FORECASTING CONSUMERS EXPENDITURE - A COMPARISON BETWEEN ECONOMETRIC AND NEURAL-NETWORK MODELS

This paper is motivated by the difficulties faced by forecasters in pr edicting the decline in the growth rate of consumers': expenditure in the late 1980s. The econometric specifications of four competing expla nations are replicated and the static forecasts compared with the actu al outturns. The same data are then used to estimate neural network mo dels. The main issue is whether the neural network technology can extr act any more from the data sets provided than the econometric approach . It is found that the neural network models describe the decline in t he growth of consumption since the late 1980s as well as, but no bette r than, the econometric specifications included in the exercise, and a re shown to be robust when faced with a small number of data points. H owever, whichever approach is adopted, it is the skill of choosing the menu of explanatory variables which determines the success of the fin al results.