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 develop a new automatically-computable test for super exogeneity, using a variant of general-to-specific modeling.  Based on the recent developments of impulse saturation applied to marginal models under the null that no impulses matter, we select the significant impulses for testing in the...

This chapter describes the issues confronting any realistic context for economic forecasting, which is inevitably based on unknowingly mis-specified models, usually estimated from mis-measured data, facing intermittent and often unanticipated location shifts.  We focus on mitigating the...

Almost no economic time series is either weakly or strictly stationary: distributions of economic variables shift over time.  Thus, the present treatment of expectations in economic theories of inter-temporal optimization is inappropriate.  It cannot be proved that conditional expectations...

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...

We demonstrate major flaws in the statistical analysis of Beenstock, Reingewertz and Paldor (2012), discrediting their initial claims as to the different degrees integrability of CO2 and temperature.

We identify anthropogenic contributions to atmospheric CO2 measured at Mauna Loa using a statistical automatic model selection algorithm (Autometrics).  We find that vegetation, temperature and other natural factors alone cannot explain the trend or the variation in CO2 growth.  Industrial...

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...

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...

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...