Do Technological Innovations Affect Unemployment? Some Empirical Evidence from European Countries
Round 1
Reviewer 1 Report
This paper deals with an extremely important and hot topic and provides interesting novel macro evidence. Although I am generally positive, the paper needs some key revisions.
The introduction should be extended and the novelty of the contribution better stressed. Moreover, the discussion of the skill-biased-technological-change (SBTC) literature should be extended (see the additional references below).
The literature review is basically ok, but should be updated through the implementation of the references listed below. In addition, the macro, micro and sectoral levels of analysis should be better separated and qualified (p.4).
Table 2 should report the acronyms used for the variables in the following tables. For the expected signs, use positive and negative, not direct and indirect.
The GMM-SYS performance with such a small number of observations should be discussed and qualified.
FN 2 (p11) is unclear and should be reported at the bottom of Table 6.
The conclusions should be considerably extended, discussing why the macro-analysis is inconclusive: composition effects, measurement limitations, countries’ specificities, macro-determinants of unemployment not included in the analysis (for instance concerning the labor supply, institutional and historical circumstances), etc.
References: most of papers reported as working papers were published in journals (for instance the ones by Vivarelli and co-authors), please update.
Additional references to be discussed and added to the final bibliography:
Autor, D.H., 2015. Why are there still so many jobs? The history and future of workplace automation. Journal of Economic Perspectives, 29, 3-30.
Berman, E., Bound, J. & Griliches, Z. (1994). Changes in the demand for skilled labor within U.S. manufacturing industries. Quarterly Journal of Economics, 109, 367-398.
Bogliacino, F., Vivarelli, M., 2012. The job creation effect of R&D expenditures. Australian Economic Papers 51, 96-113.
Bonanno, G. (2016), ICT and R&D as inputs or efficiency determinants? Analysing Italian manufacturing firms (2007-2009), Eurasian Business Review, 6, 189-213.
Brynjolfsson, E., McAfee, A. 2011. Race Against the Machine: How the Digital Revolution is Accelerating Innovation, Driving Productivity, and Irreversibly Transforming Employment and the Economy. Lexington, MA: Digital Frontier Press
Ciriaci, D., Moncada-Paternò-Castello, P., Voigt, P., 2016. Innovation and job creation: a sustainable relation? Eurasian Business Review 6, 189-213.
Evangelista, R., Vezzani, A., 2012. The impact of technological and organizational innovations on employment in European firms. Industrial and corporate change 21, 871-899.
Frey, C.B., Osborne, M.A., 2017. The future of employment: how susceptible are jobs to computerisation? Technological Forecasting and Social Change 114, 254-280.
Haile, G. - Srour, I. - Vivarelli, M. (2017), Imported Technology and Manufacturing Employment in Ethiopia, Eurasian Business Review, 7, 1-23.
Meschi, E. - Taymaz, E. - Vivarelli, M. (2016), Globalization, Technological Change and Labor Demand: A Firm Level Analysis for Turkey, Review of World Economics, 152, 655-680.
Meschi, E. - Taymaz, E. - Vivarelli, M. (2011), Trade, Technology and Skills: Evidence from Turkish Microdata, Labour Economics, 18, S60-S70.
Piva, M., Santarelli, E., Vivarelli, M., 2005. The skill bias effect of technological and organisational change: Evidence and policy implications. Research Policy 34, 141-157.
Piva, M., & Vivarelli, M. (2009), The role of skills as a major driver of corporate R&D. International Journal of Manpower, 30, 835-852.
Van Reenen, J., 1997. Employment and technological innovation: Evidence from U.K. manufacturing firms. Journal of Labour Economics, 15, 255-284.
Vivarelli, M., 2014. Innovation, Employment and Skills in Advanced and Developing Countries: A Survey of Economic Literature. Journal of Economic Issues 48, 123-154.
Vivarelli, M., Evangelista, R., Pianta, M., 1996. Innovation and employment: Evidence from Italian manufacturing. Research Policy 25, 1013-1026.
Author Response
We appreciate for very valuable comments of the reviewer. All comments to the review are attached.
Author Response File: 
Author Response.pdf
Reviewer 2 Report
the paper is not so creative. it uses existing data and tests a very simple hypothesis. the findings are not surprising either. Major flaws:
1. the time period is not long enough to cause any major shift in the economy. it would have been better to do this with innovations in the past decades - even century
2. there are so many variables. governments initiating training programs can impact this.
3. also economic crises are known to cause an increase in R&D, so reverse relations do exist
4. relationships are not causalities - authors treat them so
Author Response
1. The time period is not long enough to cause any major shift in the economy. it would have been better to do this with innovations in the past decades - even century
This suggestion coul be considered as the idea for new research because analysing available data we didn‘t aim to examine the long run effects of technological innovatins on unemployment. As it was indicated in the paper „Data covers the period of 2000 – 2012 on yearly basis, thus this enables us to capture just short-term effect of technological innovation on unemployment.”
2. There are so many variables. governments initiating training programs can impact this.
Our model includes a lot of unemployment controls (see Table 2) and one of them is bnf that covers government expenditures on active and passive unemployment programs, including training, financial support to start own bussiness and etc. Might be acronym bnf suggests government spending on social benefits is misleading.
3. Also economic crises are known to cause an increase in R&D, so reverse relations do exist
This feedback effect is also discussed in Innovation in the Crisis and Beyond, in: OECD Science, Technology and Industry Outlook 2012. (OECD, 2012) “In order to prevent firms from reducing their R&D expenses and to maintain the national R&D capacities, policymakers in many industrialized countries, including Austria, Denmark and Sweden, reacted immediately to the most recent crisis and increased the public R&D budget.”
To deal with potential endogeneity of R&D variable as well as others we used SGMM estimation method with internally predetermined instrumental variables.
4. relationships are not causalities - authors treat them so
Cause was replaced with affect / impact
Round 2
Reviewer 2 Report
the paper is acceptable - the authors should include their response to my prior comments as limitations and future research at the end if they have not done so yet
Author Response
Comments of the reviewer were included for future research in the conclusions.
