When breaks occur, equilibrium-correction models (EqCMs) based on cointegration face forecasting problems.  We investigate approaches to alleviate forecast failure following a location shift, including updating, intercept corrections, differencing, and estimating the future impact of an...

As it is almost 50 years since Phillips (1958), we analyze an historical series on UK wages and their determinants.  Huge changes have occurred over this long run, so congruence is hard to establish: real wages have risen more than 6 fold, and nominal 500 times; laws, technology, wealth...

Structural models` inflation forecasts are often inferior to those of naive devices. This chapter theoretically and empirically assesses this for UK annual and quarterly inflation, using the theoretical framework in Clements and Hendry (1998, 1999). Forecasts from equilibrium-correction...

A new test for non-linearity in the conditional mean is proposed using functions of the principal components of regressors.  The test extends the non-linearity tests based on Kolmogorov-Gavor polynomials (Thursby and Schmidt, 1977, Tsay, 1986, and Terasvirta, Lin and Granger, 1993), but...

Our strategy for automatic selection in potentially non-linear processes is: test for non-linearity in the unrestricted linear formulation; if that test rejects, specify a general model using polynomials, to be simplified to a minimal congruent representation; finally select by encompassing...

General unrestricted models (GUMs) may include important individual determinants, many small relevant effects, and irrelevant variables.  Automatic model selection procedures can handle perfect collinearity and more candidate variables than observations, allowing substantial dimension reduction...

Even in scientific disciplines, forecast failures occur.  Four possible states of nature (a model is good or bad, and it forecasts well or badly) are examined using a forecast-error taxonomy, which traces the many possible sources of forecast errors.  This analysis shows that a valid model can...

Success in accurately forecasting breaks requires that they are predictable from relevant information available at the forecast origin using an appropriate model form, which can be selected and estimated before the break.  To clarify the roles of these six necessary conditions, we distinguish...

Model selection from a general unrestricted model (GUM) can potentially confront three very different environments: over-, exact, and under-specification of the data generation process (DGP).  In the first, and most-studied setting, the DGP is nested in the GUM, and the main role of...