This chapter presents a unified set of estimation methods for fitting a rich array of models describing dynamic relationships within a longitudinal data setting. The discussion surveys approaches for characterizing the micro dynamics of continuous dependent variables both over time and across...

I develop methods that produce consistent estimates of the Vasicek-Basel IRB (VAIRB) credit risk model parameters. I apply these methods to Moody's data on corporate defaults over the period 1920–2008 and assess the model fit and construct hypothesis tests using bootstrap methods. The results...

The particular concern of this paper is the construction of a confidence region with pointwise asymptotically correct size for the true value of a parameter of interest based on the generalized Anderson-Rubin (GAR) statistic when the moment variance matrix is singular. The large sample behaviour...

Measuring bias is important as it helps identify flaws in quantitative forecasting methods or judgmental forecasts. It can, therefore, potentially help improve forecasts. Despite this, bias tends to be under represented in the literature: many studies focus solely on measuring accuracy. Methods...

In forecasting count processes, practitioners often ignore the discreteness of counts and compute forecasts based on Gaussian approximations instead. For both central and non-central point forecasts, and for various types of count processes, the performance of such approximate point forecasts is...

This paper shows how the dynamic linear model with fixed regressors can be efficiently estimated. This dynamic model can be used to distinguish spurious correlation from state dependence and we show that the integrated likelihood estimator is adaptive for any asymptotics with T increasing where...

In this study, I investigate the necessary condition for consistency of the maximum likelihood estimator (MLE) of spatial models with a spatial moving average process in the disturbance term. I show that the MLE of spatial autoregressive and spatial moving average parameters is generally...

Motivated by the desire to probe macroeconomic tail events and to capture non-linear economic dynamics, we estimate two types of regime switching models: threshold VAR and Markov switching VAR. For each of the models, we estimate regimes which carry the interpretation of recessionary/normal and...