ICT and resilience in times of crisis: evidence from cross-country micro moments data

ABSTRACT

ICT-intensive firms are often found to have a better performance than their non-ICT-intensive counterparts. Along with investing in ICT capital they have to adapt their production and business processes in order to reap the potentials implied by the use of ICT. Are these firms also more resilient in times of crisis? We study this question by exploiting a novel and unique data set from the Micro Moments Database. Covering 12 countries, 7 industries and the period from 2001 to 2010, the data allow us to distinguish between ICT-intensive and non-ICT-intensive firms within industries. We find evidence that indeed during the crisis in 2008 and 2009, ICT-intensive firms were hit less hard with respect to their productivity. This holds in particular for firms from service industries. Moreover, ICT-intensive firms were also more successful in introducing process innovations during that period which could explain their better productivity performance compared to non-ICT intensive firms.

KEYWORDS:

• ICT
• innovation
• productivity
• economic crisis
• resilience
• meso-level data

JEL CLASSIFICATION:

• H12
• J24
• O31
• O47

Acknowledgments

We are grateful for helpful comments from an anonymous referee, the editor, Eric Bartelsman, Eva Hagsten, Mary O'Mahony and to the participants of seminars at ZEW, ECB as well as the University of Giessen and the VfS annual conference 2017. The paper benefited greatly from financial support within the scope of the SEEK research programme and was written mainly at ZEW. For further information on projects of the authors see http://www.zew.de/de/team/ibe/ and http://www.zew.de/de/team/pse/ as well as the ZEW annual report on http://www.zew.de/en. This paper represents the authors' personal opinions and does not necessarily reflect the views of the Deutsche Bundesbank and Statistics Netherlands.

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1 Resilience is a complex concept, which can be defined, e.g. as the capacity of an economy to reduce vulnerabilities, to resist to shocks and to recover quickly (OECD 2016). We use the term ‘resilience’ in a rather specific and narrow way concentrating on productivity, i.e. how firms' productivity reacts to adverse economic shocks.

2 Although there are publicly accessible commercial cross-country firm-level data sets, such as Amadeus or Orbis, these data sets typically contain only a limited set of variables necessary for comprehensive econometric analyses and at the same time exhibit problems of comparability and coverage. Also, until recently, hardly any (cross-country) databases from national statistical offices did exist which would have allowed for such studies. Recently, also the OECD and the ECB embarked on distributed microdata projects (Dynemp/Multiprod and CompNet, respectively) although ICT and innovation data are not part of these endeavours yet, see Berlingieri et al. (2017) and Lopez-Garcia (2018).

3 More information about the database is provided in the Data Appendix. This description is based on Bartelsman, van Leeuwen, and Polder (2016) as well as the technical documentation (see Bartelsman, Hagsten, and Polder 2018).

4 Specifically, the ESSnet projects ICT Impact and Linking of Microdata on ICT Usage (ESSLimit), and Linking of Microdata to Analyse ICT Impact (ESSLait) are to be mentioned. Studies which made use of the data from these projects include Bartelsman, van Leeuwen, and Polder (2016), Hagsten (2016), and Pantea, Sabadash, and Biagi (2017).

5 The distributed micro data methodology and the resulting MMD is not the only way to allow cross-country analysis of firm-level data. Commercially available sources, such as ORBIS from Bureau van Dijk are sourced from Chamber of Commerce or mandatory filings of publically traded firms. However, the coverage and sources vary significantly across countries and it is costly to combine these data with other firm-level indicators.

6 We are aware that broadband access is not a perfect measure of all aspects of ICT-intensity, especially that it might not capture the use of applications which do not necessarily access the internet, such as certain IT manufacturing tools (like robots). Nonetheless, we still consider this proxy an appropriate choice since a broadband access and the usage thereof are the basis underlying many modern ICT applications and should thus be highly correlated with the use of a wide range of such applications in companies.

7 For four countries however, namely Denmark, France, Ireland and Sweden, the innovation data is available only from 2006 on.

8 Unfortunately, the innovation data in the CIS refer to product/process innovations of a firm in a three-year period, and are observed only in even years. For odd years, the MMD uses the t+1 value if the firm is present in both years in the ECIS sample. So, for the crisis period, the 2008 innovation rates concern innovation taking place in the time bracket (2006–2008). For 2009, they concern innovations taking place in the time bracket (2008–2010). This might have a downward bias on the differences over time, i.e. innovation rates in crises years might be overestimated as they refer to adjacent years as well.

9 This could be the consequences of a downward bias due to the endogeneity of capital. We also tested whether the negative coefficient is due to multi-collinearity problems between our ICT variable and the capital services measure. However, excluding the ICT variable from the regression did not affect the sign and significance of the capital coefficient.

10 Note that we can do this only for a subset of countries and years for which this information is available. Also, in an additional robustness check we added a lagged dependent variable to allow for a dynamic productivity process. This did not change our results significantly. The results are available upon request.

11 The definition of the measure of ICT intensity is fixed over the whole period of observation, i.e. in each year firms with more than 40% of employees having access to broadband internet are defined to be ICT intensive in that year of observation. To take into account that in the early years of observation only a few firms are ICT intensive whereas in later years a lot of firms belong to this category because of higher availability and adoption rates of broadband we conduct another robustness check. We exclude all observations from the period up to 2004 focusing on the later years when broadband was more widely available and adopted. The results confirm our previous findings and are available upon request.

12 Dachs et al. (2016) analyse the employment effects of product and process innovation over the business cycle. They show that process innovation may increase the resilience of firms by reducing production costs and thus increasing demand for the firms' less costly products or by improving its cost efficiency relative to non-innovative firms.

13 In our data, approximately 32 (51)% of firms in the manufacturing (service) sector are classified as being ICT-intensive.

14 This subsection describing distributed micro data analysis and the micro moments database has been taken from Bartelsman, van Leeuwen, and Polder (2016).