Journal number 4 ∘ Tinatin Loladze ∘
Important Aspects of the Impact of Innovation on Unemployment

Annotation. Today, successful modernization of the economy is achieved through competitive human capital, which is a significant factor of socio-economic development and competitiveness of the country's economy. It is no coincidence that at the beginning of the new millennium, many countries are moving to the "knowledge economy", where special importance is attached to human capital, which has a direct impact on economic indicators, activation of innovative processes and competitiveness.

This paper reviews from a theoretical point of view the results of the works of leading economists covering the impact of innovation on employment at the micro and industry level. The effect of innovation on labor demand is not easy to study.

Innovation and unemployment are two interrelated economic elements that have been discussed continuously in economic debates since the beginning of the 21st century. The conventional approach views innovation as a tool for economic transformation, resulting in economic growth and job creation. Another approach points to various mechanisms that can compensate for the primary effect of innovation, the result of which is uncertain.

Empirical studies in this field can be divided according to the level of analysis: macro, sectoral and micro levels. It should be noted that most recent empirical studies analyzing the relationship between technological innovation and unemployment cover the micro level and there is relatively little research at the macro level. The theoretical issues discussed here, which concern precisely the micro and sectoral levels, will help me to conduct a larger-scale macro-level empirical study.

Key words: Technological Innovation; Firm and Industry Level Evidence; Unemployment; Labor Demand. 

1. Introduction

Since the beginning of the industrial revolution, the global economy has been developing rapidly due to new technologies. Each new technological wave has a positive impact on economic growth, productivity and opportunities for new types of business.

Researchers study the impact of innovation on various parameters of the labor market: employment, wages, labor demand, unemployment and others. Some studies show that technological progress leads to process and product innovation, which creates jobs (Say, 2009; Schumpeter, 2017). Some argue that technological innovation may increase unemployment (Wood, 2004; Feldmann, 2013), others (Liso & Leoncini, 2011) argue that technological progress provides higher wages due to increased demand for skilled workers, while others (Piva et al., 2006) note, that technological change adversely affects skilled and unskilled workers As Alonso-Borrego and Collado (2002) observed, technological innovation is one of the main sources of job creation and destruction.

Technological innovation is one of the forces influencing long-term productivity and economic growth.

Innovations are divided into categories. The Oslo Manual1 (OECD 2005) defines 4 types of innovation: product, process, marketing and organizational. My research is about assessing the impact of technological innovation on unemployment, which is why product and process innovation are important. The separation between process and product innovation is often artificial (Flichy, 2007). However, it should be noted that this classification is mainly used in the evaluation of scientific research, when assessing the impact of technological innovations on labor market parameters.

There are different opinions among researchers about the impact of product and process innovation on employment. Some argue that product innovation provides new products to the market, which stimulates new demand and leads to a positive correlation between technological variables and employment (Vivarelli, 2014; Harrison et al., 2008). Some even argue that process innovation has a negative impact on the workforce due to the replacement of labor with new machines, machinery, which leads to increased productivity and efficiency (Van Reenen, 1997; Bogliacino & Vivarelli, 2012; Vivarelli, 2014; Marcolin et al., 2016). ). It should be said that low production costs are achieved with technological changes. This is contrary to Schumpeter's view that technological progress leads to process and product innovation, which naturally leads to job creation (Ziemnowicz, 2013). According to Marxist philosophy, it is implausible that newly developed labor-saving machines can create a sufficient number of jobs (Wood, 2004). Proponents of classical economic theory put forward a theory that Karl Marx later referred to as compensation theory: technological changes can lead to various market compensation mechanisms: new machines, lower prices, new investments and lower wages (Vivarelli, 2014). These compensation mechanisms can offset the initial impact of labor-saving innovation in process innovation (Meschi et al., 2016).

Looking at the various studies I have reviewed, I can say that the results of theoretical studies do not provide a clear answer about the impact of technological innovation on unemployment. 2 outcomes have been identified: 1. Labor-saving innovations create technological unemployment 2. Suspicious compensation mechanisms driven by prices and new demand destroy unemployment (Piva & Vivarelli, 2005).

There is relatively little research on the impact of technological innovation on labor market parameters at the macro level. According to Vivarelli (2014), macroeconomic studies of the impact of innovation on employment are limited to the 1980s and 1990s, and microeconomic studies are more recent.

A limitation of micro-level studies is that these studies do not consider the impact on competing firms in the same industry and the impact on other industries (Feldmann, 2013). Sector-level studies estimate net employment effects in specific industries, but they do not account for indirect sectoral effects of technological change (Bogliacino & Vivarelli, 2012). Industry level studies are more popular than micro level studies.

The main findings of industry-level studies are that process innovation is labor-saving, while product innovation is employment-friendly (Mehta & Mohanty, 1993; Huo & Feng, 2010) and that technological innovation increases the relative demand for skilled workers (Machin & Van Reenen, 1998; Morrison Paul & Siegel, 2001).

2. The Common Theoretical Framework

Mercantilists believed that the introduction of new machines would be linked to the employment problem. According to Freeman and Soete (1994), a series of regulations were introduced in France and England to control the use of machines in the production process. A number of proponents of the period, including James Stewart, advocated active government protectionism of strategic industries to prevent mass unemployment and social upheaval. According to this theory, the mechanization of labor will lead to further reductions in prices. This will lead to increased prosperity in the long run. Despite the prevalence of this argument among economists and politicians alike, David Ricardo was the most famous classical economist to question the long-run benefits of technological innovation.

Following Ricardo, Marxist approaches view technological progress as a deliberate means by capitalists of controlling labor power. Neoclassical views propagated the idea of the existence of self-equilibrium based on Say's law.

Along with the general equilibrium view, the principle of factor substitution became the mainstay of economic analysis. According to this principle, the most profitable combination of labor and capital gives the efficient current price. Technological innovation can lead to the temporary destruction of labor. The supposed mismatch is not due to a lack of work caused by technological progress, but may be due to a decrease in wages that may coincide with a reduced demand for labor. Analysis of the downstream effect shows that the relative depreciation of capital caused by the technological process leads to a lower interest rate, which encourages investment activity. Two opposing forces operate in the capital market: on the one hand, under conditions of diminishing returns to scale, the marginal productivity of capital decreases with capital accumulation, which reduces the corresponding demand. On the other hand, the supply of capital decreases, which is caused by the low interest rate (Calvino & Virgillito, 2018).

The Keynesian approach was characterized by an alternative perspective of a "self-regulating system". Say's law applies only under conditions of full employment. The main difference between Keynes and the neoclassical economists can be defined mainly in their theoretical view of the economic system, not in terms of the extent of government intervention.

In general theory, unemployment is only a temporary phenomenon. During a recession phase, a low level of aggregate demand will lead to a lack of private investment due to low expectations of future profits. In the economic recovery phase, aggregate demand needs to be stimulated, which affects the creation of positive investment expectations. Higher investment will increase the demand for labor, which will lead to lower unemployment. However, Keynesian theories pay less attention to the role of technical progress and the introduction of labor-saving technologies. In fact, Keynes develops the theory of booms and busts caused by investments. But the investment mechanism, in general theory, is only related to the indefinite idea of profit expectations.

In contrast, Schumpeter's analysis was particularly straightforward. In particular, it is built on the concepts of cluster innovation, product life cycle, imitation and diffusion: the interaction of these elements determines the emergence of cycles or waves. Unemployment arises as a result of technological innovation, which takes a long time to diffuse and affects different sectors asymmetrically. Innovation is seen as a painful process that creatively destroys the old and makes way for the new. Nevertheless, Schumpeter does not believe in the possibility of structural/Keynesian unemployment (Dosi et al., 1988).

Schumpeter's legacy has been carried over to neo-Schumpeterian/new growth theories, with a continued emphasis on the supply side, as well as evolutionary-institutionalist theories. The latter, espoused mainly by Chris Freeman, Carlotta Pérez, and Luc Soet, attempts to refine the notion of economic fluctuations—sometimes associated with long Kondratieff waves (Kondratieff & Stolper, 1935). Kondratieff in his theory about big business cycles substantiated the existence of big cycles with a duration of 50-60 years. According to him, before the beginning of the upward wave of the big cycle, there are deep qualitative changes in the economic activity of the society, which are manifested by essential innovations in techniques and technologies. These innovations mean the implementation of innovations in the economy.

English scientist John Bernal made a significant contribution to the development of innovation theory. He indicates that periods of prosperity in science coincide with increases in economic activity and technical progress as a result of the use of innovations (Bernal, 1956).

2.1 Compensation mechanism    

Vivarelli (2013, 2014) discussed different classifications of compensation mechanisms. As a result of reviewing the literature, I distinguished classical-neoclassical and Keynesian-Schumpeterian mechanisms. Classical-neoclassical mechanisms can be classified as follows: New machines - As a result of technical progress, new machines are introduced, possibly displacing the workforce; Decrease in prices - The increase in productivity with the introduction of new technologies leads to a decrease in production costs. This effect in competitive markets leads to further price reductions. Lower prices lead to higher demand and therefore higher employment; Decrease in wages - This mechanism operates in the market for factors of production and has symmetric effects on the price reduction process. The movement of the labor force leads to an excess of labor supply, thus reducing wages. The increase in labor demand is rebalancing the market tensions caused by the first wave of labor oversupply; New investments - Accumulated additional profits can be invested by entrepreneurs in physical capital, expanding productive capacity and, therefore, labor demand.

Keynesian-Schumpeter mechanisms can be divided as follows: Increase in incomes - When workers can earn commensurate gains from increased productivity, technical progress can lead to increases in wages and consumption. This leads to higher demand, which leads to an increase in employment through the famous Keynesian mechanism; New product - Introducing new branches and products can stimulate consumption. Higher consumption means higher demand and therefore employment. At the firm level, new products can cannibalize sales of older products, leading to ambiguous net effects. Additionally, at the industry level, product innovators may face increased demand through market expansion because the new product may satisfy previously unmet customer needs. This effect has a positive effect on employment. On the other hand, product innovators can erode the market shares of non-innovators through the so-called business-stealing effect, as older products become obsolete. Finally, we must not forget that new products can be produced more efficiently because of the advantages between product and process innovation strategies.

Unfortunately, it is difficult to determine the effectiveness of the above compensation mechanisms. Therefore, we must highlight several limitations.

The compensatory mechanism by reducing prices should balance the reduction in aggregate demand associated with layoffs. For its effectiveness, it is necessary: 1. significant price elasticity of goods, which are affected by price reduction; 2. High relevance of these goods in workers' consumption; 3. Non-oligopoly market structures. Accordingly, the extent to which price cuts affect the composition of aggregate demand depends on whether the above conditions are met. Such conditions of limited validity may result in unchanged or even reduced total demand (Calvino & Virgillito, 2018).

3. Results of Empirical Research

3.1 Evidence at the firm level

 Vivarelli (2014) emphasized that there is a positive relationship between innovation and employment in the microeconometric literature. Especially when R&D or product innovation are taken as indicators of innovative activity. A number of microeconometric studies use R&D or the number of patents as indicators of innovative activity. Such studies fail to distinguish the effects of the above compensating mechanism, but generally estimate correlations that represent the net result of a complex interaction of various forces on employment.

Traditional analyzes of the impact of innovation on employment at the firm level use R&D expenditures or patent data as indicators of innovation activities. These two variables capture innovation in different ways and suffer from different limitations and measurement problems.

Given the significant microeconomic heterogeneity, firm-level innovation effects can be characterized by volatile effects on employment. Bogliacino (2014) identifies two potential mechanisms that can lead to nonlinear firm-specific employment R&D elasticities. These are: scale effect and size effect.

There are many studies describing the positive relationship between innovation and employment (Hall, 1987; Yang & Huang, 2005; Yasuda, 2005; Van Reenen, 1997; Greenhalgh. et al., 2001)

It should be noted that firms of different sizes, ages and sectors of activity may have different results in establishing the relationship between innovation and employment. For example, according to the findings of Stam & Wennberg (2009), R&D positively affects the employment growth of young high-tech firms, but the same cannot be said for the employment growth of low-tech start-up.

3.2  Evidence at the industry level

Industrial analysis of innovation and employment spans the long term. There are recent studies that examine their relationship at the industry level. Bogliacino & Pianta (2010) further examine the relationship between innovation and employment at the industry level in eight European countries, using CIS 2, 3 and 4 data between 1994 and 2004. Analyzed the effects of cost competitiveness (CC) and technological competitiveness (TC) on employment change, distinguishing manufacturing and service sectors according to Pavitt's revised taxonomy (Pavitt, 1984; Archibugi, 2001). They estimate the industry-level labor demand curve, which includes CC, TC, labor wages, industrial dynamism, and productivity growth. It is concluded that CC has a negative effect on employment change, while TC has a positive effect. In addition, their findings emphasize the negative effect of wages and the effect of positive dynamism. However, they argue that the significant differences in Pavitt's classes prove that innovation strategies differ across sectors. That particular mechanisms operate within each class as a result of specific technological, demand and labor market factors.

Pavitt's taxonomy mainly includes large industrial firms and divides them according to the trajectories of technological change according to the sources of technology, the demands of customers and the mode of feasibility (Pavitt, 1984).

4. The Role of Aggregation

Different levels of aggregation play a crucial role in how innovation affects employment and employment growth. Studies that focus on the relationship between firm-level productivity and employment combine firm- and industry-level analyses. In fact, productivity and process innovation are particularly related to innovation with labor-saving effects. It is based on Schumpeter's idea that more competitive firms are better able to gain market share. Based on evolutionary theory, the dynamic relationship between productivity and employment shares can be well represented by the replicator dynamics equation (Calvino & Virgillito, 2018):

 

Where,

  

S_i,t is the market share of firm , which varies with the ratio of the firm's productivity (or competitiveness) to the industry weighted average  and that the  parameter indicates the intensity of the selection process. This equation aims to understand how the dynamics of market shares are combined with firms' relative performance. Given the market entry and exit process, the replicator dynamics equation describes the endogenous sustained cyclical dynamics in market shares.

Equation (1) can be written as follows (Calvino & Virgillito, 2018):

 

Where,

 

And  n_i,t   is the employment share of firm i.

If ∏_i,t is the labor productivity of firm i at time t, than AP_j,t represents the total sector productivity of firm i in sector j (Calvino & Virgillito, 2018):

 

The temporal variation of sectoral total productivity can be rewritten as (Calvino & Virgillito, 2018):

 

The first element represents the within component and aims to reflect the evolution of productivity, keeping market shares constant: to some extent, it realizes the learning process that takes place inside the firm. The second element is the between component, which aims to reflect the market selection process and tracks the time evolution of market shares when Productivity is constant. The last term captures the covariance between the two effects (Calvino & Virgillito, 2018).

The reviewed theory shows once again that the relationship between process innovation, here linked to productivity, and employment can take different forms when considering different levels of aggregation. 

5. Empirical Evidence: Challenges and Limitations

First of all, innovative activity proves to be an inherently complex phenomenon. The use of different innovation variables, starting from patents and R&D expenditures or innovative ideas, is an obvious challenge and substantially limits the empirical regularities of econometric analyses. Many of the microeconometric studies presented rely on innovative survey data that provide comprehensive information. Innovative activities suffer from significant quantitative deficiencies. In fact, data like the CIS are typically self-reported, which can be particularly subject to measurement error and anonymization challenges. In addition, they often do not contain comprehensive information on firm characteristics, have sampling problems, depending on the representativeness of a particular sample (Mairesse & Mohnen, 2010).

Product innovation generally includes both new and significantly improved goods and services. Process innovation, on the other hand, involves new or significantly improved production methods, delivery methods, hardware, equipment or software changes and may tend to increase quality or decrease cost.

Table 1a and Table 1b list authors who have investigated the impact of technological innovation on the labor market. Here we report the interaction between the instrument(s) measuring technological innovation as the exogenous variable(s) and the labor market outcome(s) as the endogenous variable(s). 

Table 1a. Researches about Impact of technological innovations on the labor market (sectoral level)

Level of Analysis	Author(s), Year	Measurement Instrument(s) for Technological Innovation(s) as Exogenous Variable(s)	Labor Market Outcome(s) as Endogenous Variable(s)	Positive	Negative	Non-Significant/Unclear
Sectoral Level	Mehta and Mohanty (1993)	Technology elasticity (adoption)	Labor demand		X
	Berman et al. (1994)	Investment in computers, expenditures on R&D	Skilled labor force demand	X
	Bogliacino and Vivarelli (2011) Bogliacino and Vivarelli (2012)	R&D expenditure	Labor demand	X
	Goux and Maurin (2000)	New technologies usage	Labor demand			X
	Gera et.al. (2001)	The stock of R&D, the stock of patents	Skilled labor force demand	X
	Morrison Paul and Siegel (2001)	Investment in technology, R&D investment	Labor demand		X
	Evangelista and Sanova (2002)	Innovation intensity	Employment		X
	Piva et al. (2006)	ICT technologies	Skilled and unskilled labor force demand		X
	Pieroni and Pompei (2008)	Patent per capita	Gross job turnover rate	X
	Bogliacino and Pianta (2010)	R&D expenditure, expenditure for innovation-related machinery	Employment	X
	Huo and Feng (2010)	The index of process and product innovation intensity	Employment	X

 Sourse: (Matuzeviciute et.al. 2017) 

Table 1b.Researches about Impact of technological innovations on the labor market (micro level)

Level of Analysis	Author(s), Year	Measurement Instrument(s) for Technological Innovation(s) as Exogenous Variable(s)	Labor Market Outcome(s) as Endogenous Variable(s)	Positive	Negative	Non-Significant/ Unclear
Micro Level	Casavola et al. (1996)	R&D expenditure, patents, software licenses	Employment	X
	Doms et al. (1997)	Automation technologies	Wages, occupational mix, workforce education	X
	Dunne et al. (1997)	R&D stock, technology adoption	Employment, labor share change	X
	Van Reenen (1997)	Patents	Employment	X
	Blanchflower and Burgess (1998)	Introduction of new technology	Employment	X
	Klette and Forre (1998)	R&D investments	Job creation			X
	Smonly (1998)	Product and process innovations	Employment	X
	Boone (2000)	Product and process innovations	Unemployment		X
	Gatti (2000)	Product-oriented and knowledge-based R&D	Unemployment	X
	Greenan and Guellec (2004)	Product and process innovation	Employment	X
	Aguirregabiria and Alonso-Borrego (2001)	Investment on R&D, purchases of technological capital	Employment by occupations	X
	Falk and Seim (2001)	Investment in IT	High-skilled employment	X
	Greenan et al. (2001)	R&D expenditure, IT adoption and intensity of usage	Wages, skill composition, employment	X
	Luque (2005)	Technological intensity	Skill mix changes	X
	Piva et al. (2005)	R&D expenditure	Employment (blue-collars, white-collars)			X
	Greenhalgh et al. (2001); Lachenmaier and Rottmann (2007); Yang and Lin (2008); Lachenmaier and Rottmann (2011)	R&D, patents	Employment	X
	Hall et al. (2008); Harrison et al. (2008); Dachs and Peters (2014); Falk (2015)	Product and process innovations	Employment	X
	Baccini and Cioni (2010)	Introduction of ICT	Demand for skilled workers			X
	Coad and Rao (2011)	R&D expenditure, patents applications	Total number of jobs	X
	Meschi et al. (2011)	R&D expenditure, technological transfer from abroad, foreign ownership	Demand for skilled labor	X
	Evangelista and Vezzani (2012)	Product and process innovations	Employment	X
	Bogliacino et al. (2012); Ciriaci et al. (2016)	R&D expenditure	Employment	X
	Meschi et al. (2016)	R&D expenditure; the obtained availability of a foreign patent or other appropriable devices developed abroad; investment in foreign machinery and equipment per worker	Employment blue-collars, white-collars)	X
		investment in domestically produced machinery and equipment per worker	Employment (blue-collars, white-collars)		X
	Haile et al. (2017)	The share of foreign ownership	Skilled and unskilled labor	X (skilled workers)		X (unskilled workers)

 Sourse: (Matuzeviciute et.al. 2017) 

Conclusion

The progress of society is related to innovation. It led to great progress in all spheres of human activity and life. It can be said that the process of economic development is the process of implementing innovations in all elements of the economic system.

Implementation of innovations in the world started from the 70s of the last century and reached the highest level of development in the advanced countries of the world. That is why the economy of these countries is called innovative economy. Innovative economy is based on knowledge, innovation flow, technology, information, institutions, human capital, production organization, products, etc. Continuous improvement, intellectual work of scientists and innovators, not just capital. Science, invention, innovation represent a single organic factor of development in such an economy (Abesadze, 2015).

Innovation affects the demand function and process innovation changes the production function. At the firm level, process innovation contributes more to employment growth (than product innovation) (Greenan & Guellec, 2000). Sector-level innovation indicators for 37 industry sectors are examined to answer whether technical change affects the sector level. As it turns out, innovation is positively related to employment. A distinction is made between product and process innovation, and industry-level employment benefits more from product innovation.

Arguments used at the firm and sector level are combined by different effects: process innovation is accompanied by job creation at the expense of competitors, while product innovation has a more moderate effect and does not harm other competing firms.

The net effect of innovation on employment at the industry-wide level may differ from survey-based firm-level results. Firm-level analysis does not allow these results to be extended to the entire industry. There are several reasons why these firm-level results cannot be applied to the industry level (Harrison et al., 2008; Piva & Vivarelli, 2005):

• It is impossible to distinguish the effect of market expansion and business stealing; For example, if employment is increased by the innovative firm, the share of other firms will decrease;
• Entry and exit of firms is not observed, innovators may foreclose non-innovators;
• Entirely new economic branches may emerge and to create completely new jobs. 

Acknowledgement: This research #PHDF-22-1709 has been supported by Shota Rustaveli National Science Foundation of Georgia (SRNSFG).

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