Japan, where factor markets work relatively well, a strongly positive relationship between farm size and productivity has been found (Kawasaki 2010). Recent innovations in crop breeding, tillage, and information technology also make it easier to supervise labor, thus tending to attenuate or eliminate large operations’ disadvantages<sup>3</sup> in a way that may have altered or even reversed the traditional farm sizeproductivity relation in Eastern Europe and South America (Helfand and Levine 2004, Lissitsa and Odening 2005).

# **2.2 Implications for Rwanda**

Whether small farms make efficient use of the resources at their disposal is particularly relevant for African countries aiming to modernize their agricultural sector and make the transition from subsistencebased to a market-driven rural economy. A belief in large holdings’ superior performance led influential observers to urge policy-makers to abandon ‘smallholder romanticism’ and aim to leapfrog to ‘efficient’ large scale farming based on industrial methods (Collier and Venables 2011). Others claim that, once conditions are accounted for, small farmers remain the most efficient (Larson _et al._ 2012) so that a strategy based on the traditionally high poverty elasticity of smallholder agriculture (Ligon and Sadoulet 2008), possibly supported by investment further up the value chain, will be appropriate.

Empirical evidence from Africa on this issue remains ambiguous, partly due to vast variation of relative land scarcity, capital access, and mechanization across countries. If investment is important and poor farmers’ access to finance and insurance constrained, difficulties in accessing financial markets may lead to a positive relationship between farm size and productivity as in Sudan (Kevane 1996). In Kenya, profits per acre were also found to increase monotonically with farm size while the relationship between output per acre and size was U-shaped with a minimum at about 5 ha, a finding partly attributed to crop composition changing across farm sizes (Carter and Wiebe 1990). Detailed grouped farm survey data for Malawi in the 1980s point towards a significant positive relationship between farm size and output per hectare, apparently driven by constrained capital access (Dorward 1999). A positive relationship between output per hectare and farm size also was found in Zambia, although it becomes U-shaped if endogeneity of plot size is considered (Kimhi 2006).

By contrast, in situations with little mechanization, a strong negative relationship between output and farm size is often found even after adjusting for other factors. For example, in Malagasy rice farms, inclusion of household fixed effects and controls for soil nutrients that are generally not observable does

> 3 Pest-resistant and herbicide-tolerant varieties facilitated broad adoption of zero tillage and, by reducing the number of steps in the production process and the labor intensity of cultivation, allowed management of larger areas. The ability to have machinery operations guided by GPS technology rather than driver’s skills makes close supervision of labor less relevant while information technology can generate data to help better supervise labor. The scope for substituting crop and pest models and remotely sensed information on field conditions for personal observation also reduces the advantage of local knowledge and experience in tactical farm decisions while climate change and the associated greater variability of climatic conditions reduces the value of traditional knowledge (Deininger and Byerlee 2012b).

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