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 thedigital 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.

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

cesare pozzi;
2020

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 thedigital 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.
978-88-6685-021-2
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11369/400013
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