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Credit Ratings in the Presence of Bailout: The Case of Mexican Subnational Government Debt

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  • Fausto Hernández-Trillo

    ()

  • Ricardo Smith-Ramírez

    ()

Abstract

Searching for an explanation for investment grades assigned to virtually bankrupt subnational governments in LDCs, we study the determinants of bond ratings for municipalities in Mexico. Our data set includes ratings from three agencies: S&P, Fitch, and Moody´s. To control for selectivity in the process of choosing an agency, we model the problem as a tri-variate selfselection process with ordinal responses. Additionally, in order to circumvent the estimation of multidimensional integrals, we implement a Monte Carlo Expectation Maximization (MCEM) algorithm. We find that not only financial but also political factors, such as number of voters and political party in power, are important and show evidence that the probability of bailout has a heavy weight in the rating process. Our outcomes question the purpose of rating sub-national debt in LDCs with a bailout tradition, since in those cases the market may assess the risk of subnational entities as that of sovereign instruments.

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Bibliographic Info

Article provided by LACEA - LATIN AMERICAN AND CARIBBEAN ECONOMIC ASSOCIATION in its journal JOURNAL OF LACEA ECONOMIA.

Volume (Year): (2009)
Issue (Month): ()
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Handle: RePEc:col:000425:008585

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Related research

Keywords: Credit Ratings; Bailout; Subnational Governments; Debt;

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  1. Carmen M. Reinhart, 2002. "Default, Currency Crises, and Sovereign Credit Ratings," World Bank Economic Review, World Bank Group, vol. 16(2), pages 151-170, August.
  2. Millon, Marcia H & Thakor, Anjan V, 1985. " Moral Hazard and Information Sharing: A Model of Financial Information Gathering Agencies," Journal of Finance, American Finance Association, vol. 40(5), pages 1403-22, December.
  3. Borsch-Supan, Axel & Hajivassiliou, Vassilis A., 1993. "Smooth unbiased multivariate probability simulators for maximum likelihood estimation of limited dependent variable models," Journal of Econometrics, Elsevier, vol. 58(3), pages 347-368, August.
  4. Moon, Choon-Geol & Stotsky, Janet G, 1993. "Testing the Differences between the Determinants of Moody's and Standard & Poor's Ratings: An Application of Smooth Simulated Maximum Likelihood Estimation," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 8(1), pages 51-69, Jan.-Marc.
  5. Donald P. Morgan, 2002. "Rating Banks: Risk and Uncertainty in an Opaque Industry," American Economic Review, American Economic Association, vol. 92(4), pages 874-888, September.
  6. Carleton, Willard T & Lerner, Eugene M, 1969. "Statistical Credit Scoring of Municipal Bonds," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 1(4), pages 750-64, November.
  7. Natarajan, Ranjini & McCulloch, Charles E. & Kiefer, Nicholas M., 2000. "A Monte Carlo EM method for estimating multinomial probit models," Computational Statistics & Data Analysis, Elsevier, vol. 34(1), pages 33-50, July.
  8. Bekaert, Geert & Harvey, Campbell R., 1997. "Emerging equity market volatility," Journal of Financial Economics, Elsevier, vol. 43(1), pages 29-77, January.
  9. Reinhart, Carmen, 2002. "Sovereign Credit Ratings Before and After Financial Crises," MPRA Paper 7410, University Library of Munich, Germany.
  10. Eli M. Remolona & Michela Scatigna & Eliza Wu, 2008. "A ratings-based approach to measuring sovereign risk," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 13(1), pages 26-39.
  11. Keane, Michael P, 1992. "A Note on Identification in the Multinomial Probit Model," Journal of Business & Economic Statistics, American Statistical Association, vol. 10(2), pages 193-200, April.
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