What Gender disparity has been documented in households' liability management (e.g., use of expensive credit facilities and delay or omission of advantageous refinancing) as well as asset allocation (e.g., non-participation in stock markets and lack of portfolio diversification). Both the welfare and individual cost of these financial mistakes are substantial. Our project seeks to identify through which mechanisms financial mistakes are made, and the characteristics to explain the behavior of individuals and households, and where the gender disparity arises. Why Previous studies estimating deep preference parameters of importance for policy are usually assessed without explaining individuals' underlying heterogeneity - and reported as conditional means. This implicitly assumes that one policy tool works the same for all individuals, irrespective of gender. Our project aims to solve this shortcoming and enable us to identify and describe a more realistic mechanism of choices - and understand how policy interventions can be designed and targeted at the type of individuals for which it is relevant. How The econometric methods developed to uncover deep parameters of interest at the individual level are built on simulation of distributions, optimization at the individual level, and the calculation of many-dimensional matrixes when characterizing network effects. Usually, these models are built and executed for samples over a few thousand observations. As our research projects are modeling behavior over several million individuals over long periods, we need substantial computational power to handle algorithms' complexity. The grant provides the computational ability to execute these methods on large samples. SSR Females are, on average, reported to pay higher interest rates on loans. Is this gender disparity explained by discrimination or by choices? Understanding mechanisms of discrimination are of the essence to have the ability to design policies to reduce discrimination. The current project proposal will provide novel insights of interest to academia, market participants, and policymakers to design more social responsible and fair financial markets.