Use of financial diaries to understand smallholder investment finance a cross country analysis in Mozambique, Tanzania and Pakistan

Purpose - The purpose of this paper is to evaluate the relative importance of different sources of finance for agricultural and non-agricultural investments using unique Smallholder Financial Diaries collected by Consultative Group to Assist the Poor (CGAP) in Mozambique, Pakistan and Tanzania at the individual and household level. Design/methodology/approach - Following the analytical framework of variance decomposition developed in Samphantharak and Townsend (2010), this study develops a method to quantify how much each cash deficit associated to investments and expenses of interest co-move with different financing sources. Findings - This paper finds that self-finance, rather than formal or informal finance from external providers, is the main financing source for long-term and short-term smallholder agricultural investments. Further, the paper finds that the main source of self-finance varies depending on the economic opportunities faced by smallholders, with non-agricultural income as the dominant financing source for some, while agricultural income dominating for others. Research limitations/implications - Given CGAP’s Smallholder Financial Diaries is not nationally representative, research results should be interpreted carefully. However, to the best of the authors’ knowledge, this is the first paper to analyze financing sources for smallholder households making use of high frequency financial data for individuals in developing countries. Practical implications - These findings imply that financial inclusion policies specifically targeting smallholders and the agricultural sector would benefit from enabling the development of an ecosystem of diverse financial services that respond simultaneously to both agriculture and non-agriculture needs. Originality/value - This is paper furthers the authors’ knowledge on how smallholder households are financing their agricultural investments. Moreover, it applies methods in new ways to exploit a unique data set.