This study provides evidence on the role of public firms’ financial reports in the state‐bond secondary market. I investigate the informational role of corporate earnings announcements and find that public firms’ monthly earnings signals aggregated to the state level are positively associated with contemporaneous state‐bond returns. Further analyses reveal that public firms’ earnings announcements predict traditional economic indicators and contain incremental information that is independent of the traditional economic indicators. In cross‐sectional analyses, I show that the earnings–returns relation is especially pronounced when bondholders face longer investment horizons and higher credit risks. Taken together, the evidence indicates a positive externality of corporate financial reports in alleviating the opacity in the municipal bond secondary market.

In recent years, credit rating agencies have faced increased regulatory pressure and investor criticism for their ratings’ lack of timeliness. This study investigates whether and how rating agencies respond to such pressure and criticism. We find that the rating agencies not only improve rating timeliness, but also increase rating accuracy and reduce rating volatility. Our findings support the criticism that, in the past, rating agencies did not avail themselves of the best rating methodologies/efforts possible. When their market power is threatened by the possibility of increased regulatory intervention and/or reputation concerns, rating agencies respond by improving their credit analysis.

The author demonstrates that despite variables that are integrated, the fundamental issues on structural equation modeling raised by the Cowles Commission remain valid and standard estimation and testing procedures can still be applied. A basic framework linking the multiple time series model and the dynamic simultaneous equation model is provided and implications under the long-run cointegrating relations are discussed. Conditions for identifying both the short-run dynamics and long-run equilibrium conditions are given. Limiting properties of the least squares and simultaneous equation estimators under cointegration are derived. Implications for hypothesis testing are also discussed.

[This paper is concerned with the identification and estimation of the parameters in a dynamic simultaneous equations model with stationary disturbances when both the endogenous and exogenous variables are subject to random measurement errors. A frequency domain approach is suggested to fully utilize the information contained in the data. The first part of this paper explores the identification criteria. The second part of this paper suggests estimation methods for such a model. Both full information and limited information estimation methods are studied and their respective gains and losses are evaluated.]

[The model extlesstex-math extgreater$Y_\it\= extbackslashSigma _\k\( extbackslashbeta _\k\+ extbackslashdelta _\ik\+y_ k\)x_\ikt\= extbackslashvarepsilon _\it$ extless/tex-math extgreater with extlesstex-math extgreater$ extbackslashdelta _\ik$ extless/tex-math extgreater and extlesstex-math extgreatery_ k\ extless/tex-math extgreater random is considered as a means of pooling the time series of a cross-section sample. The model is placed in a mixed analysis of variance framework. Relationships between various estimation criteria are derived and their asymptotic properties compared. Some implementation problems are also discussed.]

Cheng F. Lee, Manak Gupta, An Inter-Temproal Approach to the Optimization of Dividend Policy with Pre- Determined Investment: A Further Comment, The Journal of Finance, Vol. 32, No. 4 (Sep., 1977), pp. 1358-1361