https://www.oecd-ilibrary.org/science-and-technology/closing-the-italian-digital-gap_e33c281e-en
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Title page
Contents
Acknowledgements 4
Executive summary 5
1. Introduction 10
2. The digital gap of the Italian economy: key macroeconomic facts 16
2.1. The Italian digital gap in the National Accounts 17
2.2. The Italian gap in investments in intangible capital 20
2.3. Cross-country comparison in digital technology adoption 20
3. Data and descriptive analysis 22
4. Explaining the Italian digital gap: microeconomic evidence 25
4.1. Conceptual framework 25
4.2. Within-firm determinants of technology adoption and its returns 26
4.3. The diffusion of ultra-speed broadband infrastructure 28
4.4. STEM education 32
4.5. The R&D tax credit 36
4.6. Supporting digital adoption: an evaluation of the hyper-depreciation subsidy 38
4.7. Additional factors outside the firm: spillovers and finance 48
5. The impact of COVID-19 on the digital gap of Italian firms 49
5.1. The impact of the COVID-19 on the performance of Italian firms, by initial level of digitalisation 52
5.2. The impact of the COVID-19 crisis on the digital divide between Italian firms 55
6. Conclusions and policy implications 59
Endnotes 63
References 65
Annex A. Additional tables and figures 76
Annex B. Data and descriptive analysis 85
Data 85
Descriptive analysis: characterising the digital transformation in Italy 87
Endnotes to Annex B 96
Annex C. Explaining the Italian digital gap 97
A Framework to Understand Digital Transformation in Firms 97
Internal factors 98
External factors 107
Within-firm determinants of the digital transformation 112
R&D and intellectual property products 129
Factors outside the firm affecting the digital gap of Italian firms 131
Endnotes to Annex C 137
Figure 2.1. Multifactor productivity - index 1995=100 16
Figure 2.2. Slow productivity growth in Italy is driven mostly by micro and small firms 17
Figure 2.3. Investments in ICT capital - percentage of GDP 18
Figure 2.4. Investments in intangible capital - percentage of GDP 18
Figure 2.5. Investments in different types of intangibles as a percentage of GDP 19
Figure 2.6. Investments in economic competencies as a percentage of gross value added in the business sector - 2015 20
Figure 2.7. Results of the ICT surveys, holding fixed sectoral distribution - 2015-18 21
Figure 3.1. Labour productivity by number of technologies adopted 24
Figure 4.1. Drivers of digital technology adoption and of its returns 26
Figure 4.2. Diffusion of NGA broadband connection across Italian municipalities, 2012-18 28
Figure 4.3. The effect of NGA broadband supply on the adoption of enabling technologies 29
Figure 4.4. The effect of NGA broadband supply on the adoption of digital technologies 30
Figure 4.5. The effect of NGA broadband supply on labour productivity, revenues, and employment 31
Figure 4.6. Universities with STEM program and their MNCS score 32
Figure 4.7. Share of highly educated workers and education 33
Figure 4.8. STEM programs and advanced technology adoption by firm size class 34
Figure 4.9. STEM programs and complementarity between skills and advanced technology adoption 35
Figure 4.10. Average expenditure on intramural R&D - 2013=100 37
Figure 4.11. Average expenditure on intramural R&D by quartiles of the 2013-14 distribution of R&D expenditures - 2013=100 38
Figure 4.12. The hyper-depreciation policy: number of beneficiaries, total allowance and total investments subsidised - 2016-18 39
Figure 4.13. Ex-ante firm characteristics and use of the hyper-depreciation 41
Figure 4.14. Effect of the hyper-depreciation on technology adoption - 2018 43
Figure 4.15. Adoption rates of advanced technologies among beneficiaries of the hyper-depreciation and their counterfactual control group 44
Figure 4.16. Complementarity between hyper-depreciation and NGA supply for advanced digital technologies 45
Figure 4.17. Effect of the hyper-depreciation on firm outcomes - growth rate between 2015 and 2018 46
Figure 4.18. Effect of the hyper-depreciation on skill education 46
Figure 4.19. Effect of the hyper-depreciation on labour productivity by skill of the top-executive 47
Figure 5.1. Probability that the firm is temporarily or permanently closed in November 2020 and digital technology adoption - different technologies 52
Figure 5.2. Probability that revenues increased y-o-y over June-October 2020 and digital technology adoption - different technologies 53
Figure 5.3. Probability of closure by firm productivity and adoption of advanced digital technologies 54
Figure 5.4. Probability of having adopted teleworking over June-November 2020 and digital technology adoption - different technologies 55
Figure 5.5. Probability of improving digital communication and collaboration by digital technology adopted - bundles of technologies 56
Figure 5.6. Probability that the firm increased its investments by type of expenditure and number of technologies adopted in 2018 57
Boxes
Box 4.1. Estimating the amount of subsidised investments by the hyper-depreciation 40
Box 4.2. Propensity score matching to assess the impact of the hyper-depreciation strategy 42
Box 5.1. Digitalisation and the COVID-19 crisis: empirical strategy 51
Annex Tables
Table A A.1. Descriptive statistics of the R&D survey sample analysed in Section 4.5 83
Table A A.2. Balancing of 2013 firm-level characteristics and 2011-2013 trends between firm usingand not using the hyper-depreciation - by... 84
Table A B.1. Adoption rates of digital technologies by size and age 91
Table A B.2. Size-age coefficients for business technologies/advanced digital technologies - United States and Italy 92
Table A B.3. Adoption rates by labour productivity deciles 92
Annex Figures
Figure A A.1. Labour productivity gap between national and global frontier - Italy and the United States 76
Figure A A.2. Results of the ICT surveys, by sector - 2015-18 77
Figure A A.3. Results of the ICT surveys by size class, holding sectoral distribution fixed - 2015-18 77
Figure A A.4. The effect of NGA broadband supply on the adoption of advanced digital technologies - by skill intensity in 2012 78
Figure A A.5. The effect of NGA broadband supply on labour productivity - by skill intensity in 2012 79
Figure A A.6. Probability that the firm is temporarily or permanently closed in November 2020 and digital technology adoption - bundles of... 80
Figure A A.7. Probability that revenues increased y-o-y over June-October 2020 and digital technology adoption - bundles of technologies 80
Figure A A.8. Probability of having adopted teleworking over June-November 2020 and digital technology adoption - bundles of technologies 81
Figure A A.9. Probability of improving digital communication and collaboration by digital technology adopted - different technologies 81
Figure A A.10. Probability that the firm reduced its investments by number of technologies adopted in 2018 82
Figure A B.1. Adoption rates, aggregate value added and aggregate employment of adopting firms by digital technologies, year 2018 88
Figure A B.2. Sectoral distribution of adopters of digital technologies 89
Figure A B.3. Adoption rates across Italian geographic areas 90
Figure A B.4. Distribution of firms by number of technologies adopted 93
Figure A B.5. Bundling of digital technologies among adopters of advanced digital technologies and users of online platforms for e-sales 94
Figure A B.6. Labour productivity by number of technologies adopted 95
Figure A C.1. Drivers of digital technology adoption and of its returns 98
Figure A C.2. Distribution of value added by sectoral digital intensity - 2018 or latest available year 99
Figure A C.3. ICT investments, software investments, and R&D expenditures as a share of GDP - difference in growth rates between Italy and... 100
Figure A C.4. Adoption rates by skill-intensity of the workforce and labour productivity gains from technology adoption and skill-intensity of the... 113
Figure A C.5. Productivity gains of a high-skilled workforce by firm size and number of digital technologies 114
Figure A C.6. Estimated complementarity between advanced digital technologies and workers with different education 116
Figure A C.7. Estimated complementarity between advanced digital technologies and workers with different education by geographic area 117
Figure A C.8. Share of firms by skill of top-executive, all economy, sectors 119
Figure A C.9. Share of firms with HS top executive, by geographic area, holding fixed firm's sector 120
Figure A C.10. Share of firms with HS top executive, by size, holding fixed firm's sector and area 120
Figure A C.11. Share of firms with HS top executive, by age, holding fixed firm's sector, area and size 121
Figure A C.12. Share of firms with HS top executive, by productivity decile, holding fixed firm's sector, area, size and age 121
Figure A C.13. Share of firms adopting technologies by skill of top-executives 123
Figure A C.14. Share of firms with HS top-executive by number of technology adopted 123
Figure A C.15. Labour productivity by number of technologies adopted and skill of the top executive 124
Figure A C.16. Returns to advanced technology, high-skilled labour, and their complementarity 125
Figure A C.17. Complementarity between advanced technology and high-skilled labour by geographic area 126
Figure A C.18. Probability of having at least one middle manager - by education of the top executives and firm size 127
Figure A C.19. Probability of having middle managers with high education - by education of top executive and firm size 128
Figure A C.20. Technology adoption by existence and education of middle managers - conditional on education of top-executives 128
Figure A C.21. Share of firms with no, low-skilled, and high-skilled middle managers, by number of technologies adopted 129
Figure A C.22. Advanced technology adoption by firm size and R&D status 130
Figure A C.23. Probability of applying for a patent 131
Figure A C.24. Spillover effects by reference market and by type of technology 132
Figure A C.25. Spillover effects by quartiles of the distribution of sector-province level, Herfindhal-Hirschmann index 133
Figure A C.26. Provincial spillovers for firms active in areas where there is or there is not a PID/DIH institution 134
Figure A C.27. Leverage and adoption over the life cycle 135
Figure A C.28. Effect of credit supply shocks on advanced technology adoption 136
Annex Boxes
Box A C.1. Estimating complementarities between digital technologies and inputs: a production function approach 115
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