Micro-econometric and Micro-Macro Linked Models: Impact of the National Agricultural Advisory Services (NAADS) Program of Uganda—Considering Different Levels of Likely Contamination with the Treatment

Samuel Benin (), Ephraim Nkonya (), Geresom Okecho, Josee Randriamamonjy, Edward Kato, Geofrey Lubade and Miriam Kyotalimye
Additional contact information
Samuel Benin: International Food Policy Research Institute (IFPRI)
Geresom Okecho: National Agricultural Advisory Services
Edward Kato: International Food Policy Research Institute (IFPRI)
Geofrey Lubade: National Agricultural Research Organization
Miriam Kyotalimye: Association for Strengthening Agricultural Research in Eastern and Central Africa

A chapter in Development Policies and Policy Processes in Africa, 2018, pp 85-95 from Springer

Abstract: Abstract An important problem in causal inference and estimation of treatment effects is identifying a reliable comparison group (control observations) against which to compare those that have been exposed to the treatment (treated observations). It is common knowledge that the estimate obtained by the difference in the values of the indicator of interest associated with the two groups could be biased due to lack of overlap in the covariate distributions or common support between the treated and control observations (Dehejia and Wahba 2002; Imbens and Wooldridge 2009). This is especially problematic with non-experimental control observations (Dehejia and Wahba 2002) in which case combining propensity score matching and regression methods has been suggested to yield more consistent estimates of the treatment effect than using either method alone (Imbens and Wooldridge 2009). Matching removes self-selection bias due to any correlation between the observable (pre-treatment) covariates and the dependent variable, while regression isolates the effect of change in the covariates on change in the dependent variable over the period of the treatment. Using the combined approach, this paper discusses the effect of using different sets of control groups on estimates of treatment effects of the agricultural extension system in Uganda, the National Agricultural Advisory Services (NAADS) program.

Keywords: National Agricultural Advisory Service (NAADS); Agricultural Extension System; Control Observations; Dehejia; Treatment Observation (search for similar items in EconPapers)
Date: 2018
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:aaechp:978-3-319-60714-6_4

Ordering information: This item can be ordered from
http://www.springer.com/9783319607146

DOI: 10.1007/978-3-319-60714-6_4

Access Statistics for this chapter

More chapters in Advances in African Economic, Social and Political Development from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().