The value of selecting the best forecasting model as the basis for empirical economic policy analysis is questioned. When no model coincides with the data generation process, non-causal statistical devices may provide the best available forecasts: examples from recent work include intercept...

We develop forecast-error taxonomies when there are unmodeled variables, forecast 'off-line'.  We establish three surprising results.  Even when an open system is correctly specified in-sample with zero intercepts, despite known future values of strongly exogenous variables, changes in...

Understanding the workings of whole economies is essential for sound policy advice - but not necessarily for accurate forecasts.  Structural models play a major role at most central banks and many other governmental agencies, yet almost none forecast the financial crisis and ensuing...

Unpredictability arises from intrinsic stochastic variation, unexpected instances of outliers, and unanticipated extrinsic shifts of distributions.  We analyze their properties, relationships, and different effects on the three arenas in the title, which suggests considering three associated...

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...

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...

Unpredictability arises from intrinsic stochastic variation, unexpected instances of outliers, and unanticipated extrinsic shifts of distributions.  We analyze their properties, relationships, and different effects on the three arenas in the title, which suggests considering three associated...

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...

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...