Start-ups survival through a crisis. Combining machine learning with econometrics to measure innovation

Economics of Innovation and New Technology

42 Pages Posted: 18 Feb 2021

See all articles by Marco Guerzoni

Marco Guerzoni

Università degli Studi di Milano-Bicocca - Department of Economics, Management and Statistics (DEMS)

Massimiliano Nuccio

Ca Foscari University of Venice - Department of Management

Consuelo Nava

affiliation not provided to SSRN

Date Written: January 19, 2020

Abstract

This paper shows how data science can contribute to improving empirical research in economics by leveraging on large datasets and extracting information otherwise unsuitable for a traditional econometric approach. As a test-bed for our framework, machine learning algorithms allow to create a new holistic measure of innovation following a 2012 Italian Law aimed at boosting new high-tech firms. We adopt this measure to analyse the impact of innovativeness on a large population of Italian firms which entered the market at the beginning of the 2008 global crisis. The methodological contribution is organised in different steps. First, we train seven supervised learning algorithms to recognise innovative firms on 2013 firmographics data and select a combination of those models with the best prediction power. Second, we apply the latter on the 2008 dataset and predict which firms would have been labelled as innovative according to the definition of the 2012 law. Finally, we adopt this new indicator as the regressor in a survival model to explain firms' ability to remain in the market after 2008. The results suggest that innovative firms are more likely to survive than the rest of the sample, but the survival premium is likely to depend on location.

Keywords: innovation, machine learning, survival, start-ups

Suggested Citation

Guerzoni, Marco and Nuccio, Massimiliano and Nava, Consuelo, Start-ups survival through a crisis. Combining machine learning with econometrics to measure innovation (January 19, 2020). Economics of Innovation and New Technology , Available at SSRN: https://ssrn.com/abstract=3769024

Marco Guerzoni (Contact Author)

Università degli Studi di Milano-Bicocca - Department of Economics, Management and Statistics (DEMS) ( email )

Piazza dell'Ateneo Nuovo, 1
Milan, 20126
Italy

Massimiliano Nuccio

Ca Foscari University of Venice - Department of Management ( email )

San Giobbe, Cannaregio 873
Venice, 30121
Italy

Consuelo Nava

affiliation not provided to SSRN

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