Analysis of macroeconomic effects of entrepreneurship wage subsidies using the system dynamics and geometric compromise programming approach

Entrepreneurship, as one of the cornerstones of economic development, ranks among the policy priorities of many countries. The sustainability of newly established businesses is critically important for the success of the entrepreneurial ecosystem. Government subsidies are frequently utilized as tools to alleviate the financial challenges faced by entrepreneurs and to facilitate the business start-up process. Entrepreneurship support aims to increase employment, ensure the sustainability of new ventures, and stimulate economic growth. In particular, non-repayable wage subsidies hold strategic importance in strengthening the entrepreneurial ecosystem and creating new employment opportunities. These subsidies help entrepreneurs reduce early-stage costs and establish their business processes on a sustainable foundation. Government-provided support for entrepreneurs not only enhances the success of individual businesses but also contributes to macroeconomic objectives. Considering that a significant portion of newly established businesses cease operations within the first few years, the importance of cash flow and cost management becomes evident. In this context, direct cost-reducing incentives, such as wage subsidies, play a vital role in improving business sustainability and promoting economic stability. This study examines the dynamic effects of wage subsidies on the labor market, the real sector, and public finance, while also evaluating their contributions to macroeconomic goals. Studies examining the macroeconomic effects of entrepreneurship and wage subsidies often rely on dynamic equilibrium models, statistical analyses, and system dynamics (SD) methodologies. In countries like Germany and Canada, policies aimed at supporting unemployed entrepreneurs, increasing employment, and fostering economic integration have been analysed for their short- and long-term impacts. Similarly, in countries such as Portugal, Italy, and Chile, sectoral or regional subsidy measures have been found effective in enhancing the sustainability of young and technology-based enterprises. In Taiwan, China, and South Korea, the analysis of subsidy programs in renewable energy and automotive sectors using SD models underscores the importance of feedback loops in policy design. Traditional analytical methods fail to fully capture the complex interactions and feedback mechanisms inherent in entrepreneurship and wage subsidies. In contrast, SD models and other innovative approaches provide more comprehensive insights compared to conventional analyses. Studies employing the SD approach investigate the dynamic interactions and feedback mechanisms of subsidy programs. Addressing gaps in the literature, this study introduces a novel approach by integrating SD methodologies with geometric compromise programming (GCP), enabling a broader analysis of entrepreneurship and wage subsidies. This innovative method offers critical insights for policymakers aiming to design more effective and sustainable subsidy mechanisms. The primary focus of the study is to understand the reciprocal interactions among system components, analyse their dynamic impacts over time, and propose actionable solutions for policy design. The modeling processes serve as a robust tool for evaluating the long-term effects of government subsidy and developing strategic recommendations. By providing both theoretical depth and practical applicability, these methodologies enhance the scientific contributions of this research. Entrepreneurship is a dynamic process that interacts with numerous distinct policy domains, making its analysis inherently complex and multifaceted. Consequently, the effectiveness of entrepreneurship support measures must be addressed through a multidimensional perspective that captures the intricate interplay of various factors. The System Dynamics (SD) approach provides a robust and versatile methodology for modeling and analyzing such complex systems. By examining interconnected feedback loops and behavioral changes over time within the entrepreneurship ecosystem, SD facilitates the prediction of the impacts of policy recommendations with a high degree of reliability. Geometric Compromise Programming (GCP) further complements this analytical framework by serving as a critical tool in multi-criteria decision-making problems, offering balanced solutions that are particularly valuable for policy design. This methodological synergy allows for the development of comprehensive, evidence-based strategies that align with both immediate and long-term policy objectives. This study adopts an integrated framework combining operations research methodologies for the analysis of government support policies. By leveraging a combination of regression analyses during the identification and validation of system parameters, the research ensures a robust empirical foundation for the model. Additionally, statistical methods such as the t-test and Mean Absolute Percentage Error (MAPE) have been employed to rigorously evaluate model accuracy and validity. The modeling process commenced with the definition of the objectives and scope of the System Dynamics (SD) model. The dataset was categorized into three levels: raw, semi-processed, and processed, allowing for their application at various stages of the modeling process to enhance the precision and robustness of the analysis. Following this, a causal loop diagram was developed. This diagram served as a critical tool for visualizing the interactions among these parameters, offering significant insights into the socioeconomic impacts of entrepreneurship subsidy policies by mapping out the feedback relationships inherent within the system. Subsequently, a stock and flow diagram was constructed to provide a more detailed representation of the system, enabling the simulation of resource flows and the modeling of dynamic changes within the system over time. In the design of the model, three subsystems—real sector, labor market, and government—were established, each comprising components meticulously designed to address specific objectives. This subsystem structure ensured that the model was comprehensive and aligned with the multidimensional nature of the analysis. The validation of the model was conducted through a rigorous process involving three core tests: the behavior sensitivity test, the integral error test, and the reality test. The behavior sensitivity test examined the model's response to parameter changes, identifying potential enhancements that increased the reliability and robustness of the model's outputs. The integral error test assessed the model's accuracy in long-term forecasts, demonstrating that changes in time steps had minimal effects on the model's outcomes, thereby affirming its stability over extended periods. Lastly, the reality test evaluated the model's alignment with real-world data using statistical techniques such as the Mean Absolute Percentage Error (MAPE) and t-tests. The results confirmed that the model accurately represents real-world systems with a high degree of fidelity. This study focuses on two primary objectives: first, to analyse the impact of subsidy policies on entrepreneurship, employment, and tax revenues; and second, to determine the optimal parameter values of such subsidy mechanisms to enhance the efficiency of achieving the identified objectives. Within the modeling process, key decision variables were defined, including the subsidy rate, subsidy period, subsidy amount limit, and the subsidized new firms ratio. For the model's benefit variables, the number of new firms, the number of workers, and the amount of generated tax revenues were selected. Furthermore, the cost variables associated with the model were incorporated to evaluate the financial burden of wage subsidy programs on governments. In the final stage of implementation, the GCP model was integrated to complement the optimization capacity of the System Dynamics (SD) model. By combining the SD model with the GCP method, the optimal levels of decision variables across seven distinct scenarios were determined, and simulations were conducted to explore the behavior of these variables. This integrated approach allowed for an in-depth assessment of the economic impacts of entrepreneurship wage subsidy mechanisms on the broader economic system. The process not only provided valuable insights into the dynamic interactions within the system but also enhanced the applicability of the model as a critical tool in policy formulation and development. Through this methodology, the study delivers a robust framework for evaluating and optimizing entrepreneurship subsidy policies, contributing significantly to the design of effective and sustainable economic interventions. During the modeling process, historical data were analysed, and simulations were conducted to inform the design of future subsidy policies. Using the Insight Maker software, an SD model was developed to evaluate different scenarios, and optimization processes were applied to determine the optimal solution values. The results revealed that, for all cases, the optimal subsidy rate was 100%, and the subsidized new firms ratio was either 100% or close to it. In the first three scenarios, the objective function comprised benefit and cost variables, with the optimal subsidy period determined to be 11 months. In the subsequent three scenarios, the optimal values for all decision variables produced relatively similar results. In the final scenario, which included all three benefit objective variables in the objective function, the optimal subsidy period was calculated to be 24 months, with an optimal subsidy amount limit of 3991 Turkish Liras (TL). The seventh scenario yielded the highest results in terms of all three benefit variables, while the second and third scenarios produced the lowest values. Graphical analyses of all scenarios followed a similar pattern, indicating that the normalized benefit and cost objective variables moved in parallel over time and exhibited consistent behavior in long-term dynamics. The findings indicate that while entrepreneurship wage subsidies exhibit limited effects in the short term, they contribute significantly to economic growth and employment in the long term. Notably, it was observed that the impact of these subsidies begins to materialize with a one-year delay. This result underscores the importance of timing and duration in the design of subsidy programs, highlighting the necessity for long-term strategic planning. In cases where the extension of the subsidy period is necessary, it has been determined that lowering the upper limit is critical for ensuring cost-effectiveness. The findings of this study emphasize the importance of striking a balance in the design of subsidy policies, demonstrating the need to reconcile cost-effectiveness with long-term benefits. This research provides valuable insights for policymakers, offering guidance on optimizing the economic benefits of subsidy measures while maintaining cost-efficiency. Future studies are recommended to design entrepreneurship wage subsidy more effectively, taking into account sectoral and regional differences. Additionally, evaluating other subsidy mechanisms provided to entrepreneurs, such as equipment or rental subsidies, within a similar analytical framework would be beneficial. It is also suggested that entrepreneurship subsidy be analysed in greater depth in terms of business scale and sector, and that subsidy policies in Turkey be compared at the international level. This thesis presents an integrated model to assess and optimize the effectiveness of subsidy policies, offering guidance for future research.