Technology changes and the emergence of new technologies strongly affect the labor market and its components(Bruckner, LaFleur, et al. 2017). Researchers and theorists(Wicksell 1961, Pigou 1962, Marx 1969, Appelbaum and Schettkat 1995, Vivarelli and Pianta 2000, Bogliacino and Pianta 2010) of different schools of economics h


Technology changes and the emergence of new technologies strongly affect the labor market and its components(Bruckner, LaFleur, et al. 2017). Researchers and theorists(Wicksell 1961, Pigou 1962, Marx 1969, Appelbaum and Schettkat 1995, Vivarelli and Pianta 2000, Bogliacino and Pianta 2010) of different schools of economics have tried to identify the amount of these changes and how they affect the labor market in the framework of theoretical and experimental work. From a theoretical point of view, any improvement in technology and technological innovation, on the one hand, destroys existing employment and, on the other hand, creates new job opportunities through product innovation. But this scientific controversy continues because there is no unique model or variable to evaluate the impact of technological change in the literature. However, each of these studies sheds some light on the subject.

Today, new technologies are widely affected by the fear of technological unemployment (Brynjolfsson and McAfee 2011). Regarding the relationship between technology and employment, two fundamental theories contradict each other, with the former stating that technological innovations the same amount of production save labor and create technological unemployment,(Petit 1995, Vivarelli 1995, Vivarelli and Pianta 2000, Coad and Rao 2011, Vivarelli 2014, Dosi and Mohnen 2019, Sasaki 2020, Zhu, Qiu, et al. 2021)and the other claims that it can offset the direct destructive effects of process innovation on employment or even more so by indirect economic effects through product innovation.

Therefore, economic theory does not have a clear answer about the impact of technological change on employment, which depends on several factors; the first of which is the complexity of the indicator of technological change and innovation. Measuring technology change is a very complex subject. Because technology has a wide and deep concept and every day with the spread of science and knowledge, new technologies are either invented or used in the process of production, distribution, and exchange. Some of these technologies affect the way they are produced and distributed, and some of them introduce new products and services to the market.

If at one time technologies such as steam engines, electric conveyors or information technology caused great economic changes and the so-called industrial revolution, today extensive technologies such as artificial intelligence, robotics, virtual reality, cloud system, simulation, Internet, and other technologies in the form of The Fourth Industrial Revolution (or Industry 4.0), they affect economic markets. The labor market and its components such as employment, unemployment, new jobs, wages, and the quality of human labor are undoubtedly affected by these changes. Accordingly, identifying and measuring these changes is a vital issue in economic research.

Previous Empirical Evidence

In recent years, due to the importance of the subject, many studies have been conducted to measure the impact of technological changes on employment at different economic levels (micro and macro)[see; Hall and Heffernan (1985), Layard and Nickell (1985), Van Reenen (1997), Greenan and Guellec (2000), Antonucci and Pianta (2002), Piva and Vivarelli (2005), Lachenmaier and Rottmann (2007), Benavente and Lauterbach (2008), Zimmermann (2009), Bogliacino and Pianta (2010), Meriküll (2010), Coad and Rao (2011), Evangelista and Vezzani (2012), Vivarelli (2014), Van Roy, Vertesy et al. (2015), Ciriaci, Moncada-Paternò-Castello et al. (2016), Ugur and Mitra (2017), Ugur, Awaworyi Churchill et al. (2018), Dosi, Piva et al. (2019)] But all researchers have used almost identical tools and proxies to measure the amount of technology in their research.

For example, Greenan and Guellec (2000)using the variables of process innovation and product innovation, the positive effects of technology on employment were achieved. Then Antonucci and Pianta (2002)used the variables of sales innovation cost and the share of new or improved product in sales to measure technology in their research. Also, Piva and Vivarelli (2005)in 2005 using the cost of research and development failed to achieve a clear result of the impact of technology on employment then Mastrostefano and Pianta (2009) used the level of innovation of companies in products or production process and the share of new or improved product in sales to measure technology, which achieved the positive role of product innovation on employment of high-tech industries.

A year later Bogliacino and Pianta (2010)used the variables of research and development, new product, and new product line in their research and observed the positive effects of technology on employment. Coad and Rao (2011)also cited patents and paid expenditure research and development as indicators for measuring technological change. In 2016 Ugur, Awaworyi et al. (2016)used the variables of research and development intensity, number of patents, number of trademarks, and expansion of knowledge and information and communication technology.

Dosi, Piva et al. (2019)used two variables of technology improvement by adding or moving capital and improving technology without capital and new equipment to measure the impact of technology on employment. Not all variables used can show the positive and negative effects of all variables at all economic levels. The reason that inconsistent and ambiguous results have been obtained from previous studies to measure the impact of technological change on employment is the use of different single variables to show technological change. It seems that building a technology composite indicator to show the impact of technology in different conditions and environments on other variables such as employment, economy, etc. is a basic need.

For more on Table A, see the details of the variables used and the results by breakdown economic level.

Table A: Previous Empirical Evidence

Level of AnalysisAuthor(s), YearMeasurement Instrument(s) for Technological Innovation(s)Labor Market Outcome(s) as Endogenous Variable(s)result

















Sectoral level

Mehta and Mohanty (1993)Technology elasticity (adoption)Labor demandnegative
Berman, Bound et al. (1994)Investment in computers, expenditures on R&DSkilled labor force demandpositive
Greenan and Guellec (2000)Product and process innovationJobs flow – employment growthAt firm-level, (+) effect of process innovation > than the product on employment growth. Industry-level employment benefits more from product innovation
Goux and Maurin (2000)New technologies usageLabor demandunclear
Gera, Gu et al. (2001)The stock of R&D, the stock of patentsSkilled labor force demandpositive
Morrison Paul and Siegel (2001)Investment in technology, R&D investmentLabor demandnegative
Evangelista and Savona (2002)Innovation intensityEmploymentnegative
Piva, Santarelli et al. (2006)ICT technologiesSkilled and unskilled labor force demandnegative
Garofalo, Rycx et al. (2008)Patent per capitaGross job turnover ratepositive
Mastrostefano and Pianta (2009)diffusion of technology, product innovationEmployment growth & Demand, wages,(+) Effect of demand growth, (−) role of wage changes, low effects of diffusion of innovation, (+) role of product innovation, only in high-innovation industries
Huo and Feng (2010)The index of process and product innovation intensityEmploymentpositive
Meriküll (2010)Product and process innovationJob flows – employment growthProduct innovation has mild effects at the firmlevel, (+) at the industry. Process innovation weakly (+) at firm-level, (-) at the industry. Limited net effects
Bogliacino and Pianta (2010)R&D expenditure, expenditure for innovation-related machineryEmploymentpositive
Araújo, Bogliacino et al. (2011)R&D expenditureLabor demandpositive
Lucchese and Pianta (2012)Product and process innovation (up-down-swings)Employment growth &In upswings (+) effect of product innovation; in downswings (−) effect of process innovation
Bogliacino, Piva et al. (2012)R&D expenditureLabor demandpositive
Dosi, Piva et al. (2019)disembodied technological change (R & D), embodied technological changesEmploymentthe positive impact of disembodied technological change (R & D) in the upstream sector and also the positive impact of embodied technological changes in the downstream sector.























Casavola, Gavosto et al. (1996)R&D expenditure, patents, software licensesEmploymentpositive
Doms, Dunne et al. (1997)Automation technologiesWages, occupational mix, workforce educationpositive
Dunne, Haltiwanger et al. (1997)R&D stock, technology adoptionEmployment, labor share changepositive
Van Reenen (1997)PatentsEmploymentpositive
Blanchflower and Burgess (1998)Introduction of new technologyEmploymentpositive
Klette and Førre (1998)R&D investmentsJob creationunclear
Smolny (1998)Product and process innovations3Employmentpositive
Boone (2000)Product and process innovationsUnemploymentnegative
Gatti (2000)Product-oriented and knowledge-based R&DUnemploymentpositive
Greenan and Guellec (2000)Product and process innovationEmploymentpositive
Greenhalgh, Longland et al. (2001)R&D, patentsEmploymentpositive
Aguirregabiria and Alonso-Borrego (2001)Investment in R&D, purchases of technological capitalEmployment by occupationspositive
Falk and Seim (2001)Investment in ITHigh-skilled employmentpositive
Greenan, Mairesse et al. (2001)R&D expenditure, IT adoption, and intensity of usageWages, skill composition, employmentpositive
Luque (2005)Technological intensitySkill mix changespositive
Piva and Vivarelli (2005)R&D expenditureEmployment (blue-collars, white-collars)unclear
Lachenmaier and Rottmann (2007)R&D, patentsEmploymentpositive
Benavente and Lauterbach (2008)Product and Process innovationEmployment growth(+) Effect of product innovation. No effect of process
Yang and Lin (2008)R&D, patentsEmploymentpositive
Hall, Lotti et al. (2008)Product and process innovationsEmploymentpositive
Stam and Wennberg (2009)R&DEmployment growthNo average effect between R&D and employment growth. (+) Effect on top 10% and high tech
Zimmermann (2009)Product and process innovation QuantileEmployment growth(+) Effect of process innovation on employment for both growing and shrinking SMEs. Stronger effects on high-growth SMEs
Baccini and Cioni (2010)Introduction of ICTDemand for skilled workersunclear
Lachenmaier and Rottmann (2011)R&D, patentsEmploymentpositive
Coad and Rao (2011)R&D expenditure, patents applicationsTotal number of jobspositive
Meschi, Taymaz et al. (2011)R&D expenditure, technological transfer from abroad, foreign ownershipDemand for skilled laborpositive
Crespi and Tacsir (2012)Product and Process innovationEmployment growth(+) Effect of product, no effect of process innovation
Evangelista and Vezzani (2012)Product and process innovationsEmploymentpositive
Bogliacino, Piva et al. (2012)R&D expenditureEmploymentpositive
Dachs and Peters (2014)Product and process innovationsEmploymentpositive
Harrison, Jaumandreu et al. (2014)Product and Process innovation (old and new products)Employment growth &(−) Effect of process innovation under fixed output. (+) Effect of product innovation
Triguero, Córcoles et al. (2014)Persistent innovationEmployment growth(+) The link between persistent process innovation and employment growth, no role of persistent product innovation
Van Roy, Vertesy et al. (2015)patent quality information (forward citation)Employment growth(+) Effect of patenting activities on employment but valid only for high-tech manufacturing sectors
Herstad and Sandven (2015)different types of innovative activitiesEmployment growth(+) Correlation between ex-ante growth and innovative activity (+) Effect of process innovation on ex-post employment growth, for firms in the top of the distribution
Falk (2015)Product and process innovationsEmploymentpositive
Kwon, Park et al. (2015)Product and process innovationsEmploymentpositive
Ciriaci, Moncada-Paternò-Castello et al. (2016)R&D expenditureEmploymentpositive
Ugur and Mitra (2017)Product and process innovationsDemand for skilled laborThe positive effect of technology on employment when specialized and scientific people are studied
Ugur, Awaworyi Churchill et al. (2018)IPRs, ICT, R&DEmploymentPositive but low impact of innovation on employment
Reference no: EM132069492



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