Rating Sub-National Government Debt in LDCs: Does size matter?

In this paper we study the determinants of both the decision to be rated and the ratings for sub-national governments in a prominent LDC, Mexico. One of the main findings is that entity size does matter; as a matter of fact, population size is one of the two rating determinants common to all the raters under analysis. In a country with a long bailing-out history, these results support our too-big-to-fail hypothesis. Namely, large entities select themselves to be rated (and so to obtain new debt) because they know they have political power; and secondly, raters know that the probability that federal government bail out large entities is high. Under these circumstances requiring the services of a rating firm has little sense since market may assess the risk of these entities as that of the sovereign instruments. If so, sub-national governments may save the cost of the grading. Besides, the assessment of sovereign debt risk is normally free of charge. Methodologically, we extend and modify Moon and Stostsky (1993) seminal work in several ways. First, our model considers six latent dependent variables (instead of four). Second, we formulate a Monte Carlo Expectation Maximization (MCEM) algorithm to circumvent the estimation of multidimensional integrals in lieu of using the probability simulator of Borsch-Supan and Hajivassiliou (1993). Finally, our discussion is based on marginal effects rather on parameter estimates.