Forecasting with econometric models

Here’s another interesting example where explanatory and predictive tasks create different models: econometric models. These are essentially regression models of the form: Y(t) = beta0 + beta1 Y(t-1) + beta2 X(t) + beta3 X(t-1) + beta4 Z(t-1) + noise An example would be forecasting Y(t)= consumer spending at time t, where the input variables can be consumer spending in previous time periods and/or other information that is available at time t or earlier. In economics, when Y(t) is the state of the economy at time t, there is a distinction between three types of variables (aka “indicators”): Leading, coincident, and … Continue reading Forecasting with econometric models

Data mining competition season

Those who’ve been following my postings probably recall “competition season” when all of a sudden there are multiple new interesting datasets out there, each framing a business problem that requires the combination of data mining and creativity. Two such competitions are the SAS Data Mining Shootout and the 2008 Neural Forecasting Competition. The SAS problem concerns revenue management for an airline who wants to improve their customer satisfaction. The NN5 competition is about forecasting cash withdrawals from ATMs. Here are the similarities between the two competitions: they both provide real data and reasonably real business problems. Now to a more … Continue reading Data mining competition season