This paper examines the rise of the VAR approach from a historical perspective. It shows that the VAR approach arises as a systematic solution to the issue of 'model choice' bypassed by Cowles Commission (CC) researchers, and that the approach essentially inherits and enhances the CC legacy...

We characterize modern econometrics in terms of the emergence a widely accepted analytical framework. A major theme which dominated much of the debate through the century was whether and how econometric models can reflect theory-generated economic structures. In the period prior to the 2nd world...

Measurement forms the substance of econometrics. This chapter outlines the history of econometrics from a measurement perspective - how have measurement errors been dealt with and how, from a methodological standpoint, did econometrics evolve so as to represent theory more adequately in relation...

This paper studies the properties of the sieve bootstrap for a class of linear processes which exhibit strong dependence. The sieve bootstrap scheme is based on residual resampling from autoregressive approximations the order of which increases slowly with the sample size. The first-order...

A new test is proposed for the null of absence of serial correlation. The test uses a data-driven smoothing parameter. The resulting test statistic has a standard limit distribution under the null. The smoothing parameter is calibrated to achieve rate-optimality against several classes of...

This paper develops theoretical results for the estimation of radial basis function neural network specifications, for dependent data, that do not require iterative estimation techniques. Use of the properties of regression based boosting algorithms is made. Both consistency and rate results are...

Testing the rank of a matrix of estimated parameters is key in a large variety of econometric modelling scenarios. This paper describes general methods to test for the rank of a matrix, and provides details on a variety of modelling scenarios in the econometrics literature where these tests are...

Identification in the context of multivariate state space modelling involves the specification of the dimension of the state vector. One identification approach requires an estimate of the rank of a Hankel matrix. The most frequently used approaches of rank determination rely on information...

In this paper we consider GMM based estimation and inference for the panel AR(1) model when the data are persistent and the time dimension of the panel is fixed. We find that the nature of the weak instruments problem of the Arellano-Bond estimator depends on the distributional properties of the...

Panel datasets have been increasingly used in economics to analyse complex economic phenomena. One of the attractions of panel datasets is the ability to use an extended dataset to obtain information about parameters of interest which are assumed to have common values across panel units....