Do Electricity use per person and Government effectiveness go together across countries?

Across 189 countries the link before adjusting for anything is r = +0.63, on a scale from -1 (opposite) to +1 (in step). A version that uses only each country's rank gives +0.80.

Does the link hold within countries over time, not just across countries?

Comparing each country only with itself across 1996-2024, and setting aside what happened worldwide in each year, the link is +0.062 (198 countries, 4,739 country-years). Using year-to-year changes, it is +0.034.

Does Electricity use per person cause Government effectiveness?

This analysis cannot answer that. It shows only that the two go together. A link between two country measures, adjusted or not, does not show that either one changes the other. Country figures also say nothing about individual people.

Electricity use per person vs. Government effectiveness

Fades after adjusting for income

Across 189 countries, Electricity use per person and Government effectiveness rise and fall together at r = +0.63 (on a scale from −1 to +1, where 0 means no link). Comparing only countries with similar income (GDP per person) shrinks it to +0.21, which could easily be chance (q = 0.20, 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. Caution: direction is not consistent across regions.

Comparing countries across the middle half of electricity use per person, 734 to 5,744 kWh per person, government effectiveness is better by 0.539 points at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 0.132 points.

Link before adjusting (r)+0.628p = 3.8e-22 · 189 countries

After adjusting for national income+0.215p = 0.003 · likely range [+0.07, +0.35]

p, allowing for regions0.064standard error 0.095 · 7 regions

Check for luck (q)0.203across 13,797 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.

Electricity use per person · kWh per personlink with income +0.93 · proxy

Government effectiveness · index (approx. -2.5 to 2.5)link with income +0.85 · 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

best-fit line line after adjusting

Four ways to measure the link

Method	r	p	Countries
Standard (Pearson), not adjusted	+0.628	3.8e-22	189
By rank (Spearman), not adjusted	+0.800	1.9e-43	189
Standard (Pearson), adjusted for national income	+0.215	0.003	189
By rank (Spearman), adjusted for national income	+0.056	0.447	189

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 189 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: +0.413 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from +0.196 (without GUY) to +0.238 (without BHR). 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: BHR (+0.023).

Fragile: this link may not hold up.

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	27	+0.14
Europe & Central Asia	50	+0.21
Latin America & Caribbean	35	+0.22
Middle East, North Africa, Afghanistan & Pakistan	22	-0.12
Sub-Saharan Africa	46	+0.15

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	63	-0.08
Middle third	63	+0.14
Richest third	63	+0.15

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	110	+0.32
Muslims	50	+0.08

By last european coloniser

	n	r
France	25	+0.04
Never a European colony	21	+0.41
Spain	19	+0.37
United Kingdom	62	+0.10

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 = +0.277 after dropping 10 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 29years. 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 = +0.062, 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 electricity use per person moved did not tend to see their government effectiveness move with it.

Across countries (adjusted)+0.215for comparison

Within countries+0.129each country vs itself

…and vs the same year elsewhere+0.062q = 0.714 · 198 countries

Year-on-year changes+0.034q = 0.359

Read with care.

Almost all of this indicator's variation is between countries, not within them, so the within-country estimate rests on a small part of the data.

4,739 country-years (one country in one year), 198 countries, 1996–2024, about 24 years each on average. Share of the variation that happens within countries over time: 3% for Electricity use per person, 6% for Government effectiveness. 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): +0.062. 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.

This curve peaks at the edge of the window (lag -10), so it is still drifting where the search stops. That pattern usually reflects a slow trend left over in the data, not a link with real timing. The peak value should not be read as the “true” link at the right lag.

The data

	kWh per person	index (approx. -2.5 to 2.5)	Years
Iceland ISL	48,424	1.65	2024
Norway NOR	24,490	1.84	2025, 2024
Bahrain BHR	23,919	0.6	2024
Kuwait KWT	18,402	0.328	2025, 2024
Qatar QAT	18,030	1.13	2025, 2024
Canada CAN	16,090	1.76	2025, 2024
United Arab Emirates ARE	16,053	1.26	2024
Bhutan BTN	15,742	0.581	2024
Finland FIN	15,610	1.82	2025, 2024
Saudi Arabia SAU	13,385	0.783	2024
United States USA	13,061	1.36	2025, 2024
Sweden SWE	12,866	1.77	2025, 2024
Korea, Rep. KOR	12,090	1.49	2025, 2024
Brunei Darussalam BRN	12,016	0.835	2024
Greenland GRL	10,740	1.35	2024

Ember, Yearly Electricity Data; population from Our World in Data, with processing by Our World in Data
Kaufmann, D. and A. Kraay, Worldwide Governance Indicators, World Bank

Sources

Electricity use per person

Electricity demand per person (kWh)

Ember · via Our World in Data · CC BY 4.0 · updated annual

All the electricity a country uses in a year, divided by its population, in kilowatt-hours (kWh). One kWh runs a 100-watt bulb for ten hours. It counts the power made at home plus imports, minus exports, including the power lost in wires along the way. So it is a little higher than "consumption" figures that leave those losses out. Use per person ranges from under 100 kWh a year in parts of Africa to over 50,000 in Iceland, where aluminium smelters use most of it, so a few industries can set a small country's figure. It rises steeply with income, and is measured in percentage terms (on a log scale) where it is used for adjusting. No "better" direction is set: more electricity can mean more comfort and industry, or more waste.

Government effectiveness

Government Effectiveness (estimate)

World Bank · CC BY 4.0 · updated annual

How this was computed

Data used: most recent value in 2010-2025; values come from 2022–2025. 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 13,797 pairs at once, using the Benjamini–Hochberg method. Underlying data last updated DYB 2024. How the country data works · explore Electricity use per person and Government effectiveness

This page shows that two measures go together. It does not show that Electricity use per person changes Government effectiveness, or the reverse. These figures also describe countries, not individual people. See the ecological fallacy.