In this paper we examine the properties of a simple criterion-based, likelihood ratio type test of parameter restristions for standard GMM estimators in autoregressive panel data models. A comparison is made with recent test proposals based in the continuously-updated GMM criterion (Hansen,...

In this paper we explore a new approach to estimation for autoregressive panel data models, based on projecting the unobserved individual effects on the vector of observations on the lagged dependent variable. This approach yields estimators which coincide with known generalized method of...

We compare the finite sample behaviour of various unit root tests for micro panels where the number of individuals is typically large, but the number of time periods is often very small. As in this case some econometric estimators do not identify the parameters of interest when the processes are...

In this paper we consider the properties of a simple test of parameter restrictions based on standard two-step efficient GMM estimators. The test is computed simply as the difference between the minimised values of the GMM criterion function in the restricted and unrestricted models. We compare...

We compare the finite sample performance of a range of tests of linear restrictions for linear panel data models estimated using the generalized method of moments (GMM). These include standard asymptotic Wald tests based on one-step and two-step GMM estimators; two bootstrapped versions of these...

The class of Functional Signal plus Noise (FSN) models is introduced that provides a new, general method for modelling and forecasting time series of economic functions. The underlying, continuous economic function (or 'signal') is a natural cubic spline whose dynamic evolution is driven by a...

A continuous time econometric modelling framework for multivariate market event (or 'transactions') data is developed in which the model is specified via the vector stochastic intensity. This has the advantage that the conditioning sigma-field is updated continuously in time as new information...

Functional Signal plus Noise (FSN) models are proposed for analysing the dynamics of a large cross-section of yields or asset prices in which contemporaneous observations are functionally related. The FSN models are used to forecast high dimensional yield curves for US Treasury bonds at the one...