Analysis of Modern Econometric Model System Based on Panel Data and Intelligent Fuzzy Clustering Model

Abstract

Analysis of the modern econometric model system based on panel data and intelligent fuzzy clustering model is studied in this paper. We use normalized sensitivity to analyze the sensitivity of the general multi-layer feed-forward network econometric model. The sensitivity not only considers the first-order partial derivative information, but also takes into account the distribution of economic system inputs. Classical econometric models are mostly in the form of constant parameters. However, with the development of non-classical econometric models, other parameter forms have emerged, including variable parameters, non-parameters, and semi-parameters. Hence, we consider the core aspects of the different perspectives to construct the efficient model. The designed approach is simulated on the collected data sets and the compared with the other methods.