2 resultados para adverse selection component

em University of Connecticut - USA


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One way to measure the lower steady state equilibrium outcome in human capital development is the incidence of child labor in most of the developing countries. With the help of Indian household level data in an overlapping generation framework, we show that production loans under credit rationing are not optimally extended towards firms because of issues with adverse selection. More stringent rationing in the credit market creates a distortion in the labor market by increasing adult wage rate and the demand for child labor. Lower availability of funds under stringent rationing coupled with increased demand for loans induces the high risk firms to replace adult labor by child labor. A switch of regime from credit rationing to revelation regime can clear such imperfections in the labor market. The equilibrium higher wage rate elevates the household consumption to a significantly higher level than the subsistence under credit rationing and therefore higher level of human capital development is assured leading to no supply of child labor.

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Credit-rationing model similar to Stiglitz and Weiss [1981] is combined with the information externality model of Lang and Nakamura [1993] to examine the properties of mortgage markets characterized by both adverse selection and information externalities. In a credit-rationing model, additional information increases lenders ability to distinguish risks, which leads to increased supply of credit. According to Lang and Nakamura, larger supply of credit leads to additional market activities and therefore, greater information. The combination of these two propositions leads to a general equilibrium model. This paper describes properties of this general equilibrium model. The paper provides another sufficient condition in which credit rationing falls with information. In that, external information improves the accuracy of equity-risk assessments of properties, which reduces credit rationing. Contrary to intuition, this increased accuracy raises the mortgage interest rate. This allows clarifying the trade offs associated with reduced credit rationing and the quality of applicant pool.