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\hypersetup{pdftitle={The Impact of Farmer Field School Training on Productivity and Crop Income: Evidence from Smallholder Maize Farmers in Oromia, Ethiopia},pdfauthor={Admassu Tesso Huluka},pdfsubject={Tropentag 2016: Abstract},pdfkeywords={Crop economic income, difference in difference, impact evaluation, productivity, propensity score matching},pdfpagemode=None,colorlinks=true}
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\parbox[b]{13.4cm}{\centering \large{\textbf{Tropentag, September 18-21, 2016, Vienna, Austria}}\\[1ex] \Large{``Solidarity in a competing world ---\\fair use of resources''\\[2ex]}}
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\Large{\textbf{The Impact of Farmer Field School Training on Productivity and Crop Income: Evidence from Smallholder Maize Farmers in Oromia, Ethiopia\footnote{\textbf{Contact Address:} Admassu Tesso Huluka, Association for Strengthening Agricultural Research in Eastern and Central Africa (ASARECA), Capacity Building and Knowledge Transfer Theme, Cheleleki, Nekemte, Ethiopia, \mbox{e-mail}: \email{admassutesso@gmail.com}}\\[0.8ex]}}
\normalsize{\textsc{Admassu Tesso Huluka}}
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\begin{itemize*}
\item[]{\small{\textit{Association for Strengthening Agricultural Research in Eastern and Central Africa (ASARECA), Capacity Building and Knowledge Transfer Theme, Ethiopia}}}
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\index[author]{Huluka, Admassu Tesso}
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\textbf{Abstract}
\begin{abstract}
\normalsize{
This study examines the impact of Farmer Field School (FFS) training programme on productivity and the net crop income of the smallholder farmers. The FFS programme was sponsored by the Ethiopian government and launched in 2010. The study aims to compare the impact of the training on productivity and net crop income of those FFS graduate sand non-FFS graduate maize farmers in Oromia, Ethiopia. For this, panel data were collected in two rounds from 446 randomly selected households of three districts consisting of 218 FFS graduate farmers and 228 non-FFS graduate farmers. The analytical procedure has involved three stages: in the first stage, descriptive analysis was used to detect existence of difference in the outcome indicators between the two farmer groups. In the second stage, a semi"=parametric impact evaluation method of propensity score matching with several matching algorithms was applied. In the third stage, difference"=in-difference was used as robustness check in detecting causality between programme intervention and the change in outcome indicators. The result shows that the crop productivity growth rate of the FFS graduate farmers was statistically lower than those of non FFS graduates. However, net crop income growth rate of the FFS graduate farmers was not statistically different from those of non-FFS graduates. In most cases, FFS graduate farmers became heavily involved in various mandatory meetings and other activities thereby reducing the time they had for their agricultural activities.  Consequently, FFS graduate farmers allocated statistically less family labour per hectare than non-FFS graduates. Following these findings, a number of policy recommendations are suggested.   }

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\noindent \textbf{Keywords:} Crop economic income, difference in difference, impact evaluation, productivity, propensity score matching
\index[key]{Crop economic income}
\index[key]{Difference in difference}
\index[key]{Impact evaluation}
\index[key]{Productivity}
\index[key]{Propensity score matching}
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