Across 170 countries, Out of school, primary and Price level rise and fall together at r = -0.26 (on a scale from −1 to +1, where 0 means no link). Comparing only countries with similar income (GDP per person) flips the link to +0.12 (q = 0.036, allowing for the many pairs tested). The first figure pointed the other way only as richer and poorer countries differ. Caution: correlation moves sharply once outliers are trimmed.
Comparing countries across the middle half of price level, 0.341 to 0.691 ratio to the US, out of school, primary is better by 3.83% of primary-age children at the top of that range than the bottom. Comparing only countries with similar national income, the gap reverses, to 2.06% of primary-age children the other way.
Link before adjusting (r)-0.259p = 0.001 · 170 countries
After adjusting for national income+0.119p = 0.122 · likely range [-0.03, +0.27]
p, allowing for regions0.135standard error 0.069 · 7 regions
Check for luck (q)0.036across 18,622 pairs
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.
Out of school, primary · % of primary-age childrenlink with income -0.45 · moderate
Price level · ratio to the US (US = 1)link with income +0.72 · high
“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
-0.259
0.001
170
By rank (Spearman), not adjusted
-0.314
3.0e-5
170
Standard (Pearson), adjusted for national income
+0.119
0.122
170
By rank (Spearman), adjusted for national income
+0.056
0.473
170
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 170 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: +0.139 (a minus sign means it grew).
How solid is it?
Leaving out one country at a time, r ranges from +0.097 (without BRB) to +0.145 (without GNQ). 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: GNQ (+0.026).
Fragile: this link may not hold up.
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
18
-0.40
Europe & Central Asia
48
-0.30
Latin America & Caribbean
33
+0.12
Middle East, North Africa, Afghanistan & Pakistan
18
+0.05
Sub-Saharan Africa
44
+0.14
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
57
+0.15
Middle third
56
+0.17
Richest third
57
-0.19
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
100
+0.05
Muslims
44
+0.17
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
France
23
+0.25
Never a European colony
19
+0.53
Spain
19
-0.06
United Kingdom
52
+0.07
By official ideology
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
Nationalist
25
+0.20
No strong official ideology
107
-0.00
By party system
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
A few parties banned
22
-0.09
No parties banned
115
+0.07
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 = -0.089 after dropping 22 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 34years. So a link here can’t come from anything about a country that stays the same, such as its history, geography, institutions or culture.
Within countries over time, there is no link that is clearly more than chance (r = -0.021, comparing each country only with itself over the years, and each year only with the same year elsewhere). Whatever the cross-country picture shows, countries whose out of school, primary moved did not tend to see their price level move with it.
Across countries (adjusted)+0.119for comparison
Within countries+0.042each country vs itself
…and vs the same year elsewhere-0.021q = 0.809 · 168 countries
Year-on-year changes-0.018q = 0.212
3,314 country-years (one country in one year), 168 countries, 1990–2023, about 20 years each on average. Share of the variation that happens within countries over time: 20% for Out of school, primary, 26% for Price level. The margins of error allow for each country appearing many times, and for each year’s value being close to the year before.
Year-to-year changes are a cautious test, not a final answer. Looking only at changes from one year to the next removes each country’s own trends. But it also makes measurement mistakes louder, which pulls the results toward zero. A near-zero result here is weak evidence of no link, not proof.
With one measure years behind the other
Same year (lag 0): -0.021. A peak away from zero does not show which comes first. These series change slowly — this year’s value is close to last year’s. That makes the curve smooth and nearly symmetric, whatever produced the data. Even a sharp peak at one lag (a gap of some years) would not prove that one measure changes the other.
The largest value on this curve (-0.08 at lag +8) is higher than the same-year one by 0.06. That gap is not a finding. It is the largest of 21 closely related estimates, and picking the biggest of many tests always makes it look bigger. That is exactly why nothing on this site is ranked or chosen by lag.
The data
% of primary-age children
ratio to the US (US = 1)
Years
Equatorial Guinea GNQ
65.6%
0.449
2015, 2023
Sudan SDN
43.8%
0.265
2019, 2023
Cabo Verde CPV
41.8%
0.528
2022, 2023
Niger NER
40.4%
0.292
2024, 2023
Liberia LBR
38.3%
0.542
2022, 2023
Central African Republic CAF
37.9%
0.482
2012, 2023
Angola AGO
36.8%
0.385
2023
Burkina Faso BFA
34.3%
0.315
2024, 2023
Mali MLI
34%
0.294
2023
Kenya KEN
32.9%
0.316
2022, 2023
Lesotho LSO
32.2%
0.33
2024, 2023
Guinea-Bissau GNB
30.5%
0.394
2010, 2023
Gabon GAB
28.8%
0.489
2019, 2023
Curacao CUW
27.9%
0.81
2024, 2023
Honduras HND
26.6%
0.505
2024, 2023
World Bank, World Development Indicators Feenstra, Robert C., Robert Inklaar and Marcel P. Timmer (2015), "The Next Generation of the Penn World Table", American Economic Review, 105(10), 3150-3182, www.ggdc.net/pwt. Data: Penn World Table version 11.0, Groningen Growth and Development Centre, doi:10.34894/FABVLR.
UNESCO Institute for Statistics · CC BY 4.0 · updated quarterly
Children of primary-school age not enrolled at any level. Treated as measuring the same thing as gross primary enrolment, which is on the site. They are two ways of asking whether children are in school, so their agreement is not a finding.
Price level of household consumption, compared with the US (Penn World Table)
Groningen Growth and Development Centre, University of Groningen · via DataverseNL · CC BY 4.0 · updated irregular (new versions every few years)
How expensive the things households buy are in a country, compared with the US in the same year, when money is changed at the market exchange rate. A value of 0.5 means a typical basket of goods and services costs about half what it would in the US. Richer countries tend to be more expensive. It comes from the same price comparisons used to adjust GDP for what money buys, so it shares a building block with GDP per capita (PPP). Years in which the Penn World Table flags the price comparison as unreliable are left out. No "better" direction is set.
How this was computed
Data used: most recent value in 2010-2025; values come from 2010–2025. 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 18,622 pairs at once, using the Benjamini–Hochberg method. Underlying data last updated V-Dem v16; V-Party v2. How the country data works · explore Out of school, primary and Price level
This page shows that two measures go together. It does not show that Out of school, primary changes Price level, or the reverse. These figures also describe countries, not individual people. See the ecological fallacy.
More links with Out of school, primary or Price level