Manuscript Topics

Applied economics is one of the most receptive scientific fields to the new developments on quantitative (and qualitative) methods, as well as to the advances in data science. In recent times, scholars have relied on advances in quantitative research methods that have sought to refine and overcome traditional statistical techniques, pushing forward the discipline to new limits.

This special issue aims to contribute to Applied Economics continuing to be a fertile scientific field where new developments in data science and quantitative methods can be put into practice, as this will result not only in the refinement of such methods but also in advances of great social utility in the socioeconomic field. In addition, given the rapid pace and broad spectrum of contemporary advances in quantitative research methods, this issue pretends to give the scholars the opportunity to explore their important questions from multiple novel angles.

The above-mentioned techniques include ̶ but not limited to ̶ economic modelling, time series analysis, supervised and unsupervised machine learning, deep learning, text mining, graph networking, spatial and spatial-temporal statistics, statistical software, among others. Articles on ethics on analysis of data, data governance, feature engineering, and management of SQL and NoSQL economic databases are also very welcome.

In brief, this special issue is an attempt to bring some applications of recent quantitative methodological developments to the readers of ERA interested in economic problems and challenges, or in the developments themselves. It will allow them to understand much better how the methodological innovations are shaping and redefining the business and economic sphere.

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