placestats

Frequent prayer vs. Informal employment

Fades after adjusting for income

A country is not a person. Countries where more people are counted as belonging to this group also tend to differ on the other measure, and that is all. It does not follow that the people in the group are the people with the different score. Making that leap is called the ecological fallacy: reading a pattern across places as a fact about individual people. It is the most common misuse of this kind of data. Religion also varies strongly with region, history and national income, so much of what looks religious here is really those. That is what the adjusted figures are for. The religion shares are estimates for two years only, and the survey questions are asked in rounds that can be ten years apart.

Across 55 countries, Frequent prayer and Informal employment rise and fall together at r = +0.72 (on a scale from −1 to +1, where 0 means no link). Comparing only countries with similar income (GDP per person) shrinks it to +0.29, which could easily be chance (q = 0.15, allowing for the many pairs tested, and allowing for countries in the same region being alike). So the first figure mostly shows richer countries differing from poorer ones, not a link between these two things.

Comparing countries across the middle half of frequent prayer, 39% to 83.7% of respondents, informal employment is worse by 36.5% of employment at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 11.3% of employment.

Link before adjusting (r)+0.716p = 8.0e-10 · 55 countries
After adjusting for national income+0.294p = 0.031 · likely range [+0.03, +0.52]
p, allowing for regions0.036standard error 0.103 · 6 regions
Check for luck (q)0.151across 12,497 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.

Frequent prayer · % of respondentslink with income -0.68 · high
Informal employment · % of employmentlink with income -0.88 · proxy

Both of these rise and fall closely with national income, so a strong link between them before adjusting was close to certain. Read the adjusted figure, not the first one.

“Link with income” is how closely each measure tracks GDP per person across countries, from −1 to +1.

Every country as a dot

Frequent prayer · % of respondents →Informal employment · % of employment →11.6%98.4%0.7%93.1%Argentina: 54% of respondents, 51.6% of employmentArmenia: 71.7% of respondents, 76.1% of employmentBangladesh: 78% of respondents, 84% of employmentBolivia: 82.7% of respondents, 83.9% of employmentBrazil: 77.4% of respondents, 35.6% of employmentChile: 37.4% of respondents, 26.4% of employmentColombia: 87.9% of respondents, 56% of employmentCyprus: 69.4% of respondents, 1.68% of employmentCzechia: 13.8% of respondents, 2.26% of employmentGermany: 30.2% of respondents, 2.49% of employmentEcuador: 82.9% of respondents, 68.5% of employmentEgypt, Arab Rep.: 96.6% of respondents, 68.6% of employmentSpain: 20.2% of respondents, 2.2% of employmentEstonia: 12.4% of respondents, 2.4% of employmentEthiopia: 94.9% of respondents, 77.7% of employmentUnited Kingdom: 24.1% of respondents, 6.51% of employmentGeorgia: 60.6% of respondents, 51.5% of employmentGhana: 95.5% of respondents, 78% of employmentGreece: 66.4% of respondents, 3.58% of employmentGuatemala: 73.2% of respondents, 75.9% of employmentHaiti: 95.4% of respondents, 91.6% of employmentIndonesia: 95.3% of respondents, 81% of employmentIndia: 68.4% of respondents, 88.1% of employmentIraq: 84.1% of respondents, 67.6% of employmentJordan: 86.9% of respondents, 55.1% of employmentKenya: 93.3% of respondents, 86.5% of employmentKyrgyz Republic: 68.3% of respondents, 57.5% of employmentKorea, Rep.: 19% of respondents, 29.1% of employmentLebanon: 80.9% of respondents, 55.5% of employmentMaldives: 93.5% of respondents, 47.3% of employmentMexico: 71.9% of respondents, 56.4% of employmentMyanmar: 83.3% of respondents, 80.7% of employmentMongolia: 17.8% of respondents, 27.1% of employmentNigeria: 98.4% of respondents, 93.1% of employmentNicaragua: 76.3% of respondents, 81.8% of employmentNetherlands: 23% of respondents, 2.63% of employmentPakistan: 89.8% of respondents, 88.7% of employmentPeru: 66.6% of respondents, 70.5% of employmentPoland: 63.2% of respondents, 8.62% of employmentWest Bank and Gaza: 90.5% of respondents, 48.8% of employmentRomania: 65.2% of respondents, 2.21% of employmentRussian Federation: 27% of respondents, 19.3% of employmentRwanda: 73.7% of respondents, 84.3% of employmentSerbia: 28.7% of respondents, 17.8% of employmentSlovak Republic: 41.5% of respondents, 4.37% of employmentSlovenia: 22.5% of respondents, 0.7% of employmentSweden: 18.3% of respondents, 2.83% of employmentThailand: 41.4% of respondents, 63.2% of employmentTajikistan: 67.6% of respondents, 63.6% of employmentTunisia: 76.5% of respondents, 36.9% of employmentTurkiye: 71% of respondents, 27.7% of employmentUruguay: 40.6% of respondents, 28.5% of employmentViet Nam: 11.6% of respondents, 67% of employmentSouth Africa: 73.6% of respondents, 34.8% of employmentZimbabwe: 94.2% of respondents, 85% of employmentCYPCZEESTGRCHTIINDKENNGAROUSWETHAVNM

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted+0.7168.0e-1055
By rank (Spearman), not adjusted+0.7177.1e-1055
Standard (Pearson), adjusted for national income+0.2940.03155
By rank (Spearman), adjusted for national income+0.2540.06455

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 55 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: +0.422 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from +0.257 (without IDN) to +0.375 (without VNM). 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: VNM (+0.081).

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.

nr
Europe & Central Asia20+0.29
Latin America & Caribbean12+0.33

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.

nr
Poorest third19+0.22
Middle third18+0.31
Richest third18-0.10

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.

nr
Christians32+0.32
Muslims14+0.54

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.

nr
United Kingdom14+0.29

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 = +0.294 after dropping 0 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 respondents
% of employment		Years
Nigeria NGA98.4%93.1%2022, 2024
Egypt, Arab Rep. EGY96.6%68.6%2022, 2024
Ghana GHA95.5%78%2014, 2015
Haiti HTI95.4%91.6%2014, 2012
Indonesia IDN95.3%81%2022, 2023
Ethiopia ETH94.9%77.7%2022, 2021
Zimbabwe ZWE94.2%85%2022, 2024
Maldives MDV93.5%47.3%2022, 2019
Kenya KEN93.3%86.5%2022, 2019
West Bank and Gaza PSE90.5%48.8%2014, 2025
Pakistan PAK89.8%88.7%2022, 2025
Colombia COL87.9%56%2022, 2025
Jordan JOR86.9%55.1%2022, 2023
Iraq IRQ84.1%67.6%2022, 2021
Myanmar MMR83.3%80.7%2022, 2020

Haerpfer, C. et al., World Values Survey; EVS, European Values Study
United Nations Global SDG Indicators Database; series compiled by the International Labour Organization (8.3.1) and the UN Office on Drugs and Crime (16.3.2)

Sources

Frequent prayer

Share praying at least several times a week

World Values Survey Association and European Values Study · via Our World in Data · Free for non-commercial use with attribution · updated irregular (survey waves, roughly every 5 years)

Private practice. Attendance is public practice, and importance is belief. The three can differ: a country can pray often and attend rarely. Asked only from the 2014 wave on, so it covers about eighty countries. No "better" direction is set, for the same reason as attendance.

Informal employment

Share of employment that is informal

International Labour Organization · via Our World in Data · CC BY 3.0 IGO · updated annual

Workers with no contract, no social protection or no registered employer, as the ILO (the UN's labour agency) makes them comparable across national labour force surveys. The World Bank's copy of this series was retired, so it comes from the UN's database for the Sustainable Development Goals.

How this was computed

Data used: most recent value in 2010-2025; values come from 2012–2025. 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 6 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 Frequent prayer and Informal employment

This page shows that two measures go together. It does not show that Frequent prayer changes Informal employment, or the reverse. These figures also describe countries, not individual people. See the ecological fallacy.

More links with Frequent prayer or Informal employment