in devel-oping countries, Lucas concludes that while the theoretical literature onfamily strategies that link migration with education, marriage, and riskspreading has proved to be fruitful, ‘‘The empirical literature still offersno more than a few isolated examples. Replication or rejection of resultsin other contexts should be a high research priority’’ (1997: 753). Weaddress this research priority in our present study. Moreover, genderand marital status differences would be expected within decision-makingframeworks, and how these differences affect short-term and longer-termintentions to migrate is a focus of this study.

Gender, marital status and migration

While neoclassical microeconomic theory usually assumes that males arethe household migration decision makers and females are ‘‘tied’’migrants (Pedraza, 1991; Riley and Gardner, 1993; Pessar, 1999), newhousehold economic theory takes into consideration gender and powerdynamics within the household. According to this theoretical model,many poor developing country households cannot depend on a singlesource of income, and as a consequence combine income from a numberof sources if at all possible. This may involve home-based enterprises formen and women as well as wage work. Thus the household needs to bal-ance available male and female adult and child labour resources withjobs that are available.

Examples of gender in household decision-making in the South Africanagricultural context include young boys who may be ‘‘lent’’ out as cattleherders, and girls as domestic help (Gelderblom, 2005), while somewomen may need to combine a job with domestic responsibilities. Ifwage work is not available in the immediate area, the household labourallocation strategy may necessitate that one or more members becomeinvolved in circular migration. Todes’ study in Newcastle, South Africafound that because of their association with reproductive activities,women were more likely to stay behind, with men leaving as circularmigrants (1998). Posel’s study in rural South Africa showed that marriedwomen’s decision processes may be constrained by their roles in thehousehold as care-givers for children and older adults (2002). Posel fur-ther argues that women’s traditional roles in farming may reduce theirprobability of migration for work, and that particularly marriedwomen’s mobility is restricted by men in the household (2003). In sum-mary, Gelderblom concludes that, ‘‘The (household strategies) approachis effective to a point in illuminating the decision-making of households,




but it is constrained by the way that it focuses on household goals tothe exclusion of individual goals (Gelderblom, 2005: 276; Wolf, 1990).’’We address this research issue in our present study.

Recent anthropological case studies have documented how men andwomen experience migration differently. For example, Pessar illustratesthat the decision to send an unmarried daughter abroad involves consid-eration of the daughter’s sexual freedom and promiscuity in addition tothe economic benefits (1999). Also, while women may migrate indepen-dently, such decisions may be limited by the needs of the household.Chant and Radcliffe write that in the Philippines ‘‘…migration decisionsof young single women are usually structured with respect to potentialbenefits for the household as a whole’’ (1992: 15). Thus, in such circum-stances women’s decision to migrate may be based on the needs of thehousehold rather than on their own individual advancement. Also, ithas been argued that compared to men, women attach greater impor-tance to the family and culturally are expected to do so in many socie-ties (Chant and Radcliffe, 1992). However, evidence from thePhilippines has also shown that while married women are motivated tomove for their children’s future, young Filipinas do migrate partly toearn money for their own future as well (Oishi, 2002).

Prior studies that have separately analyzed male and female migrationintention and behaviour support an imperative to further examine gen-der differences in migration (Hugo, 1999; Kanaiaupuni, 2000; Cerruttiand Massey, 2001). Kanaiaupuni finds that in Mexico high femaleemployment reduces the likelihood that men begin migrating (2000).Furthermore, higher levels of education increase migration amongwomen, but have a negative effect on men’s migration. Similar evidencehas been found among migrants to South Africa from Lesotho, Zimba-bwe, and Mozambique. Dodson posits that, ‘‘Female migrants tend tobe better educated than their male counterparts with lack of educationseeming to discourage female mobility while encouraging male mobility’’(1998: 1). Oishi finds that women from major sending countries such asthe Philippines and Sri Lanka have higher autonomy in the household,suggesting that women’s autonomy is an important determinant ofmigration behaviour for females (2002). Hence, education andemployment experiences may have different effects on male and femalemigration.

Cerrutti and Massey’s Mexican study finds that while adult men movefor employment, adult women migrate for family reasons (2001).




However, younger daughters tend to move for work, and the determi-nants of their migration are similar to those of sons and fathers. Thisfurther indicates that while gender is an important dimension in migra-tion patterns, it is cross-cut by other variables such as age and, in partic-ular, marital status. Migration intentions and behaviour may differbetween married males versus never married males and married femalesversus never married females. For example, young single females may bemore similar on migration intentions and behaviours to young singlemales as compared to older married females (Chant and Radcliffe,1992). Kanaiaupuni shows that in Mexico migration risks were higherfor single women relative to married women (2000). Also, single individ-uals may be more likely to base their intentions to move on what is bestfor their own future, while those who are married are more likelyto consider what is best for the household and other members of thefamily.

While prior migration studies have attempted to incorporate genderand marital status differences in migration intentions and behaviour,none have empirically tested how male and female migration intentionsmay differ by decision-making strategies. We also examine whether thisrelationship differs by marital status for the neoclassical and newhousehold economic decision-making framework expressed by surveyrespondents in South Africa. Grounded in the preceding review of theeconomic and gender migration theory literature, we test the followinghypotheses:

1a. Based on the neoclassical microeconomic theory assumption thatmigration is a result of expected positive returns accruing to theindividual, we hypothesize that respondents expressing a ‘‘bestfor own future’’ migration decision perspective will have highershort-term and longer-term intentions to migrate than thoseholding either ‘‘household income maximization’’ or ‘‘householdwell-being’’ decision perspectives.

1b. The alternative hypothesis, based on the new household eco-nomic theory assumption that migration ensues as a result of ahousehold’s attempt to maximize expected household income, isthat respondents expressing a ‘‘household income maximization’’migration decision perspective will have higher short-term andlonger-term intentions to migrate than those holding all otherindividual or household well-being decision perspectives.

2. The relationship between migration decision perspective andintentions to migrate is expected to be conditioned by gender and




marital status, with stronger ‘‘best for own future’’ effects fornever married males and stronger ‘‘reducing household risk’’ and‘‘best for other family members’’ perspective for married females.

3. The predictors of migration intentions are expected to vary forthe gender-marital status groups, particularly for education,household income and work status.

South African migration context

South Africa still suffers from the legacy of racially-based stratificationand spatial separation. The effects of past apartheid policy particularlyaffected the black-African population, which now constitutes nearly 78per cent of the national population. While not prevented, African spatialmigration was severely constrained by the pass (influx control) laws, andthe forced resettlement of millions of Africans and minority groups.Densely populated rural informal settlements with no economic basecame into being in the former homeland areas during the process of dis-placed urbanization, thereby increasingly separating most Africans’ placeof employment and place of residence (Gelderblom and Kok, 1994).

Within this context, several salient factors affect current migration inten-tions by rural and urban residents. The first is public policy. Kotze andHill chronicle the historical impact of disjointed regional economicdevelopment resulting from the discovery of mineral wealth, the regula-tion of transnational labour migration, and the internal migration passlaws of the apartheid period (1997). More recently, after the influx con-trols were removed, many of the largest metropolitan areas such asJohannesburg and Cape Town have experienced large influxes of Afri-can migrants from all areas of South Africa. As if the dam of unrealizedmigration intentions had been broken, an impact of the political andpolicy changes of the mid-1990s has been a return to internal migrationpatterns similar to the pre-apartheid period (Kok et al., 2003).

Second, the historically dominant patterns of internal migration have beenrural-to-urban and rural-to-rural streams. However, the 2001 South Afri-can census showed that 54 per cent of the population now lives in urbanareas. With the transition in residential structure to urban places, urban-to-urban is the emergent migration pattern, and this pattern will gainsalience as the urbanization transition continues in South Africa. Third,the dynamics of temporary versus more permanent urban migration maybe changing. According to Gilbert and Crankshaw, ‘‘The evidence sug-gests that few of Soweto’s migrants are sojourners and that many have




lived in Johannesburg for a long time. They are different from themigrants of an earlier age who spent three years on a work contract andthen went home’’ (1999: 2389). The dynamics of temporary versus morepermanent migration can be expected to have an impact on intentions tomigrate as migrant networks become solidified by stable family and friendties in destination urban areas. It would also be expected that the demo-graphic composition of rural formerly temporary intended migrants wouldbe dominated by young adults with generally higher intentions to move insearch of employment opportunities, while urban-to-urban streams wouldinclude somewhat older and more experienced workers who typically havelower intentions to migrate (Mazur, 1998).

DATA AND METHODS

The data used for the study are from the 2001–2002 Causes of Migra-tion in South Africa Survey, sponsored by the Human Sciences ResearchCouncil (HSRC). The survey collected information from 3,618 house-holds in 711 enumeration areas. In addition to the household question-naire, a randomly selected adult between the ages of 18–69 years oldcompleted an individual questionnaire. A stratified cluster random sam-pling design was utilized for the survey based on several strata: 1) thelocal government, 2) spatial development initiative areas, and 3) popula-tion groups of African ⁄Black, Coloured, Indian ⁄Asian, and White. Datafor the household and for the randomly selected adult (age 18–69 yearsold) household member who completed the individual questionnaire areused in this analysis. All descriptive and multivariate models are basedon weighted data, where weights were adjusted to retain the originalsample size. Cases with missing values were excluded from the analysisresulting in a final sample of 3,306 individuals.

Dependent variables

The dependent variables used for the analysis are two measures of inten-tions to migrate at two different time horizons.

1. Intend to move in the next twelve months: This measure combinedthe responses of two questions: a) plan to move from this area tosettle permanently in another area in South Africa or in anothercountry, with b) plan to move from this area for a few monthsto work or look for work or for other reasons and then return tothis area.




2. Intend to move in the next five years: This measure combined thetwo responses above for the next twelve months with responsesto similar permanent and temporary migration intention ques-tions concerning migration in one to five years.

Table 1 provides descriptive statistics on the percentage who intend tomigrate in the next twelve months and next five years for the totalSouth African sample, as well as samples segmented by sex and then bymarital status (never married and married samples) within each gender.Migration intentions refer mostly to internal migration. While somereferred to international destinations– United States, Great Britain,Australia— the majority named other areas within South Africa.

As shown in Table 1, nearly one-in-six (16.6%) of the total SouthAfrican adult population report intentions to migrate from their presentarea of residence in the next twelve months. If the time period isextended to five years, the survey results indicate that just over one-in-four (26.1%) of all South African adults intend to migrate. Whenexamining male and female samples separately, intentions to migrate inthe next twelve months are similar, 17.5 per cent for men and 15.7 percent for women. In the long-term, a higher percentage of men report anintention to migrate (29.8%) compared to women (22.8%). In furtherexamining intentions to migrate by marital status and sex, we find thatnever married men and women have quite similar intentions to migrate.In the short-term 19.6 per cent of never married men and 22.7 per centof never married women intend to migrate, while in the next five years34.5 per cent of never married men and 34.0 per cent of never marriedwomen intend to migrate. For married respondents, men report a higher

TABLE 1

PER CENT DISTRIBUTION OF DEPENDENT VARIABLES

SamplesIntention to migratein next 12 months

Intention to migratein next 5 years

Total (3306) 16.6% 26.1%Male (1278) 17.5% 29.8%Never married (495) 19.6% 34.5%Married (694) 14.2% 23.9%

Female (2028) 15.7% 22.8%Never married (675) 22.7% 34.0%Married (1000) 10.1% 13.7%

Source: Causes of migration in South Africa survey, 2001–02.




intent to migrate than women both in the short-term (14.2% vs. 10.1%)and long-term (23.9% vs. 13.7%).

While respondents were not asked about the ‘‘certainty’’ of their inten-tions to migrate, they were asked the reverse question: ‘‘How unlikely is itthat you will never move away from this area?’’ Over 82 per cent ofrespondents who intend to move in the next five years responded that itwas unlikely that they will never move away from this area, Furthermore,of those who reported they intend to migrate in the next five years andnamed an intended destination area, over 70 per cent reported they were‘‘likely or very likely to actually move to that place.’’ This evidence sug-gests that migration behaviour is not only seen as available to South Afri-can adults, but also that individuals are certain that their intentions will berealized.

Independent variables

Since the primary goal of this paper is to examine how the neoclassicalmicroeconomic decision-making framework and new household eco-nomic framework predict migration intention by gender and marital sta-tus, the individual respondents’ migration decision-making perspectivewas measured by the answer to the following question, ‘‘In thinkingabout whether you intend to move or stay here, on which of the follow-ing, if any, will you base your decision (to move or stay)?.’’ Fourresponse categories were provided: 1) On what would be best for yourown future, 2) On the household’s need for a higher income, 3) Onreducing the risk of bad things happening to this household, and 4) Onwhat is best for family members who are not currently part of thishousehold. In addition, respondents were encouraged to provide open-ended responses and were urged to offer multiple motives. After allresponses were recorded, interviewers repeated all the answers given bythe respondent and asked respondents which statement best reflects howthey approach the decision. This methodology, which combined openand closed-category questions and follow-up ‘‘best’’ choice response,provides inherently meaningful data on individually-defined migrationdecision rules. In this paper we use the respondent’s ‘‘best’’ choiceresponses to operationalize the decision-making perspective. A limitationof this study is that it did not include in its methodology an in-depthformat that could elucidate how easy it was for respondents to separatetheir motives. However, respondents did answer readily with almost nonon-response or ‘‘don’t know’’, and almost all were able to say which ofthe ‘‘best’’ choice response was for them.




Overall, 67.8 per cent of this South African population sample state thattheir decision to migrate will be based on what is ‘‘best for one’s ownfuture’’, 17.4 per cent will base their decision on their household’s needfor a higher income, 8.8 per cent will base their decision on reducing therisk of bad things happening to their household and 6.0 per cent statetheir decisions will be based on what is ‘‘best for family members’’ whoare not currently part of their household or on another perspective. Veryfew respondents (less than 1%) gave other meaningful open-endedresponses, and these data have been combined with the ‘‘best for familymembers’’ category. Also, 1.2 per cent did not choose any category andhave been deleted from the analysis.

Several covariates known to be associated with migration intentions andbehaviour are also included in the models. These include measures of: 1)marital status, 2) life satisfaction, 3) family and friend migration pres-sure, 4) human capital, 5) race ⁄ ethnic and demographic characteristics,and 6) household resources. Frequency distributions of all independentvariables in the total sample and how they are coded for the analysisare provided in the Appendix Table A1.

The analysis strategy is to first present cross-tabulations of intentions tomigrate in the next twelve months and next five years by migration deci-sion rules for men and women. Next, a series of logistic regressionmodel results are presented. The analysis is stratified first by sex toexamine differences between male and female South African respondentson their intentions to migrate in the short-term and long-term by migra-tion decision-making frameworks and marital status, controlling forindividual and household covariates. Male and female samples are fur-ther stratified along the dimension of marital status with separate analy-ses for married and never married individuals. Thus, we analysemigration determinants for never married men, married men, never mar-ried women, and married women. We do not include separate regres-sions of widowed, divorced and separated individuals due to insufficientsample sizes.1

RESULTS

Descriptive results

Table 2 presents cross-tabulations of intentions to move in the nexttwelve months and next five years by the individual respondent’s stated




migration decision rule. This relationship is examined separately for menand women.

Among both men and women, those who state that their migration deci-sions would be based on their own future have the highest percentage ofintentions to move in the short-term. About 20 per cent of men and 18per cent of women in this category intend to move compared to lessthan 13 per cent intending to move in the next twelve months in theother household decision framework categories. Women expressing adecision-making framework that is based on what is ‘‘best for otherfamily members’’ have the lowest percentage of intentions to move inthe short-term (3.0%). In the long-term, among women, those who statetheir decisions would be based on what is ‘‘best for their own future’’have the highest percentage of intentions to move while for men it isthose expressing a what is ‘‘best for other family members’’ decision rulethat have the highest percentage of intentions to move, although differ-ences in percentages are very small.

When examining migration decision framework differences by time-frame, individuals expressing a ‘‘best for own future’’ decision rulereported higher intentions to migrate in the next twelve months for bothmen (20% vs. about 11% in all other decision frameworks) and women(18% vs. 11.3%, 13.3% and 3.0%) compared to other decision-makingframeworks. In contrast, percentages of intentions to migrate in the nextfive years are similar across categories of migration decision rules.

TABLE 2

PERCENTAGE INTENDING TO MIGRATE IN NEXT 12 MONTHS AND NEXT 5 YEARS

BY SEX AND MIGRATION DECISION RULES IN SOUTH AFRICA

Male Female

12 Months 5 Years

TotalN

12 Months 5 Years

TotalN

% % % %

Yes No Yes No Yes No Yes No

Best for own future 20.4 70.6 30.4 69.6 807 18.4 81.6 24.7 75.3 1201Maximize householdincome

11.9 88.1 29.0 71.0 227 11.3 88.7 18.6 81.4 382

Reduce household risk 10.6 89.4 25.1 74.9 166 13.3 86.8 20.4 80.0 301Best for other familymembers

11.1 88.9 32.5 67.5 78 3.0 97.0 17.1 82.9 144

Source: As Table 1.




Bivariate associations suggest that the strategy that is driving an individ-ual’s intent to migrate differs by gender and time frame. The strength ofthese relationships is tested in logistic regression models controlling forindividual and household determinants of migration intent.

Regression results

Gender and intentions to migrate

Table 3 shows logistic regression results (odds ratios > 1.00 indicatehigher likelihood to move and <1.00 higher likelihood to stay [lowerlikelihood to move]) of the effects of migration decision rules and mari-tal status on male and female intentions to migrate in the next twelvemonths and the next five years, controlling for individual and householdvariables. (Please refer to Appendix Table A2 for the logistic regressionresults with the full set of variables).

In support of the neoclassical microeconomic theory, the results inTable 3 show that for both men and women, those who state they

TABLE 3

MIGRATION DECISION RULES AND MARITAL STATUS DETERMINANTS1 OF

INTENTIONS TO MIGRATE IN NEXT 12 MONTHS AND NEXT 5 YEARS BY SEX:

LOGISTIC REGRESSION ODDS RATIOS

Model Components

12 mos. odds ratios 5 yrs odds ratios

Male Female Male Female

A. Migration decision rules(Maximize HH income)

Best for own future 2.34*** 1.97** 1.29 1.68**Reduced household risk 1.48 1.72+ 1.47 1.66+Best for other family members 0.88 0.23** 1.11 1.09

B. Marital status (married)Never married 0.42*** 1.66** 0.51** 2.20***Widowed 2.26 1.92+ 2.05 1.95*Divorced and separated 5.33*** 2.55* 2.34** 2.19*

Number of cases 1278 2028 1278 2028Intercept 0.72 )1.21** 2.26*** )0.55-2 Log-likelihood 935 1429 1224 1723Chi-square likelihood ratio 249*** 337*** 333*** 455***

Reference category in parentheses +p < .10; *p < .05; **p < .01; ***p < .001.1Model is controlling for life satisfaction, migration pressure, human capital, demographiccharacteristics, and household resources. Appendix Table A2 shows results for all thecovariates.Source: As Table 1.




would base their migration decisions on what is ‘‘best for their ownfuture’’ are significantly more likely to migrate when compared to indi-viduals that state they would base their decisions on ‘‘maximizing house-hold income’’ (this new household economic assumption is the referencecategory in this analysis). For men that hold a ‘‘best for own future’’migration decision-making framework, the odds of intending to migratein the short-term are 2.34 times higher than men holding a ‘‘maximizehousehold income’’ decision-making framework. However, no differ-ences are observed between migration decision-making frameworks inpredicting long-term migration intentions for men. For women the oddsof intending to migrate are 1.97 times higher for intentions in the short-term and 1.68 times higher for intentions in the long-term for thoseexpressing a ‘‘best for own future’’ decision rule compared to a ‘‘maxi-mize household income’’ decision rule.

Some support is found for the new household economic theory, but onlyfor women. Women who state that their migration decisions would bebased on ‘‘reducing household risk’’ are more likely to intend to movethan those expressing maximizing household income as a strategy. Thisis marginally significant (p < .10) for intending to move in the nexttwelve months (Odds ratio [OR]: 1.72) and for intending to move in thenext five years (OR: 1.66). It is also important to note here that womenexpressing a ‘‘maximize household income’’ strategy are more likely tomove in the short-term when compared to those expressing a ‘‘best forother family members’’ migration perspective.

The table also presents the effects of marital status on intentions tomigrate, controlling for all other variables in the model. Marital statusdifferences by gender are clearly evident in the results. Never marriedmen are 58 per cent less likely to intend to migrate in the next12 months and 49 per cent less likely to intend to migrate in the next5 years compared to married men. While married men have significantlyhigher odds of intending to migrate than never married men, in contrastmarried women are significantly less likely to intend to migrate thantheir never married counterparts. Both men and women that aredivorced or separated are more likely to intend to migrate than marriedindividuals in the long-term and short-term. For women, being widowedis also a significant predictor of increased migration intentions in thelong-term. Thus, in the South African context, results show that marriedwomen overall have significantly lower odds of intending to migratecompared to never married, widowed, and divorced and separatedwomen.




Marital status and gender specific intentions to migrate

With contrasting results of intentions to migrate for men and womenwith regards to decision-making strategies and marital status, next werun a series of logistic regression models for separate samples of nevermarried men, married men, never married women and married womento examine how the effects may vary by these gender and marital statuscategories. Table 4 presents logistic regression results of intentions tomigrate in the next twelve months and Table 5 shows the results ofintentions to migrate in the next five years for married and never mar-ried samples for men and women.

Results show that the predictors of migration intentions are different forthe gender-marital status groups. First, congruent with the gender spe-cific model findings and in support of the neoclassical economic theory,the evidence shows that never married men and women who report thattheir migration decisions would be based on what is ‘‘best for their ownfuture’’ have significantly higher odds of intending to migrate in theshort-term in comparison to those who say that they would base theirdecisions on maximizing household income. For never married men, theodds are 22.5 times higher and for never married women the odds are2.23 times higher. However, the neoclassical economic argument is onlyvalid for never married individuals. A striking observation here is thatfor married men those that report their decisions would be based on‘‘what is best for their own future’’ are 64 per cent less likely to migrate(thus more likely to stay) than those reporting ‘‘maximizing householdincome’’ decision frameworks. This lends support to the new householdeconomic theory of maximizing household income as a strategy inmigration behaviour, but only for married men in the short-term. Nodifference in intention by decision framework is found for marriedwomen in the short-term.

The effects of migration decision rules on intentions to move differ forthe five year time horizon. It is only for never married women that the‘‘best for own future’’ decision-making framework significantly increasesintentions to migrate. For married men the ‘‘reducing household risk’’perspective increases odds (OR: 2.62) of intentions to migrate, howeverfor never married men this perspective significantly reduces odds (OR:0.20) of intentions to migrate (thereby increasing the likelihood to stay)when compared to those holding a maximizing household income per-spective. Thus, for married men reducing household risk seems to be animportant migration decision perspective, but for never married men




TABLE 4

DETERMINANTS OF INTENTIONS TO MIGRATE IN THE NEXT 12 MONTHS BY SEX

AND MARITAL STATUS: LOGISTIC REGRESSION ODDS RATIOS

Model Components

Male Female

MarriedNever

married MarriedNever

married

A. Migration decision rules(Maximize HH income)Best for own future 0.36** 22.5*** 0.83 2.23*Reduced household risk 0.98 2.60 1.74 0.87Best for other family members 0.04 6.00+ 0.66 0.01*

B. Life satisfaction 0.87 0.52*** 0.71** 0.75***C. Migration pressure

Family ⁄ friend pressure to migrate-Yes 0.47 2.35+ 2.69** 2.19*Family ⁄ friend pressure to stay-Yes 0.93 0.95 0.66 1.76+

D. Human capital1. Educational attainment (Up to primary)

Secondary school (8–11) 1.20 0.79 2.11* 1.69High school (12) 2.32+ 0.53 2.33+ 1.06Post school qualification 1.68 3.62* 6.76*** 1.07Education not reported 1.17 0.81 3.30 1.39

2. Currently working – Yes 12.4*** 0.85 1.14 0.573. Ever lived outside this area-Yes 1.28 3.08*** 2.36* 1.37E. Demographic characteristics1. Age 0.80* 0.70*** 0.74*** 0.76***2. Race ⁄ Ethnicity (Indian ⁄ Asian)

African ⁄ Black 1.60 0.48+ 1.06 1.763. Household size (1–3)

4–5 persons 0.20*** 0.47+ 1.10 0.44*6 + persons 0.17*** 0.89 0.48+ 0.44**

F. Household resources1. Monthly household income (No income)

<R1000 0.01*** 1.65 2.17* 0.81R1,001-2,500 0.05*** 0.43 0.40 1.28>R2,500 0.06*** 0.16+ 0.56 7.54***Refused to answer 0.02*** 0.48 0.36 0.10

2. Home ownership-Yes 1.34 1.91+ 0.67 0.703. Quality of water (Very good ⁄ good)

Acceptable 0.35 1.92 0.43+ 0.89Poor ⁄ uncertain ⁄ no service 3.65** 2.29* 2.46** 0.62+

4. Quality of electric service(Very good ⁄ good)Acceptable 0.99 0.80 6.30*** 3.00**Poor ⁄ uncertain ⁄ no service 1.50 0.59 0.53 2.42**

Number of cases 694 495 1000 675Intercept 0.91 )1.51 )1.02 )0.38)2 Log-likelihood 308 345 415 601Chi-square likelihood ratio 260*** 144*** 263*** 123***

Reference category in parenthesis +p < .10; *p < 0.5; **p < .01; ***p < .001.Source: As Table 1.




TABLE 5

DETERMINANTS OF INTENTIONS TO MIGRATE IN NEXT 5 YEARS BY SEX AND

MARITAL STATUS: LOGISTIC REGRESSION ODDS RATIOS

Model Components

Male Female

MarriedNever

married MarriedNevermarried

A. Migration decision rules(Maximize HH income)

Best for own future 0.79 1.08 1.37 1.78*Reduced household risk 2.62* 0.20* 2.19+ 1.27Best for other family members 0.29 1.92+ 1.16 1.23

B. Life satisfaction 0.63*** 0.48*** 0.61*** 0.75***C. Migration pressure

Family ⁄ friend pressure to migrate-Yes 1.77 4.44*** 3.25*** 7.13***Family ⁄ friend pressure to stay-Yes 0.67 1.25 1.05 1.32+

D. Human capital1. Educational attainment (Up to primary)

Secondary school (8–11) 0.21*** 2.23* 4.18*** 1.24High school (12) 1.15+ 1.36 4.24*** 1.48Post school qualification 1.11 10.1*** 36.31*** 1.83Education not reported 0.40 2.44 5.98** 1.79

2. Currently working – Yes 7.66*** 0.46* 0.76 0.593. Ever lived outside this area-Yes 1.02 2.44*** 1.22 1.62*E. Demographic characteristics1. Age 0.80** 0.58*** 0.80*** 0.80***2. Race ⁄ Ethnicity (Indian ⁄ Asian)

African ⁄ Black 2.23* 0.63 1.03 0.803. Household size (1–3)

4–5 persons 0.87 0.72 0.69 0.56+6+ persons 0.36** 0.70 0.48* 0.89

F. Household resources1. Monthly household income (No income)

<R1000 0.03*** 2.52** 1.07 0.71R1,001-2,500 0.11*** 2.32+ 0.42 1.36>R2,500 0.12*** 0.49 0.76 3.72**Refused to answer 0.04*** 2.40 0.47 0.97

2. Home ownership-Yes 0.74 1.25+ 0.92 0.54**3. Quality of water (Very good ⁄ good)

Acceptable 1.17 2.22+ 0.33** 0.76Poor ⁄ uncertain ⁄ no service 1.63 1.32 2.39** 0.57*

4. Quality of electric service(Very good ⁄ good)Acceptable 0.50 1.25 7.18*** 0.92Poor ⁄ uncertain ⁄ no service 0.60 0.74 1.10 2.88***

Number of cases 694 495 1000 675Intercept 2.49** 2.05** )1.04 0.65-2 Log-likelihood 487 454 554 718Chi-square likelihood ratio 276*** 184*** 245*** 147***

Reference category in parentheses +p < .10; *p < .05; **p < .01; ***p < .001.Source: As Table 1.




maximizing household income is more important for intentions tomigrate in the longer time horizon. While never married men andwomen are driven by the neoclassical argument, married men are drivenby the ‘‘maximize household income’’ argument in the twelve monthtime horizon. The new household economic argument appears to be ofgreater significance when thinking of whether or not to move in the fiveyear time horizon.

Other determinants of migration intentions

Consistent with prior literature that has shown that education, incomeand employment experiences have different effects on the migrationbehaviour of men and women; we find similar differences in the SouthAfrican context (shown in Appendix Table A2). Women with any levelof education above a primary level are significantly more likely to intendto migrate compared to women with up to primary level education,while for men it is only those with a post-school qualification that aresignificantly more likely to intend to migrate. Household income is animportant predictor for men’s intentions to migrate but not women’sintentions. Men with no income (reference category) are more likely tointend to migrate both in the short-term and long-term.

In separate regressions by marital status (Tables 4 and 5), we find thatthe importance of education in increased intentions to migrate is onlyobserved among married women. Educated married women (those withany education above a primary level) are more likely to intend tomigrate both in the short-term and long-term compared to women withprimary education or less. This is particularly salient for intentions inthe long-term. No education differences are observed among nevermarried women. For never married men those with a post-school qualifi-cation are significantly more likely to intend to migrate both in theshort-term and long-term, while married men with secondary schooleducation are significantly less likely to migrate in the next five years.

With regards to income, having any level of household income versusno household income significantly decreases married men’s likelihood ofintending to migrate in both time horizons. In contrast, for never mar-ried men there is some evidence of higher odds of intending to migratewith higher household income. Never married men with a monthlyhousehold income of less than R1000 are 2.52 times more likely tointend to migrate in the long-term than never married men with nohousehold income. Among women, while we found that higher income




is associated with higher intentions to migrate, there are differencesbetween married and never married women. For never married women,those with substantially higher incomes (above R2501) are more likelyto intend to migrate compared to those with no income both in theshort-term (OR: 7.54) and long-term (OR: 3.72), but for married womenthose with less than R1000 are more likely to intend to migrate in thenext twelve months (OR: 2.17). These gender differences in householdincome determinants of migration intentions may indicate that a ‘‘bestfor own future’’ motivation for migration for never married women isonly possible in the context of higher family income.

Other salient results of covariates in the models are that currently work-ing married men have the highest odds of intending to migrate com-pared to other groups both in the short-term and long-term (odds ratioof 12.4 and 7.6, respectively). However, never married women that arecurrently working are 57 per cent more likely to intend to stay in thenext twelve months and 59 per cent more likely to intend to stay in thenext five years. Currently working, however, does not significantly affectthe odds of intending to move or stay for never married men and mar-ried women. It appears that for never married men and women it is theexperience of having lived outside of the area that increases their intentto migrate in the longer time horizon while this is not the case for mar-ried men and women. However, in the short-term never married menand married women have higher odds of intending to migrate if theyhave had experience living outside the area.

Perceived migration pressure from friends and family has a greater influ-ence on women’s intentions to migrate. Particularly in the short-termboth married and never married females are 2.69 and 2.19 times, respec-tively, more likely to intend to migrate if they perceive normative pres-sure from family or a friend. For intentions in the long-term, except formarried men, perceived normative pressure increases migration intentionodds for all other groups.

Race is only significant for intention to migrate in the long-term formarried men. African ⁄Black married men are 2.23 times more likely tomigrate in the next five years. Larger household size is also associatedwith lower odds of intending to migrate. While in the short-term thiseffect is seen for married men and never married women, for intentionsin the long-term both married men and married women are 64 per centand 52 per cent, respectively, less likely to migrate. Lastly, life satisfac-tion and age are significant determinants of both twelve month and five




year migration intentions for all gender and marital status groups.Higher satisfaction with life is related to lower likelihood of intending tomove, and migration intentions decline as age increases.

DISCUSSION AND CONCLUSION

The main objective of this research was to test the thesis that the migra-tion decision-making rules framework from the neoclassical microeco-nomics and the new household economics vary for specific gender andmarital status population groups in explaining migration intentions. Theresults showed consistent support for this thesis. First, in support of theneoclassical microeconomic theory assumption, the findings supporthypothesis one that respondents (both men and women) expressing a‘‘what is best for own future’’ migration decision perspective have signif-icantly higher intentions to migrate than those holding householdincome maximization or household well-being decision perspectives. Thefinding of very little difference in the ‘‘best for own future’’ motivationfor migration intentions among never married women and men is evi-dence against the prevalent notion of altruism in female migration deci-sion making. However, the ‘‘best for own future’’ perspective was notsupported for long-term migration intentions for men as the resultsshow that there are no significant differences between migration decisionperspectives in predicting male intentions to migrate in the next fiveyears. This suggests the importance of time horizon and gender onmigration decision-making rules. Men are more likely to take an individ-ualistic approach when thinking of moving in the immediate future, butnot in the longer-time horizon.

In general, never married men and women are more likely to intend tomove than married individuals in both time horizons, while divorcedand separated men and women also have higher migration intentionsthan married adults. Married women are the least likely to migrate com-pared to all other marital status categories for women. This is consistentwith Posel’s finding in South Africa that women who were married weresignificantly less likely than other rural women to be migrant workers(2003). Our results provide further evidence supporting the argumentthat married women in South Africa are constrained on their mobilityand decision to migrate by their role in the household as care-givers forchildren and older adults, perhaps due to restrictions placed by men inthe household. Consequently, unmarried women have greater freedomin their decisions to move (Posel 2002, 2003).




Second, we find evidence that the effect of migration decision perspec-tive on intention to migrate is conditioned by marital status as shown inthe separate regression models for never married and married men andwomen. Never married men show the strongest ‘‘best for own future’’effects on intentions to migrate in the short-term, while never marriedwomen expressing ‘‘best for own future’’ decision perspective havehigher intentions to migrate both in the short-term and long-term. Thissuggests that the neoclassical argument of individual attainment beingthe driving force for migration intentions is most applicable to the nevermarried populations. In the long term, however, it is the ‘‘reduce house-hold risk’’ perspective that appears to be a more significant decision-making perspective for move rather than stay intentions of married menand to a lesser extent married women. In general, the ‘‘maximize house-hold income’’ perspective (the reference category in our analysis) showedresults for lower intentions to move and higher intentions to stay thanthe ‘‘best for own future’’ or ‘‘reducing household risk’’ perspectives.Explanations for these marital status conditioned results may includepossible changes in the normative obligations of never married men andwomen to provide direct income support for the household, as opposedto pursuing their own social mobility opportunities in the context of ris-ing well-being expectations in post-apartheid South Africa.

Third, several covariates of intentions to migrate also differ by genderand marital status. In particular education, income, and work statusaffect migration intentions differently for men and women by maritalstatus. Human capital as measured by educational attainment beyondprimary level is an important predictor of higher odds of female migra-tion intentions versus male intentions, particularly married women.Income works in opposite ways for men and women. For married menthe evidence shows that any level of income increases the odds of inten-tions to stay, while for women higher levels of income increases theodds of intentions to move. Work status is a significant predictor ofintentions to migrate for males but in opposite directions. For marriedmen, if they are currently working they are more likely to intend tomove in the future while for never married men this increases theirprobability of intending to stay. These results are consistent with priorliterature on gender differences in migration behaviour (Kanaiaupuni,2000; Cerrutti and Massey, 2001). Our findings show that some of thesegender differences may also be a result of different expectations andmotivations for married and never married individuals. Female auton-omy as indicated by higher education levels for married women are par-ticularly important in their decisions to migrate because of household




constraints placed on their mobility (Posel, 2002). For married men ifthe household is doing well financially this leads to lower odds ofintending to migrate.

A key proposition of the Theory of Planned Behaviour in social psy-chology is that behavioural intentions are shaped by normative pressureby family members and friends. This theoretical proposition providessubstantive insight to the new household economic argument that migra-tion decision-making involves (unmeasured) conflict and bargaining inthe household, as well as the possible application of gender power.According to this position even though the respondent may express aposition on his ⁄her migration decision-making, the household bargainingprocess may determine migration outcomes. Our study provide insightson this ‘‘black box’’ issue with evidence based on respondent’s answersto direct questions about perceived pressure from family members andfriends to migrate or to stay. Although only one-fourth of the respon-dents reported family or friend pressure to move or stay, the regressionresults showed that individually-held migration decision rules and per-ceived pressure to move or stay have significant independent and addi-tive effects on migration intentions. And, the effect of family and friendpressure is gendered, with greater effect on women’s than men’s inten-tions to move or stay. However, the gender power argument is only par-tially supported as family and friend pressure to move but not pressureto stay show significant effects. These findings indicate a different SouthAfrican context than in the 1980s when lower off-farm opportunities forwomen made rural households more likely to dispatch young men thanwomen to work elsewhere. The family and friend pressure evidence alsoshows the articulation of normative influence concepts from the socialpsychology decision-making literature to the economic arguments ofmigration as a household strategy.

In summary the results of this study provide systematic evidence thatthe neoclassical microeconomic theory proposition of migration deci-sions based on the ‘‘maximizing one’s own future’’ motivation is moreapplicable for never married men and women, the ‘‘maximizing house-hold income’’ proposition for married men with short-term migrationintentions, and the argument of migration to ‘‘reduce household risk’’ ismore applicable for longer time horizon migration intentions of marriedmen and women, at least in South Africa. These results contribute tothe household strategies literature by providing new evidence on the wayhousehold strategies and individual goals jointly affect intentions of menand women to move or stay (Gelderblom, 2005).




NOTES

1. An alternative framing of this analysis, as suggested by a reviewer, wouldbe to explore what explains the respondent’s identified migration decision-making perspective, rather than using the decision making perspective toexplain migration intentions. While certainly a valid topic for futureresearch, we argue that the major focus of migration theory is on indicatorsof migration outcomes. An argument for shifting the dependent variable todecision making rules is the assertion that many ⁄most members of a ruralhousehold would rather stay at home than migrate, given the migrationdecision rules of reducing household risk and minimizing household risk.From this perspective the new household economic theory is more a state-ment of motivation for non-migration than migration. While providing afull multi-nominal logistic analysis test of this argument is beyond the scopeof the present paper, the marginal frequencies in Table 2 provide descrip-tive evidence that supports the stay-at-home rather than move argument formigration intentions in the next 12 months for respondents holding maxi-mizing household income and reduce household risk decision perspectives,but rejects the argument for migration intentions in the next five yearswhere the intended move-stay percentages are quite similar for males acrossall decision making perspectives.

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APPENDIX

TABLE A1

FREQUENCY DISTRIBUTION OF INDEPENDENT VARIABLES IN THE MODEL,

N = 3306

Independent Variables Distribution1 N1

A. Migration decision rulesMaximize household income 17.4% 609Best for own future 67.8% 2008Reduced household risk 8.8% 467Best for other family members ⁄ other perspective 6.0% 222

B. Marital statusMarried 40.5% 1694Never married 49.6% 1170Widowed 6.7% 273Divorced ⁄ separated 3.2% 169

C. Life satisfactionVery dissatisfied 16.8% 368Dissatisfied 19.9% 576Neither or don’t know 11.0% 372Satisfied 35.1% 1422Very satisfied 17.2% 568

D. Migration pressure1. Family ⁄ friend pressure to migrate –Yes 9.7% 2432. Family ⁄ friend pressure to stay –Yes 17.2% 458

E. Human capital1. Educational attainment

Up to primary 41.1% 826Secondary school 23.3% 863High school 23.1% 976Post school qualification 8.0% 425Education not reported 4.5% 216

2. Currently working – Yes 34.0% 12633. Ever lived outside this area – yes 41.5% 1329F. Demographic characteristics1. Age

16–19 9.5% 20920–24 14.7% 41125–29 13.0% 34230–34 15.3% 38635–39 9.7% 41140–44 8.8% 36345–49 8.2% 32550–54 7.6% 27955–59 4.6% 20860–64 4.4% 19865+ 4.3% 174

2. Race ⁄ EthnicityAfrican ⁄ Black 77.7% 1485Indian ⁄ Coloured ⁄ White 22.3% 1821




TABLE A1

CONTINUED

Independent Variables Distribution1 N1

3. Household size1–3 persons 26.5% 10974–5 persons 27.9% 12026+ persons 45.6% 1007

G. Household resources1. Monthly household income

No income 37.7% 1090Less than R1000 34.5% 910R1,001-2,500 11.1% 391More than R 2,500 10.6% 594Refused to answer 6.1% 321

2. Home ownership – Yes 74.8% 25923. Quality of water

Very good ⁄ good 57.1% 2173Acceptable 13.9% 497Poor ⁄ uncertain ⁄ no service 29.0% 636

4. Quality of electricityVery good ⁄ good 58.6% 2195Acceptable 14.1% 453Poor ⁄ uncertain ⁄ no service 27.3% 658

1Percentages are based on weighted data. Frequencies reported are unweighted. Per-centages may not add to 100% due to rounding.Source: As Table 1.

TABLE A2

DETERMINANTS OF INTENTIONS TO MIGRATE IN NEXT 12 MONTHS AND

NEXT 5 YEARS BY SEX: LOGISTIC REGRESSION ODDS RATIOS

Model Components

12 mos. 5 yrs

odds ratios odds ratios


A. Migration decision rules(Maximize HH income)Best for own future 2.34*** 1.97** 1.29 1.68**Reduced household risk 1.45 1.72+ 1.47 1.66+Best for other family members 0.88 0.23** 1.11 1.10

B. Marital status (Married)Never married 0.42*** 1.66** 0.51** 2.20***Widowed 2.26 1.92+ 2.05 1.95*Divorced and separated 5.33*** 2.55* 2.34** 2.18*

C. Life satisfaction 0.71*** 0.73*** 0.62*** 0.71***




TABLE A2

CONTINUED

Model Components

12 mos. 5 yrs

odds ratios odds ratios


D. Migration pressureFamily ⁄ friend pressure tomigrate – Yes

0.81 2.05** 2.13*** 3.58***

Family ⁄ friend pressure tostay – Yes

1.05 1.19 0.98 1.05

E. Human capital1. Educational attainment

(Up to primary)Secondary school (8–11) 0.81 2.41*** 0.72 2.12***High school (12) 1.03 1.70* 1.04 1.97***Post school qualification 2.44* 3.11*** 2.81*** 5.48***Education not reported 1.25 2.81*** 1.05 2.82***

2. Currently working – Yes 2.11** 1.01 1.69** 1.183. Ever lived outside this area – Yes 2.73*** 1.49* 2.33*** 1.46**F. Demographic characteristics1. Age 0.66*** 0.79*** 0.63*** 0.80***2. Race ⁄ Ethnicity (Indian ⁄ Asian ⁄coloured ⁄ white)

African ⁄ Black 0.93 1.30 1.30 0.853. Household size (1–3 persons)

4–5 persons 0.47** 0.56** 0.82 0.56**6 + persons 0.77 0.56** 0.65* 0.73+

G. Household resources1. Monthly household income

(No income)<R1000 0.51** 1.01 0.59** 0.90R1,001–2,500 0.44** 0.59 0.93 0.64>R2,500 0.19*** 1.87+ 0.47* 1.48Refused to answer 0.24*** 0.35+ 0.45* 0.60

2. Home ownership – Yes 1.63* 0.70* 1.08 0.70*3. Quality of water (Very good ⁄ good)

Acceptable 1.16 0.61* 1.57+ 0.50**Poor ⁄ uncertain ⁄ no Service 1.92** 1.06 1.06 1.06

4. Quality of electric service(Very good ⁄ good)

Acceptable 0.44** 3.95*** 0.62* 2.13***Poor ⁄ uncertain ⁄ no service 0.66+ 1.74** 0.78 2.30***

Number of cases 1278 2028 1278 2028Intercept 0.72 )1.21** 2.26*** )0.55)2 Log-likelihood 935 1429 1224 1723Chi-square likelihood ratio 249*** 337*** 333*** 455***

Reference category in parentheses +p < .10; *p < .05; **p < .01; ***p < .001.Source: As Table 1.




Documents

Individual versus Household Migration Decision Rules: Gender and Marital Status Differences in Intentions to Migrate in South Africa