A Combination of tools: NLS and NN Estimation of the Expenditure in Durables. Determinants, trend and Forecasting in the Vehicles Sector.

摘要

The aim of this work is to develop an equation to explain quarterly movements in personal consumption expenditure in durable goods and specifically in motor vehicles. In particular, we focus in the role of liquidity. Two sets of instruments are used. The description is done using a non-linear least squares (NLS) technique while the forecasting is done using a Neural Network. The model obtained using the NLS, even if showing a quite high goodness of fit, is quite unstable and the results are highly dependent on the starting values of some parameters. Furthermore, the high number of parameters estimated do not allow to perform a comprehensive set of econometric test. This set of reasons suggested to move to a method of forecasting able to overcome these problems. The tool used for perform the forecasting is a trained back-propagation MLP neural network.