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The economic importance of financial literacy among individuals necessitates policy intervention. Estimation of financial literacy is a prerequisite for strategies to improve financial literacy. This paper, using data collected from the educated young adults in Kerala, the most literate state in India, builds a predictive model for financial literacy employing logistic regression. The study reveals the low level of financial literacy in the state. The model points to the significance of gender, age, religion, discipline of study, occupation, and personal income as determinants of financial literacy. The findings have implications for policies aimed at improving the financial literacy of young adults in India. [ABSTRACT FROM AUTHOR]

Summary Income diversification continues to be a key strategy for poor rural households, including those that are progressively developing and those operating under increasing distress. The ability of a household to diversify has been shown to depend upon its demographic and economic characteristics and its physical and social context. This paper considers the effects of intra-village social networks on household income diversification in one of the poorest and most ethnically diverse areas of the Indian state of Kerala. Using techniques adapted from spatial econometrics, we find that social connections within a village magnify the impacts of household characteristics such as education and number of adults by a factor of 3.6 times. Models with alternative measures of network centrality (degree and eigenvector) indicate that the number of network connections that a household has is more important than the centrality of those connections. Finally, we use social contact information to calculate assortative mixing based on caste. The results suggest social stratification in these villages, with higher levels of stratification associated with lower levels of income diversification. [ABSTRACT FROM AUTHOR]