Unpredictability in economic analysis, econometric modeling and forecasting

Unpredictability and the Foundations of Economic Forecasting

We revisit the concept of unpredictability to explore its implications for forecasting strategies in a non-stationary world subject to structural breaks, where model and mechanism differ. Six aspects of the role of unpredictability are distinguished, compounding the four additional mistakes most likely in estimated forecasting models. Structural breaks, rather than limited information, are the ...

Econometric Forecasting

This lecture is confined to forecasting in the context of time and, consequently, time series (time-series forecasting). There are also forecasting problems outside the time context, for example if k out of n data points are observed and the remaining n − k points are to be ‘predicted’. In a wide sense, all extrapolations can be viewed as forecasts. However, we will consider only forecast probl...

Econometric Forecasting

Several principles are useful for econometric forecasters: keep the model simple, use all the data you can get, and use theory (not the data) as a guide to selecting causal variables. But theory gives little guidance on dynamics, that is, on which lagged values of the selected variables to use. Early econometric models failed in comparison with extrapolative methods because they paid too little...

Spatial Econometric Issues for Bio-Economic and Land-Use Modeling

We survey the literature on spatial bio-economic and land-use modelling and review thematic developments. Unobserved site specific heterogeneity is common in almost all of the surveyed works . Heterogeneity appears also to be a significant catalyst engendering significant methodological innovation. To better equip prototypes to adequately incorporate heterogeneity, we consider a smorgasbord of ...

Economic and Econometric Models