Understanding poverty dynamics in Ethiopia: Implications for the likely impact of COVID‐19

• Published date: 01 November 2021
• Author: Tseday Jemaneh Mekasha,Finn Tarp
• Date: 01 November 2021
• DOI: http://doi.org/10.1111/rode.12841

1838 

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       Rev Dev Econ. 2021;25:1838–1868.

wileyonlinelibrary.com/journal/rode

Received: 24 March 2021 

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  Revised: 9 September 2021 

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  Accepted: 11 September 2021

DOI: 10.1111/rode.12841  

SPECIAL ISSUE ARTICLE

Understanding poverty dynamics in Ethiopia:

Implications for the likely impact of COVID- 19

Tseday JemanehMekasha

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FinnTarp

Department of Economics, University of 

Copenhagen, Copenhagen K, Denmark

Correspondence

Tseday Jemaneh Mekasha, Department 

of Economics, University of 

Copenhagen, Øster Farimagsgade 5, 

Building 26, DK- 1353 Copenhagen K, 

Denmark.

Email: tjm@econ.ku.dk

Funding information

This study was prepared under the 

ExPov/DEEP project funded with UK aid 

from the UK government and managed 

by Oxford Policy Management (OPM)

Abstract

We  aim  at  identifying  vulnerable  groups  that  face  a 

higher risk  of falling  into poverty  due to  the COVID- 19 

pandemic. Applying a synthetic panel data approach, our 

analysis of  poverty  and  vulnerability transitions  during 

the pre- COVID period shows not only a high rate of pov-

erty persistence in Ethiopia but also a high probability of 

moving from  vulnerable  nonpoor  status  to poor  status. 

Given  the  observed  persistence  of  poverty  and  greater 

risk of  downward  mobility, even  in  the pre- COVID  pe-

riod, it is highly likely that poverty persistence and down-

ward  mobility  will  be  aggravated  during  the  current 

pandemic.  A  detailed  poverty  profiling  exercise  shows 

that households  where  the household  head  is less  edu-

cated, engaged  in the  service sector,  self- employed, and 

a domestic worker  are population segments  with a high 

rate of downward mobility. As the emerging evidence on 

the socioeconomic impact  of  COVID  shows,  these seg-

ments of the population are also the ones relatively more 

affected by the pandemic. Overall, the pandemic is likely 

to result in a serious setback to the progress made in pov-

erty  reduction  in  Ethiopia.  Poverty  reduction  policies 

should thus target not only the existing poor but also the 

vulnerable nonpoor.

KEYWORDS

Ethiopia, mobility, poverty dynamics, synthetic panel, 

vulnerability

This  is  an  open  access  article  under  the  terms  of  the  Creative  Commons  Attribution-NonCommercial License,  which  permits  use, 

distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes. 

© 2021 The Authors. Review of Development Economics published by John Wiley & Sons Ltd.

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MEKASHA and TARP

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INTRODUCTION

Ethiopia has witnessed rapid economic growth since the mid- 2000s. For instance, over the  sample 

period considered  in  this study  (2011– 2016),  the country  registered  an annual  gross  domestic 

product (GDP) growth rate above 9% (World Bank,2020a). Poverty reduction through sustained 

economic growth has been  one of the  overarching development objectives in Ethiopia,  particu-

larly since  the start of  the  new millennium. Therefore,  the government  of Ethiopia  has imple-

mented various  national  development plans  and  strategies  with a  particular  focus  on poverty 

reduction. During  the period  2010/2011– 2015/2016,  the strong  economic growth  performance 

matches visible progress in poverty reduction. In  particular, between 2010/2011 and 2015/2016, 

the proportion of people living  below the national poverty line decreased by 21%,  from 29.6% to 

23.5% (World Bank,2020a). Compared  to the share  of people living  below the national  poverty 

line in  2000  (44.2%), this  amounts  to a  20.5  percentage point  decrease  and can  be  considered 

major progress (World Bank,2015).

However, there  is visible  spatial  heterogeneity in  terms  of  the extent  of  poverty  reduction. 

For instance, between 2010/2011  and 2015/2016,  while urban  poverty decreased  by 42%,  rural 

poverty decreased  by  16%.  See also  Stifel  and Woldehanna  (2014) for  a  detailed  discussion of  

poverty trends  during 2000– 2011 and  the heterogeneities  in the  observed trends. In particular, 

these authors document steady but uneven progress during the period in question— while urban 

areas experienced the greatest gains in the first half of the decade, rural areas realized their gains 

in the latter half of the decade.

In the current changing world, maintaining such gains in poverty reduction appears to be a 

major challenge as  adverse unanticipated shocks increase  the risk of  vulnerability and there-

fore impede the progress made in poverty reduction. This is particularly the case in the context 

of  Ethiopia as  shocks related  to food  and  fuel prices,  heavy reliance  on rain- fed  agriculture, 

recurrent droughts,  internal  conflicts, and  the  recent desert  locust  invasion are  likely  to in-

crease the vulnerability of households, particularly those living in rural areas. In addition, the 

current COVID-  19 pandemic, apart from its immediate impact on the health of Ethiopian citi-

zens, is likely to push vulnerable households into poverty as the various containment measures 

are likely to decelerate economic activity  by slowing down the production  and distribution of 

goods and  services, among others.  It is  thus important to  identify both  the poor and  the vul-

nerable nonpoor and to  profile their socioeconomic characteristics. This  can help us not  only 

to understand the factors responsible for poverty transitions and lack thereof but also to assess 

which sections  of the  society are  likely to  be highly  affected by  the impact  of the  COVID- 19 

pandemic.

In view of  the above,  this study aims  at taking a  fresh look at  poverty dynamics in  Ethiopia 

during the  COVID- 19 pandemic.  Analysis of  poverty  dynamics requires observing  the  poverty 

status of units at  different points  in time,  and this  requires the  use of  panel data.  However, as 

a  large  and  nationally  and  subnationally  representative panel  data  set  is  lacking  in  Ethiopia, 

we employ  the  synthetic panel  data approach,  following  Dang and  Lanjouw  (2013) and  Dang 

et al. (2014),  using  the  last  two  rounds  of  the  Household  Consumption  Expenditure  (HCE) 

 survey (2010/2011 and 2015/2016) data.

JEL CLASSIFICATION

I31; I32; D31; O55