We estimate a monthly income process using annual longitudinal household-level income data, in order to understand the nature of income risk faced by households at high frequency, and to provide an input for models that wish to study household decision-making at higher frequency than available...

We examine the effect of uncertainty arising from policy-shock volatility on yield-curve dynamics. In contrast to the assumption of many macro-finance models, policy-shock processes appear to be time varying and persistent. We allow for this heteroskedasticity by constructing a no-arbitrage...

The paper suggests and studies count data models corresponding to previously studied spatial econometric models for continuous variables. A novel way of incorporating spatial weights is considered for both time and space dynamic models with or without simultaneity. The paper also contains a...

In this paper, we make two contributions to the MSV literature. First, we propose two new MSV models that account for leverage effects. Second, we compare the small sample performances of Quasi Maximum Likelihood (QML) and Monte Carlo Likelihood (MCL) methods through Monte Carlo studies for...

We develop new procedures for maximum likelihood estimation of affine term structure models with spanned or unspanned stochastic volatility. Our approach uses linear regression to reduce the dimension of the numerical optimization problem yet it produces the same estimator as maximizing the...

__Abstract__ The paper investigates the impact of jumps in forecasting co-volatility, accommodating leverage effects. We modify the jump-robust two time scale covariance estimator of Boudt and Zhang (2013) such that the estimated matrix is positive definite. Using this approach we can...

This paper introduces an easy to follow method for continuous time model estimation. It serves as an introduction on how to convert a state space model from continuous time to discrete time, how to decompose a hybrid stochastic model into a trend model plus a noise model, how to estimate the...

A neglected aspect of the otherwise fairly well developed Bayesian analysis of cointegration is the point estimation of the cointegration space. It is pointed out here that, due to the well known non-identification of the cointegration vectors, the parameter space is not an inner product space...

This paper deals with the issues of identification and estimation in the canonical model of contagion advanced in Pesaran and Pick (2007). The model is a two-equation nonlinear simultaneous equations system with endogenous dummy variables; it also represents an extension of univariate threshold...

The paper illustrates some of the well-known problems with cointegration analysis in order to provide some perspective on the usefulness of cointegration techniques in applied economics. A number of numerical examples are employed to compare econometric estimation on the basis of both...