Linking e-Government to Socio-Demographics. A Multi-Model Approach Using Panel Data, Regression, and Neural Networks

Abstract

. The emergence of the Internet as a central phenomenon of the post-industrial era has generated structural changes in all socio-economic processes, including public administration. On this note, e-government has become the new practice, aimed to reshape the relationship between state and citizen, but showing considerable differences in the way it is adopted worldwide. Therefore, this paper proposes a methodology for assessing whether socio-demographic characteristics such as the urban population, the average years spent in school, or the overall median age of the population can successfully explain the level of e-government adaptation (measured through the EGDI). To observe it, we will use data from six years, from 2010 to 2020, and 130 countries of the UN. As tools, we have employed a multi-model approach that consists of regression and neural network models, with two main directions of analysis: individual yearly methods and longitudinal panel data.