The new-Keynesian Phillips curve (NKPC) includes expected future inflation as a major feedforward variable to explain current inflation.  Models of this type are regularly estimated by replacing the expected value by the actual future outcome, then using Instrumental Variables or Generalized...

The new-Keynesian Phillips curve (NKPC) includes expected future inflation to explain current inflation. Such models are estimated by replacing the expected value by the future outcome, using InstrumentalVariables or Generalized Method of Momentsmethods. However, the underlying theory does not...

We model expenditure on food in the USA, using an extended time series.  Even when a theory is essentially 'correct', it can manifest serious mis-specification if just fitted to data, ignoring its observed characteristics and major external events such as wars, recessions and policy changes. ...

We consider three 'cases studies' of the uses and mis-uses of mathematics in economics and econometrics.  The first concerns economic forecasting, where a mathematical analysis is essential, and is independent of the specific forecasting model and how the process being forecast behaves.  The...

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...

When a model under-specifies the data generation process, model selection can improve over estimating a prior specification, especially if location shifts occur. Impulse-indicator saturation (IIS) can ‘correct’ non-constant intercepts induced by location shifts in omitted variables, which...

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...

Although a general unrestricted model may under-specify the data generation process, especially when breaks occur, model selection can still improve over estimating a prior specification.  Impulse-indicator saturation (IIS) can 'correct' non-constant intercepts induced by location shifts in...