We consider model selection for non-linear dynamic equations with more candidate variables than observations, based on a general class of non-linear-in-the-variables functions, addressing possible location shifts by impulse-indicator saturation.  After an automatic search delivers a simplified...

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...

We consider selecting an econometric model when there is uncertainty over both the choice of variables and the occurrence and timing of multiple location shifts.  The theory of general-to-simple (Gets) selection is outlined and its efficacy demonstrated in a new set of simulation experiments...

In many countries, house prices are subject to boom/bust cycles and in some these are linked to severe economic and financial instability.  Overheating can have both a price and a quantity dimension, but it is likely that they are linked by common drivers.  However, much depends on the...

Using village data from Tanzania, we test whether gifts and loans between households are voluntary while correcting for mis-reporting by the giving and receiving households.  Two maintained assumptions underlie our analysis: answers to a question on who people would turn to for help are good...

We evaluate automatically selecting the relevant variables in an econometric model from a large candidate set.  General-to-specific selection is outlined for a constant model in orthogonal variables, where only one decision is required to select, irrespective of the number of regressors (N T)...

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...

Several aspects of GARCH(p, q) models that are relevant for empirical applications are investigated. In particular, it is noted that the inclusion of dummy variables as regressors can lead to multimodality in the GARCH likelihood. This invalidates standard inference on the estimated...

We investigate alternative robust approaches to forecasting, using a new class of robust devices, contrasted with equilibrium correction models.  Their forecasting properties are derived facing a range of likely empirical problems at the forecast origin, including measurement errors, implulses,...

Inflation is a far from homogeneous phenomenon, a fact often neglected in modeling consumer price inflation.  Using a novel methodology grounded in theory, the ten sub-components of the consumer price index (excluding mortgage interest rates), are modeled separately and forecast,...