Results of the model of out-migration

The results of all three models (all individuals, men, and women) are presented in table 14 below. Individual characteristics are presented first and then variables are grouped in terms of the asset categories of the livelihoods framework.

Table 14. Results of model of out-migration

Odds Ratios

All Women Men

Gender (1/0) (I) (male reference) 1.757** Age (I) (15-19 reference)

12-14 0.789 0.975 0.659

20-24 1.696* 1.630 1.875

25-29 1.117 0.856 1.559

30 plus 0.253** 0.219** 0.367*

Never Married 0.797 0.697 1.072

Human Capital Assets

Education (I) (no education reference)

Some primary (1/0) 3.948** 4.773** 2.139

Completed primary (1/0) 4.108** 4.745** 3.068

Some secondary (1/0) 3.186* 3.489* 2.682

Completed secondary or more (1/0) 4.503** 5.873* 3.627* Natural Capital Assets

Cultivated Area (ha.) (H) 0.999 0.990 1.004

Social Capital Assets

Mingas (1/0) (H) 0.742 0.930 0.578

Labor-sharing (1/0) (H) 1.193 1.177 1.385

Previous out-migrant (H) 3.515** 3.869** 3.438**

Physical Capital Assets

Local oil employment(%)(C) 0.838 1.079 0.536*

Other local employment(%)(C) 1.301 1.430 1.031

Mediating Factors Social

Ethnicity of household (kichwa reference)

Shuar 0.891 0.809 0.835 Huaorani 1.270 1.216 1.156 Cofán 0.920 1.337 0.531 Secoya 0.270** 0.102** 0.389* Mixed 0.780 0.991 0.377 Accessibility

Travel time to market (hrs.) (C) 0.955 0.972 0.958

Constant 0.008** 1.219 0.013

Community Random Effect 0.051* 0.000 0.000

Log Likelihood -2030.1 -1119.1 -869.1

*p<.05, **p<0.01

Note: All dummy variables for years 1990-2001 were insignificant and are not shown

The final model with all individuals was estimated with 14754 person-year observations and 296 migration events due to the censoring discussed above and instances of missing data. The estimated coefficients of the model, β, are presented as odds ratios, equal to eβ. The odds ratios can be interpreted as the multiplicative effect of a one unit increase of the predictor on the probability of out-migration relative to the probability of no outmigration. Odds ratios that are greater than one indicate a positive association between the independent variable and out- migration and odds rations between 0 and 1 indicate a negative association. For categorical variables the odds ratios can be interpreted as the increase or decrease in odds of participation in comparison to a reference category.

In general very few of the household or community independent variables were found to significantly influence out-migration, and primarily the characteristics of individuals determined the odds of out-migration. The age of the individual was significant and negatively associated with migration indicating that the odds of migration decreases with each additional year in age. The specification of the model using age groups rather than a continuous variable for age reveals that the relationship between age and out-migration is actually curvilinear, and the odds of migration is higher in the 15-19 and 20-24 age groups than the 12-14 or 25-29 age groups. The odds of out-migration declined significantly for adults who are over 30. Gender was also

significantly associated with out-migration, with women being 1.7 times as likely to out-migrate as men. Finally, marital status of the individual is insignificant and people who are single were just as likely as those who were married or in a union to out-migrate.

Human capital was an important factor influencing out-migration as education was significant and positively associated with migration. The likelihood of migration increased with the level of education completed by individuals. Even those with just some primary education

were 3 times as likely to out-migrate as those with no education. Similarly, those who had completed primary and those with some secondary education were approximately 3 times as likely to out-migrate. Those who had completed a secondary education were most likely to out- migrate and were five times as likely to depart the community as those with no education. In a specification of the model not shown, the odds of migration among those who had completed their secondary education were significantly higher than those who had completed primary. At the household and community levels, the natural capital factors including the total land area of the household in 2001, was not found to be significantly associated with the odds of out-migration. The results suggest that cultivated area as specified in the model has little

influence on out-migration among the indigenous population.

Similarly, the social capital variables for the household were not significantly associated with out-migration, except for the migration experience of the household. Individuals were more than 3 times as likely to out-migrate after a previous member of the household had out-migrated from the community, suggesting that information from the experience of the first out-migrant influences the migration decision of other members of the household.

Surprisingly, neither the local employment opportunities nor various specifications of accessibility to markets and urban areas were found to be significantly associated with out- migration. Individuals in communities with local employment opportunities were just as likely to out-migrate as those in communities without these local opportunities. Similarly, those living in communities distant from local markets or from urban areas were just as likely to out-migrate as those close to urban areas.

Finally, there were few ethnic differences related to the likelihood of out-migration. Only the Secoya were found to differ from the other groups, and individuals who were Secoya

were far less likely to out-migrate from their communities in comparison to the other groups. Cofan, Shuar, Huaorani, and Kichwa individuals all had similar odds of out-migration.

Modeling males and females separately reveals just a few small differences in the factors that influence out-migration. For both men and women, the odds of migration are highest among the young age groups between 12 and 29 and then decline significantly after 30. Marital status is insignificant for both groups, despite the descriptive findings that indicated that a greater

percentage of females who out-migrated were married than males. Among both men and women a previous out-migration of a member of the household significantly increases the odds of out- migration. Both men and women were three times as likely to migrate if a previous member of the household had already out-migrated from the community.

The influence of education on the odds of out-migration, however, does differ between males and females. For men, only those who had completed a secondary education stood out as being more likely to out-migrate than the reference group, those with no education. Among men, individuals with all other levels of completed education had similar odds of migration as those with no education. Among women, however, individuals with any level of education had greater odds of out-migration than those with no education.

The final observed difference is the significance of the presence of an oil business near the community. The odds of migration were significantly lower for men living in communities where oil companies were active in the area. These individuals were only half as likely to out- migrate as those living in communities without active oil companies in the area.