The economics of inequality

Data sources and definitions

Dr. Matthias Schnetzer

October 21, 2022

Has inequality been rising lately?

What inequality do you mean exactly?

Illustrations by https://openpeeps.com.

How is income defined and how do we measure it?

Income concepts according to Canberra Group

ID Concept Aggregate
1 Income from employment 1a + 1b
  1a Employee income
  1b Income from self-employment
2 Property income
3 Income from household production
4 Current transfers received
5 Income from production 1 + 3
6 Primary income 1 + 2 + 3
7 Current transfers paid (taxes, fees, etc.)
8 Disposable income 6 + 4 - 7

Source: United Nations (2011), 11

System of National Accounts (SNA)

ID Concept
D.1 Compensation of employees
  D.11 Wages and salaries
  D.12 Employers social contributions
B.2G Operating surplus, gross
B.3G Mixed income, gross
D.4 Property income
  D.41 Interest
  D.42 Distributed income of corporations
  D.43 Reinvested earnings on foreign direct investment
  D.44 Investment income disbursements (e.g. insurances)
  D.45 Rent

Austrian tax law

ID Concept Description
1 Income from agriculture and forestry Farmers, forest managers
2 Income from self-employment E.g. Freelancers, Architects, Lawyer, Doctors, Consultants, CEO if she holds > 25%
3 Business income All other self-employed activities
4 Employee income Employees, retirees
5 Renting and lease of land Particularly renting of real estate properties
6 Property income Savings accounts, dividends (final taxation with capital income tax)
7 Other income Income from speculation, income from selling private property, etc.

Income data sources in Austria

Income Type Aggregate time series Long-term distribution Short-term distribution
Employee income WTD SSD WTD SSD WTD SSD SES EU-SILC HFCS
Self-employed ITD (IWITD) ITD (IWITD) EU-SILC HFCS
Property income CGT (ITD) EU-SILC HFCS
Transfers Various admin. sources EU-SILC HFCS
Disposable household income SNA HBS EU-SILC HFCS

Administrative and survey data sources: Wage tax data (WTD), Income tax data (ITD), Integrated wage and income tax data (IWITD), Social security data (SSD), Capital gains tax data (CGT), System of National Accounts (SNA), European Survey of Income and Living Conditions (EU-SILC), Household Finance and Consumption Survey (HFCS), Household Budgetary Survey (HBS), Structure of Earnings Survey (SES)

What is EU-SILC?

  • European Union Statistics on Income and Living Conditions (by Eurostat)
  • Harmonized sample survey in private households
  • Replaced European Community Household Panel (1994-2001) in 2003
  • Conducted in all EU member states and Switzerland, Norway, Iceland, Turkey, Serbia and Macedonia
  • Sample:
    • 🇦🇹 Stratified random sample from population register with approx. 6,000 households annually
    • 🇪🇺 approx. 135,000 households (use weights!)
  • Interview mode: CAPI/CATI
  • Rotating 4 year panel; Ad-hoc modules
  • Standard documentation for Austria:

Income data in EU-SILC

Individual level:

  • employee cash or near cash income
  • cash benefits or losses from self-employment
  • pension from individual private plans
  • unemployment benefits
  • old-age benefits
  • survivor benefits
  • sickness benefits
  • disability benefits
  • education-related allowances

Household level:

  • income from rental of a property or land
  • family/children related allowances
  • social exclusion not elsewhere classified
  • housing allowances
  • regular inter-household cash transfers received
  • alimonies received
  • interest, dividends, profit from capital investments in incorporated business
  • income received by people aged under 16

Note: Variables that use administrative data are highlighted.

Do income data from various sources fit together?

Administrative versus survey data

Impact on response behavior:

  • Social desirability
  • Sociodemographic characteristics
  • Survey design
  • Learning effect


Source: Angel et al. (2019)

Mean reverting errors

Source: Angel et al. (2019)

How do we explain the mismatch?

Source: Angel et al. (2019)

What about capital income?

Source: Ertl et al. (2022)

How do you measure personal income inequality?

Common properties of inequality measures

  • Anonymity principle: it does not matter who earns the income
  • Population principle: the absolute population size does not matter, only proportions do
  • Relative income (or scale) principle: Relative incomes matter, not the absolute levels
  • Dalton (or transfer) principle: A regressive transfer within the distribution increases inequality
  • Anonymity principle: In an economy composed of two people, Mr. Smith and Mrs. Jones, where one of them has 60% of the income and the other 40%, the inequality metric should be the same whether it is Mr. Smith or Mrs. Jones who has the 40% share
  • Population independence: The income inequality metric should not depend on whether an economy has a large or small population. An economy with only a few people should not be automatically judged by the metric as being more equal than a large economy with lots of people.
  • Scale principle: If every person’s income in an economy is doubled (or multiplied by any positive constant) then the overall metric of inequality should not change.
  • Dalton principle: In its weak form it says that if some income is transferred from a rich person to a poor person, while still preserving the order of income ranks, then the measured inequality should not increase. In its strong form, the measured level of inequality should decrease.

Reading recommenation: Cowell (2011)

Lorenz curve and Gini coefficient

Gini coefficient: \[\frac{A}{(A+B)} \in (0, 1)\]
Alternative: Half of the relative mean absolute difference \[G= \frac{\sum_{i=1}^{n}\sum_{j=1}^{n}|y_i - y_j|}{2n^2\bar{y}}\]

Alternative inequality measures

  • Shares
  • Ratios (point or share ratios, e.g. Palma ratio)
  • General Entropy (GE) measures:
    • Decomposable
    • Determine distance parameter \(\alpha\) (lower values put more weight on changes in lower tail; higher values at the top;)
    • \(\alpha = 0\): Theil‘s L (mean log deviation)
    • \(\alpha = 1\): Theil‘s T: \(\frac{1}{N} \sum_{i=1}^{N}\frac{y_i}{\bar{y}} ln\left(\frac{y_i}{\bar{y}}\right) \in (0; ln(N))\)
    • \(\alpha = 2\): Half the squared Coefficient of Variation (ratio of std. deviation to mean)

Income distribution in the National Accounts

National Accounts

Institutional sectors in the SNA

Ownership (S.11)
Non-financial corporations		 (S.12)
Financial corporations		 (S.13)
General government		 (S.14)
Households		 (S.15)
NPIs serving households
Public sector Public non-financial corporations Public financial corporations All government units and government NPIs
National private sector National private non-financial corporations National private financial corporations All households All NPIs serving households
Foreign-controlled sector Foreign-controlled non-financial corporations Foreign-controlled financial corporations

Note: The sectors presented in this table are domestic sectors (S.1). S.2 accounts for the rest of the world (RoW).

Income accounts in the SNA

Income accounts
Gross domestic product (GDP) at market prices (I)
- Consumption of fixed capital
= Net domestic product
(I)
+ Primary incomes receivable from the rest of world Rest of world
- Primary incomes payable to the rest of world Rest of world
= Gross national income (GNI) at market prices
- Consumption of fixed capital Depreciation
= Net national income at market prices
- Taxes on products Government
+ Subsidies on products Government
= Net national income at factor cost Production factors

Data for Austria (in billion Euro)

Gross domestic product  (MP) → Primary income with rest of world (ROW)
1 
Compensation of employees → Wage tax
21 
Compensation of employees → Social security cont. Employees
22 
Compensation of employees → Social security cont. Employers
31 
Gross domestic product  (MP) → Taxes on products – Subsidies
46 
Gross domestic product  (MP) → Consumption of fixed capital
66 
Net national income (FC) → Net operating surplus + mixed income
80 
Compensation of employees → Net wages and salaries
102 
Net national income (FC) → Compensation of employees
176 
Gross domestic product  (MP) → Net national income (FC)
256 
Gross domestic product  (MP)
370
Gross domestic product (MP)
Net national income (FC)
256
Net national income (FC)
Compensation of employees
176
Compensation of employees
Consumption of fixed capital
66
Consumption of fixed capital
Taxes on products – Subsidies
46
Taxes on products – Subsidies
Primary income with rest of world (ROW)
1
Primary income with rest of world (ROW)
Net operating surplus + mixed income
80
Net operating surplus + mixed income
Net wages and salaries
102
Net wages and salaries
Wage tax
21
Wage tax
Social security cont. Employees
22
Social security cont. Employees
Social security cont. Employers
31
Social security cont. Employers256.166.446.41175.880.3102.220.72230.8

Wage share = Compensation of Employees / Net national income at factor cost

Bibliography

Angel, Stefan/Disslbacher, Franziska/Humer, Stefan/Schnetzer, Matthias (2019). What did you really earn last year?: Explaining measurement error in survey income data. Journal of the Royal Statistical Society: Series A (Statistics in Society). DOI: 10.1111/rssa.12463
Cowell, Frank (2011). Measuring inequality. Oxford University Press.
Ertl, Michael/Humer, Stefan/Moser, Mathias/Schnetzer, Matthias (2022). The micro-macro gap in property incomes: Consequences for household income inequality. Journal of Income Distribution.
United Nations (2011). Canberra group handbook on household income statistics (2nd ed.). Geneva: United Nations.

PI 2159 Special Topics in Economic Policy | Winter term 2022/23

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The economics of inequality Data sources and definitions Dr. Matthias Schnetzer October 21, 2022

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  • The economics of inequality
  • Has inequality been...
  • How is income defined and how do we measure it?
  • Income concepts according to Canberra Group
  • System of National Accounts (SNA)
  • Austrian tax law
  • Income data sources in Austria
  • What is EU-SILC?
  • Income data in EU-SILC
  • Do income data from various sources fit together?
  • Administrative versus survey data
  • Mean reverting errors
  • How do we explain the mismatch?
  • What about capital income?
  • How do you measure personal income inequality?
  • Common properties of inequality measures
  • Lorenz curve and Gini coefficient
  • Alternative inequality measures
  • Income distribution in the National Accounts
  • National Accounts
  • Institutional sectors in the SNA
  • Income accounts in the SNA
  • Data for Austria (in billion Euro)
  • Bibliography
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