This paper investigates inclusive growth in agricultural value chains, with a focus on smallholder participation, upgrading behavior, and outcomes related to agricultural productivity, agricultural profits, and smallholder incomes. The purpose of the paper is to advance understanding of inclusive growth by reviewing empirical evidence from twelve agricultural value chains that have engaged and benefited smallholders. The review of evidence focuses on three central questions:

Production, Finance, and Improved Technologies (PROFIT) was a multi-sector value chain intervention in Zambia from 2005-2011. It focused on upgrading retail inputs and services and measuring the effect on beef and cotton value chains. Among the findings were:

- Shifts in approach, emphasis and location during the course of program complicated or invalidated parts of the research plan.

- The combination of quantitative and qualitative evidence presented suggests positive outcomes and impacts for smallholder participants in the project's beef and retail activities.

Smallholder farmers in Zambia comprise 85 per cent of the farmers’ population. Such farmers are regarded as not creditworthy and furthermore their agricultural productivity could be improved. The aim of this paper is to present recent evidence on value chain financing (VCF) as a framework to increase access to agricultural finance for Zambian smallholder farmers. Such financing will act as an enabler to mechanize and, in turn, might improve productivity. Qualitative data collection techniques were followed to provide the results as presented in three illustrative case studies.

This ILRI discussion paper reviews 20 value chain interventions and discusses the econometric techniques used to address the validity of findings. It explores the use of propensity score matching, instrumental variables, difference in difference, regression discontinuity, and randomized controlled trials. Qualitative and participatory methods are also examined with the idea that they may be able to better capture the complexity of value chain processes.

The women’s crop tool attempts to elicit women’s and men’s levels of control over important decision making (land allocation, land preparation, use of inputs, weeding, use of labor, harvesting, marketing, use of income) for their main crops. Both qualitative (FGDs) and quantitative (HH survey) measurements can be done to collect sex-disaggregated data on control. This can reveal both women’s and men’s perception of their own control and each other’s control.