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Evidence from developed countries shows debt and bankruptcy to be correlated with medical expenditures. In Mexico, the formal financial sector does not lend for health needs. So, the solution is often found by borrowing from relatives, friends, and moneylenders, or pawning belongings after using savings, if any. Despite the recent and growing literature on income and health, and health financing, we have not come across a single study analyzing pawning and health. Our study fills this gap using a sample of 400 government owned pawnshop users from Puebla, Mexico. The findings from the study revealed that health expenditures are a significant reason for pawning and having medical insurance does not reduce the probability to pawn. Also, catastrophic health expenditures are correlated with a higher probability of not redeeming the pledge. We found that most pawnshop users have low income and losing a pledge is positively correlated with low or middle income and the number of people in the household.

Evidence suggests that, in the presence of imperfect market institutions, individuals devote resources to the establishment of reliable connections to attenuate the frictions that reduce trading and insurance opportunities. In this chapter, the author surveys the relevant literature on strategic formation of networks and use it to study this particular economic situation. A simple model is built to show that the investment in strong ties often, though not always, produces stable configurations that manage to improve upon the imperfections of market institutions.

This chapter discusses the empirical application of a class of strategic network formation models, using the approach to identification introduced by de Paula, Richards-Shubik, and Tamer (2018). The author emphasizes the interplay between model specification and computational complexity, and suggests tactics to make empirically realistic models become tractable. Two detailed examples, on friendship networks and coauthorship networks, are used to illustrate these issues and to demonstrate the performance of the approach with both simulation and empirical evidence. Also, the author presents extensions to the estimation method, which expand the potential range of applications, and which provide statistical inference with minimal computational burden.