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.