Corporate tax rate vs. Migrant share of population
Fades after adjusting for income
Across 86 countries, Corporate tax rate and Migrant share of population rise and fall together at r = -0.52 (on a scale from −1 to +1, where 0 means no link). Comparing only countries with similar income (GDP per person) leaves r = -0.40, which could easily be chance (q = 0.14, allowing for the many pairs tested, and allowing for countries in the same region being alike). Caution: correlation moves sharply once outliers are trimmed.
Comparing countries across the middle half of corporate tax rate, 18.1% to 28% of profit, migrant share of population is 9.36% of population lower at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 6.39% of population.
How to read these.r runs from −1 (one goes up as the other goes down) to +1 (they rise together), and 0 means no link. Adjusting for national income means comparing countries with the same GDP per person, so differences in wealth can’t explain the link. Income is used in percentage terms, since an extra $1,000 means more to a poor country than to a rich one. p is how likely a link this strong would be if there were really none. Below 0.05 means it is unlikely to be chance. Very small values are written in short form: 1.1e-32 means a decimal point followed by 31 zeros and then 11, so very close to zero. The likely range is where the true figure probably lies, and a range that crosses zero means the link could easily be chance. Countries in the same region tend to resemble each other, so the third figure allows for that, which gives a fairer p. The standard error is the typical size of the error in r. Finally, testing this many pairs means some will look strong by luck alone. A q below 0.05 means this link is unlikely to be one of those.
“Link with income” is how closely each measure tracks GDP per person across countries, from −1 to +1.
Every country as a dot
best-fit line line after adjusting
Four ways to measure the link
| Method | r | p | Countries |
|---|---|---|---|
| Standard (Pearson), not adjusted | -0.521 | 2.8e-7 | 86 |
| By rank (Spearman), not adjusted | -0.391 | 0.000 | 86 |
| Standard (Pearson), adjusted for national income | -0.399 | 0.000 | 86 |
| By rank (Spearman), adjusted for national income | -0.192 | 0.078 | 86 |
The rank version uses only each country’s place in line, from lowest to highest, so a few extreme countries count for less. The adjusted and unadjusted versions use the same 86 countries: those that report both measures and GDP per person. So the gap between them comes from the adjustment, not from a change in which countries are counted. Drop in the size of r after adjusting: +0.122 (a minus sign means it grew).
How solid is it?
Leaving out one country at a time, r ranges from -0.432 (without MLT) to -0.335 (without TCA). The bar above shows that range on a scale from −1 to +1, with the solid line at the full result. The single country that moves r most: TCA (+0.064).
- correlation moves sharply once outliers are trimmed
- sign flips once outliers are trimmed
- direction is not consistent across regions
Within each region
Countries are not separate, unrelated cases, and neighbors share a lot. A link that holds inside each region is far more believable than one that shows up only when comparing regions.
| n | r | ||
|---|---|---|---|
| East Asia & Pacific | 13 | -0.59 | |
| Europe & Central Asia | 33 | -0.09 | |
| Latin America & Caribbean | 15 | -0.53 | |
| Sub-Saharan Africa | 13 | +0.32 |
By income third
If the link shows up only in the richest third of countries, it is a feature of rich countries, not a general pattern.
| n | r | ||
|---|---|---|---|
| Poorest third | 29 | -0.12 | |
| Middle third | 28 | -0.36 | |
| Richest third | 29 | -0.56 |
By largest religious group
Countries grouped by a label they share, such as main religion, rather than by a number. Groups of fewer than twelve countries are not shown. These groups differ in income, region and history all at once. So a gap between them is a place to start asking questions, not an answer.
| n | r | ||
|---|---|---|---|
| Christians | 53 | +0.23 | |
| Muslims | 14 | -0.80 |
By last european coloniser
Countries grouped by a label they share, such as main religion, rather than by a number. Groups of fewer than twelve countries are not shown. These groups differ in income, region and history all at once. So a gap between them is a place to start asking questions, not an answer.
| n | r | ||
|---|---|---|---|
| United Kingdom | 23 | -0.45 |
Without outliers (countries far outside the middle half of countries on either measure, by more than one and a half times the width of that middle half): r = +0.048 after dropping 11 countries.
Two series, one country
Both measures over the years for one country you pick. The two charts are stacked so they share only the years along the bottom.
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Over time, within countries
Everything above compares countries with each other at one moment. This section compares each country only with itself over 0years. So a link here can’t come from anything about a country that stays the same, such as its history, geography, institutions or culture.
Not enough history inside each country to look at this over time. That needs countries measured for several years in a row, and at least one of these measures is measured too rarely.
The data
% of profit | % of population | Years | |
|---|---|---|---|
| India IND | 48.3% | 0.3% | 2018, 2024 |
| Malta MLT | 35% | 37% | 2018, 2024 |
| Congo, Dem. Rep. COD | 35% | 1% | 2018, 2024 |
| France FRA | 34.4% | 13.8% | 2018, 2024 |
| Brazil BRA | 34% | 0.7% | 2018, 2024 |
| Portugal PRT | 31.5% | 10.8% | 2018, 2024 |
| St. Vincent and the Grenadines VCT | 30% | 4.8% | 2018, 2024 |
| Seychelles SYC | 30% | 10.2% | 2018, 2024 |
| Senegal SEN | 30% | 1.5% | 2018, 2024 |
| Nigeria NGA | 30% | 0.6% | 2018, 2024 |
| Mexico MEX | 30% | 1.3% | 2018, 2024 |
| Kenya KEN | 30% | 1.8% | 2018, 2024 |
| Gabon GAB | 30% | 17.7% | 2018, 2024 |
| Australia AUS | 30% | 30.4% | 2018, 2024 |
| Argentina ARG | 30% | 4.3% | 2018, 2024 |
OECD databases as named on each indicator: PISA, Social Expenditure Database (SOCX), Income Distribution Database, Development Assistance Committee statistics, Family Database, Government at a Glance, Corporate Tax Statistics, employment and environment statistics
World Bank, World Development Indicators
Sources
Corporate tax rate
Combined statutory corporate income tax rate
OECD · via Our World in Data · CC BY 4.0 (OECD terms and conditions) · updated annual, except the snapshots noted per indicator
The headline tax rate on company profits, national and local combined, for over ninety countries and territories. That is the widest coverage of any OECD series here. It is the rate written in law, not the rate firms actually pay after allowances and tax avoidance. From a 2019 release kept as a snapshot, so the series ends in 2018. No "better" direction is set.
Migrant share of population
International migrant stock (% of population)
UN Population Division, International Migrant Stock · CC BY 4.0 · updated quarterly
People living outside the country they were born in, as a share of the population. It counts people at one moment, while the net migration already on the site counts moves over a year. Published every five years until 2020, and for 2024.
How this was computed
Data used: most recent value in 2010-2025; values come from 2018–2024. To adjust for income, each measure is first predicted from GDP per person (in percentage terms, on a log scale) with a straight-line fit. Only what is left over is then compared. This is called a partial correlation. The line is drawn the standard way (ordinary least squares), which picks the line that comes closest to all the countries at once. The error margins allow for countries in the same region resembling each other, using 7 World Bank regions. The q-value corrects for testing all 12,497 pairs at once, using the Benjamini–Hochberg method. Underlying data last updated DYB 2024. How the country data works · explore Corporate tax rate and Migrant share of population
This page shows that two measures go together. It does not show that Corporate tax rate changes Migrant share of population, or the reverse. These figures also describe countries, not individual people. See the ecological fallacy.
More links with Corporate tax rate or Migrant share of population
- Migrant share of population vs Urbanization before +0.57 → after adjusting +0.32
- Informal employment vs Migrant share of population before -0.60 → after adjusting -0.24
- Migrant share of population vs Regulatory quality before +0.56 → after adjusting +0.19
- Corruption Perceptions Index vs Migrant share of population before +0.51 → after adjusting +0.18
- Migrant share of population vs Vulnerable employment before -0.56 → after adjusting -0.15
- HDI vs Migrant share of population before +0.53 → after adjusting -0.09
- Life expectancy vs Migrant share of population before +0.52 → after adjusting +0.07
- Government effectiveness vs Migrant share of population before +0.52 → after adjusting +0.07