We consider forecasting with factors, variables and both, modeling in-sample using Autometrics so all principal components and variables can be included jointly, while tackling multiple breaks by impulse-indicator saturation. A forecast-error taxonomy for factor models highlights the impacts of...

To forecast an aggregate, we propose adding disaggregate variables, instead of combining forecasts of those disaggregates or forecasting by a univariate aggregate model. New analytical results show the effects of changing coefficients, misspecification, estimation uncertainty, and mismeasurement...

"Econometrics: Alchemy or Science?" analyses the effectiveness and validity of applying econometric methods to economic time series. The methodological dispute is long-standing, and no claim can be made for a single valid method, but recent results on the theory and practice of model selection...

This book confronts the practical problems of modelling aggregate time series data, in a systematic and intergrated framework. The main problem in econometric modelling of time series is discovering sustainable and interpretable relationships between observed economic variables. The primary aim...

This Handbook provides up-to-date coverage of both new developments and well-established fields in the sphere of economic forecasting. The chapters are written by world experts in their respective fields, and provide authoritative yet accessible accounts of the key concepts, subject matter and...

When location shifts occur, cointegration-based equilibrium-correction models (EqCMs) face forecasting problems. We consider alleviating such forecast failure by updating, intercept corrections, differencing, and estimating the future progress of an 'internal' break. Updating leads to a loss of...

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-Gabor polynomials ([Thursby and Schmidt, 1977], [Tsay, 1986] and [Teräsvirta et al., 1993]), but...

Reducing the number of over-identifying instruments, or adding them to a structural equation, increases estimation dispersion. Added instruments should be insignificant under correct specification, with parameter estimates nearly unaffected, confirmed by Monte Carlo. Selecting instruments does...

This timely Handbook reviews many key issues in the economics of energy and climate change, raising new questions and offering solutions that might help to minimize the threat of energy-induced climate change.