Research gaps and questions

1.2.1 Research objective 1

The first essay of this dissertation addresses the role of extension in fostering knowledge and adoption of complex agricultural technologies such as ISFM. A considerable body of literature concludes that providing training to farmers enhances their knowledge and adoption of tech-nologies (e.g. De Brauw et al., 2018; Feder et al., 2004; Fisher et al., 2018; Godtland et al., 2004; Kondylis et al., 2017; Nakano et al., 2018; Ogutu et al., 2018; Takahashi, Mano, et al., 2019). Yet, evidence is less clear when it comes to diffusion to peers, a crucial determinant of success of farmer-to-farmer extension. While a series of studies finds positive effects of training some farmers on their neighbors’ knowledge or behavior (Fisher et al., 2018; Nakano et al., 2018; Takahashi, Mano, et al., 2019), others suggest that neither knowledge (Feder et al., 2004;

Rola et al., 2002; Tripp et al., 2005) nor technology diffusion (Kondylis et al., 2017; Van den Berg & Jiggins, 2007) to peers takes place. Niu and Ragasa (2018) observe that while knowledge transmission from extension agents to lead farmers and from there to other farmers occurs, important pieces of information get lost along the way due to selective attention of both

communicators and recipients. Yet, other research suggests that incomplete information trans-mission can be counterbalanced by reminders of commonly neglected information (Hanna et al., 2014). Overall, the available evidence shows that farmer-to-farmer technology dissemina-tion is a multifaceted process that does not occur automatically. It is reasonable to assume that this is particularly true in the case of system technologies, i.e. sets of technologies that should be used in combination, where farmers have to learn about each individual practice as well as the importance of applying them jointly. While there is an emerging strand of literature on farmer-to-farmer extension, studies do mostly not focus on the integrated uptake of system technologies, despite the high policy relevance. In addition, there is hardly any evidence on how incomplete information spillovers from extension beneficiaries to their neighbors can be counterbalanced by additional interventions. This leads to the first set of research questions of this thesis:

(1) Does farmer-to-farmer extension and an additional intervention in form of a video in-crease knowledge and adoption of ISFM?

(2) Do the interventions have differential effects on farmers who are actively involved in extension activities and non-involved farmers in the same communities?

(3) Do gains in ISFM knowledge increase its adoption?

(4) Which forms of knowledge are particularly relevant?

The first essay addresses these questions by means of a randomized controlled trial (RCT) and data from 2,382 farm households in the Ethiopian highlands. In addition to the experimental set-up, matching techniques and a causal mediation analysis are used to answer the research questions.

1.2.2 Research objective 2

The second and third essays focus on the effects of ISFM adoption at the plot and household level, respectively. There is a well-established body of literature on the plot- and household-level impacts of individual or combined uptake of a large variety of agricultural or natural re-source management practices (e.g. Abro et al., 2017, 2018; Becerril & Abdulai, 2010; Di Falco et al., 2011; Jaleta et al., 2016; Kassie et al., 2010; Khonje et al., 2015, 2018; Manda et al., 2016; Noltze et al., 2013; Takahashi & Barrett, 2014; just to mention a few); some of which analyze technology combinations that can be classified as ISFM, such as intercropping, conser-vation tillage or improved seeds (Arslan et al., 2015; Kassie et al., 2015; Teklewold et al., 2013).

However, relatively few studies using micro-level data look into the combined use of organic and inorganic fertilizers with improved seeds, the core ISFM technologies, and those that exist

(Adolwa et al., 2019; Wainaina et al., 2018) only estimate effects on productivity, crop or household income. Yet, as concluded in a recent review article by Takahashi, Muraoka, et al.

(2019), more evidence on ISFM beyond these traditional yield and income effects is needed.

This is particularly important since ISFM usually goes along with substantial investments of capital and labor for the purchase, preparation, transportation and application of inputs. More-over, much of the evidence on the yield-enhancing effects of ISFM stems from well-managed trial fields rather than plots managed by ‘regular’ smallholders. Since ISFM is considered knowledge- and management-intensive, effects achieved by the latter might differ from those achieved under best agricultural practices on trial plots (Jayne et al., 2019). Hence, in order to draw a more comprehensive picture on the impacts of ISFM in resource-constrained small-holder systems, evidence on the profitability of additional resource investments is required. The second article of the thesis addresses this research gap with the following question:

(5) What are the plot-level effects of ISFM adoption on land productivity and net crop value, as well as on labor demand, labor productivity and financial returns to labor?

More precisely, the paper focusses on the effects of organic fertilizer, inorganic fertilizer, im-proved crop varieties and combinations thereof on 6,247 wheat, maize and teff¹ plots managed by 2,040 Ethiopian farm households. The study distinguishes between two different agroeco-logical zones, and uses a multinomial endogenous switching model to tackle issues with self-selection.

Lastly, it is important to assess the broader implications of adopting a capital- and labor-inten-sive system technology at the household level. Since farm households commonly diversify their livelihoods between different agricultural and non-agricultural economic activities, adopting ISFM for some crops might imply reallocation effects of household resources (in particular labor), as suggested by Takahashi and Barrett (2014) for example. Hence, net implications for a household are not clear, even if ISFM goes along with productivity increases. For instance, household food security can be influenced by both farm and off-farm income (Babatunde &

Qaim, 2010). Hence, while agricultural productivity gains associated with a technology can positively influence food security, this effect might be muted if technology adoption withdraws resources from other economic activities. Another issue of concern are possible effects on chil-dren’s education, which are hardly addressed in studies on technology adoption (with the

1 Teff is a small cereal grain (annual grass) originating from the Northern Ethiopian highlands. While it is hardly grown in other parts of the world, it presents a major staple in Ethiopian and Eritrean diets (Baye, 2010).

exception of Takahashi & Barrett, 2014). On the one hand, increased demand for household labor may increase children’s work burden, with potential negative effects for their education.

On the other hand, income gains may induce higher investments in human capital formation and thus, positive effects on children’s education. In order to create more evidence on welfare effects at the household level related to ISFM, the third article of this dissertation focusses on the following:

(6) What are the effects of ISFM adoption on crop, household and off-farm income, as well as on food security, labor demand and children’s education?

This essay uses data from 2,059 maize, wheat and teff growing households in two agroecolog-ical zones in Ethiopia, and distinguishes between a rather lax and a stricter definition of ISFM.

The inverse probability weighting regression adjustment method is used, and propensity score matching as robustness check.