placestats

Old-age spending vs. Physicians

Holds up after adjusting for income

Across 42 countries, Old-age spending and Physicians rise and fall together at r = +0.57 (on a scale from −1 to +1, where 0 means no link). It holds up almost unchanged when only countries with similar income (GDP per person) are compared (r = +0.55, q = 0.0036, allowing for the many pairs tested).

Comparing countries across the middle half of old-age spending, 5.23% to 9.69% of GDP, physicians is better by 0.801 per 1,000 people at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 0.73 per 1,000 people.

Link before adjusting (r)+0.572p = 7.6e-5 · 42 countries
After adjusting for national income+0.553p = 0.000 · likely range [+0.30, +0.74]
p, allowing for regions5.8e-5standard error 0.031 · 5 regions
Check for luck (q)0.004across 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.

Old-age spending · % of GDPlink with income +0.17 · independent
Physicians · per 1,000 peoplelink with income +0.85 · proxy

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

Every country as a dot

Old-age spending · % of GDP →Physicians · per 1,000 people →1.87%13.7%1.696.58Australia: 4.46% of GDP, 4.09 per 1,000 peopleAustria: 13.2% of GDP, 5.51 per 1,000 peopleBelgium: 10.2% of GDP, 3.57 per 1,000 peopleBulgaria: 8.09% of GDP, 4.33 per 1,000 peopleCanada: 5.59% of GDP, 2.82 per 1,000 peopleSwitzerland: 6.32% of GDP, 4.48 per 1,000 peopleChile: 3.28% of GDP, 3.33 per 1,000 peopleColombia: 5.7% of GDP, 2.54 per 1,000 peopleCosta Rica: 4.58% of GDP, 2.69 per 1,000 peopleCzechia: 7.96% of GDP, 4.35 per 1,000 peopleGermany: 9.94% of GDP, 4.53 per 1,000 peopleDenmark: 9.27% of GDP, 4.5 per 1,000 peopleSpain: 10.3% of GDP, 4.29 per 1,000 peopleEstonia: 6.82% of GDP, 3.47 per 1,000 peopleFinland: 13% of GDP, 3.61 per 1,000 peopleFrance: 12.4% of GDP, 3.28 per 1,000 peopleUnited Kingdom: 7.41% of GDP, 3.3 per 1,000 peopleGreece: 13.6% of GDP, 6.58 per 1,000 peopleCroatia: 7.39% of GDP, 3.91 per 1,000 peopleHungary: 7.33% of GDP, 3.46 per 1,000 peopleIreland: 2.75% of GDP, 3.88 per 1,000 peopleIceland: 3.29% of GDP, 4.37 per 1,000 peopleIsrael: 4.92% of GDP, 3.8 per 1,000 peopleItaly: 13.7% of GDP, 4.19 per 1,000 peopleJapan: 8.29% of GDP, 2.65 per 1,000 peopleKorea, Rep.: 3.62% of GDP, 2.61 per 1,000 peopleLithuania: 6.44% of GDP, 4.47 per 1,000 peopleLuxembourg: 7.19% of GDP, 2.98 per 1,000 peopleLatvia: 7.82% of GDP, 3.4 per 1,000 peopleMexico: 5.11% of GDP, 2.59 per 1,000 peopleNetherlands: 7.19% of GDP, 3.88 per 1,000 peopleNorway: 8.43% of GDP, 4.97 per 1,000 peopleNew Zealand: 5.06% of GDP, 3.61 per 1,000 peoplePeru: 1.87% of GDP, 1.69 per 1,000 peoplePoland: 9.74% of GDP, 4.03 per 1,000 peoplePortugal: 11.1% of GDP, 5.85 per 1,000 peopleRomania: 8.18% of GDP, 3.63 per 1,000 peopleSlovak Republic: 7.15% of GDP, 3.7 per 1,000 peopleSlovenia: 9.55% of GDP, 3.37 per 1,000 peopleSweden: 10.1% of GDP, 4.41 per 1,000 peopleTurkiye: 4.88% of GDP, 2.24 per 1,000 peopleUnited States: 6.8% of GDP, 3.68 per 1,000 peopleAUSAUTFINFRAGRCIRLISLITAKORPERPRTTUR

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted+0.5727.6e-542
By rank (Spearman), not adjusted+0.4640.00242
Standard (Pearson), adjusted for national income+0.5530.00042
By rank (Spearman), adjusted for national income+0.4380.00442

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 42 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: +0.019 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from +0.466 (without GRC) to +0.600 (without FRA). 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: GRC (-0.086).

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 Asia30+0.44

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 third14+0.88
Middle third14+0.40
Richest third14+0.43

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
Christians35+0.54

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 = +0.436 after dropping 2 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 = +0.035, 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 old-age spending moved did not tend to see their physicians move with it.

Across countries (adjusted)+0.553for comparison
Within countries+0.409each country vs itself
…and vs the same year elsewhere+0.035q = 0.832 · 42 countries
Year-on-year changes-0.005q = 0.796
Read with care.
  • Much of the within-country association disappears once shared global year effects are removed, which points to a common worldwide trend rather than a country-level relationship.

1,138 country-years (one country in one year), 42 countries, 1990–2023, about 27 years each on average. Share of the variation that happens within countries over time: 18% for Old-age spending, 30% for Physicians. 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

0.20−0.2-100+10years Physicians trails Old-age spending →lag -10: r = 0.108 (n = 820)lag -9: r = 0.123 (n = 855)lag -8: r = 0.131 (n = 889)lag -7: r = 0.145 (n = 922)lag -6: r = 0.126 (n = 956)lag -5: r = 0.100 (n = 993)lag -4: r = 0.084 (n = 1,024)lag -3: r = 0.088 (n = 1,053)lag -2: r = 0.088 (n = 1,082)lag -1: r = 0.067 (n = 1,110)lag +0: r = 0.035 (n = 1,138)lag +1: r = 0.023 (n = 1,125)lag +2: r = 0.010 (n = 1,091)lag +3: r = -0.006 (n = 1,052)lag +4: r = -0.022 (n = 1,015)lag +5: r = -0.023 (n = 976)lag +6: r = -0.049 (n = 938)lag +7: r = -0.059 (n = 899)lag +8: r = -0.083 (n = 853)lag +9: r = -0.106 (n = 812)lag +10: r = -0.117 (n = 776)

Same year (lag 0): +0.035. 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 (+0.14 at lag -7) is higher than the same-year one by 0.11. 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 GDP
per 1,000 people		Years
Italy ITA13.7%4.192021, 2022
Greece GRC13.6%6.582021, 2022
Austria AUT13.2%5.512021, 2023
Finland FIN13%3.612021
France FRA12.4%3.282022
Portugal PRT11.1%5.852021, 2022
Spain ESP10.3%4.292021, 2022
Belgium BEL10.2%3.572021, 2022
Sweden SWE10.1%4.412021
Germany DEU9.94%4.532021, 2022
Poland POL9.74%4.032021, 2023
Slovenia SVN9.55%3.372021, 2022
Denmark DNK9.27%4.52021
Norway NOR8.43%4.972021, 2023
Japan JPN8.29%2.652022

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

Old-age spending

Public spending on old-age benefits

OECD · via Our World in Data · CC BY 4.0 (OECD terms and conditions) · updated annual, except the snapshots noted per indicator

Public pensions and other benefits for older people. It mostly reflects how old a country is and how its pensions are set up. That is why its strongest link is with the share of people aged 65 and over.

Physicians

Physicians (per 1,000 people)

World Health Organization · CC BY 4.0 · updated quarterly

Reported irregularly, so the latest value in the time window used is from a different year for different countries. Hospital beds, already on the site, have no "better" direction, since more beds is not plainly better. More doctors is closer to plainly better, so a direction is set on that basis.

How this was computed

Data used: most recent value in 2010-2025; values come from 2017–2023. 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 5 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 Old-age spending and Physicians

This page shows that two measures go together. It does not show that Old-age spending changes Physicians, or the reverse. These figures also describe countries, not individual people. See the ecological fallacy.

More links with Old-age spending or Physicians