Effect of rural inequality on migration among the farming households of Limpopo Province, South Africa

Abstract

This thesis describes a study undertaken in the semi arid areas of Limpopo among rural households with or without migrant workers in their households. The study aimed at analyzing and establishing the association between unequal distribution of land and other productive assets and rural household migration decisions; and to ascertain the relationship between migration remittances received by migration sending households and rural inequality in the migration sending economies. In essence, two important phenomena of inequality and migration are addressed simultaneously from two related angles: the effect of rural inequality on migration behaviour and the effect of migration (through cash and in-kind remittances) on rural inequality. A combination of explorative and confirmative economic analytical tools was used for empirical data analysis. Explorative analysis was meant to present distribution characteristics of the data including frequency analysis, descriptive statistics and cross tabulation; correlation and non-parametric analysis. In the confirmative analysis model specific deterministic relationships among variables or response models were used to confirm the existence of relationships. First, the Gini coefficient technique and Lorenz curves were used to measure inter household income and asset inequality. Factor Analysis (FA) was used to combine variables and create new but fewer factors; and logistic regression analysis LRA) was used to determine variables that positively or negatively affect migration. A survey was conducted among 573 rural households selected from 24 villages of Limpopo in the Central, Southern and Western Regions. Two types of research instruments were used. The first was a semi-structured village questionnaire to gather qualitative information about the villages by interviewing key informants. The second instrument was a structured household questionnaire, which provided information on household composition and characteristics, household income land and other assets, environmental issues, migration and remittances. The household head or his/her deputy responded to a major part of the questionnaire but the migrants responded to some of the migration and remittance related questions. Findings from the Gini coefficient measure and Lorenz curves indicated uneven assets distribution and that landlessness is common in Lebowa. However, comparatively, land and income are more evenly distributed than the other assets. The results of the correlation matrix indicate that there is a negative correlation between the presence of migrants and per-capita household assets and per-capita land ownership (-0.043 and – 0.126 respectively). A one tailed t test indicated that per-capita land is significantly related to the presence of migrants within households (p<05). The presence of migration in a household was also negatively correlated with adult equivalent landholding. Households with migrants tended to have smaller landholdings and the relationship between migration and other asset categories were negative, implying an inverse relationship between them and the propensity to migrate. Variables influencing migration were aggregated using Factor analysis and on the basis of the factor loadings four factors (components) with the largest loadings were identified as: household land and income factor, livestock factor, asset (farm and non farm) factor and lastly pension and household composition factor. The Logistic regression analysis (LRA) using a non-metric, dichotomous dependent ‘dummy variable for presence of migrants in households showed that: the presence of migrant(s) is significantly influenced by per-capita land, per-capita income, per-capita all assets, and total assets (p<05). The results show that a unit increase in value of per capita assets will result to 0.1 percent change in the odds ratio against migration; a unit increase in pension received by a member in a household will result in a 0.6 per cent change in odds ratio against migration; as pension money increases there would be less incentive for members of the household receiving it to migrate. However, a unit increase in per capita income will not result in any change in the odds ratio of migration. In the Central, Southern and Western regions of Limpopo households with smaller land holding per capita tended to have migrants, however, the pattern of migration from these areas does not support the hypothesis that higher inequality of land holding lead to higher out-migration. The Western Region, which has better land distribution than the other two regions, has a higher proportion of households with migrants than the other two regions. Thus, migration must be influenced by a complex association of variables other than just land. Livestock did not have significant influence on migration from the rural areas. This is not surprising for Limpopo, since the province is not well endowed with livestock as a form of asset. Nevertheless, households with migrants have higher total value of livestock than those without migrants. The empirical findings have shown that remittances are an important source of livelihood and the relationship between migration and rural inequality depend critically on how remittances and the losses and gains of human resources through migration are distributed across households. Different income sources add to income inequality but at different rates and extent. In the case of Limpopo, remittances account for a smaller percentage of total inequality (14.9%) than that of salaries and wages (72.3%); pensions contribute the least to the rural income inequality, contributing only 4.3%. This means that remittances are distributed more evenly than salaries and wages among the households that receive them. It means also that even some migration sending households at the lower end of the income spectrum in rural areas have access to some migrant remittances. Income inequality decreases considerably when migrant remittances are combined with income from other sources; in our case it drops by fifteen percentage points from 0.62 to 0.47. The influence of migration remittances upon income inequality will tends to become more favourable as migration opportunities spread throughout the villages.