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Degree of socio-economic marginality in Ethiopia, using the following conditional indicators of the health sector: 1. Illiteracy rate (% of population (>5years) not being able to read and write in their native language) 2. Net not enrolment ratio primary school (total no. of students (age 7-14) being not enroled, expressed as % of total pop. in primary school age) 3. Net not enrolment ratio secondary school (total no. of students (age 15-18) being not enroled, expressed as % of total pop. in secondary school age) Data source: 1. Central Statistical Agency(CSA), ICF International (2012): Ethiopia Demographic and Health Survey 2011. Addis Ababa, Ethiopia; Calverton, USA 2./3. Central Statistical Agency (CSA) (2007): Population and Housing Census. Atlas of Ethiopia 2007. Washington DC, USA
The current study explores the determinants of long-term growth in small-scale agriculture in a rural area of Rwanda, with a special focus on intergenerational mobility of income and poverty over the past two and a half decades. We use a unique panel dataset that spans over a 26 year-period, constructed from two waves of household surveys conducted in Nyabihu, the most densely populated rural district in Rwanda. The first wave of data was collected by the International Food Policy Research Institute (IFPRI) from 190 respondents in 1986. While in the second survey done in 2012, we followed the same households and the households of family members who split off from them in order to construct a dataset of extended families that consists of 164 original households and 200 split-off households. The analysis of the demographic structure shows that the sample population has increased by 88 percent over the past two and a half decades. Econometric results indicate that human fertility is positively associated with initial household income, and household head’s age, but inversely correlated with mother’s age at marriage and mother’s education. In this context, we found evidence of Boserup effect in the study area. Accordingly, there is a positive and statistically significant correlation between household size and agricultural intensification as well as farm productivity. However, the obtained inverse association between the family size and per capita expenditure speaks for immediate policy to reduce the growth of population in the study area. The findings from Cobb-Douglass function estimation suggest that factors such as labor, capital, land, and land quality are the key drivers of output growth. Agricultural production in the study area is characterized by decreasing returns to scale economies, with high output elasticities of labor (0.48), followed by lower elasticities of capital (0.17) and land (0.13). However, productivity of labor will not continue to grow at the pace of consumption demand, considering decreasing marginal returns of labor and the prevailing level of population growth. Pathways to less labor intensive agricultural and off-farm employment are highly desirable. The use of cellular phones by farmers has significantly increased output level and income in recent years. The study finds that agricultural output of mobile phone users is at least 38 percent higher than output of non-users, whereas their income level is about 26 percent higher. The provision of network infrastructure and electricity in the study area can enhance agricultural development through increased adoptions of telecommunication technology by smallholder farmers. The transmission matrices and regression results suggest strong income mobility and relatively small persistence of assets holding across generations, especially with regard to land and livestock which are considered as eminent assets in the study area. Everything else being equal, a ten percent increase in parental landholding is associated with a three percent increase in available land for the children. Similarly, an increase of ten percent in parent’s livestock is associated with a two percent increase in livestock for their offspring. Besides, the data suggest a relatively small degree of persistence of poverty across generations in the study area. Therefore, key policy options should not only aim at controlling the population growth, but also ensuring a fair distribution of wealth to ensure poverty reduction and rural development in Rwanda.