Analysis of industrial economics by means of neural nets

Abstract

This work was has been done in order to see the feasibility of prediction of the performance of firms in industrial economics, using two different methods. One was the a multilayered perceptron and the other the a linear prediction filter. A data base of industrial corporations of Spain was used for the experiments. The predicted variables that were the benefits of the corporations and sales. The information used for the prediction was related to the internal variables of each corporation, the relative position in the sector, and additional macroeconomic data. Also some statistical tests were done in order to ascertain the reliability of the results. It was found that the results with the neural net based predictor were statistically more reliable than linear prediction in the sense that results were more accurate with a better confidence margin.