Quantitative Methods: An Introduction for Business Management

11

Time Series Models

Forecasting is a common task in business management. In Chapter 10, on simple linear regression models, we have met a kind of statistical model that can be used as a forecasting tool, provided that

• We are able to find potential explanatory variables
• We have enough data on all the relevant variables, in order to obtain reliable estimates of model parameters

Even though, strictly speaking, linear regression captures association and not causation, the idea behind such a model is that knowledge about explanatory variables is useful to predict the value of the explained variable. Unfortunately, there are many cases in which we are not able to find a convincing set of explanatory variables, or we lack data about them, possibly because they are too costly to collect. In some extreme cases, not only do we lack enough information about the explanatory variables, but we even lack information about the predicted variable. One common case is forecasting sales for a brand-new kind of product, with no past sales history. Then, we might have to settle for a qualitative, rather than quantitative forecasting approach. Qualitative forecasting may take advantage of qualified expert opinion; various experts may be pooled in order to obtain both a forecast and a measure of its uncertainty.¹ Actually, these two families of methods can be and, in fact, are often integrated. Even when plenty of data are available, expert opinions are a valuable commodity, since statistical models ...