The estimation of models involving discrete mixtures is a common practice in econometrics, for example to account for unobserved heterogeneity. However, the literature is relatively uninformative about the measurement of the precision of the parameters. This note provides an analytical...

We consider maximum likelihood (ML) estimation of mean and covariance structure models when data are missing. Expectation maximization (EM), generalized expectation maximization (GEM), Fletcher-Powell, and Fisher-scoring algorithms are described for parameter estimation. It is shown how the...

Normal-distribution-based maximum likelihood (ML) and multiple imputation (MI) are the two major procedures for missing data analysis. This article compares the two procedures with respects to bias and efficiency of parameter estimates. It also compares formula-based standard errors (SEs) for...

An important property of Fisher information is that it decreases weakly under transformation of random variables. Kagan and Rao (2003) [A. Kagan, C.R. Rao, Some properties and applications of the efficient Fisher score, J. Statist. Plann. Inference 116 (2003) 343–352] showed that, in the...

The estimation of models involving discrete mixtures is a common practice in econometrics, for example to account for unobserved heterogeneity. However, the literature is relatively uninformative about the measurement of the precision of the parameters. This note provides an analytical...

This paper investigates the transparency of derivative disclosures of Australian firms in the extractive industries using 1998 to 2001 financial reports. The quality of financial reporting has become a major corporate governance issue since the collapse of prominent companies such as Enron in...