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The Relationship Between Economic Growth and Unemployment


Globally, there is the acceptance that from an economic point of view, the GDP growth rate of any economy increases employment and reduces unemployment. The theory behind this is ‘Okun’s Law’ which concerns the relationship between output and unemployment. Mainly in the most developed countries, the theory has been among the most famous; on top of this, it holds several countries. Unemployment and own economic and social implications are among the most significant issues and problems facing different policymakers, with high rates of unemployment, mean labor deficiency in the market, and deepening poverty incidences (Abbas, 2014).

The predominant features of unemployment are very high persistence all over the world. This shows the importance of critically understanding the relationship between economic growth and unemployment, especially the most appropriate aimed at employment reduction. However, some issues still need to be solved on top of the economic and social repercussions of high unemployment rates (Abbas, 2014).

The relationship between output and unemployment is crucial because it helps answer whether the size of unemployment follows the autonomous route independence, especially from the macroeconomic variables. Both economic growth and unemployment are fully affected and are influenced by lesser or greater business extent cycles (Thapa, Dhakal, & Gurung, 2022). This project seeks to and expects that there is a long relationship between the given variables. In this project, output in high rates leads to or rather will contribute to unemployment reduction.

When the unemployment rate is high, it is challenging to run the economy effectively. Employment growth or decline impacts the labor market, namely the demand and supply of workers. The equilibrium of the labor market with respect to the supply of labor is profoundly affected by a country’s preexisting demographic circumstances and mobility. According to the ‘Wage Fund Theory,’ manufacturers only hire a small number of workers due to a shortage of capital; hence unemployment rises. According to some economists, unemployment is to blame for the current supply-and-demand crisis. Similarly, overproduction contributes to joblessness since it drives down commodity prices, requiring fewer individuals to be employed. When there is a shortage of demand for their goods, manufacturers reduce the cost of their products, close their businesses or factories, and lay off workers.

Okun’s law and study at large remain very significant theories in the macroeconomic field. Much of the economic research has used this law in different dimensions, and it states that an ‘a1% reduction in the employment rate would reduce 3% of the output. On the same note, it is postulated that the 1% increment in growth rate above the growth trend rate would contribute to 0.3% in unemployment reduction. On the reverse of this, a 1% increment in the unemployment rate means roughly over 3% loss in the Gross Domestic Product growth (Thapa, Dhakal, & Gurung, 2022). To keep the unemployment rate constant, the above-discussed relationship means that the GDP growth rate must equalize its potential growth. The potential output growth rate has to be lower than the GDP growth rate so that there could be a decrease in unemployment.

Several studies have been conducted concerning the empirical relationship between the output or, instead, economic growth and unemployment (Soylu, Çakmak, & Okur, 2018). Most of these studies proved the validity of the relationship between output and unemployment rates. Research carried out by Chand, Tiwari, & Phuyal (2017) found that growth rarely means economic gains, which shows that Okun’s coefficient is statistically insignificant. Through the use of the literature reviewed, the standardized version of Okun’s law is represented below:

yt =βo +β1u + et


y = The actual output product

u = The level of unemployment

e = The white-noise disturbance term

From the above-given equation, (B) is called the Okun coefficient, which indicates the changes in the actual output resulting from the changes in unemployment. This estimation in elasticity gives the measure of the relation between economic growth and employment, whereby the low estimates of Okun’s coefficient suggest little correlation between the unemployment rate and high estimates, especially in the slope, showing the support of the law.

A recent study conducted by Chand, Tiwari, & Phuyal (2017), showed that the relationship is greatly affected by mainly created job types like manual jobs, also by the provided incentives where the employers choose between local and foreign employees, and lastly by the choices availed where nationals make concerning the acceptance of local jobs and being willingly unemployed to wait and search for job opportunities in the public sector or the oversees. In their research, they elaborated that despite achieving a high and strong Gross Domestic Product in the region, this created many jobs for both the public and the private sector. On the other hand, unemployment, especially among the locals, never reduced or declined. However, it fluctuated around the fair, high level of 15%, which meant that foreign workers occupied the newly created job opportunities. This is due to domestic workers having relatively higher reservation wages, focusing on high expectations for obtaining jobs in the foreign markets or the public sector.

Additionally, at least half of the unemployed indicated that they are unwilling and uninterested in accepting available jobs based on the prevailing wages. From this, we can fully deduce that the unemployment issue and problem in the region reflect the behavioral nature of unemployment rates, where there is much hope in reforming the acceleration in labor market regulations in the region. Aimed at ensuring people from the region consider the available and existing job opportunities, there is a need for continuous improvements in higher salaries and working conditions, which is a clear point to the locals.

According to studies by Alhdiy et al. (2015), they found and established that traditional factors have no crucial roles in the growth of different regimes and economies. However, Chand, Tiwari, & Phuyal (2017) realized that the allocation of resources and efficiency, especially in the short run, play significant roles in the growth process of any economy. As given, in emerging and transitional economies, unemployment poses a critical problem. On the same note, Soylu, Çakmak, & Okur (2018) add their work’s influence on the relationship between growth and unemployment. The researchers found that technological innovation has dual effects on the economy and, more so, its growth. The economists explained further different types of effects. They proved that technological processes help reduce unemployment rates based on their capitalization effect. Rapid growth increases or raises the returns of different firms, businesses, and establishments where new businesses are launched for sharing profit purposes, thus creating new job openings and opportunities.

Very quick and rapid technological innovations make many laborers unemployed. Technological progress and growth have crucial or rather play crucial roles in minimizing unemployment, though this remains limited to a few areas as regional disparities emerge. There exist different and very many theories regarding the issues of economic growth and employment. Distinct aspects are always involved in these issues, whereas rational theories have always focused on different mechanisms for returning the economy to regular unemployment dates.

Thapa Dhakal & Gurung (2022) research concentrated on regional unemployment. Their evaluation was based on how other unemployment differences differ in the business cycles. On the same note, they focused on the exact findings of the disparities in unemployment. Through their research, they found out that the industry plays a role in the creation of regional unemployment. Though different factors have always been used to establish the relationship between the two prospects, their results in some instances prove that a relationship exists, though, in others, it is found the other way around. Different institutions have always been utilized aimed at the reduction of unemployment rates. Unemployment relation and real wage have been analyzed in their research, and they found out that real wage increases the natural unemployment rate.

Unemployment remains high because of the persistence of supply-side shocks and is caused by the labor market’s current and existing demand shocks. For instance, supply chain rules, regulations, and policies like income policies and tax systems, once implemented, could lead to the reduction of unemployment rates in different countries, both developed and developing nations. The national economy’s two most critical macroeconomic indicators are the gross domestic product and unemployment (Adelowokan et al., 2019). There is a relatively strong inverse ratio link between the two indicators at the level of the various economies. Unemployment is influenced by a wide range of other issues, all of which must be considered when devising plans for the near, intermediate, and far futures.

The growth rate in different countries, especially the developing ones, is quite good though the employment generation is not that high. The acts of unemployment increase at high rates, and workforce planning experience rarely produces crucial results toward minimizing unemployment rates in different regions and nations. Pakistan is an example.

Economic expansion has been shown to have a negative effect on the unemployment rate, as found by Hassan and Nassar (2015). Balan (2014) found that the GDP negatively influences unemployment and that the average net salary has a favorable effect on young unemployment. Moreover, it shows that the unemployment rates and gross domestic product (GDP) of the United States, the United Kingdom, and Japan are different and more or less affected in the same way as a sample in their population and as a case study. A negative correlation between unemployment and GDP has been observed in the United States and the United Kingdom but not in Japan. Hence, inflation and economic expansion are not directly proportional to one another.

Inflation hinders progress in the economy. Younger workers have a higher unemployment rate than their more experienced counterparts because of their lack of marketable skills. Adelowokan et al. (2018) also showed that young individuals have less experience than older people, making it harder for them to get a job and requiring them to accept lower pay for doing the same amount of labor as their more seasoned counterparts. Employers have been boosting pay above the equilibrium level to encourage workers to work more, leading to a rise in unemployment. Intending to lower employee turnover, the efficiency wage model maintains wages above the level at which the market clears. The efficient wage structure exacerbates the lack of employment opportunities.

The working class tends to know less about the factors contributing to joblessness. They learn everything they know from the media. The media caters to the public’s need for scandal, and many still hold that job seekers’ laziness is the root cause of the employment crisis. Inflation can have positive and negative effects on unemployment, depending on the state of the economy and the availability of jobs. In addition, it has been discovered that a greater rate of inflation encourages workers to work and creates a negative effect on unemployment compared to inflation, which is lower.

As a measure of how efficiently a country’s economy is allocating its resources, the unemployment rate is an essential macroeconomic indicator. However, even if the economy is functioning at total capacity, the unemployment rate will still be over zero due to frictional and structural unemployment. The time it takes to match people with jobs constitutes “frictional unemployment.” Due to factors such as a lack of accurate data on available jobs, employees’ reluctance to relocate, and stagnant wages, this period is very variable (Thapa, Dhakal, & Gurung, 2022). The commodity demand fluctuates over time, making sectoral transitions familiar in an economy. As a result, it will take time for the workforce to adapt to this new industry.

The level of unemployment at which an economy is functioning at its maximum efficiency is known as its natural unemployment rate. Thus, unemployment exists, but it is primarily due to frictional unemployment. The acronym NAIRU, which stands for “Non-Accelerating Inflation Rate on Unemployment,” is occasionally used to refer to this natural unemployment rate. Inflation will spike rapidly since businesses will have to pay more to attract and retain workers if unemployment falls below the NAIRU. Inflation will be lower if the unemployment rate is higher than the NAIRU because wages will be reduced to compensate.

Economic expansion and joblessness tend to go in opposite directions. The unemployment rate tends to drop as economic growth accelerates, all else being equal. Reduced output and slower economic growth are the inevitable results of a rising unemployment rate. In other words, rising unemployment rates are correlated with a more robust economy (Chand, Tiwari, & Phuyal, 2017). Therefore, economic growth measures should be developed and implemented to help lower the unemployment rate. The classical approach holds that this causes a rise in the demand for both products and services, as well as for workers.

Poverty alleviation is greatly aided by healthy economic growth. However, economic progress has both positive and negative effects on poverty. Despite stagnant or declining per capita income, poverty levels have decreased dramatically. In some situations, however, significant economic growth and per capita income do not lead to a corresponding reduction in poverty (Chand, Tiwari & Phuyal, 2017). increased prosperity can alleviate human suffering by cutting down on expenses people have to make do with their lack of wealth. Economic growth is essential, but not sufficient, for lowering poverty rates, which is a crucial takeaway.

On the flip side, poverty is a powerful brake on economic expansion. A country’s ability to produce goods suffers when its poor population is less healthy and productive. In addition, poverty dampens economic growth by discouraging people from saving and investing. Additionally, the poor have less access to financial markets due to stringent collateral criteria for bank borrowers. The impoverished, therefore, have no way to put money aside (Thapa, Dhakal, & Gurung, 2022). When the pace of growth in per capita income is low, poverty rises. In most cases, as poverty levels are lowered, economic conditions improve. By boosting a country’s output, effective social and economic policies (such as funding for primary education and healthcare facilities) can lift people out of poverty.

The expansion of the human population is another driving force behind the rise in GDP per person in real terms. Although a negative relationship between population growth and income has been documented, correlation does not prove causality. Although capital per worker and output per worker remains constant in the steady state, population expansion has offered light on increasing both at the steady state. When the birthrate rises, the steady-state amount of capital per worker decreases, and output per worker decreases (Thapa, Dhakal, & Gurung, 2022). For this reason, policymakers carefully monitor the population growth rate and intervene if that pace is deemed unsustainable for achieving or maintaining high standards of living. In most circumstances, low population growth is correlated with high income. However, additional factors may link low population growth to high wealth, such as women’s labor force participation, educational attainment, and access to contraceptives.

From a neoclassical economics perspective, technological development is another underlying element that determines real GDP growth. It is widely believed that this explanation is crucial to make sense of the continuous improvement in people’s level of life. The model accounts for technological advancement as a factor that increases worker productivity by a constant percentage (Abbas, 2014). The steady-state increase or decrease in capital stock is proportional to the amount invested, less needed to break even (due to factors like depreciation, population expansion, and the growth rate induced by technical processes). So, if people save more, the economy will develop faster until it reaches a stable state. When we go over this threshold, technical advancement will determine the development.

Unemployment can be kept to a minimum with the help of growth. Three cointegrating vectors exist. Maximum eigenvalue statistics also reveal a causal link between economic growth, unemployment, capital, labor, trade openness, and human capital over the long term. For Easterly, the case of Pakistan exemplified growth without development (Abbas, 2014). The country’s inability to produce and pay back its debt was exacerbated by its low social indicators. Reduced unemployment was not a notable result of growth policies.

Another major issue is the broken nature of the job market. Inequality and poverty have worsened as a result, and people’s living standards have been negatively impacted. The poor have been hit hardest by the drop in production. According to available data, the labor force has been growing, but the economy’s capacity has not. That is why there is a growing informal economy with low wages and rising unemployment. The rate of economic expansion must be increased.

Unemployment can only be lowered by fostering sustained economic growth. The key to a healthy economic expansion, investment-friendly policies, and a secure political environment. The competitive strategy needs industrial policy as its foundation (Özel, Sezgin, & Topkaya, 2013). The time has come for policies that encourage exports. To successfully combat unemployment, it is essential to create industrial zones outside of major urban centres. Unemployment may be reduced in urban and rural regions by enacting policies that place a premium on labor. ; Additional work is required to increase Human Capital and build infrastructure to facilitate rapid growth while reducing unemployment through labor-intensive policies.


In conclusion, this research project sought to establish the relationship between economic growth, that is, through Gross Domestic Product and unemployment. In some aspects, literature shows that these two are related, while on the other hand, they are not related. Sometimes as seen, lack of economic growth rarely explains the problem of unemployment. The report has different insights on important policy implications where economic policies focusing on structural changes and reforms concerning labor are more applicable and appropriate. There seems to exits a very close relationship between the two terms though they are independently and most of the literature as seen shows that when there is a high economic growth rate, the unemployment rates are low where is mostly applies for regions where the locals are willing to work for the available prevailing wages. For the regions showing the opposite, the project found though there is high economic growth rates, there could be high unemployment rates as the job opportunities are taken by the foreign workers.


Abbas, S. (2014). Long-term effect of economic growth on unemployment level: In case of Pakistan. Journal of Economics and Sustainable Development, 5(11), 103-108.

Adelowokan, O. A., Maku, O. E., Babasanya, A. O., & Adesoye, A. B. (2019). Unemployment, poverty and economic growth in Nigeria. Journal of Economics & Management, 35, 5-17.

Alhdiy, F. M., Johari, F., Daud, S. N. M., & Rahman, A. A. (2015). Short and long term relationship between economic growth and unemployment in Egypt: An empirical analysis. Mediterranean Journal of Social Sciences, 6(4), 454-454.

Chand, K., Tiwari, R., & Phuyal, M. (2017). Economic growth and unemployment rate: An empirical study of Indian economy. Pragati: Journal of Indian Economy, 4(2), 130-137.

Özel, H. A., Sezgin, F. H., & Topkaya, Ö. (2013). Investigation of economic growth and unemployment relationship for G7 Countries using panel regression analysis. International Journal of Business and Social Science, 4(6).

Soylu, Ö. B., Çakmak, İ., & Okur, F. (2018). Economic growth and unemployment issue: Panel data analysis in Eastern European Countries.

Thapa, R., Dhakal, S. C., & Gurung, B. (2022). Relationship between Unemployment Rate and Economic Growth in Nepal: An Econometric Estimation. Turkish Journal of Agriculture-Food Science and Technology, 10(8), 1586-1593.


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