In comparative studies on income inequality, Belgium frequently stands out as an exception: the level of inequality is low and has not increased over the last few decades, contrasting with the experiences of many other Western countries. In this paper, we apply the methodology of the Distributional National Accounts to reconsider the evolution of income inequality in Belgium between 1985 and 2022. Our findings underscore the impact of aligning the distributional information in microdata with national accounts aggregates. We unveil a previously unobserved rise in income inequality in the aftermath of the financial crisis. Through a decomposition by income source, it is ascertained that this rise in inequality is predominantly attributable to increasing capital income inequality, which in turn is due to a shifting composition of capital income. Specifically, the significance of interests from savings accounts and other fixed-rate assets has diminished significantly in comparison to dividends and undistributed profits.

Belgium exhibits a rather constant level of income inequality during the last decades, contrary to Germany, the United States and some Nordic countries, which have all faced substantial increases in inequality. We use the available income surveys from 1985 to 2020 to describe the evolution of income inequality by means of the Gini index. Earnings inequality has slightly decreased in the last two decades, at least if one takes into account the impact of the substantial increase in employment of, especially, older people and women. Though the education gap in earnings is widening, the rapid increase in (mostly female) education may have a dampening effect on earnings inequality. The income surveys largely underestimate financial capital incomes. Moreover, by definition, these do not cover undistributed profits of the corporate sector. When correcting for this, it turns out that pre-tax factor income inequality increased substantially between 2009 and 2016. The redistributive role of the welfare state through taxes has increased, while redistribution through the social security system exhibited a more irregular course. While there has been an increase in assortative matching in the last two decades, its impact on the evolution of income inequality is unclear.

Belgium exhibits a rather constant level of income inequality during the last decades, contrary to Germany, the United States and some Nordic countries, which have all faced substantial increases in inequality. We use the available income surveys from 1985 to 2020 to describe the evolution of income inequality by means of the Gini index. Earnings inequality has slightly decreased in the last two decades, at least if one takes into account the impact of the substantial increase in employment of, especially, older people and women. Though the education gap in earnings is widening, the rapid increase in (mostly female) education may have a dampening effect on earnings inequality. The income surveys largely underestimate financial capital incomes. Moreover, by definition, these do not cover undistributed profits of the corporate sector. When correcting for this, it turns out that pre-tax factor income inequality increased substantially between 2009 and 2016. The redistributive role of the welfare state through taxes has increased, while redistribution through the social security system exhibited a more irregular course. While there has been an increase in assortative matching in the last two decades, its impact on the evolution of income inequality is unclear.

In this article, we elicit the assumptions needed for an assessment of a joint reform of personal income and indirect taxes in a consistent conceptual framework. One often lacks an encompassing model for both labor supply decisions in real world tax and benefit contexts and the allocation of disposable income to commodities. We characterize households' labor supply decisions by a random utility random opportunity model of job choice. We illustrate the framework with a Belgian tax reform proposal that shifts the burden away from labor taxes to indirect taxation. We find substantial empirical evidence that, both from a distributional and from a budgetary perspective, it is important to account for the impact of indirect taxes on the labor supply decision of households. The cost recovery effects of the tax shift are negative. This is, among other things, explained by the income effect in our job choice model.

We use population-wide data from linked administrative registers to study the distributional pattern of mortality before and during the first wave of the Covid-19 pandemic in Belgium. Over the March-May 2020 study period, excess mortality is only found among those aged 65 and over. For this group, we find a significant negative income gradient in excess mortality, with excess deaths in the bottom income decile more than twice as high as in the top income decile for both men and women. However, given the high inequality in mortality in normal times, the income gradient in all-cause mortality is only marginally steeper during the peak of the health crisis when expressed in relative terms. Leveraging our individual-level data, we gauge the robustness of our results for other socioeconomic factors and decompose the role of individual vs. local effects. We provide direct evidence that geographic location effects on individual mortality are particularly strong during the first wave of the Covid-19 pandemic, channeling through the local number of Covid infections. This makes inference about the income gradient in excess mortality based on geographic variation misguided.

Empirical welfare analyses often impose stringent parametric assumptions on individuals’ preferences and neglect unobserved preference heterogeneity. In this paper, we develop a framework to conduct individual and social welfare analysis for discrete choice that does not suffer from these drawbacks. We first adapt the broad class of individual welfare measures introduced by Fleurbaey (2009) to settings where individual choice is discrete. Allowing for unrestricted, unobserved preference heterogeneity, these measures become random variables. We then show that the distribution of these objects can be derived from choice probabilities, which can be estimated nonparametrically from cross-sectional data. In addition, we derive nonparametric results for the joint distribution of welfare and welfare differences, as well as for social welfare. The former is an important tool in determining whether those who benefit from a price change belong disproportionately to those who were initially well-off. An empirical application illustrates the methods.

Meer dan een op drie werknemers leed in 2020 inkomensverlies door tijdelijke werkloosheid of door een terugval in inkomen uit flexi-jobs. Gemiddeld verloor een getroffen werknemer 15,1% aan bruto jaarinkomen. De verhoogde uitkeringen brachten dat verlies terug tot een daling van 3,1% in beschikbaar jaarinkomen (of € 858). Een langdurige terugval op tijdelijke werkloosheid zorgt voor grotere inkomensverliezen, ondanks de bijkomende premie voor langdurig tijdelijk werklozen. Het gebrek aan sociale bescherming van inkomen verworven onder het flexi-statuut drijft het inkomensverlies fors op. Voor werknemers die tijdelijk werkloos werden en een flexi-job zagen wegvallen, kan het verlies in beschikbaar inkomen zelfs oplopen tot 30%.

To find out how happy Belgians are, we must first dive deeper into the underlying question as to how concepts such as happiness and life satisfaction can actually be measured. We then examine what gives the average Belgian a high level of life satisfaction, and how satisfied he or she is with various facets of life.

We can now go one step further and examine what influences the health differences described in the previous chapter. This question often forms the subject of a loaded debate, as it is closely linked to the issue of the degree of individual responsibility for health problems. Biological factors naturally play an important role: it is obvious that ageing is accompanied by deteriorating health, for example. However, biological factors are not the main explanation for the health differences between different socio-economic groups. This chapter therefore discusses the impact of lifestyle, living environment and job characteristics on health. We then focus specifically on the health dimension of "emotional well-being". Finally, we place our results in a broader time perspective as it seems that health differences are partly determined by various characteristics of the parents.

Like many Western countries, Belgium has undergone major demographic changes in recent decades. Although many people still regard a two-parent family with children as the typical family, this family type only represents a relatively small proportion of the current demographic landscape and therefore of our sample. In Chap. 1, we already discussed the fact that the type of family in which a person lives affects his or her level of well-being. Before going into the various dimensions of well-being in more detail in the following chapters, it is therefore a good idea to examine in greater depth the composition of families.

In this book, we try to give a picture of the individual well-being of Belgians. We describe which aspects of life determine this well-being and how these aspects are distributed in Belgium. Particular attention is paid to the situation of Belgians who achieve the lowest levels of well-being, as well as the situation of specific groups such as children, the elderly and single-parent families.

Traditionally, economists have identified well-being with market command over goods rather than with the "state" of a person.The books in this series go precisely beyond the traditional concepts of consumption, income or wealth and offer a broad, inclusive view of inequality and well-being.

In Chapter 1, we already emphasised that a family's income—or the expenditure that a family can afford—is very important component of well-being. As explained in Chapters 4 and 5, income and expenditure do not fully coincide. In this chapter, we will discuss in more detail how Belgian families divide their expenditure between different categories of goods and services, as this offers an interesting view of their way of life.

In Chap. 10, we discussed the average spending patterns of different types of families. More specifically, we illustrated how the total expenditure on non-durable goods and services is divided between food, clothing or housing, for example. However, this distribution of the family's total expenditure between various different goods and services does not reveal who these goods are intended for. Nonetheless, this distribution of consumption within the family is crucial for the individual well-being of the family members. The MEQIN dataset enables various conclusions to be drawn about this distribution for Belgium.

On average, Belgians with a decent income, good health, a relationship and work are happier than others. So couldn't we simply use reported happiness as an indicator for steering or evaluating policy? If all citizens want to be happy, it would be very easy to make political decisions using an overall happiness score as a guiding policy indicator.

In an average class of twenty children, this means that four children are growing up in a family living below the poverty line. These figures often conceal a complex reality and a wide gap between the children growing up in poverty and the other children in the class. In this chapter, we will try to shed light on this gap for various different dimensions of well-being.

In Part II, we already gave several examples of pairwise correlations between poor scores for various dimensions of well-being (health and income, income and job quality, housing and health, etc.). In this chapter, we examine the correlation between three important dimensions of well-being (material welfare, health and housing) in a more systematic way.

As a result of the ageing population, the number of elderly people in our society is rising sharply. Most of them are no longer active on the labour market and therefore need to live on other sources of income. We are mainly referring to pensions here, as well as investment income. It is generally accepted that Belgian pensions for private sector employees are on the low side. Moreover, it is often assumed that pensions can only remain affordable if people work for a longer period on average. At the same time, the health status of the elderly tends to deteriorate, leading to higher care costs. Concerns about pensions and rising care costs are therefore causing concern about the future quality of life of the growing group of elderly people in our society.

Material welfare can be viewed from various different perspectives. Firstly, we can focus on disposable incomes. Disposable income is defined as the monthly net income from the work of all the family members together with benefits, transfers and pensions, as well as income from capital and investments. The greater the disposable income, the more material welfare can be acquired. We can also look at expenditure, i.e. the total amount of money spent each month on goods and services such as food, housing, clothing and transport. This expenditure represents the quantity of goods and services consumed: the higher the level of consumption, the greater the material welfare.