Minimum tillage (MT) is a farming practice that reduces soil disturbance by limiting tillage only to planting stations. MT is an integral part of Climate Smart Agriculture aimed at raising agricultural productivity, improving farmer livelihoods and building climate resilient farming systems in sub-Saharan Africa. However, there are questions on its suitability for smallholder farmers in the region. This paper assesses the impacts of MT on crop yield and crop income using an endogenous switching regression (ESR) model applied to cross sectional data from 751 fields, of which 17% were under MT in Zambia. The ESR framework accounts for heterogeneity in the decision to adopt MT or not and consistently predicts the outcomes of adopters and non-adopters had they not adopted and adopted, respectively. The results suggest that adopting MT was associated with an average yield gain for maize, groundnut, sunflower, soybean and cotton of 334 kg/ha but it had no significant effects on crop income (from sales and for subsistence) of households in the short-term. These results are partly explained by partial adoption: even among adopters, only 8% of cultivated land was under MT. In these circumstances, although MT confers some yield benefits, the gains may be insufficient to offset the costs of implementation and translate into higher incomes and better livelihood outcomes in the short-term. Additional costs associated with MT include implements, herbicides, and labor for weed control and for land preparation. Assumptions of labor saving from preparing land in the dry season and cost savings by reduced fuel use and weed pressure are aspirational because of the prevalent customary land tenure and communal grazing systems, and because mechanization and the use of herbicides to control weeds remain low among smallholders. Nevertheless, if the longer-term productivity gains from MT are large enough, these may offset the higher implementation costs of MT due to economies of scale and may eventually result in improved incomes and food security. These findings may help to explain the perceived low uptake rates for MT in Zambia and call for lowering implementation costs through extension specific to MT and by adapting MT to local contexts.
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Because MT involves many different possible tillage practices, these components may have different cost implications. However, data on the direct costs of each possible component were not collected in the survey.
Defined in the Zambian context as the use of reduced or zero mechanical disturbance of the soil through animal-draught or mechanized ripping, zero tillage with jab planters or dibble sticks or planting basins made by hand hoe (Haggblade and Tembo 2003).
I did not use the other two CA practices (crop rotation and residue retention) to focus on the full CA package because the joint uptake of all the three CA principles including MT is much lower (at 1.7%) compared to 17% for MT alone in the sample. Crop rotation and residue retention, are complementary to MT.
MT is generally considered risk reducing, but due to data limitations, risk is not formally considered in this paper.
Due to budget and time constraints, this study was only a cross section and not panel. The latter would have been more appropriate.
This underlies the logic of the Di Falco et al. (2011) IV admissibility test. Because the IV should affect the outcome only through the treatment, it therefore follows that the IV should not directly affect outcomes even for the untreated subsample. This result should hold by construction for the treated sample if the IV is relevant and admissible.
I also estimated the Local Average Treatment Effects (LATE) because the ATT may not be so informative since the adoption of MT is low. The LATE results from Two Stage Least Squares (2SLS) following (Wooldridge 2010) are available from the author upon request. The ATT is still relevant in this case because 17% of the field plots in the sample used MT. Whether that is low adoption at the field level is an open question. The ATT results are better than the LATE results.
cattle =0.7, donkey = 0.5, pigs = 0.2, goats =0.1, chicken = 0.01, duck = 0.06.
The asset value was computed as the sum of the quantity of productive assets, e.g., ploughs, ox-carts, lorries, and bicycles, and their market prices.
I also estimated a LATE as a possible better impact measure compared to ATT on account that MT adoption was low in the sample. The LATE results (available from the author) were not better.
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This work was funded by the Norwegian Agency for Development Cooperation through the Center for International Forestry Research (CIFOR) [agreement no. GLO-3945 QZA 13/0545]. Additional funding from USAID through the Innovation Lab for Food Security Policy is acknowledged. An earlier version of this paper was published as part of my PhD thesis at the School of Economics and Business at the Norwegian University of Life Sciences (NMBU). I thank Arild Angelsen, three reviewers and the editors of Food Security for their very helpful comments and suggestions on the paper.
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Ngoma, H. Does minimum tillage improve the livelihood outcomes of smallholder farmers in Zambia?. Food Sec. 10, 381–396 (2018). https://doi.org/10.1007/s12571-018-0777-4
- Minimum tillage
- Impact assessment
- Crop yield
- Crop income
- Endogenous switching