Big Data, Public Investment and Economic Growth in the COVID-19 Epidemic. Evidence from an ANNs Experiment on EMU Countries

EasyChair Preprint 4720

Abstract

The paper examines the effects of higher public investments in and for digital transformation and Big Data (BD) on the economic output in EMU coun-tries as a possible policy action able to respond efficiently to the decline in global activity due to the COVID-19 pandemic. The adverse effects on economic growth are expected to be very significant; mobility fell substantially in all states, even ones that have not adopted major distancing mandates since the beginnings. Thus, larger investments accelerating the digital transformation in EMU coun-tries might generate a positive GDP effect countervailing the COVID-19 crisis. In order to test this hypothesis, we develop a dataset able to represent among GDP determinants, the contribution of public investments in digital evolution and related technologies in EMU countries, and build an architecture via Artificial Neural Networks through a Deep Learning experiment using Python software to test it. The results confirm that a significant change in public investments on dig-ital technologies and BD will generate a positive change in GDP in an accelera-tion process. This outcome advises policymakers to use forthcoming public re-sources from the European Recovery Funds also in accelerating the EMU econ-omies’ digital transformation by investing in the healthcare sector, investee com-panies, and throughout the modernization of the Central Public Administration.

Keyphrases: Artificial Neural Networks, Big Data, Codiv-19, EMU, digital technology, economic growth, policy action, public investment

@booklet{EasyChair:4720,
  author    = {Giovanna Morelli and Marco Mele and Cesare Pozzi},
  title     = {Big Data, Public Investment and Economic Growth in the COVID-19 Epidemic. Evidence from an ANNs Experiment on EMU Countries},
  howpublished = {EasyChair Preprint 4720},
  year      = {EasyChair, 2020}}