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AGORA INTERNATIONAL JOURNAL OF ECONOMICAL SCIENCES, 
AIJES, ISSN 2067-3310, E - ISSN 2067 – 7669, VOL. 15 (2021) 

 

Some issues on the correlation between wage income and labour 

productivity 

Rica Ivan1, Călin Tănase Ladar2 

1 Faculty of Electrical Engineering and Information Technology, Control Systems Engineering and 

Management Department, University of Oradea, Oradea, Romania 
2 Faculty of Environment Protection, University of Oradea, Oradea, Romania 

E-mails rika_ivan2005@yahoo.com, ladarcalin@yahoo.com   

Abstract  

In Romania, both the business environment stakeholders and the academics consider that the path on reaching 

the average level of development of the European Union and implicitly the adoption of the Euro currency, can be 

achieved only by improving the standard of living that is the citizens’ income, which can be reached only by 

increasing labour productivity. One of the objectives of the European Union is to reduce the disparities between 

regions, as confirmed by the evolution of GDP/ capita in the less prosperous Eastern Europe countries in 

comparison with the more developed EU Members States from Western Europe. There are a number of factors 

impacting the labour productivity and wage incomes, and the onset of the COVID 19 pandemic has accelerated 

the adoption of automation, digitalisation and remote work, which will significantly contribute to the 

disappearance of less skilled jobs and the consolidation of those who are highly qualified ones, the latter being 

less sensitive to the adoption of new technologies.                 

Keywords: labour productivity, wage income, automation, pandemic, increased competitiveness, European 

Union 

1 Introduction  

According to the National Bank of Romania, the relationship between the average gross wage 

and labour productivity marks two inextricably linked indicators. However, labour 

productivity is not the only factor that influences the dynamics of wage costs, the latter being 

also affected by the phase of the economic cycle, and how relaxed/ tightened the labour 

market is. According to NBR data, over the period 2009-2017 the average real wages 

increased by about 45%, while labour productivity increased by only 27%, urging caution in 

terms of wage increases.                                      

In order to join the euro area, in addition to other core economic indicators, Romania must 

also reach a minimum level of real convergence of 75% of the EU average in terms of GDP 

per capita. Romania’s per capita income gap is now much larger than the average of the top 

10 eurozone Members States, when compared to the income that Portugal, Slovakia or Spain 

were facing with when they joined the euro area. Therefore, in the absence of a per capita 

income close to the European average, Romania cannot consider itself as being a developed 

economy, comparable to that of the euro area Members States, and it remains part of the area 

of developing countries. In January 2021, the average gross wage in Romania was 5,549 lei, 

that is an average net wage of 3,176 lei net. i.e. about 660 euros. 

A key factor in getting closer to the average level of development of the euro area Member 

States is to increase competitiveness, i.e. productivity. However, capping the pace of wage 

growth in relation to the productivity rate increase leads to the continuation of the exodus of 

Romania's labour force to developed economies, which, in turn, leads to a slowdown in 

economic development.                             

mailto:rika_ivan2005@yahoo.com
mailto:ladarcalin@yahoo.com


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The salary level in a company depends on several factors such as: the size of the company, the 

economic sector in which it operates, whether it is a national or a multinational company, the 

relationship between labour supply and demand in that economic sector, its  position on the 

market and its market share, the profitability of the business field, the employee's salary 

history, and, last but not least, labour productivity.                

The tremendous differences between wages paid within the developed countries when 

compared to the developing countries, such as Romania, are not caused as much by 

differences in productivity rate per capita as by other factors such as immigration control. If 

free movement of labour was total, most workers in developed countries would be replaced 

by workers in developing countries, who would accept lower wages. In 2019, a bus driver in 

Romania was paid on average net wage of about 3,000 lei net i.e. about 630 euros. In the 

same year, his peer in Sweden was paid at least 34,000 SEK i.e. about 3,200 euros. In other 

words, the Swedish driver is paid more than 5 times more than his Romanian peer, which is 

not related to a productivity more than 5 times higher. In order to build a truly fair society, the 

myth that a person is paid according to his personal worth cannot be accepted (Chang Ha, 

2011). Even in those sectors of developed economies where employees are truly more 

productive than their peers working in the economies of the developing countries, their 

high(er) productivity is largely due to the system, organizational structure of companies and 

not to individuals themselves. The productivity of these employees is due to the fact that they 

live in economies with superior technologies, better organized companies, better institutions, 

and with a more developed infrastructure, all these being factors that have been achieved in 

time, over generations. 

According to the data published by the OECD in 2019 and having 2010 as reference year, 

Romania recorded almost the highest rate of increase in labour productivity per hour among 

all the 43 countries reviewed, reaching in 2019 to a ratio of 140.3 compared to 2010, being 

the second best after Ireland (142.4), while the poorest performers were Greece (93.0), 

Luxembourg (100.8) and Italy (101.2). According to the data presented in the “Ziarul 

Financiar” newspaper Romania had the fastest increase in wage income over the period 2013-

2018, as well as one of the largest increases in terms of labour productivity rates in the 

European Union, but the share of value added that was transferred to labour factor was small. 

The business model of keeping labour costs low, especially below the level of labour 

productivity growth, especially in Central and Eastern European countries which was imposed 

by foreign investors has reached its limits. Economic growth, as a consequence of increasing 

labour productivity in an economy, is directly proportional to the production and consumption 

of resources, which inevitably affects the environment. Thus, societies need to rethink the 

economic model on which they rely on with a focus on sustainable and environmentally 

friendly growth, while improving the quality of people’s lives. 

2 MAIN PRODUCTIVITY CONCEPTS USED 

The OECD uses the concept of labour productivity in terms of GDP per hour worked as a 

basic indicator for calculating labour productivity. This concept measures the efficiency of the 

labour factor combined with other factors of production used in the production process. Thus, 

labour productivity only partially reflects the capacity of workers or the intensity of their 

effort, and it depends on other factors such as invested capital, technological or organizational 

changes, economies of scale, etc. 

Another concept used is total factor productivity (TFP), which refers to how efficient and 

intense the inputs used in the production process are. The increase in this type of productivity 

is the result of technological improvements and innovations adopted over time. Technological 



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progress is inversely proportional to the labour factor, in the sense that an increase of 

technological progress leads to a decrease in the amount of labour incorporated. 

According to Eurostat, labour productivity measures the amount of goods made and services 

performed by each person that is labour factor or the output/ input ratio of labour. In the case 

of structural indicators, labour productivity can be measured by multiplying gross domestic 

product (GDP) by the number of people employed or the number of hours worked. 

Productivity is influenced by several factors, among which the most important to mention are: 

efficiency, a factor that means the amount of goods/ services that can be obtained using a 

certain volume of production factors; technology, a factor that includes scientific outcomes, 

organizational techniques, quality of the new elements generated meaning the goods produced 

and services provided; decreasing real costs while maximizing profit; correlation with the 

current economic cycle since there are periods of productivity increase or slowdown, 

depending on the phases of the economic cycle. Firms tailor their capital and labour force 

according to fluctuations in terms of demand. Another factor is the standardization of 

production processes, in the sense that the comparison of different production processes may 

lead to finding the less efficient production processes. 

Structuralism is a contemporary theory suggesting that wage growth demands drive up the 

inflation rate, and the pace of wage growth rising should be one percentage point above the 

rate of productivity growth in order to achieve an annual inflation rate of 2-3%, which is 

targeted by central banks. 

Labour productivity may also be defined as the production obtained in relation to the labour 

force unit, which can consist in the number of hours worked, as well as in the number of 

employees. The variant that is based on the number of hours worked is the most used, being 

considered the most appropriate; at the opposite pole is the labour productivity related to the 

number of employees which is appreciated due to its simplicity, yet it does not consider the 

changes in the average time worked or the role of those workers who do not have the status of 

employees, but who can have an important contribution in the production process. 

The theory of wage income efficiency (Galgóczi, 2017) considers that firms that adopt the 

model of paying their employees wages over the market level compared to those that believe 

that revenues should increase only with increasing labour productivity is a rational solution, 

since this model acts reversibly, first by increasing wage income leading to increased labour 

productivity and thus avoiding the trap of maintaining low wages. 

The efficiency in using labour does not depend strictly on the material conditions of 

production, but also on the quality of the labour force. Nowadays, the workforce is subject to 

higher demands than in the past when more rudimentary production techniques were used. 

The technical progress determined the change of the weight of the effort from the physical 

side to the intellectual side, determining more accuracy in the lucrative activity. Thus, the 

increased qualification has become an important condition for the efficient use of human 

resources. The skilled workforce generates a greater amount of production in the same unit of 

time than in the case of the less skilled labour force. There is a strong positive correlation 

between the level of professional training and labour productivity. The advent and 

development of computers has led to improved efficiency of employees, leading to an 

increase in demand for highly skilled labour, which has triggered increased wages for the 

latter compared to low- or unskilled employees. 

The impact of unequal income in relation to economic growth depends on a number of 

factors, including the initial level of income and the geographical distribution thereof within 

an area or region. Urbanization degree influences economic growth depending on the level of 



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development of an economy and the initial distribution of income. While high levels of 

income inequality can be limiting factors in long-term economic growth, increasing income 

gaps as well as urban agglomerations. Thus, many developing countries currently face a high 

share of low per capita income, but also high income, yet in a much lower share. There is no 

emphasis in the literature on the fact that economic growth and income inequality are not 

equal in an economic space and that the effects of income inequality on economic growth 

may differ depending on the geographical concentration of economic activity. It is important 

to consider both factors i.e. income inequality and urban agglomeration factors, as well as 

changes incurred in these factors within an economy, but also how these two factors interact 

with each other. In conclusion, the literature emphasizes that, in the short run, there is a 

positive correlation between income inequality and economic growth, but in the long run, this 

correlation tends to become negative. Moreover, high levels of income inequality appear to 

negatively affect low-income countries compared to those with high incomes. Employees 

working in larger cities are paid higher wages, a kind of urban wage premium (Ehrlich M., 

Overman H. 2020), because they make workers more productive. Larger cities also tend to 

attract better-educated employees who are more productive and have higher earnings. 

Consequently, GDP per capita is higher in these cities. 

Labour productivity should not be mistaken with the total factor productivity, which excludes 

human impact and the physical accumulation of capital, focusing only on the contribution of 

new changes in technology and in business management (McKinsey Global Institute, 2021). 

According to recent studies (ILO, 2020), income inequality tends to be less predominant in 

countries where there are a large number of employees who benefit from collective labour 

agreements. 

3 THE IMPACT OF THE COVID19 PANDEMIC ON THE CORRELATION 

BETWEEN INCOME AND LABOUR PRODUCTIVITY 

The onset of the COVID 19 pandemic was an incentive factor for many companies to 

accelerate the use of technologies such as digitalisation and automation, which has led to 

increased productivity by replacing employees or increasing production per employee. 

Prior to the COVID 19 pandemic, productivity growth was not always correlated with wage 

growth. For example, in the US, the average wages increase was 19% below productivity 

growth as compared to year 2000. If the average wage of a US employee had increased in the 

same pace with the productivity, by 2020 it would have been approximately 9,000 USD/ year 

higher. The onset of the pandemic has triggered a dramatic drop in terms of consumption but 

also to an increase in savings, especially in the case of high-income households, as well as job 

losses, especially in the case of lower-income households. 

The analyses made by specialists show that approximately 60% of the productivity increase is 

due to firms that have applied measures to reduce labour costs as well as other production 

costs, such as, for instance, via automation. Since these productivity gains are not used to 

generate new jobs and increase wage incomes, then there will be a growing gap between 

productivity and wage growth. 

Trade automation and liberalization have profoundly altered the labour market in the 

developed economies, offering disproportionate benefits for highly qualified employees to the 

detriment of other employees. Technological changes have reduced the demand for low- and 

middle-wage employees, who work, for example, on factory assembly lines, and have 

increased demand for highly-skilled employees who are also better paid. 



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According to recent studies (McKinsey, 2020), in Europe, approximately 53 million jobs will 

be subject to the automation process, and a large part of the jobs that will be lost will be 

replaced by technology and health investments based jobs. 

The outbreak of the COVID 19 pandemic has led to an increase in remote work, leading to 

increased productivity, by reducing costs related to office space, equipment and supplies, 

giving companies the opportunity to hire highly skilled workers who do not reside in the 

locality where the companies have their headquarters. However, remote work is not possible 

in all industries, such as agriculture or construction, and differs from one country to another, 

depending on the degree of digitalisation thereof. 

With regard to the ever-increasing implementation of technology and especially of artificial 

intelligence (AI), it is very likely that it will significantly contribute to loss of jobs involving 

low or medium skill levels, but without having a major impact on jobs requiring high 

qualification. These technology-related professional changes are more likely to occur, 

especially in cities with large urban agglomerations. 

Automation and use of AI in economic processes causes a major increase in labour 

productivity, but also a decrease in the number of employees. However, these factors do not 

evenly influence the industries or jobs in one industry. For example, the table below presents 

the jobs with the highest and lowest productivity are not likely to be affected by automation in 

the coming years in Europe are shown in the following table: 

Jobs most likely to be influenced by 

automation and Artificial Intelligence 

Jobs less likely to be influenced by 

automation and Artificial Intelligence 

Mine, construction, manufacturing, and 

transportation workers                       

Teachers                                                                      

Machine operators and assembly line workers                                                                                                     Medical and bioscience personnel, physicists, 

mathematicians, engineers 

Office workers                                                         Managers and personnel in the legislative and 

administrative field                                                     

Vehicle operators                                                               Skilled agricultural workers                                               

Source: Nedelkoska and Quintini (2018) 

Highly qualified jobs imply the existence of problem-solving skills, and they are not 

characterized by routine tasks or require high communication skills, which makes it difficult 

to adopt automation. Countries such as Sweden, which have a significant share of its 

workforce employed in areas involving high skills, are less exposed at risk entailed by 

automation. Job market in northern European countries is less sensitive to automation than 

those in Eastern Europe, mainly due to the way the work is organized within the same 

economic sectors and only to a lesser extent due to the structure of the economy. 

The changes generated by the automation and digitalisation trigger a tendency of polarization 

of the labour market, in the sense of increasing inequalities; currently one finds that a greater 

focus is put on investments related to increased digitalisation and less on investments related 

to the qualification of manpower. 

4 Conclusions  

Despite the fact that the GDP/ capita indicator is often used in comparing the level of 

development between different economic areas, given the high inequalities between the 

incomes of its inhabitants, GDP growth would only partially reflect the reduction of the 

poverty rate. The improvement of the living standard, of social welfare, the increase of the 



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labour productivity and implicitly of the national wealth, all of the above up determine the 

degree of development of an economy. 

In order to converge towards the level of developed countries in the European Union, 

Romania should focus on economic activities that involve creativity and innovation, an 

increased added value in the case of exports, which determines the existence of higher wage 

incomes, as against the current model which focuses on economic activities related to 

distribution, marketing, etc. which entail the presence of a less skilled labour force, lower 

wages and thus remaining caught in the poverty trap. 

In order to avoid the trap of low income capping and to achieve sustainable economic growth, 

Romania needs to focus on at least four strands of action, namely: digitalisation, innovation, 

mitigating climate change, developing workforce skills and social inclusion. 

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