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A food security indicator for technology impact assessment is needed that can be constructed with available data, is comparable over time and space, and represents the multiple dimensions of food security.

In this chapter, we review some commonly used food security indicators, analyze the extent to which these indicators satisfy key criteria, and introduce a food security indicator constructed for use in an economic impact assessment and that exhibits a number of desirable properties.

This income-based indicator is similar to a consumption-based poverty indicator, utilizing an estimate of the income required to purchase a food “basket” that meets nutritional requirements and comparing the food security income requirement to a household’s per capita income.

The applicability of the indicator is illustrated with an analysis of the impacts of legume inoculation technology developed for smallholder farms in Tanzania and other parts of Africa. We conclude with a discussion of suggested improvements for food security indicators used for technology impact assessment.

The article makes a modest attempt to explore the level of financial literacy (FL) amongst the farmers in India. An effort was also made to unearth the factors affecting such FL.

The study used secondary data on 11,030 farmers across various regions of India from the Financial Inclusion Insight Survey, 2017. Standard and Poor Global FL questions were used to measure the level of FL amongst the respondents. In addition to the appropriate statistical tools and techniques, the censored tobit regression model and generalized structural equation model were applied to explore the determinants of FL of the Indian farmers.

The outcome of the study indicated that the majority of Indian farmers are financially illiterate. The average FL score obtained by the sample farmers was found to be only 33%. The results of the study signaled significant regional variation in FL amongst the farmers across India. Apart from the regional variation in FL, farmer type, state-specific agricultural productivity, gender, marital status, age, educational attainment and financial inclusion were found to be the major determinants of the FL amongst the farmers.

Evaluation of FL amongst farmers is scanty in the literature in developed nations and especially in the context of emerging economies, like India. The authors tried to fill this gap by exploring FL and its determinants amongst Indian farmers. In addition to this, the study for the first time used a comprehensive and rich dataset of 11,030 Indian farmers while exploring the level of FL and its determinants.