Abstract

In most developing countries, such as Ethiopia, rural-urban migration is perceived as disrupting the rural areas’ labor market and leading to resource allocation from the agriculture sector to the manufacturing and service sector while hurting the former. The key concern here is that rural-urban migration presents a loss of human capital for migrant-sending rural areas, which will leave subsistence agriculture, dominated by smallholder farmers, without the required labor force for the agriculture sector and, in turn, hurt food production thereby increasing food insecurity in the economy. However, such concern neglects the catalytic role of labor mobility in making the rural labor and land market efficient which improves allocation of economic resources across sectors and spatially. Hence, it is worth revisiting the possible benefit of labor mobility for rural growth. Studies on the impact of rural-urban migration on the rural economy have produced mixed results. Some showed that the rural-urban migration does not affect agricultural sector, while others found evidence of a decline in labor input among households left behind. However, there is some evidence that rural-urban migration reduces disguised unemployment in the rural labor market and enhances land use intensity.
This study is a comprehensive exploration that provides new empirical evidence to better understand the impact of labor mobility on the border rural economy transformation by studying households’ participation in origin communities factor markets pre- and post-migration. The study contributes to the development economics literature using evidence from Ethiopia in two main ways. First, it contributes to the nascent but burgeoning literature in Africa, that demonstrate the role of labor mobility in facilitating rural transformation. The second contribution is related to the rich nature of the panel data used that allows rigorous analysis of impact of migration on a wide range of outcomes.

We aim to measure the impact of rural-urban migration, in this regard, there are two fundamental problems: i) the nonrandom selection of households into migration, and ii) the would-be outcome if migrant households did not send out migrants (missing data). The key concern attached with the nonrandomized selection is that observable and unobservable factors affect the outcome and migration decision making of households differently. This biases the impact measurement. Thus, the best way to assess the impact is to identify the missing data through statistical estimation of the counterfactual from a pool of without-migrant households. The robustness of the impact analysis is conditioned on how the created comparison, without-migrant household group, is statistically similar to the migrant household group. We apply a nonrandomized impact analysis method called nonparametric pre-processing matching techniques for parametric outcome analyses. Such empirical analysis requires a multitopic longitudinal dataset. The study uses the ten-year-long Ethiopian Socioeconomic Panel Survey (ESPS), a panel household data collection project conducted by the Ethiopian government in collaboration with the World Bank Living Standards Measurement (LSMS). The ESPS is a rich panel survey conducted in two phases: the first covers the period 2011 to 2016, and the second covers the period 2019-2022. The longevity of the panel data offers the opportunity to study how a change in economic development model following the change in government in Ethiopia in 2018 influences the impact of rural-urban migration on rural labor supply, land use, and agriculture outcomes.

The result indicates that labor mobility has a positive impact on the intensity of labor use, agriculture output per capita, and land rental markets. This positive impact is observed regardless of government ideology and ideological change in public policy, though the magnitudes of the impact are different. The positive ATT value for cultivated/cropland per capita reaffirms that the lost labor in rural areas does not leave the rural land uncultivated and hurt agriculture production. Instead, households with migration increased their family labor supply than it would be the case if the household is without migration by an equivalent of 120 and 69 days during pre- and post-government change, respectively. This implies that migration reduces disguised unemployment in rural areas. The reduction in surplus labor in rural areas is expected to facilitate the rise in labor productivity and output per worker; hence, we observe positive ATT for output per worker from the results in both scenarios, by about 1256 Birr and Birr 3540 in pre and post government change periods, respectively. Also, the rising output per worker suggests that migration enables the remaining household members in migrant-origin households to adequately feed off their land. The results also attest that migration plays a role in creating an efficient rural land market. Table 5 shows that the share of households renting out land is higher by 1.2 and 1 percentage points with migration than without during the pre- and post-government change eras, respectively. Thus, migration improves the efficiency of the land markets, too.