Association for Public Policy Analysis & Management

Existing literature on municipal bond sales demonstrate that there are a number of factors which determine the borrowing cost in the municipal bond markets. Credit outlook, which is assigned by the credit agencies, is provided with the rationale to help resolve information asymmetry problems which arises from information differences and conflicting interests among the active players in the market. Credit outlooks play a significantly different role from credit ratings. It serves as a monitoring and surveillance tool, and also disciplining factor to issuers. However, there is very little empirical research testing the credit outlook as a key element in municipal markets, and their role in determining local government borrowing costs. Expanding information asymmetry information theory, this study will examine how the credit outlook are determined. I will use a sample from 108 largest city governments (FY2003-2012) that were assigned credit outlooks. The credit outlook of the Moody’s, one of the major credit rating agencies is the main dependent variable of interest in this analysis. Underlying credit outlook variables are coded as binary variables (negative and stable / positive and stable). The change and volatility of four broad categories provided by the Moody’s standard to gauge the credit ratings - 1) Economic Strength, 2) Financial Strength, 3) Management and Governance, and 4) Debt Profile – will be used to test the determinants of credit outlooks. Using key variables in those measures, the empirical strategies are three-fold. First, I will run the fixed effect panel logit of the level of key measures. Second, I will run the fixed effect panel logit of the difference model which refers to the difference between the current level and the average of last three years to see how steep change in each variable affects credit outlooks. Third, I will run the fixed effect panel logit of the volatility of key measures. The expectation of the models is that, by definition, the change of key measures in fiscal strength would be the important determinants of credit outlooks, not the level itself. This analysis will help fill the void and encourage further investigation of the role of credit outlook in municipal bond markets. Plus, it will contribute to the bond sales literature by exploring the roles of signals by credit outlooks in the bond markets.