Table 9 Review of some recent studies...

Table 9

Review of some recent studies about agricultural extension and farmer field school programs

Country	Research methods^a	Treatment of the program^b	Core outcome variables^c	Effect of the program	References
(1)	(2)	(3)	(4)	(6)	(7)
China	Descriptive comparisons	STB program	Maize and wheat yield, and nitrate use efficiency (NUE)	− About 500 and 600 kg per ha increase in wheat and maize yield, respectively − NUE increased significantly for both wheat and maize production	Zhang et al. (2016)
China	RCT	FFS with sustainable and low-carbon farm management technologies	Farming knowledge acquisition among rice farmers	− About 7.6% increase in knowledge, with a heterogeneous treatment effect − No results about rice yield, and carbon emissions related to rice production	Guo et al. (2015)
Indonesia	DID	FFS + IPM	Rice yields Pesticide use	− No significant impact observed, either in increasing yield or decreasing insecticides	Feder et al. (2004)
Vietnam	DID	FFS + IPM	Knowledge on IPM, pesticide use and rice yield	− About 56.6% better score on knowledge gain; no significant increase on rice yield	Rejesus et al. (2012)
Thailand	DID	FFS + IPM (over three-year period)	Chemical pesticide reduction, and rice productivity	− Significant reduction of the pesticide application − No effect on rice yield increase	Praneetvatakul and Waibel (2006)
Sri Lanka	RCT	FFS + IPM (over five- year period)	Rice production	− Significant reduction of insecticide application − More likely practicing soil fertility management	Tripp et al. (2005)
Peru	PSM	FFS + IPM	Knowledge gain and potato productivity	− About 14% points increase of farming knowledge − No direct estimation about potato yield	Godtland et al. (2004)
East Africa (incl. Kenya, Tanzania and Uganda)	DID, PSM and covariate matching	FFS + IPPM	Crop productivity Livestock productivity Agricultural income	− Crop productivity increased by 80% in Kenya, and 23% in Tanzania − Livestock production increased 31% in Kenya, and 26% in Uganda − Agricultural income increased by 104% in Tanzania, but much less in Kenya and Uganda	Davis et al. (2012)
Uganda	RDD	Extension services and NGO-supported model farmer and community promotion	Advanced maize seeds (HYV) adoption, and food sufficiency	− Minimum impact on adaptation of HYV seeds − About 5.4% points increase of food sufficiency	Pan et al. (2018)
Uganda	DID + FE	Agricultural extension with ICT and SMS	Crop structure, and maize productivity	− It has changed crop choices, more commercially oriented crops − However, no increase in maize productivity	Van Campenhout (2017)
Mozambique	RCT	AE through contact farmers (CFs), SLM	Technology adoption, and maize yield (revenue per hectare)	− About 19.6% increase of technology adoption among CFs − Increase contact farmers' maize yield about 0.13–0.24 standard deviation − No further effects for other farmers	Kondylis et al. (2017)

Country	Research methods^a	Treatment of the program^b	Core outcome variables^c	Effect of the program	References
(1)	(2)	(3)	(4)	(6)	(7)
China	Descriptive comparisons	STB program	Maize and wheat yield, and nitrate use efficiency (NUE)	− About 500 and 600 kg per ha increase in wheat and maize yield, respectively − NUE increased significantly for both wheat and maize production	Zhang et al. (2016)
China	RCT	FFS with sustainable and low-carbon farm management technologies	Farming knowledge acquisition among rice farmers	− About 7.6% increase in knowledge, with a heterogeneous treatment effect − No results about rice yield, and carbon emissions related to rice production	Guo et al. (2015)
Indonesia	DID	FFS + IPM	Rice yieldsPesticide use	− No significant impact observed, either in increasing yield or decreasing insecticides	Feder et al. (2004)
Vietnam	DID	FFS + IPM	Knowledge on IPM, pesticide use and rice yield	− About 56.6% better score on knowledge gain; no significant increase on rice yield	Rejesus et al. (2012)
Thailand	DID	FFS + IPM (over three-year period)	Chemical pesticide reduction, and rice productivity	− Significant reduction of the pesticide application − No effect on rice yield increase	Praneetvatakul and Waibel (2006)
Sri Lanka	RCT	FFS + IPM (over five- year period)	Rice production	− Significant reduction of insecticide application − More likely practicing soil fertility management	Tripp et al. (2005)
Peru	PSM	FFS + IPM	Knowledge gain and potato productivity	− About 14% points increase of farming knowledge − No direct estimation about potato yield	Godtland et al. (2004)
East Africa (incl. Kenya, Tanzania and Uganda)	DID, PSM and covariate matching	FFS + IPPM	Crop productivityLivestock productivityAgricultural income	− Crop productivity increased by 80% in Kenya, and 23% in Tanzania − Livestock production increased 31% in Kenya, and 26% in Uganda − Agricultural income increased by 104% in Tanzania, but much less in Kenya and Uganda	Davis et al. (2012)
Uganda	RDD	Extension services and NGO-supported model farmer and community promotion	Advanced maize seeds (HYV) adoption, and food sufficiency	− Minimum impact on adaptation of HYV seeds − About 5.4% points increase of food sufficiency	Pan et al. (2018)
Uganda	DID + FE	Agricultural extension with ICT and SMS	Crop structure, and maize productivity	− It has changed crop choices, more commercially oriented crops − However, no increase in maize productivity	Van Campenhout (2017)
Mozambique	RCT	AE through contact farmers (CFs), SLM	Technology adoption, and maize yield (revenue per hectare)	− About 19.6% increase of technology adoption among CFs − Increase contact farmers' maize yield about 0.13–0.24 standard deviation − No further effects for other farmers	Kondylis et al. (2017)

Note(s): ^aAbbreviations used in Column 2: DID: Difference-in-Difference estimation; FE: Fixed Effect estimation; PSM: Propensity Score matching; RCT: Randomized Controlled Trail; RDD: Regression Discontinuity Design; ^bAbbreviations used in Column 3: AE: Agricultural Extension; FFS: Famer Field School; IPM: Integrated Pesticide Management; IPPM: Integrated Pest and Production Management; ICT: Information and Communication Technologies; SMS: Short Messages; SLM: Sustainable Land Management; T&V: Training and Visiting model of agricultural extension; ^cAbbreviations used in Column 4: NUE: Nitrate Use Efficiency

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