The search for the key drivers of economic growth in capitalist economies has been a focal point of economic analysis since the days of classical economists like Adam Smith, David Ricardo, and Karl Marx. To better understand growth and the forces enabling capitalist economies to expand their production of goods and services, economists often categorise economic factors into two independent groups.
On one hand, there are demand-side factors such as consumer spending and investment, which primarily drive economic fluctuations. On the other hand, there are supply-side factors like technological innovation and labour force growth, which set the potential output path of an economy. This potential output represents the maximum production level an economy can achieve without causing inflation, acting as a centre of gravity for actual economic dynamics.
Potential output is particularly crucial for Eurozone countries due to its significant role in fiscal regulations and monetary policy. Fiscal rules, such as those governing structural budget balance, require countries to align their budgets with potential output to ensure sustainable public finances. The European Central Bank (ECB) monitors the output gap—the difference between actual and potential output—to assess whether economies are approaching inflationary limits. Both fiscal and monetary policies thus rely heavily on the concept of potential output, highlighting its importance in maintaining economic stability and growth.
This research aims to enhance the understanding of economic growth through a simple demand-led model that incorporates hysteresis—the lasting effects of demand-side dynamics on potential output. Despite increasing recognition of hysteresis, few studies have developed straightforward dynamic models integrating these mechanisms. Notable exceptions include the work of Fazzari, Ferri, and Variato (2020), who examined hysteresis effects on US economic growth using a simple demand-led model. This study extends their framework, using Italy's economy from 1979 to 2018 as a case study, and introduces key conceptual and methodological changes to improve model accuracy and uncertainty analysis.
Italy's economic context, marked by low and stagnant GDP and labour productivity growth, high unemployment, and widespread involuntary part-time employment, provides a unique setting for this investigation. The Fazzari, Ferri, and Variato (2020) model is demand-led, with potential output as the upper boundary for economic dynamics. Demand-side factors, especially autonomous components like government spending and exports, shape the system's evolution. Hysteresis mechanisms link potential output to changes in unemployment rates and capital stock accumulation, challenging traditional views that separate supply-side and demand-side dynamics.
Dynamic simulations of the model across various scenarios yield critical insights. Accurate simulations require specific values for key parameters, such as the propensity to save and the long-run target capital-output ratio. The model reveals a trade-off between accurately describing demand-side and supply-side dynamics, particularly regarding labour productivity evolution post-1990s and general labour supply trends over the study period.
The empirical simulations show that the stability of steady-state solutions depends mainly on certain demand-side parameters. The adjustment speed for expected growth (α)—indicating how many years of past yearly growth are used by households to form future growth expectations (with higher α implying a longer memory)—and the adjustment speed for the capital-output ratio (λ)—showing how quickly the actual capital-output ratio converges to its long-run value set by firms—are critical.
Accurate scenarios for the Italian economy fall outside the unstable range, ensuring stable economic dynamics. However, the value of α suggests caution due to the implied long memories of past growth in forming future expectations.
Our research introduces unique conceptual and methodological tools that enhance the analysis of economic growth. The use of Causal Loop Diagrams (CLDs) visually represents feedback loops and interdependencies within the model, making complex relationships easier to understand and communicate. Additionally, our empirical analysis employs the All-Factors-At-a-Time (AAT) method, which allows for simultaneous variation of all model parameters across their feasible ranges. This approach offers a more comprehensive and realistic examination of non-linear systems compared to traditional methods.
For policymakers, recognising hysteresis and integrating these advanced tools into economic models can lead to more informed and effective decision-making. By considering the long-term impacts of demand-side policies on potential output, and using visual and comprehensive analytical methods, policymakers can better navigate the complexities of economic growth and stability. This research advocates for a more integrated and nuanced approach to economic policy, fostering broader dialogue and enhancing our collective understanding of growth dynamics.
While this research provides valuable insights, it acknowledges several limitations. Methodologically, the study relied on assumptions about the initial capital-output ratio and growth rates due to a lack of initial data, potentially impacting model accuracy. The empirical approach, while intuitive, may lack the mathematical rigour needed for robust results, and more advanced econometric techniques could enhance parameter estimates. Conceptually, the model struggled to capture supply-side dynamics, particularly labour productivity stagnation and labour supply evolution. The reliance on exogenous inputs for autonomous demand components limits the model’s ability to fully replicate real-world demand-side dynamics.
Future research should build on this work by expanding the current model to better capture case-specific information, particularly recognising the impact of austerity measures on Italy’s economy. Revising the hysteresis mechanisms is crucial to accurately reflect the dynamics of supply-side variables, incorporating factors such as labour protection legislation and financialisation proxies. Additionally, addressing inequality and ecological constraints within the model could provide a more comprehensive understanding of sustainable economic growth. These aspects are critical for enhancing the model’s applicability and relevance in public and policy debates.
Moreover, comparative analysis using different models, such as the Solow-Swan model, could offer unique perspectives on economic growth theories and their assumptions. Exploring the connection between economic modelling and policymaking, particularly how diverse economic theories are integrated into policymaking, presents another promising avenue. This could involve interviews with experts to understand how models are employed in major policymaking institutions and how a plurality of economic theories can be effectively communicated to the public. By addressing these areas, future research can enhance the robustness and applicability of economic growth models.