Income Inequality in Belgium

 The sources outline a transition from traditional survey-based analysis to a more comprehensive Distributional National Accounts (DINA) methodology to study income inequality in Belgium between 1985 and 2022. This shift is necessitated by the fact that standard household surveys often fail to capture the "entire income pie," particularly at the upper end of the distribution, leading to a "stable inequality" narrative that the DINA approach challenges.

The Core Methodology: Distributional National Accounts (DINA)

The DINA methodology seeks to reconcile the discrepancy between micro-level distributional information (surveys and tax records) and macroeconomic aggregates (National Accounts). While household surveys typically focus on disposable income, DINA aims to distribute the total Net National Income (NNI) among the population.

The sources define four distinct DINA income concepts to track inequality at different stages of the economic flow:

1. Pre-tax factor income (DINA1): Income before any taxes, social contributions, or benefits, representing payments to labor and capital.
2. Pre-tax post-replacement income (DINA2): Adjusts factor income for social benefits that act as income replacements, such as pensions and unemployment benefits.
3. Post-tax disposable income (DINA3): Subtracts all remaining taxes and adds remaining cash social benefits.
4. Post-tax national income (DINA4): Adds in-kind benefits (health, education) and collective consumption (police, defense), returning the total to the NNI aggregate.

Integrating and Correcting Microdata

To inform these accounts, the researchers utilize three major Belgian surveys: the Socio-Economic Panel (SEP), the European Community Household Panel (ECHP), and EU Statistics on Income and Living Conditions (EU-SILC). However, because surveys suffer from nonresponse and misreporting by wealthy households, the methodology incorporates several "top corrections":

• Top Earnings Adjustment: Administrative tax records (IPCAL) are used to adjust the top of the earnings distribution. Using the "BFM-method" (Blanchet, Flores, and Morgan), researchers reweight and replace survey observations above an endogenously determined "merging point" to ensure the top is accurately represented.
• Wealth and Capital Income Imputation: Because surveys like EU-SILC poorly cover financial income, the researchers use Predictive Mean Matching (PMM) to link EU-SILC with the Household Finance and Consumption Survey (HFCS). This allows for a more granular distribution of capital assets.
• Missing Wealthy Correction: A Pareto model is employed to account for the "missing wealthy" who are absent even from wealth surveys, further refining the distribution of capital income.

Linking Macro and Micro Levels

The methodology involves mapping every component of NNI to a conceptual counterpart in the microdata. When components match well (e.g., wages), the survey values are simply rescaled to match the macro total. For components without a direct survey counterpart, such as undistributed profits, the methodology distributes them based on proxies like stock ownership or financial capital income.

To maintain international comparability, the sources advocate for a "broad equal-split" scenario. In this approach, total household income is divided equally among all adults (aged 20+) in the household, rather than using traditional equivalence scales.

Contextual Impact: A New Narrative

This methodological rigor changes the understanding of Belgian inequality. While survey data suggested a stable or decreasing trend, the DINA approach reveals a rise in income inequality following the financial crisis. By decomposing the Gini coefficient by income source, the researchers identified that this rise is driven primarily by shifting capital income, specifically the growth of dividends and undistributed profits relative to more widely distributed interest earnings.

The key findings in the sources challenge the long-standing narrative that Belgium is an "exception" to the global trend of rising income inequality. While traditional survey data suggest that inequality in Belgium has remained low and stable—or even decreased over the last twenty years—the application of the Distributional National Accounts (DINA) methodology reveals a significant, previously unobserved increase in inequality following the financial crisis.

1. The Divergence from Survey Data

The most striking finding is the discrepancy between survey-based results and the DINA results.

• Survey Narrative: According to EU-SILC survey data, the Gini coefficient for equivalised disposable household income actually decreased from 26.7 in 2003 to 24.5 in 2022.
• DINA Reality: The macro-aligned DINA series shows that both the level and trend of inequality are higher and more volatile. Specifically, from 2013 onwards, the alignment of microdata with National Accounts aggregates reveals a marked increase in income inequality, diverging sharply from the "stable" trend reported in earlier empirical evidence.

2. Rising Pre-Tax Inequality (DINA1)

The sources indicate a robust increase in pre-tax factor income inequality (DINA1), which represents income before any government redistribution.

• Between 2008 and 2022, the Gini coefficient and the top 10% income share both increased by 8 percentage points.
• While labor income inequality has remained relatively stable, it is the primary driver of the level of inequality due to its 70% share of total income. However, the trend of increasing inequality is fueled by capital.

3. Capital Income as the Primary Driver

The most significant finding regarding the shift in Belgian inequality is the changing composition of capital income.

• Collapse of Interest Income: Income from fixed-rate assets and savings accounts, which is more widely distributed across the population, has effectively vanished as a major income source. Its share of total capital income dropped from 17.9% in 2009 to just 1.6% in 2019.
• Growth of Concentrated Capital: Conversely, more unequally distributed components, such as dividends and undistributed profits, have increased significantly. Undistributed profits tripled between 1985 and 2022, with its share of Net National Income (NNI) rising from 7.7% to 12.6%.
• Concentration at the Top: Detailed analysis shows that the top 10% of the capital income distribution receives approximately 98% of all undistributed profits.

4. The Role and Limits of Redistribution

The findings highlight that the Belgian welfare state actively buffered rising inequality for several years before the "dam" broke.

• Postponed Rise: While pre-tax inequality began rising in 2008, the increase in post-tax disposable income (DINA3) did not manifest until 2013. This suggests that the tax and benefit system "worked harder" to offset the rising factor inequality during the immediate aftermath of the financial crisis.
• The Turning Point: After 2013, the continued rise in pre-tax inequality was no longer offset by a corresponding increase in redistribution, leading to the observed rise in post-tax inequality.

5. Robustness Through "Top Corrections"

By incorporating administrative tax records (IPCAL) and wealth surveys (HFCS), the researchers confirmed that their findings were robust and that standard surveys were "missing the rich".

• These "top corrections" (adjusting for the top 1% and the missing wealthy) confirm the rising trend but at a much higher overall level of inequality than previously estimated.
• This granular data confirms that the decline of fixed-interest income and the rise of undistributed profits are the "smoking guns" behind the recent surge in Belgian inequality.

The sources analyze income inequality in Belgium through a detailed sectoral and component-based decomposition, revealing that while labor income defines the level of inequality, structural shifts within the corporate sector and capital income components drive the recent rising trend.

Sectoral Analysis: The Retreat of the Household Sector

The Belgian economy is divided into five institutional sectors: non-financial corporations (S11), financial corporations (S12), general government (S13), households (S14), and non-profit institutions (S15). A primary finding of the sectoral analysis is the declining share of the household sector in the total "income pie".

• Shrinking Household Share: In 1985, the primary income of the household sector (S14) accounted for 91.9% of Net National Income (NNI); by 2022, this share had dropped to 77.5%.
• Corporate Growth: This decline is mirrored by the rapid growth of the non-financial corporate sector (S11), which grew at an annual rate of 3.5%, significantly outpacing the household sector's 1.4% growth.
• Government Sector Dynamics: The government sector's (S13) share of primary income also increased, largely due to a spectacular decline in interest payments on government debt, which boosted its net primary income balance,.

Component Analysis: The Divergence of Labor and Capital

The sources decompose NNI into labor income, mixed income for the self-employed, and various forms of capital income (rents, interest, dividends, and undistributed profits),.

• Labor Income (The Level): Employee compensation remains the dominant income source, representing roughly 60-70% of NNI,. Because of its massive share, labor income is the primary factor explaining the overall level of inequality,. However, labor income inequality has remained relatively stable over the period.
• Capital Income (The Trend): While labor income is stable, capital income is the driving force behind the rise in inequality observed after the financial crisis,.
• The Internal Shift in Capital: A critical "component shift" occurred within capital income. Interest income, which is more widely distributed across the population, effectively vanished, dropping from 17.9% of total capital income in 2009 to just 1.6% in 2019.
• Concentrated Profits: Conversely, undistributed profits and dividends—which are highly concentrated at the top of the distribution—increased significantly,. Undistributed profits tripled between 1985 and 2022, growing from 7.7% to 12.6% of NNI,.

Structural Impact on Inequality

This component analysis explains why traditional surveys missed the rising inequality: surveys primarily track labor and realized interest, failing to capture the surge in undistributed corporate profits,. The DINA methodology reveals that the top 10% of the distribution receives approximately 98% of all undistributed profits, meaning the recent growth in the corporate sector (S11 and S12) has almost exclusively benefited the wealthiest Belgians.