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Improving the Targeting of Social Assistance in Albania: Evidence from Micro-simulations

  • Caterina Ruggeri LaderchiEmail author
  • Ramya Sundaram
  • Alexandru Cojocaru
  • Natsuko Kiso Nozaki
Chapter
Part of the Economic Studies in Inequality, Social Exclusion and Well-Being book series (EIAP, volume 8)

Abstract

Ndihma Ekonomike (NE), the largest social assistance program in Albania, is currently targeted through a two-stage process, combining geographical targeting with individual targeting at the local level. The program’s performance is relatively good, though recent analysis shows how the categorical filters applied to household selection restrict the coverage to a minority of poor households. Further, anecdotal evidence and focus group analysis shows that the application of the current eligibility criteria can be nontransparent and administratively cumbersome. This chapter exploits the availability of a detailed information from the 2008 LSMS and an updated poverty map (Betti et al. Updating poverty maps between censuses: A case study of Albania. In Ruggeri Laderchi and Savastano (eds). Poverty and exclusion in the Western Balkans – new directions in measurement and policy. Springer, 2012) to simulate budget-neutral improvements that could increase the coverage and the targeting performance of the program. The findings show that significant improvements in coverage of the bottom quintile could already be obtained by strengthening the link between municipal level allocations and poverty through a naïve poverty share approach (Elbers et al. Poverty alleviation through geographic targeting: how much does disaggregation help?, 2004). This chapter also presents a statistically derived proxy means testing measure. Adopting this indicator to screen beneficiaries could result in an improvement of the share of the benefits going to the bottom decile by more than 40 percentage points and could allow an increase by 33 percentage points of the coverage of this target group.

Keywords

Social Assistance Allocation Mechanism Poverty Index Block Grant Private Transfer 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

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Copyright information

© Springer Science+Business Media, LLC 2013

Authors and Affiliations

  • Caterina Ruggeri Laderchi
    • 1
    Email author
  • Ramya Sundaram
    • 1
  • Alexandru Cojocaru
    • 1
  • Natsuko Kiso Nozaki
    • 1
  1. 1.The World BankWashingtonUSA

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