Introduction

The older a society gets, the greater its aversion to change. Germany is a good example of this. The promise to maintain the status quo, which the majority of voters finds comfortable, was a key reason for Chancellor Angela Merkel's long political success. However, sticking to the status quo strengthens special interest groups and prevents adaptation to changing circumstances.¹

This was the experience of Angela Merkel's successor Olaf Scholz. His government described itself as a "progressive coalition". Instead of progress, however, his term in office was characterised by stagnation. Real gross domestic product stagnated from the formation of the coalition in November 2021 until its collapse in November 2024. This period of weakness was longer than the longest recession in the history of the Federal Republic of Germany, which lasted from 1980 to 1982.

In contrast, the destruction of outdated structures not only brings pain, but also offers opportunities.² This is because the destruction of old structures is the necessary condition for the creation of new ones. However, for this to become the "creation" of new prosperity, new structures must be formed by market forces. As the example of the Russian October Revolution of 1917 shows, replacing an old, rigid structure – the Tsarist regime – with a new, even more rigid one – the Soviet regime – only worsens the situation.

In this paper, we analyse the consequences of maintaining the status quo and allowing "destruction" for the countries of the European Union. These countries have been shaken by three major disruptions in recent decades: the capitalist transformation following the collapse of the Soviet empire in the early 1990s, the euro crisis from 2009 to 2012, and the migration crisis that peaked in 2015. The most important finding of our study is that the disruptions triggered a process of creative destruction (rather than just destruction), especially when the formation of new structures was driven by market forces.

Shock therapy through capitalist transformation

With the fall of the Berlin Wall in 1989 and the demise of the Soviet Union two years later, the Eastern European EU countries experienced a change of economic system. The disruption associated with their capitalist transformation was probably even greater than the reverse transformation to socialism four decades earlier. This is because it is much more difficult to switch from a system of centralised economic planning to the "spontaneous" order of a market economy that has grown over time.³

Although the transition from capitalism to socialism is easier to achieve – it only requires uncompromising state suppression of individual freedom – history shows that the destruction caused in the process is not followed by creation and the continuous development of the growth forces of the economy. We illustrate this with the example of Poland (Figure 1). Although real GDP per capita recovered after the Second World War, the recovery ended in 1978. The centrally planned Polish economy was unable to cope with the upheavals triggered by the oil crises of the 1970s. Real GDP per capita fell until 1991, when the capitalist transformation created circumstances that triggered the largest and longest economic upswing in Poland's history.

A key factor in the spectacular development of the Polish economy was that there was no outside help available to mitigate and delay the transformation. Destruction was followed by the release of market forces, which led to creation.⁴ The situation was quite different in the former German Democratic Republic, which received a great deal of state support from the West after unification with the Federal Republic of Germany.

Figure 2 shows the real value added in the so-called "new federal states" and in Poland. From 1991 to 1995, real value added in the new federal states grew enormously. Most of the measures for capitalist transformation and financial aid to alleviate the social consequences took place during this period. After that, growth weakened considerably. The continuation of massive financial aid up to the present day limited "destruction“ but also hindered "creation" by unleashing market forces. In contrast, the Polish economy swung onto a steady and strong growth path with the capitalist transformation without external aid to mitigate its consequences (as can be seen from the stable slope of the development of real value added shown on a logarithmic scale).

Shock therapy through the euro crisis

With the introduction of the European single currency, interest rates in many accession countries fell to levels never seen before. The reason for this was that the euro was to become the successor to the Deutschmark and therefore the low German interest rates were seen as a "benchmark" for the eurozone. In some countries, the interest rate cuts sparked a boom in the property market, while in others they tempted the state to go over the edge into debt. The Greeks, who were only able to join the eurozone in 2001 on the basis of embellished data, indulged in both.

When the newly elected Prime Minister, George Papandreou, announced in October 2009 that the budget deficit for 2009 would not be around 6 to 8 per cent of GDP – as previously reported – but actually over 12 per cent (later revised to over 15 per cent), the Greek euro bubble burst and the economy crashed (Figure 3). The country's exit from the monetary union was seriously discussed. However, the heads of state of the leading euro countries – including Germany in particular – decided to grant financial aid to keep Greece in the EMU. The aid was granted in the style of the International Monetary Fund's adjustment programmes and was linked to conditions for comprehensive economic reforms. The first bailout package was approved in May 2010 and the last programme ended in August 2018.

The conditions attached to the programmes forced the Greek government to implement comprehensive economic reforms. Following the destruction of the bubble economy, this released market forces that were able to initiate the process of creation. As a result, real gross domestic product per capita rose by 24 per cent from the first quarter of 2013 to the fourth quarter, or at an annualised rate of slightly under two per cent (Figure 3). Although this is considerably less than in Poland (just under four per cent), it is significantly better than in Germany (0.6 per cent).

Disruption through migration

Disruptions can also be triggered by migration. Already in ancient Rome, mass migrations caused enormous disruption and contributed to the fall of this empire. Currently, Europe is once again affected by mass migrations, especially from the Middle East and North Africa. The political disruption is obvious. But does immigration also create economic disruption? At first glance, the evidence is not conclusive. Against the background of its shrinking labour force, Europe needs immigration in order to be able to provide for its growing army of pensioners. On the other hand, immigration into the social systems via asylum claims represents an enormous cost burden. Which effect outweighs the other?

A comparison of the four largest EU countries that are heavily affected by immigration with Poland, which has pursued a more restrictive immigration policy, seems to support the thesis that immigration is a burden. With this argument, the Polish government has rejected the redistribution of migrants in EU countries. However, the picture may be distorted due to the small sample and the exclusion of other factors. For this reason, we will analyse this relationship econometrically below.

Consequences of disruptions in a country comparison

In the previous sections, we have analysed the consequences of disruptions using examples. Now we want to round off the case studies by comparing the economic development of the 27 EU countries. Our hypothesis is that countries affected by disruptions were able to record higher economic growth than others in the following years due to creative destruction. To this end, Figure 4 shows the average growth rates of real gross domestic product per capita for the EU countries from 2013 to 2024. We have chosen 2013 as the year for the start of the calculation because the euro crisis was largely under control at that time.⁵ We expect the countries that underwent capitalist transformation during the 1990s to have continued to benefit from the associated creative destruction in the recent past. Countries that have not experienced disruption, on the other hand, should show lower growth rates.

The data largely support our hypothesis. At the lower end of the growth scale are countries from Luxembourg to the Netherlands that have not experienced any significant disruptions. At the higher end are countries that have either undergone capitalist transformation or implemented adjustment programmes during the euro crisis. One exception is Denmark, whose economy appears to have the necessary flexibility to grow robustly under changing circumstances even without disruption.

Determinants of prosperity

In the previous sections, we have analysed the extent to which creative destruction can promote economic development. Now we want to analyse in more detail which forces are released as a result and lead to economic prosperity. To this end, we have used a panel data analysis to regress the gross domestic product per capita of the 27 EU countries in the period 1995-2024 on the variables identified as growth drivers in the economic literature.⁶ The capital stock results from the accumulation of fixed investments over time and, as a "factor of production", directly influences the level of production. Total factor productivity captures the efficiency with which production factors are combined. It reflects technological progress and the institutional quality of an economic system. Trade openness promotes specialisation, competition and knowledge diffusion.

Ideally, social spending should have an impact on human capital and social cohesion through education, health and stabilisation effects. However, under certain circumstances, social spending can have a negative impact on GDP per capita if it is inefficient or creates distortions. On the one hand, high social transfers can reduce incentives to work, for example if generous social benefits reduce the incentive to take up work or gainful employment. On the other hand, rising social expenditure often leads to a higher government spending burden, which has to be financed through higher taxes or debt – both of which can inhibit investment and reduce the growth potential. In addition, inefficiently utilised social spending can divert resources away from productive investments (e.g. infrastructure or research) and thus slow down long-term growth.

Ultimately, immigration influences both the labour supply and, in the long term, a country's production potential. Immigration can have a positive effect on GDP per capita if it expands the labour supply, mitigates demographic challenges (such as ageing) and brings human capital and innovation potential into the economy. However, immigration can also have a negative effect on GDP per capita if it is primarily fuelled by incentives such as generous social benefits rather than job or educational prospects. Under these circumstances, there is a risk of failure to integrate into the labour market, which leads to an increased fiscal burden. To capture the effect of this channel, we interacted the immigration variable with social benefits.⁷

The detailed results of our regression can be found in the appendix. Table 1 summarises the most important results and shows the elasticities of GDP per capita in relation to the respective variables. These indicate the percentage by which GDP per capita changes when the respective influencing factors change by one per cent.

In line with the economic literature, we find that capital endowment and total factor productivity have a large impact on the level of GDP per capita. Creative destruction therefore acts primarily through its influence on these variables. Openness to international trade also has a positive effect, but can be more than compensated for by an increase in social spending.

Our initial analysis of migration ended without a clear result. However, the econometric analysis shows that migration can have positive and negative effects. In general, it has a positive effect. However, if immigration takes place into the welfare state (for example through the granting of asylum), the generally positive effects are more than offset by the negative effects of immigration into the welfare state. The granting of asylum is therefore a social benefit to citizens of other countries, which – like the expansion of the welfare state as a whole – depresses economic performance.

Conclusions

In this paper, we have analysed the consequences of maintaining the status quo and allowing "destruction" for the countries of the European Union. We found that the countries that have been shaken by capitalist transformation and the euro crisis in recent decades have subsequently fared better than others that have stuck to the status quo. We also found that uncontrolled immigration through the granting of asylum or toleration weakens the economy if it places a burden on the welfare state.

The most important finding of our study, however, is that disruption triggers a process of creative destruction (rather than just destruction) when the formation of new structures is driven by market forces. Currently, Europe is experiencing new disruptions due to the shifting geopolitical balance of power and the foreign and trade policies of Donald Trump's administration. Our study suggests that Europe can emerge stronger from these disruptions if it finds the courage to dare less state and more market.

Appendix: Detailed results of the regression analysis

Our panel data analysis is based on the following regression equation:

gdp_it = β₁cap_it + β₂tfpi_t + β₃open_it + β₄soc_it+ β₅immig_it + β₆immigsoc_it + β₇debt_it + dcountry + dtime + ε_it       (1)

where gdp_it is the dependent variable, measured as GDP per capita in country i in year t. The independent variables on the right-hand side include capital stock per capita (cap_it ), total factor productivity (tfp_it, index number, 2015=100), trade openness (open_it , percentage GDP share of the sum of imports and exports), social spending (soc_it, as a percentage share of GDP), immigration (immig_it, share of immigrants in the total population), immigration into the welfare state (immigsoc_it , interaction term between immigration and social spending) and public debt (debt_it, as a percentage share of GDP). The variables dcountry anddtime stand for country and time dummies that control for unobserved, time-invariant heterogeneity between countries. Finally, ε_it is the idiosyncratic error term. The estimated coefficients β cannot be interpreted directly in economic terms, but require an additional conversion into elasticities, which we have shown in the main part of the study.

Our estimates are based on the so-called fixed-effects model. This is a panel data approach that assumes that each unit (in our context, each country) has its own unobservable characteristics that could distort the estimation of the influence of explanatory variables on the dependent variable if they are not taken into account. Fixed-effects estimation eliminates these constant, unobserved effects so that only the variation within a unit over time is used to identify the effects.

Table A.1 shows in column (1) detailed estimation results related to our sample of annual observations for 27 EU countries in the period 1995-2024. Columns (2) and (3) show additional estimation for two country groups representing the dynamic East-South (2) and the subdued West (3) of the EU.⁸ The main estimation results remain intact regardless of the country group.

If we assume endogeneity in equation (1) because, for example, a higher GDP per capita would enable a better allocation of resources or would also lead to more intensive immigration, the estimation results of the analysis in Table A.1 could be biased. In order to check the robustness of our analysis (also with regard to a possible lack of stationarity of the time series), we firstly worked with transformed variables (as non-rolling 5-year averages), secondly with lagged explanatory variables and thirdly with first-differenced variables in further estimates. All methods were able to confirm our original results.

References

Balcerowicz, Leszek (1995): Socialism, Capitalism, Transformation. Budapest: Central European University Press.

Durlauf, Steven N.; Johnson, Paul A.; Temple, Jonathan R.W. (2005): Growth econometrics. In: Aghion, Philippe; Durlauf, Steven N. (eds.): Handbook of Economic Growth, Volume 1, Part A. Amsterdam: North Holland, pp. 555-677.

Hayek, Friedrich (ed.) (1967): New Studies in Philosophy, Politics, Economics and the History of Ideas. Chicago: University of Chicago Press.

Mankiw, Gregory N.; Romer David; Weil, David N. (1992): A contribution to the empirics of economic growth. Quarterly Journal of Economics, 107(2), 407-437.

Olson, Mancur (1965): The Logic of Collective Action: Public Goods and the Theory of Groups. Harvard University Press.

Polanyi, Karl (1944, 2021): The Great Transformation. Wiesbaden: Springer Fachmedien.

Sala-i-Martin, Xavier X. (1997): I just ran two million regressions. The American Economic Review, 87(2), 178-183, 1997.

Schumpeter, Joseph A. (1942): Capitalism, Socialism and Democracy. Harper & Brothers.

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¹ Olson (1965).

² Schumpeter (1942).

³ The term "spontaneous order" was coined by the chemist and philosopher Michael Polanyi (Polanyi, 1944). However, the concept was popularised by the economist Friedrich von Hayek, who discussed it in detail in his works on the market economy and social theory (Hayek, 1967).

⁴ The transformation involved an immediate transition to a market economy, with price liberalisation, privatisation and opening up to international trade (Balcerowicz, 1995).

⁵ During the euro crisis, several adjustment programmes were launched for the affected countries from 2010 onwards. For Greece: First rescue package (2010) jointly from the EU and the IMF, which included loans totalling 110 billion euros. Second rescue package (2012) with an additional 130 billion euros and a haircut for private creditors. Third rescue package (2015) totalling 86 billion euros. For Ireland: Rescue package (2010) totalling 85 billion euros, provided by the EU and the IMF. For Portugal: Rescue package (2011) totalling 78 billion euros, also financed by the EU and the IMF. For Spain: Bank bailout (2012) of up to €100 billion to recapitalise Spanish banks. For Cyprus: rescue package (2013) totalling 10 billion euros, provided by the EU and the IMF.

⁶ See Durlauf et al. (2005), Mankiw et al. (1992) and Sala-i-Martin (1997).

⁷ There is no direct variable that would measure the effect described. By multiplying the two factors, immigration and social benefits, we can analyse the simultaneous effect of the two variables. Thus, we can observe how the effect of immigration on GDP per capita changes depending on how generous the social benefits are and independently of how immigration and social benefits individually affect GDP per capita.

⁸ The allocation of countries is based on the results of the cluster analysis. East-South includes Bulgaria, Croatia, Cyprus, Hungary, Ireland, Lithuania, Latvia, Malta, Poland, Romania, Slovakia and Slovenia. The West is made up of Austria, Belgium, the Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Italy, the Netherlands, Portugal, Spain and Sweden.