We present an efficient technique for the study of quasi-periodic oscillations in noisy, non-stationary signals, which allows the assessment of system dynamics despite phase resetting and noise. It is based on the definition of anchor points in the signal (in the simplest case increases or...

This paper describes a moments estimator for a standard state-space model with coefficients generated by a random walk. The method calculates the conditional expectations of the coefficients, given the observations. A penalized least squares estimation is linked to the GLS (Aitken) estimates of...

This metadata relates to an electronic version of an article published in Journal of statistical computation and simulation, 2002, vol. 72, no. 6, pp. 507-516. Journal of Statistical Computation and Simulation is available online at informaworldTM at...

This paper examines time-series patterns of external financing decisions and shows that publicly traded U.S, firms fund a much larger proportion of their financing deficit with external equity when the cost of equity capital is low. The historical values of the cost of equity capital have...

This dissertation studies three classes of estimators for the asymptotic variance parameter of a stationary stochastic process. All estimators are based on the concept of data "re-use" and all transform the output process into functions of an approximate Brownian motion process.The first class...

This thesis is concerned with simulation output analysis. In particular, we are inter-ested in estimating the variance parameter of a steady-state output process. The estimationof the variance parameter has immediate applications in problems involving (i) the precisionof the sample mean as a...

In the existing literature, conditional forecasts in the vector autoregressive (VAR) framework have not been commonly presented with probability distributions or error bands. This paper develops Bayesian methods for computing such distributions or bands. It broadens the class of conditional...

Many economic applications call for simultaneous equations VAR modeling. We show that the existing importance sampler can be prohibitively inefficient for this type of models. We develop a Gibbs simulator that works for both simultaneous and recursive VAR models with a much broader range of...

Causal analysis in multiple equation models often revolves around the evaluation of the effects of an exogenous shift in a structural equation. When taking into account the uncertainty implied by the shape of the likelihood, we argue that how normalization is implemented matters for inferential...

Strategic interjurisdictional behavior and the interaction over time of the mean and dispersion of average tax rates across states are analyzed in a vector autoregression model. Variance decompositions reveal that fiscal competition explains roughly one-third of the time variation of state and...