LSMS-ISA panel to explore labor market effects from large farm establishment.<sup>7</sup> Second, to account for inter-temporal variability in climatic conditions, we rely on gridded 0.1’ rainfall data publicly available from NOAA since 1980 to compute long-term mean and standard deviation of precipitation for each pixel. Calculating z-scores and matching them to kebeles then allows us to determine for each year if a kebele experienced drought (z<-1), a flood (1<z), or ‘normal’ conditions (-1≤z≤1).

# **2.4 Analytical approach and estimating equations**

As we have a census of the country’s large farms in 2014, we use time variation in smallholder kebeles’ proximity to large farms (generally or growing specific crops) in 2003/4-13/4 period to test if smallholders’ improved seed/fertilizer use, yields, employment, or resilience are affected by large farm presence. To do so, we construct, for every year, either the distance from every smallholder kebele to the next large farm of any kind (growing the same crop) or, as a measure of exposure, total large farm area (with the same crop) in a concentric circle with inner and outer radius of 0 to 25, 25 to 50 and 50 to 100 km from the kebele.

Formally, denote kebeles by _i_ , distance bands by _d_ , crops by _k_ and time by _t_ . The simplest specification then uses _dit_ or _dikt_ the distance between the centroid of kebele _i_ and the next commercial farm (or the next farm growing crop _k_ ) with squared distance to allow non-linear effects to estimate a regression of the form: ���� ��������� �������� �������� ��� ��� ����� (1) where _Yikt_ is the outcome of interest, i.e. either an indicator variable for whether a household uses improved seeds or fertilizer on crop _k_ or kebele-level yields for _k_ , �� ��� �� are a time trend and woreda fixed effect, **xikt** is a vector of control variables and the _β_ s are parameters to be estimated with main interest in _β1_ and _β2_ . Alternatively, replace _dit_ or _dikt_ by **_A_** _idt_ or **_A_** _idkt_ , a vector with the total commercial farm area cultivated (with crop _k_ ) in a concentric circle around smallholder kebele _i_ with inner and outer radius _d_ as above (0 to 25, 25 to 50, and 50 to 100 km)<sup>8</sup> to obtain an estimating equation of the form We extend this framework in two ways. To assess labor market effects, we use the LSMS-ISA survey to compute an indicator variable of whether household _i_ engaged in full-time agricultural or non-agricultural employment or temporary work by estimating versions of regressions (1) and (2) where _Yikt_ denotes the employment indicator. As a counterfactual we include in _dit_ the distance between the household and the centroid of the nearest town with population greater than 2,000. To explore if large farms establishment can

> 7 See the LSMS-ISA Ethiopia website for more information on sample design and data.

> 8 To illustrate, _Aikt(25-50)_ is the area under commercial farms growing crop _k_ within a 25-50km range of the household living in kebele _i_ . In all cases, yield (obtained through crop-cuts of randomly selected fields in the kebele) is measured at kebele level and input use at household level.

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