Detection of structural change is a critical empirical activity, but continuous 'monitoring' of series, for structural changes in real time, raises well-known econometric issues that have been explored in a single series context. If multiple series co-break then it is possible that simultaneous...

The problem of structural change justifiably attracts considerable attention in econometrics. A number of different paradigms have been adopted ranging from structural breaks which are sudden and rare to time varying coefficient models which exhibit structural change more frequently and...

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...

The problem of structural change justifiably attracts considerable attention in econometrics. A number of different paradigms have been adopted ranging from structural breaks which are sudden and rare to time-varying coefficient models which exhibit structural change more frequently and...

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...

We consider time series forecasting in the presence of ongoing structural change where both the time series dependence and the nature of the structural change are unknown. Methods that downweight older data, such as rolling regressions, forecast averaging over different windows and exponentially...

This paper studies the Ordinary Least-Squared (OLS) and Instrumental Variables (IV) estimates of the returns to schooling for male workers in Spain. OLS estimates are often biased due to the endogeneity of schooling, measurement errors or omitted variables. Proper IV estimates correct this bias....

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...