This Master’s thesis examines the relationship between public debt and climate-related natural disasters in Southern Europe, focusing on Greece, Italy, Spain, and Portugal. It analyzes how increased frequency and severity of climate events strain public finances, leading to higher debt levels and reduced economic stability. The research synthesizes existing literature and employs rigorous scenario analysis to project future fiscal outcomes, highlighting the unique vulnerabilities of these countries. The thesis concludes with policy recommendations to enhance fiscal resilience, advocating for tailored fiscal rules, increased investment in climate adaptation and mitigation, and the establishment of fiscal buffers to ensure long-term economic stability in the face of climate change.

The perspective of politicians and academia on military expenditure and its economic consequences is too often viewed from a short-term perspective and neglect the longer-term. Rising global turmoil has revealed this fragile thinking in many European countries, demonstrating that economic power is insufficient to protect their fundamental values and that it also requires military capacity (which declined significantly after the end of the Cold War). This study examines the economic consequences of military expenditure from the political, economic and military domains, focusing on Germany and the Netherlands. To determine the economic consequences, economists commonly refer to the fiscal multiplier. This study concludes that the fiscal multiplier can be used purely as a theoretical concept. Measurable data are insufficient to capture short- and long-term effects on the economy. The intangible part looks at components of economic consequences in a broader view, covering hybrid warfare, the role of climate, innovation, as well as the role of the free market, cooperation and dependency. This reveals that military expenditure is of greater importance than measurability suggests. A novum modus operandi takes a step towards a new perspective on the economic consequences of military expenditure. Herein, themes on uncertainty, unpredictability, asymmetry, efficiency and non-linearity are explored (such as whether NATO and the EU are too big).

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.

As the world's third-largest emitter of greenhouse gases, India stands at a crucial juncture in the global fight against climate change. Recognising the delicate balance India must strike between rapid economic growth and sustainable development, this research employs a Computable General Equilibrium (CGE) model tailored specifically for the nation. By incorporating Greenhouse Gas (GHG) emissions, the model delivers an in-depth analysis of the potential economic impacts of climate mitigation strategies, especially carbon taxation, within the intricate fabric of India's diverse economy. This endeavour fills a significant knowledge gap, offering a tool that policy analysts can use to harmonise India's developmental aspirations with its global climate commitments.
Tapping into the power of quantitative methodologies, the study leverages CGE models known for their proficiency in capturing a country's economic interconnections. For India, this model weaves in GHG emissions to holistically assess the economic ramifications of carbon taxation. Core to this research is data sourced from India's Social Accounting Matrix (SAM) (Pal et al., 2020), complemented by inputs from national databases capturing carbon intensities, labour productivity, and capital stock depreciation.
The application of the CGE model to India's context yielded pivotal insights. A deep dive into sectors revealed that five of them, led prominently by the coal-intensive energy sector, are responsible for over 95% of India's emissions. Notwithstanding the nation's push towards renewables, emissions are dauntingly high. While a modest carbon tax has limited impact, a more aggressive tax rate, although effective, disrupts income distribution, disproportionately affecting India's marginalised populations. The research thus underscores a synergistic approach, merging targeted reinvestments with a robust carbon tax as the linchpin for sustainable decarbonisation in India. While potent in emission reduction, such strategies necessitate protective measures, like subsidies, to prevent deepening India's socio-economic divides.
The study recognises intrinsic limitations that need addressing. The current model's architecture possesses constraints, particularly in its representation of export levels and wage growth. An endogenous presentation in these areas would provide a richer systemic view. While the research touched upon two primary tax rates, a broader exploration of tax rates is warranted to align more accurately with Key Performance Indicators (KPIs). The present pricing mechanism, which leans heavily on consumers bearing the entirety of the carbon tax, hints at a potential imbalance in economic impact and needs reevaluation. Additionally, using placeholder coefficients for decarbonisation offers a limited perspective, potentially glossing over the nuances of carbon reduction dynamics. Notably, the model's exclusion of simulations for extreme weather events is a critical oversight, which could affect its forecasting abilities, especially in climate change.
This research presents actionable policy recommendations, chiefly underscoring the role of targeted reinvestment coupled with a high carbon tax rate. With India's energy sector at the forefront, targeted reinvestments promise to bolster GDP and reduce emissions, providing a roadmap that aligns economic growth with climate mitigation. However, given India's socio-economic fabric, implementing such strategies mandates careful consideration of potential impacts, especially on vulnerable sectors like agriculture and the vast populace of lower-income households.

The critical importance of investing in renewable energy to mitigate climate change cannot be overstated. Renewable energy projects are capital-intensive and risky. With this unbalanced risk and return profile, private-sector financial actors are often not in a position to fund these projects. Furthermore, the current magnitude of renewable energy financing is still low, particularly in comparison to the climate change mitigation goals set by policymakers. Because renewable energy investments fall short of what is needed, we can speak of an investment gap in renewable energy generation and technologies

This study centres on the (private and public) renewable energy investment gap in the Netherlands. The Netherlands was chosen since the literature lacks a comprehensive overview of the nation’s renewable energy financing. Furthermore, the Netherlands has not yet met its renewable energy targets which signifies the need for increased investments in the renewable energy sector. Government funding for renewable energy projects encounters certain constraints, primarily due to the Stability and Growth Pact, which dictates that EU members must maintain fiscal discipline, meaning that the government has to operate within a specific budgetary limit. Therefore, the private sector has a pivotal role to play in bridging the renewable energy investment gap. This shows the necessity for collaboration between the public and private sectors to mitigate climate change. Governments can use policy instruments to motivate or mobilise additional green investments by private financial actors.

Against this background, this master thesis investigates the following research question: How can the mobilisation of Dutch private investors in the renewable energy sector close the renewable energy financing gap?

To address this question, four deliverables are presented. Firstly, Chapter 2 offers a comprehensive literature review within the designated field. Secondly, Chapter 4 empirically estimates the investment gap in the renewable energy supply in the Netherlands. Thirdly, statistical analysis is used to investigate the relationship between private financing and public policies and financing. Comprehensive data collection was conducted for both public and private financing; specifically, a time-series database (2004-2022) has been constructed for green financing by major Dutch banks and pension funds, drawing on annual reports and sustainability reports published by these actors.

This third deliverable includes two sub-deliverables. Firstly, Chapter 5 presents a descriptive analysis of the Dutch renewable energy financial landscape, based on the database that has been created during this research. This analysis includes research on Dutch commercial banks with a sustainability index, an analysis of the green bond market, an analysis of renewable energy consumption in the Netherlands and public policies. Secondly, Chapter 6 presents a regression analysis performed to understand the relationship between private sustainable financing on the one hand, and public policy support and direct public investments on the other hand. This was conducted with the following statistical methods: an OSL regression, univariate regression, and factor analysis. The fourth deliverable presents a validation of the findings conducted in the literature review and the regression analysis. This validation was conducted through semi-structured interviews with experts in the renewable energy sector, including private financial actors, government policy experts and an expert in renewable energy generation. This deliverable is presented in Chapter 7.

The findings of this thesis report are as follows. The analysis of the investment gap in renewable energy supply in the Netherlands shows that a substantial step-up of 132% in investments towards renewable energy supply is required for the Netherlands to reach its committed decarbonisation targets consistent with the IPCC scenario of 1,5°C global warming. Moreover, when evaluating the investment requirements against the total economic investments, investments directed toward RE need to account for 10.4% to 12.5% of all total investments in the Dutch economy by 2025 to bridge the RE investment gap. This analysis shows a sharp increase in investment requirements from now until 2030; in contrast, the period from 2030 to 2050 may not require a drastic increase. This is based on the significant initial upfront capital required to cover the cost associated with the technology development as well as economic scaling up. However, before that can occur, an initial larger investment is required. After 2030, a slowdown of the investment requirements is based on the belief that the infrastructure will be established by then and the technologies will be mature and more efficient, lowering the cost. This analysed investment gap created the base for the research, showing the need to understand the financing landscape and the relationships between the financial actors and public policies.

Once the investment gap had been estimated, the focus of the research turned to understanding its underlying causes and potential solutions for this underinvestment. A comprehensive primary data collection began when data on private financing for specific financial actors in the Netherlands proved to be missing. The results derived from the created database are various. Firstly, a sustainability index for the Dutch banks was created. This sustainability index serves as a measure of each bank’s commitment to funding aimed to mitigate climate change, relative to their respective market size. Based on this sustainability index, the analysis reveals substantial differences between those banks. Triodos, with the least market share, scores the highest in sustainability while ING which allocates the largest figure
towards sustainability is ranked second last in regards to sustainability in the banking sector relative to its size. This highlights the importance of the bank’s commitment to sustainability, irrespective of its size. Secondly, in regard to the government, expenditures for mitigating climate change are mostly in the form of subsidies towards renewable energy projects. On average subsidies were 88,62% of the total government expenditures towards mitigating climate change. The largest subsidy fund is the Stimulering Duurzame Energieproductie en Klimaattransitie (SDE++). Lastly, the research identified Dutch pension funds as the leading entity in the Netherlands’ green bond market. As of March 2023, these pension funds accounted for 53% of the country’s total green bond holdings. Moreover, they have shown an impressive increase of 286% in their green bond holdings from 2019 to 2023

The statistical findings show a positive effect of direct public financing on private financing in the Netherlands. More specifically, with a 10% increase in public financing, private financing increases by 6%. Monetary policies such as increased environmental taxation and low interest-rate lending positively affect private financing, or for a 10% increase in direct public policy support, private financing increases by 7%. Findings show that with increased renewable energy consumption, private financing increases. FITs and total energy consumption (including both renewable energy and non-renewable energy sources) show an inverse relationship with private financing, with a 10% increase in total energy consumption and price setting by FITs, the private financing decreases by 9,9%. The crucial findings emphasize the urgent need to mobilise private actors, who possess significantly more financial resources compared to the government, in mitigating the climate crisis in the Netherlands. Their active participation is essential for effectively addressing this pressing environmental challenge.

It is crucial to emphasize that, consistent with the literature review and validated by the interviews, the government does risk mitigation and helps to accelerate the renewable energy transition by subsidising heavily on the R&D phase. The Dutch government takes on the role of a market-shaping, rather than merely a market-fixing, as evidenced by their control over which technologies receive substantial subsidies. Furthermore, consistent with the literature review and validated by the interviews, the primary challenge for the Netherlands in implementing renewable technologies pertains to the commercialization phase. This phase, characterized by high-risk projects with inconsistent cash flow, simultaneously demands substantial capital investment. Financial stakeholders identify this as the Achilles heel in climate
change mitigation efforts.

Considering this vulnerability, a possible policy implementation might involve the government to alleviate the risks associated with the commercialization phase, attracting investors who are less inclined to risk, like pension funds, who possess significant capital. This could be achieved by assuring these investors that if they begin to invest in more high-risk projects, they would receive a portion of their investment back in the event of project failure, acting as a guarantee.

This thesis investigates the unprecedented labour market tension in the Netherlands post-2021, by analyzing the core drivers behind the labour market. A framework based on labour demand and supply is made in order to study the key drivers of the labour market. Through quantitative analysis it is found that the labour market tension after 2021 is primarily caused by a surge in the demand for labour, which in turn is likely to be caused by four key factors, government spending, more expenditure due to COVID-19 savings, exogenous investments in some sectors and increased net exports. It is advised to policy makers to focus more on tempering the demand for labour, if they desire to loosen up the labour market.

Recent years have shown an increased level of food insecurity: a surge in the level of poverty and hunger in low-income countries caused by higher global food prices. One of the potential causes of the commodity price spikes is the process of financialization, including an increased level of financial speculation in food commodity markets. Because the literature is inconclusive on the exact effects of speculation, this research aims to provide a fresh analysis of the potential impacts of financial speculation on food commodity prices as well as to explore policies that could influence the level of financial speculation. The main question to be answered through this research is: ‘What are the likely effects of the increase in financial speculation on the behavior of commodity prices in the current soybeans market, and which policies can be used to regulate these effects?’ First, a literature review was conducted to study sources on the potential theoretical effects of speculation, as well as sources on the current regulatory measures to counter speculation. Next, the system dynamics approach was used to investigate the role of speculative activity in price-setting behavior. Lastly, expert interviews were conducted to validate the behavior of commodity prices as shown in the model, as well as to gain knowledge on policy interventions.
Guided by the literature review, three important interacting markets were identified for inclusion in the conceptual system dynamics model for the soybeans market: the market for storage, the cash market, and the futures market. The results show how interactions between these markets determine the behavior of spot prices. Furthermore, in the literature review, speculators were found to be trend-following, fast-reacting entities who contribute to strengthening of price expectations and spot prices. The quantitative system dynamics model shows how speculators are able to amplify the oscillation of spot price behavior, which can be compared to the forming and crashing of price bubbles in a commodity market. This amplification occurs because speculators react faster to changes in spot prices than other market participants. While the model is still relatively simplistic, it creates an understanding of the system structure of financial markets that determines spot price behavior.
The research describes how experts agree on the fact that some kind of policy intervention is required to limit the negative effects of speculation. Policy makers should pay attention to the level of transparency in setting position limits and focus on clarifying and explaining the classification of speculators and hedgers. Furthermore, it is recommended that only traders with an active and real interest in the commodity should be allowed to participate in the futures market.

Rising food commodity prices pose a severe threat to vulnerable populations globally. While market fundamentals contribute to this increase, excessive speculation by financial investors is believed to play a significant role. This study aims to examine the relationship between financial speculation and agricultural commodity prices between 2000 and 2023, focusing on eight commodities: cacao, coffee, corn, rice, wheat, soybean meal, and soybeans. Additionally, the research reviews regulatory measures to mitigate the impact of financial speculators in food markets through expert interviews.

The first part of this research examines the relationship between spot and futures prices and between speculation and prices quantitatively by means of econometric statistical analyses. The econometric analyses consist of descriptive statistics, correlations, and linear Granger causality tests. Monthly data are gathered from the Food and Agricultural Organization (FOA), the International Monetary Fund (IMF), and the Commodity Futures Trading Commission (CFTC). The Granger causality tests are performed both over the whole period of research (2000-2023) and over a period with a certain price peak (2020-2023), as speculation comes often in peaks.

The findings reveal a strong relationship between spot and futures prices, except for rice, specifically futures markets seem to dominate spot markets. Granger causality tests demonstrate that futures prices can be utilized to forecast spot prices the commodities.

Regarding the relationship between prices and speculation, the descriptive statistics and correlations show weak evidence. The analysis reveals that prices and price volatility Granger cause speculation rather than the opposite, except for coffee, which exhibits bi-directional linkages. The research does not provide definitive evidence that speculation causes higher prices. However, there are issues with the "measurement" and classification (non-commercial vs. commercial traders) of the speculation variables. That ’flawed’ data could be a reason why this research cannot support the hypothesis.

Despite the inconclusive findings, the study supports the notion that market fundamentals alone do not determine prices. Excessive liquidity and the presence of more speculators than hedgers contribute to rising prices in commodity food markets, disrupting their functioning. Expert interviews highlight the need for effective regulation to address speculation. Policy recommendations include enhancing market transparency, stronger regulation of futures markets, limiting market access to actors with genuine commodity interests, and implementing global windfall taxation and a "food speculation tax" to combat financialization.

The detrimental effects of speculation in food-importing developing countries are not temporary and exacerbate existing challenges, including increased import bills, trade balance deterioration, currency depreciation, and inflation. Banning open capital accounts is recommended to mitigate the destabilizing impact of global capital flows on these economies.

The study acknowledges limitations with the use of a statistical approach. Especially since time series models, like Granger causality, cannot claim causality. This research is based on monthly data, so a lot of information within weeks (or even days) is lost. In the case of Granger causality testing, the external validity is limited because the findings only pertain to the data obtained from a particular exchange, for a particular period, and also of a particular form. Moreover, this research does not capture non-linear effects (since it uses linear Granger causality tests). Future research therefore should adopt a multi-method approach, preferably using daily data, to capture non-linear effects and enhance external validity.

With finance entering the real economy, new kinds of markets have emerged, such as futures markets, in which special contracts – called futures – are exchanged. From the early 2000s, futures on commodities have become popular among financial instruments, and we talk about "financialization of commodity markets". The uniqueness of commodity futures markets is that they see the participation of two structurally different market actors: physical commodity participants and speculators. Several, opposing claims have been made about speculation within commodity futures markets. One important claim is that the increase in speculative activity has, in certain periods of time, driven up commodity prices over and above the levels warranted by fundamentals of demand and supply.
This thesis investigates the role of speculation on the prices of two food commodities, corn (maize) and soybeans, and answers the following research question: To what extent did financial speculation have a role in rising food commodity prices over the years 2004-2023? To do so, a "multi-method" approach is employed. Specifically, the four methods are: a literature review; a replication of an econometric model; statistical inspections and linear Granger causality tests; and interviews with experts.
First, the "indirect" effect of speculation on food commodity prices through the oil market is examined with the extension of an econometric model proposed by Knittel and Pindyck. The analysis shows that, in recent periods, speculation can account for around 11% of the oil price changes. Then, through Granger-causality tests, a Granger-causation chain between oil prices, fertilizer prices and food commodity prices is found. The two findings together prove that speculation has some role in affecting oil prices, and that dynamics in oil markets are transmitted to food markets. Second, the thesis proceeds by assessing – though empirical analyses and Granger causality tests – the more direct effects of speculative activities in food commodity markets themselves on food commodity prices, as well as the relation existing between spot and futures prices. Even though the statistical evidence of speculation driving prices is found only in a few specific cases, the chapter concludes that speculation cannot be completely excluded from the factors affecting prices’ dynamics. Eventually, this thesis comes up with a theoretical-cum-empirical framework – justified and sustained by a literature review, a model replication, some statistical inspections and tests, and interviews of experts – that concludes that excessive speculation has – to some extent – been driving up and affecting commodities prices: specifically, speculation has increased volatility in futures markets.

Wealth inequality exists all over the world. This can be seen as a social problem because it violates accepted norms of egalitarian distribution. Moreover, wealth inequality can negatively affect a number of areas, including economic growth. However, wealth inequality also has advantages. For example, it provides incentives to engage in risky ventures that can lead to a more prosperous society. Thus, it would actually promote technological development and economic growth. The problem remains that wealth inequality above a certain point yields more negative than positive effects. Yet the most optimal point of wealth inequality is difficult to determine and depends on the context in which a country finds itself.

Wealth inequality is clearly a socioeconomic issue and has been increasingly studied internationally in recent years. For the Netherlands, however, it has only been examined in a handful of studies and often only one indicator has been used. The first objective of this thesis is therefore to investigate the development of wealth inequality in the Netherlands using various indicators. Moreover, these studies have done little or no research into the causes of the development of wealth inequality. As such, the second and main objective of this thesis is to examine the causes of this development in the Netherlands. During the Management of Technology (MOT) program at TU Delft, several major social issues related to technology or innovation were addressed. At the time of writing, wealth inequality is a contemporary socioeconomic issue in the Netherlands. It also affects technological development and innovation, making it relevant to the MOT program. Based on the main objective, we formulated the following main research question:

Main RQ: What factors have contributed to the development of wealth inequality in the Netherlands?

To answer this research question, we first conducted a literature review. Here, we addressed the definition of wealth, how wealth inequality can be measured, what had already been researched in the Netherlands, and the possible consequences of wealth inequality. But the most important finding from this literature review was a holistic view of the possible causes of wealth inequality. We did this primarily by analyzing studies that examined wealth inequality in countries similar to the Netherlands. We found that at least 10 macroeconomic and 8 household factors can potentially directly influence wealth inequality in a given country. We also identified indirect factors, but did not include them in this thesis.

After presenting a comprehensive overview of possible causes of wealth inequality, we developed hypotheses for these determinants. At the macroeconomic level, no hypotheses were eventually developed for the factors wealth tax, inheritance tax, and political stability. The latter was not considered relevant for the Netherlands. The other two remained constant over the years and were not meaningful to analyze. Ultimately, a total of 7 hypotheses were developed for the macroeconomic level. We omitted examining the effects of wealth inequality in this thesis, with the exception of the effect of wealth inequality on income inequality. These two factors would reinforce each other and this is better known as the snowballing-effect. Therefore, not 8 but 9 hypotheses were developed for the household level. Based on the formulated hypotheses, a conceptual model was created that served as the basis for the empirical analysis.

A descriptive analysis was then conducted. When collecting the data, the CBS database was mainly used. Occasionally, data from DNB and the World Bank were used. First, the development of wealth inequality in the Netherlands was examined. Most of the data found on household wealth covered the period 2006-2021. This period was therefore retained for the entire empirical analysis. Three indicators were used to validate the development of wealth inequality. These indicators were found to be highly correlated with each other, allowing the development of wealth inequality in the Netherlands to be confirmed with certainty. From 2006 to 2008, there was a small decline, after which it rose to record levels in 2013. From then on it fell again, and by 2021 the level was about the same as in 2008. Whether this is a desirable level of wealth inequality, we cannot say and requires further research. Subsequently, we examined the development of the possible determinants for which hypotheses were developed. We have not validated the determinants and associated indicators as in the case of wealth inequality (with the exception of income inequality). As a result, the development of the determinants entails some uncertainty. Moreover, we could not find suitable indicators for all determinants. In the end, 6 macroeconomic and 7 household determinants remained for the regression analysis.

With the remaining macroeconomic and household determinants, we first ran a simple regression to filter out the factors with significant influence on wealth inequality. We found that at the macroeconomic level, 3 factors were significant and consistent with the formulated hypotheses: housing prices, generous welfare state, and globalization. At the household level, these were 2 factors: mortgage debts and financial assets ownership rate inequality. Thus, no evidence was found for the snowballing-effect in the Netherlands. Two multiple regression analyses were then conducted: at the macroeconomic level and at the household level. It was found that all macroeconomic determinants were again significant and explained 93.7% of the variance in wealth inequality. Housing prices contributed the most to this, followed by globalization and generous welfare state, respectively. The two household determinants were also found to be significant and explained 73.8% of the variance in wealth inequality. Financial assets ownership rate inequality contributed the most to this. Based on the descriptive and regression analyses, the final conceptual model was created. Due to the limitations of the study, we could not examine whether the two regression models are correlated. Apart from that, however, we can conclude that they both predict the development of wealth inequality quite well, thus answering the main research question.

This study has filled several knowledge gaps by (1) examining and validating the development of wealth inequality in the Netherlands using various indicators, (2) constructing a comprehensive overview of possible causes of wealth inequality, and (3) empirically identifying the causes of the development of wealth inequality in the Netherlands. Furthermore, we can provide a number of insights to policymakers based on our findings. First, policymakers could compare the development of wealth inequality with the policies they implemented during this period to learn from it. This in turn could also provide new insights into the possible causes of wealth inequality in the Netherlands (at the policy level). Moreover, the significantly identified causes offer direct guidance for policymakers to influence wealth inequality in the Netherlands. This is especially true for the determinants generous welfare state, globalization, and financial assets ownership rate inequality, as they can be directly influenced by public policy. Further research should focus on identifying the consequences of the development of wealth inequality in the Netherlands. This can contribute to a better understanding of the desired level of wealth inequality in the Netherlands so that policymakers can manage it more effectively.

This integrative literature research analyses economic inequality using a system perspective. Topics related to the quantification, causes, and effects revolving around economic inequality are reviewed and presented in an overarching conceptual framework. The functioning of the conceptual framework is tested by performing an application on the Netherlands. Results show that economic inequality is a complex problem with multiple interconnecting parameters that cannot be solved with a single "silver bullet" policy. Economic inequality requires a systematic and integrative approach to enable a positive change. Also, the conceptual framework allowed to indicate numerous issues within the system of economic inequality occurring in the Netherlands that require our attention. Overall, this research offers a new perspective on the issue of economic inequality. The conceptual framework is the first in its kind and is able to inform and educate researchers, policymakers, and others about the system of economic inequality in a manner that has never been done before.

For most countries, the targets set in the sustainable development goals for 2030 are far from being met. The main cause is a lack of financing, due to the relatively high risks and low rewards associated with sustainable projects. This has caused a financing gap in developing countries of upwards of 2.5 trillion US$ annually, equal to 3% of global GDP. These unattractive aspects of sustainable investment projects result in a lack of private investment, leaving public investment as the main source of funding for these projects. A vital area within the financing gap is the lack of financing for SMEs in developing countries, which are important for economic growth and job creation. The issues faced by these countries and especially SMEs have been compounded by the COVID 19 pandemic, which has claimed countless lives, but also countless jobs in developing countries and has caused extensive economic damage. In this light, achieving impact on SDG 8: ‘Decent Work and Economic Growth’ was deemed critical for the whole of sustainable development.

Recently, blended finance, an investment type utilizing public and philanthropic capital to accelerate private investments, has become more popular. However, effective practices of using blended finance to foster job creation in developing countries through SME financing are lacking. Furthermore, there is little to no literature on investment decisions that goes into selecting projects for blended finance. In this light, this research aims to answer the following question: “What are effective practices and key investment decisions in using blended finance to fund SMEs in developing countries, focusing on impact towards achieving SDG8?

To answer this question, a literature review of the concept of sustainable development, sustainable financing methods and the role of SMEs in the developing countries was conducted. This highlighted the potential of blended finance when compared to other sustainable financing methods in being able to aid these SMEs and impact SDG 8. Afterwards, a data analysis of the performance of recent SME financing projects in developing countries, as well as a case study consisting of interviews with blended finance investment experts was conducted, in order to find effective practices of financing SMEs in developing countries to facilitate the targets set by in SDG8 and highlight how investment decisions are (to be) taken when considering blended finance projects.

It was found that even though the projects in lower-income countries within the could have stronger performance, a balance has to be struck between projects in these countries and those in slightly less low-income countries, in order to achieve consistent results. Furthermore, the use of public loan guarantees seems like a promising method but is currently suffering from a lack of willingness by banks to engage in blended finance transactions, due to solvency issues and general lower risk appetite and unfamiliarity with the methodology.

Furthermore, key investment decisions from an investor perspective lie in the specific business case of the project and whether the investment is ‘additional’ to the market. Furthermore, the attitude and capabilities of the entrepreneur behind the project are essential, as investors prefer projects in which the entrepreneur has enough skin in the game and is open to collaboration with a multitude of investors, such that one investor does not have to bear all the risks. Furthermore, it is important for investors to balance impact with financial performance, as only achieving impact through risky projects is not a sustainable business practice. More investment decisions could be made in the future if more and different blended finance methodologies would become more readily available. However, many of these, such as higher-leverage loan guarantees and first loss guarantees, are hampered by a lack of willingness again of private credit suppliers to engage in these transactions with public blended finance institutions. Furthermore, larger fund sizes would help investor diversity more, and thereby reach a wider range of projects and achieve more universal impact.

Therefore, it is recommended that if blended finance investments globally were to be expanded, that policy makers such as the UN, local governments, and the World Bank find ways to increase awareness of private credit suppliers and for them engage in more blended finance transactions. Furthermore, concrete law and regulation changes should be considered to the use of collateral, both physical and non-physical, by SMEs in developing countries, as to ensure SMEs will become more capable of engaging in loans with banks, which could then be supported by public investors in various blended finance arrangements. It is finally recommended that further research is done on this topic, especially at a larger scale and perhaps slightly into the future, when more projects will have been completed and therefore results will have become clearer. This could further explore the effectiveness of blended finance compared to other investment methods, and if found to be more effective, convey this to private parties. If these measures are to be taken and the knowledge on blended finance is expanded, it stands to reason that blended finance could be one of the tools to reduce the investment gap in sustainable development and aid in the creation of jobs in developing countries, where people need these most.

Economic growth, especially after the financial crisis of 2008, has been declining in many OECD nations. Declining economic growth has negative effects including a lower rate of productivity growth, stagnating standards of living, increases in income inequality etc. Many economists believe that stagnating fixed business investment is one of the key causes of the observed secular decline in economic growth. Hence, it is important to understand what drives business investment and how we can improve it, thereby, improving the economic growth. Thus, the objective of this thesis which is to understand the determinants of fixed investment that affects economic growth is important not only for policy-makers but also for corporations, shareholders, and workers.

In this thesis, we have analyzed the determinants of stagnating business investment in the European economies of the Netherlands and Germany using an accelerator-type model augmented with variables that measure financial constraints, business environment, labour market and network sectoral regulations. Our results show that fixed business investment as a share of GDP in the Netherlands is mainly affected by demand growth, financial constraints, uncertainty and energy prices. In case of Germany, fixed business investment is mainly affected by unemployment rate, term spreads, energy prices and regulations of the network sectors. We see that while demand is found to be statistically significant in explaining decline in business investment in the Netherlands, it is not found to be statistically significant in case of Germany. We found that business investment can be stimulated by increase in demand, real net profits of the firms, network sector regulations or by a decrease in uncertainty, energy prices, term spreads and unemployment rates considering both the Dutch and German economies. Increase in fixed component of intangible investment or decrease in level of financialization can also help in boosting business investment for these two economies.

Based on the empirical findings and literature, we looked into what lessons we can derive from a policy-making perspective. We believe that expansionary macroeconomic policies can most likely help both the Dutch and German economies to stimulate business investment. Finally, this thesis also addresses various reflections in terms of scope for further research. For instance, inclusion of firm-level variables in empirical analysis or using different measures for robustness checks are some of the aspects that can be reflected upon and used in future research.

In the face of environmental challenges of unprecedented scale and urgency, the European Commission enacted in 2019 a new comprehensive growth strategy with the aim of reaching net zero greenhouse gas emissions in 2050. Named as the European Green Deal, this strategy includes energy, biodiversity, pollution, and climate adaptation targets, and envisages that all EU actions and policies will contribute to its objectives. However, to date, specific actions addressing biodiversity, climate adaptation, and health issues from within the energy sector are still missing or lagging behind. This research proposes a new form of Renewable Energy Community (REC), which combines the use of solar photovoltaic panels with green, namely vegetated, roofs to address multiple Green Deal’s objectives. First, this form of REC was grounded in the current European legislation so to ensure its eligibility for the support schemes that Member States are currently required to devise. Next, the costs and benefits of this REC were determined with value transfer for a case study in Esch-sur-Alzette (Luxembourg) and a probabilistic cost-benefit analysis (CBA) was conducted. By applying Scenario Discovery, the CBA was simulated under different combinations of input parameters and rather than only providing multiple net present values (NPVs), the ranges of input values resulting in desirable NPVs were determined. As a result, the conditions under which the photovoltaic-green roof energy community becomes economically convenient were determined, providing guidance to national policymakers designing RECs’ incentive schemes at present.

After the U.S. financial crisis in 2008, shadow banking business in China has shown rapid development. Shadow banking refer to credit intermediary involving financial entities and financial activities outside the traditional banking regulatory system. The shadow banking system in western countries represented by the United States is mainly based on securitization and various types of financial derivatives. Different from the shadow banking system in Western countries, the shadow banking activities in China mainly revolve around commercial banks, so it can also be called commercial bank-centric shadow banking system. This master thesis first looks at the development history of Chinese shadowbanking system, identifying two different phases of Chinese shadow banking system development. Then an overall picture of how the Chinese shadow banking system is constituted is given, covering the main components within the shadow banking system. Further, this master thesis investigates the operation model of commercial bank-centric shadow banking system. As the two most important operation models, commercial bank wealth management business and interbank business are elaborated in this thesis. Besides, the main risks of the shadow banking business and the mechanisms of risk generation, transmission and amplification are also discussed. Based on the highly risky characteristics of shadow banking business, the current regulatory measures of Chinese financial regulators over the past 10 years are summarized and classified based on different regulation purposes. In addition to the above qualitative analysis, this thesis constructs a panel data set based on the annual report and financial report data of 146 listed commercial banks in China from 2010 to 2020, as well as the regulatory data in the past 10 years, and conducts an econometric empirical analysis to investigate the correlation between commercial banks’ shadow banking business scale, regulatory intensity and commercial banks’ default risk. The findings show that as the scale of commercial banks’ shadow banking business increases, the default risk of commercial banks increases; conversely, as the intensity of financial regulation increases, the default risk of commercial banks decreases accordingly. Finally, based on the qualitative and quantitative analysis results, this thesis provides feasible suggestions for future regulation of Chinese shadow banking system, while reflecting on the research methods applied in this paper and providing possible improvement points for further research.

Baumol's unbalanced growth model predicts the tendency of aggregate productivity growth to slow down in the process of tertiarisation. This thesis studies the relationship between employment structural changes and aggregate productivity growth in the case of China. William Nordhaus’s (2008) testing methodology will be applied to the China Industrial Productivity (CIP) Database that follows the KLEMS principles. The results suggest that there is a significant sign of Baumol’s cost disease in China during 1987-2010. Moreover, with more and more workers tolerating lower pay in the stagnant sectors, aggregate demand growth in the market will slow down. Eventually, the unbalanced growth may lead to economic stagnation. Hence, it is necessary to intervene in income distribution through fiscal and monetary policies to make the workers in the stagnant industries benefit from the technological progress.