Do remittances affect labour participation decisions and hours worked? Evidence from Ethiopia

Abstract

The present study examines the impact of remittances (foreign and domestic) on labour participation decisions and hours worked in Ethiopia. By exploiting nationally representative panel data obtained from the Ethiopian Socio-Economic Survey (ESS) 2013/14 and 2015/16, this study finds that receiving foreign remittances has a negative impact on the adult labour participation decisions and hours worked in Ethiopia. Its effect is also conditional on occupation, gender, and residential location. However, the impact of domestic remittances on the decision to participate in the non-domestic labour activity is mixed by residential location. Labour participation decisions for rural adults has increased but decreased for the urban. Its effect on the labour participation decisions in temporary paid jobs is also positive. On the other hand, this study finds that child labour participation decisions and hours worked are neither affected by the amount of foreign and domestic remittances nor by remittance-receiving status. The econometric technique applied logit and Tobit models, and a robustness check has been carried out using the per adult equivalent amount of remittances. This study suggested that further studies to identify causes for the negative effects on labour participation decisions and hours worked are critical to designing an appropriate policy. However, since it increases adult labour participation in rural areas and participation in temporary paid jobs, enabling policies to increase domestic remittances are highly important.

Keywords:

• Labour participation
• hours worked
• foreign remittance
• domestic remittance
• Ethiopia

JEL classifications:

• F22
• F24
• F65
• J01
• J08

PUBLIC INTEREST STATEMENT

Labour is a key resource for economic growth and development.However,its participation in the labour market and hours used for work can be affected by different factors. In this regard, the impact of remittances on labour market actvity is a priori indeterminate. Documented evidences reveal both positive and negative impacts of remittances. Therefore, analyzing how remittances are affecting the labour participation decisions and hours worked in a given economy or community is crucial for a timely and necessary intervension.

Acknowledgements

The authors would like to thank the Editor and the anonymous referee.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Statement on data availability

The data that support the findings of this study are available from the corresponding author upon reasonable request.

Notes

1. Reservation wage rate is the minimum wage rate at which a worker would be willing to accept employment (Borjas, 2016).

2. ESS2 and ESS3 are the second and the third Ethiopian Socio-economic Survey (ESS) conducted in 2013/14 and 2015/16. ESS is a collaborative project between the Central Statistics Agency of Ethiopia (CSA) and the World Bank Living Standards Measurement Study (LSMS) with the objective of availing panel data for researchers and policymakers.

3. Our study considers labour participation decision and hours worked in non-domestic activities.

4. Full derivation of the first-order condition is available with authors and can be send upon request.

5. Detail discussions on the disincentive, education and substitution effect of remittances are available in the background section.

6. 18,379 individuals of age 7–64 and 18,127 individuals of the same age group were interviewed in 2013/14 and 2015/16 survey years, respectively.

7. Remittance in the ESS module includes all kinds of private transfers in the form of cash and in-kind converted into monetary values.

8. The approach has three advantages. First, due to recall problems, significant errors are most likely to occur in the measurement of remittance amounts. Second, since the questionnaire is mainly administered to the household head if another member receives the remittance, the head may recall the remittance receipt but may not accurately recall the amount of remittance. Third, dealing with impacts of living in a remittance-receiving household or not helps to capture if the absence of a remittance sender member due to the migration cause any positive or negative effect other than the effect of the remittance.

9. ETB is Ethiopia’s official currency called Ethiopian Birr and the conversion rate into $ applied the simple average of the two-year weighted average exchange rates. 1 USD in 2013/14 and 2015/16 was ETB 19.07 and 21.10, respectively (National Bank of Ethiopia, 2013 and 2015 reports). Thus, the two-year average exchange rate is ETB 20.08.

10. The shock variable is used to control if shocks that occur during the year prior to the data collection period affect the remittance inflow and labour market outcomes. The most important shocks can be agricultural product loss, wealth or income loss, health related shocks etc.

11. Due to the lack of variability in many of the dependent variable observations, a substantial number of observations are found to be dropped from the fixed-effect estimation technique. Hence, the random effect result is added for result constancy check.

12. Winsorization is the replacement of outlier observations with a limiting extreme value. Because it avoids loss of observations, it is an important strategy of treating outliers than trimming.

13. Wealth as an important household variable for migration and remittance selection is controlled through an index predicted by the principal component analysis (PCA) method. The prediction used several assets from household durables and housing characteristics. From household durables, we used Kerosene stove, Butane stove, Electric stove, Blanket, Mattress, bed, Watch/clock, Telephone, Cell phone, Radio, tape, TV, Dish antenna, Sofa, Bicycle, Motorbike, Cart (hand), Animal cart, sewing machine Weaving equipment, Mitad-electric, Mitad-modern, Refrigerator, Car, Gold/silver, Wardrobe, Storage shelf, Biogas stove, Water storage pit, Sickle, Axe, Pick Axe, Plough, Plough (modern) and Water pump. The following indicators are used for housing characteristics: Floor, Wall, Kitchen, Roof, Light source, Toilet, Number of rooms, Drinking water, cooking fuel and Own home.

Additional information

Funding

The authors received no direct funding for this research.

Notes on contributors

Haile Ademe Ayalew

Haile Ademe Ayalew is PhD scholar in Humanities and Social Science department at Indian Institute of Technology, Roorkee and an academic staff in Economics department, Debre Tabor University, Ethiopia.

Pratap C. Mohanty

Pratap C. Mohanty (PhD) is Associate Professor of Development Economics at Indian Institute of Technology, Roorkee