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The puzzle of growth - What economic models tell us about the prospects of Europe

Recent years have been associated with the slowest economic growth of the developed economies in Western Europe since the end of World War II. The phenomenon has caught the attention of policymakers as the continent is becoming less competitive against the US and rapidly changing Asian countries. This contrasts with Europe's desire to maintain the status quo as a global trading centre. The article delves into the economic theory of development and examines the issue through the lens of models developed by Solow, Romer, and Jones. It explores the challenges of demographics, innovation, and resources.


The Solow growth model is a precursor of the research in economic development. It examines the long-term relationship between accumulated capital (K) and output (GDP, Y). The production is represented by a Cobb-Douglas function of capital and effective labour (that is, technology  multiplied by labour, A × L).


In the steady state, the economy reaches the balanced level of capital and output, which remains stable unless any exogenous shocks occur. That equilibrium in capital is achieved when the investments (savings from the consumption, s – savings rate) are equal to the depreciation of the capital stock (Acemoglu, 2009). The capital accumulation equation is hence as follows:


In the equilibrium, the output per worker (y) is therefore described as:



Where s – savings rate, n – population growth,  delta – depreciation, α – capital/labour ratio.


s, n, delta, α are exogenous in the model, so only the labour-augmenting technology growth included in the A(t) function impacts the growth of the output. The conclusions from the model are hence two-fold. Changes in savings, depreciation, and demographics can only cause level effects on the economic output. While they can help increase the GDP per capita, they are not the drivers enabling to sustain long-term growth of the economy. What really matters for the growth rate is the technological improvement. In the European context, the reference has to be made to the innovations developed in the continent. Despite the high standards of European universities, the business environment and the states are less active in research and development than the world’s counterparts, and as a result, the EU lags behind the US and China in innovation. Take, for instance, the AI ranking; Europe is not leading in any of the categories, and is experiencing a dependence on technologies from other parts of the world (Centre for Data Innovation, 2019). Most of the technologies used nowadays do not originate from the continent, as the vast majority of the production of the key supplies (such as semi-conductors) is also taking place outside of Europe. Therefore, the model recommends more emphasis on investment in new technologies, especially on the platform of the European Union, to catch up with the growth experienced in other parts of the world. In particular, it is clear the organisation have to perform a successful transition to modern energy, as stated in the EU’s plan to achieve carbon neutrality in 2050.


The slower economic growth in Europe can also be explained by concluding that the region is in the late stage of reaching the steady state, therefore locating itself in the flat part of the concave sY function (see graph below). It is a reasonable conclusion, especially given the disproportionate growth between the developed slow West and converging post-Soviet Europe. However, it is a short-term explanation that does not change the fact that in the long-term, it is the technology that puts the GDP per capita forward. The narrative that since Europe has developed so much already that it has to grow slower is, therefore, not a convincing excuse. The Solow model predicts that there is still much potential to uncover by investing in technology, as it shifts the output’s steady state upwards.


Source: Spencer & Dimand (2010).


Romer, on the other hand, in his model advocates for investments in knowledge and human capital. According to his view, the output depends on the ideas developed by the researchers, as they enhance the country’s economic group. That growth of ideas (g), however, is a function of the productivity of ideas production (z), the labour force (L), and the share of the labour force employed in research (l). 



Where A0 is the initial output.


Therefore, in order to realise a high growth rate in a country, there is a need for a qualified labour force working in research, and to facilitate the idea production by creating a helpful environment. It requires investments in higher education and research. Apart from that, economic potential can be induced through the channel of L, which can be achieved in demographic policies comprising fertility and immigration measures. Thus, countries should be encouraged to promote larger families and facilitate migrants to enter the labour force. While persuading people to have more children is really difficult in the developed, career-oriented society (see examples of failures of 500+ policy in Poland, or lump-sum childbirth cash transfer in Spain 2007-2010), there is still some room to attract foreigners to come to Europe and work towards the economic benefit of the continent. This is, however, in the light of ongoing right-wing political wave and public opposition to relaxed migrant policy, not likely to be progressing in the direction the model suggests.


The European Union has one of the highest ratios of highly qualified workforce in the world with more than 40% having completed tertiary education (Eurostat, 2022), which suggests that the situation in that matter is really good. However, there has been an increasing discussion on the curtailment of the internationalisation of education. For instance, the Netherlands is starting to call for fewer students coming from abroad amid the housing and cost of living crisis. Since international exchange of thought is a key factor for idea development (expressed in z), those threats could potentially negatively impact the future state of education in Europe.


Romer’s model (1990), though, suggests that a higher portion of researchers in the population will always bring economic growth. That is, to some extent, unrealistic. Although the number of people employed in academia has risen significantly over the last decades, the statistics on GDP per capita growth did not follow that pattern. That has been noticed by Jones (2022), who expands the model to correct for the diminishing returns to idea creation (A). When inventions are abundant, it becomes more difficult (and more resource-intensive) to come up with new ones. Therefore, he suggests a function that accounts for that by including β (amount of ideas already explored) and σ > 0 that captures the importance of ideas.



The growth is, therefore, dependent on how important the new ideas are, how much of them are already developed, and what the population growth is. The output can also benefit one-time effects of the increase in h – human capital measure. Since β cannot be decreased by the policymakers, they should focus on the demographic policies (through n) and facilitate the emergence of new ideas, by investing in research technology, for example. That brings us to the same conclusions as the combined Solow and Romer model make; that is, the main determinants of future growth are investments in population growth, human capital and new technologies.


Europe's slowing economic growth poses a significant challenge to its global competitiveness and status. Through the models described, it becomes apparent that demographic shifts, innovation dynamics, and resource management are pivotal factors influencing the region's economic trajectory. Although no model is a perfect representation of the real economy, it is practical to use a variety of them as proxies for what types of measures should be implemented. Policymakers must adopt a comprehensive approach that addresses these challenges to ensure sustained economic growth, competitiveness, and the preservation of Europe's position in the global economic landscape. By matching all of those pieces together, the continent has an opportunity for a bright economic future.


References

Acemoglu, Daron (2009). "The Solow Growth Model". Introduction to Modern Economic Growth. Princeton: Princeton University Press. pp. 26–76. ISBN 978-0-691-13292-1.

Center for Data Innovation (2019). Who Is Winning the AI Race: China, the EU or the United States? https://datainnovation.org/2019/08/who-is-winning-the-ai-race-china-the-eu-or-the-united-states/

Jones, C. I. (2022). The Past and Future of Economic Growth: A Semi-Endogenous Perspective. Annual Review of Economics, 14(1), 125–152. https://doi.org/10.1146/annurev-economics-080521-012458

Romer, P. M. (1990). Endogenous Technological Change. Journal of Political Economy, 98(5), S71–S102. http://www.jstor.org/stable/2937632

Spencer, B.J., & Dimand, R.W. (2010). The Diagrams of the Solow-Swan Growth Model





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