A MIGRATION ALLOCATION MODEL
5 THE MIGRATION SELECTION PROCESS IN THE RURAL AREAS
From the vantage point of the towns, the magnitude of the urban in-migration appears large. The views of the urban employed on the matter find expression in the words of the editorial writer quoted previously: "
. . .
far too many of them want t o exchange their rural life for town life" (Editorial, East Afncan Standard, February 8 , 1974). From the perspective of the total rural population, as reported in Chapter 3 , the proportion of the population born in the rural areas that is resident in one of the towns is very small indeed. Jn any one year only a select few leave a rural area for one of the towns.* There- fore, it is important t o determine who is leaving the rural areas.Jn this chapter the personal and economic characteristics of the men in the sample are related, where possible, t o those of the adult males who have remained in the rural areas. The intent of such a comparison is t o shed as much light as possible on the migration selection process in the rural areas. The question of who migrates really cannot be separated from the question of why people migrate. Therefore, the comparisons made here supple- ment the discussion in the previous chapter on the determinants of migration. Specifically, such personal characteristics as age and education could not be dealt with readily at the aggregate level so they are discussed here.
PERSONAL CHARACTERISTICS OF THE MIGRANTS
Among the more general determinants of migration decision-making in the rural areas, as developed in Chapter 1 and tested in Chapter 4 , there is a built-in selection pro- cess based on personal factors. Two of these, formal schooling completed and age, can be examined in detail.
According to our migration model the likelihood of a rural-to-urban move will vary directly with the level of education of the household members. Summarizing our hypothe- ses: (I) the extent of information of rural households about the towns will be correlated directly with the education of the household members; (2) because of the better access t o information and a greater ability t o adapt t o new situations, the educated are more likely t o undertake the risk of a rural-urban move; (3) the return reahzed for an additional year of education is higher in the towns than in the rural areas; and (4) given the high level of unemployment in the towns, the probability of being selected from a given stock of un- employed will vary directly with the level of education of the unemployed. As a result, the probability of being able t o profit from an urban job will vary directly with the educa- tion of the prospective migrants.
*Certain locations, of course, represent distinct exceptions to this general rule. For example, Moock (1973, p. 303) reports that two-thirds o f the adult males in a sublocation in Kakamega district were employed or searching for work outside o f the district. But, not all o f these men will be in the larger urban centers; it is to be expected that some proportion will be in towns o f less than 10,000 and in rural areas.
All of these effects of education are expressed through such variables as level of wages in the rural areas and urban centers and the probability of obtaining employment.
A less direct effect of education is the expectations o f the fanlily that has contributed t o an individual's educational expenses. T o the extent that this family views the purchase of formal education as the means for entry into the ~ n o d c r n sector of the economy, the school- leaver must try his luck in the modern sector (basically existing only in the urban centers) t o justify the investment in education. If h e is successful in the urban scene he has the reward of a good return o n a wise investment and the fanlily that has contributed t o his education can expect t o share in this reward. The changing economic conditions in the towns require ever higher levels of education t o ensure such urban rewards, but the expecta- tion and their effect o n rural--urban migration persist (Godfrey 1973, p. 71).
The effect of education o n migration can be expressed in noneconornic terms as well, in the form o f a "whitecollar hypothesis" (Godfrey 1 9 7 3 , pp. 70--71). According t o this hypothesis the educated aspire t o white-collar jobs available in the towns and for this reason they reject the rural options independent o f economic realities. This hypothesis is n o t developed here because, as Godfrey indicates, empirical evidence on the subject does n o t support the hypothesis (evidence for East Africa is provided by Maxwell (1969), Moock (1973, pp. 313-314), Heijnen (1968, pp. 96-104), and Hutton (1973, pp. 66-74)). A more likely effect, which cannot be measured readily, is the desire for additional education which tends t o rise with education completed and which requires a rural--urban move because these additional educational opportunities tend t o be limited t o the towns.
There is considerable evidence in o u r sample of a n association between education and propensity t o migrate. Table 5.1 provides the percentage distribution in each province of education completed as observed in the sainple and as reported for all inales in the comparable age groups in the 1 9 6 9 census. The comparisons made in the table indicate a rather consistent pattern across the province (the observed pattern is similar t o that reported for Ghana by Cladwell (1969, p. 62)). The men without formal education were represented poorly in the sarnple relative t o their proportions in the rural areas. Men w h o had completed 5 o r more years o f schooling were represented disproportionately in the sample of migrants.
In general, the more education completed the more overrepresented the group in the migra- tion s a n p l e (these differences are significant a t the p
<
0.01 level using a chi-square test).The 1 9 6 8 survey information o n the timing o f the rural-urban move also provides support for the hypothesis that a move t o the towns is expected o f the educated. For the men with some formal education, 6 0 percent were in school in the quarter prior t o migra- tion while 9 1 percent of the men with some secondary education were in school immedi- ately prior t o migration. Of the men w h o had completed primary education but had not continued o n t o secondary education, two-thirds had passed the Kenya Preliminary Exami- nation. This may indicate that the completion of a unit o f schooling is a propitious time for migrating because a transition into the labor force is required if i t is n o t possible t o continue in school.
In Table 5.2 the education o f the migrants is cross-tabulated with the education of their fathers. The distribution for the fathers is compared with the education of men in comparable ages as reported in the 1 9 6 2 census. The age category of 3 5 t o 5 9 was used as the appropriate age of the migrants' fathers a t the time o f the 1962 census.
Although there is a positive correlation between the education o f a migrant and the education o f his father, there does n o t appear t o be a significant difference between the education o f the fathers of the migrants and the education of all Kenyan Africans in the
TABLE 5.1 The percentage distribution of the education of the men in each province as reported in the migration survey and the 1969 census."
Province of birth Education Total
No formal education Standards Forms
or not stated 1- 4 5--8 1-2 3 - 6
Nyanza Sample Census Western
Sample Census Rift Valley
Sample Census Central
Sample Census Eastern
Sample Census Coast
Sample Census Total
Sample 12 15 4 5 1 0 1 8 100
Census 6 8 15 14 2 1 100
aThe percentages are net of numbers resident in the eight urban centers reported in Central Bureau of Statistics (Vol. 11, Table V).
SOURCE: Central Bureau of Statistics (1971, Vol. 111, Table I).
TABLE 5.2 Cross-tabulation of the education of the migrants and the education of their fathers(per-
Education of the Mierant's education
-
Distribution of themigrant's father
No formal Standards education of the men
education
?!!!
Total aged 35-39 according1 4 5-8 1-6 t o the 1962 census
No formal education 96.6 91.2 81.5 48.5 75.6 72.7
Standards 1 - 4 2 .O 5.5 10.3 27.3 13.3 18.0
Standards 5-8 1.4 3.3 7.9 23.0 10.6 8.4
Forms 1 -6 0.3 1.2 0.5 0.9
Total 100.0 100.0 100.0 100.0 100.0 100.0
SOURCE: Central Bureau of Statistics (1968, Tables 17 and 19).
c o n ~ p a r a b l e age group. Therefore, migration does n o t appear t o be determined by the level of education of the fathers of the migrants. The men appear t o come from "ordinary"
rural backgrounds and families.
Another aspect of the relationship between education and rural-urban migration is the significant variation in the distribution of the levels of education among migrants from different provinces.* Central Province and to a certain extent Nyanza Province provide proportionately more men in the secondary education group. Conversely, Coast and East- ern provinces provide a low number. Eastern and Rift Valley provinces provide propor- tionately more men with n o formal schooling and Coast and Nyanza provinces provide a disproportionate number with only some primary education.
This variation could be the result of three factors: (1) variations between provinces in employment opportunities in the rural areas that lead t o migrations t o obtain employ- ment; (2) variations between provinces in the quality of primary education which deter- mines a student's ability t o compete for the limited number of secondary school admissions available in Kenya; or (3) an unequal distribution of secondary schools among provinces which restricts opportunities for higher education in Eastern, Coast, and Rift Valley provinces.
Given that rural families view formal education as an important means of purchasing entrance t o the urban formal sector, one would expect a high correlation between the extent of out-migration and both the availability and quality of rural educational opportu- nities. If successful entrance into the urban formal sector generates remittances t o rural areas, then the high out-~nigration areas have a greater capability t o expand and improve educational facilities. Therefore, the latter two of the three factors listed above probably explain most of the variations among provinces in the level of education completed by the migrants. If so, the type of out-migration observed from Eastern, Coast, and Rift Valley provinces may well reflect a disproportionately low level of rural employment opportunities within these provinces.
THE AGE DISTRIBUTION O F THE MIGRANTS
In part, the tendency for a disproportionate number of the rural young t o move t o the towns reflects the correlation between age and education. The rapid expansion in the provision of educational opportunities after independence means many of the better- educated Kenyans are relatively young.
According t o our migration model there are several additional economic reasons for the higher tendency of the young t o migrate: (1) the opportunity costs of moving and job search are lower for the young who have not become established as yet, have not acquired specific skills, or have not taken on immediate family obligations; (2) the young typically discount the future a t a lower rate; and (3) the young have a longer time horizon over which t o recover the higher costs associated with an urban move. Finally, various social and personal factors that serve to induce rural-urban migration have a great effect on young adults (Mitchell 1969, p. 178).
The 1968 survey confirmed the expected youthfulness of the migrants. The median age of the men a t the time of migration was between 22 and 23. More than 8 0 percent of the men were less than 3 0 at the time of their migration. As indicated in Table 5.3, the propensity t o migrate is consistently higher in the 20--24 age category. The age
*A chi-square test was used for the six provinces and two education groups, primary versus secondary.
The chi-square value was significant at the p < 0.01 level.
TABLE 5.3 The percentage distribution of the age of the men in each province as reported in the migration survey and the 1969 censusP
Province of birth Ages Total
Nyanza Sample Census Western
Sample Census Rift Valley
Sample Census Central
Sample Census Eastern
Sample Census Coast
Sample Census Total
Sample 25 41 17 13 4 100
Census 22 17 15 22 24 100
UPercentages are net of numbers resident in the eight urban centers as reported in Central Bureau of Statistics (1971, Vol. 11, Table V).
SOURCE: Central Bureau of Statistics (1970, Table 111).
distribution of the migrants is significantly different from that of the rural population at the p
<
0.05 level of a chi-square test.Although the proportion in the 25-29 age category is higher in the survey than in the census (except in Coast Province), the difference for most provinces is rather small.
The proportion of migrants over the age of 30 is considerably smaller than for the rural population. For the young, 15-19 years old, the sample and the census percentages are similar, except for Coast Province where there are proportionately more in the migration sample than in the census.
The extent of the dominance of younger men in the migration process suggests that all of the postulated explanations of why the young are more likely to migrate apply in Kenya for the postindependence period. The degree of determination of the migrants t o remain in urban areas can serve as one means for sorting out the relative importance of the economic and social explanations for the high propensity t o migrate among the young adults. We turn t o this aspect of the migration process in Chapter 9.