Detail Credit risk, discrimination, and regulation in credit markets Bibliografi Author: Han, Song ; Mulligan, Casey B. (Advisor) Topik: ECONOMICS; FINANCE|BUSINESS ADMINISTRATION; BANKING|SOCIOLOGY; ETHNIC AND RACIAL STUDIES Bahasa: (EN )    ISBN: 0-591-95708-6     Penerbit: The University of Chicago Press     Tahun Terbit: 1998     Jenis: Theses - Dissertation Fulltext: 9841524.pdf (0.0B; 1 download) Abstract In this dissertation a unified framework is developed for theoretical and quantitative analysis of both statistical discrimination and taste-based discrimination in credit markets. Statistical discrimination occurs when creditors apply the statistical correlations between group identity and credit risks to individual applicants. Creditor's tastes for discrimination are modeled by psychic costs in contacting with minorities. A credit market equilibrium is characterized by Pareto optimal allocations of funds. I study the economic consequences of credit risks and creditor's preferences on screening, contract terms, and expected loan performance in perfect competitive credit markets. I show that whether the conventional hypothesis that loans to minority debtors are more profitable than to majorities with comparable credit background is valid and/or unique to taste-based discrimination depends crucially on how to measure expected loan profitability, the particular model of creditor's preferences, and the particular segments of debtors. Several testable hypotheses are derived on detecting taste-based discrimination. Using a data on FHA mortgage loans, I test the hypothesis that for the 'over-qualified' debtors, if loans to minority debtors have lower conditional expected write-offs than to majorities with the same unprohibited variables at the loan originations, then there exists taste-based discrimination against minorities. Empirical evidence fails to reject the null hypothesis of non-existence of taste-based discrimination. Opini Anda Klik untuk menuliskan opini Anda tentang koleksi ini! Lihat Sejarah Pengadaan  Konversi Metadata   Kembali

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