placestats

Capital per worker vs. Vulnerable employment

Holds up after adjusting for income

Across 165 countries, Capital per worker and Vulnerable employment rise and fall together at r = -0.73 (on a scale from −1 to +1, where 0 means no link). Comparing only countries with similar income (GDP per person) shrinks it to -0.12 (q = 0.029, allowing for the many pairs tested). Much of the first figure is that both measures rise with national income, but a very weak negative link remains.

Comparing countries across the middle half of capital per worker, $75,955 to $431,753, vulnerable employment is better by 27.2% of employment at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 3.9% of employment.

Link before adjusting (r)-0.735p = 3.0e-29 · 165 countries
After adjusting for national income-0.116p = 0.140 · likely range [-0.26, +0.04]
p, allowing for regions0.002standard error 0.022 · 7 regions
Check for luck (q)0.029across 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.

Capital per worker · 2021 international $ per workerlink with income +0.93 · proxy
Vulnerable employment · % of employmentlink with income -0.87 · 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

Capital per worker · 2021 international $ per worker →Vulnerable employment · % of employment →$4,669$1,365,0800.456%90.2%Angola: $40,771, 66.3% of employmentAlbania: $224,756, 46% of employmentUnited Arab Emirates: $960,197, 1.5% of employmentArgentina: $217,740, 22.3% of employmentArmenia: $215,201, 32.8% of employmentAustralia: $588,436, 9.12% of employmentAustria: $691,757, 7.85% of employmentAzerbaijan: $103,789, 53.8% of employmentBurundi: $5,029, 83.7% of employmentBelgium: $788,016, 11% of employmentBenin: $35,283, 78.5% of employmentBurkina Faso: $14,647, 80.6% of employmentBangladesh: $75,955, 57.3% of employmentBulgaria: $174,610, 6.92% of employmentBahrain: $656,018, 0.749% of employmentBahamas, The: $383,629, 15.9% of employmentBosnia and Herzegovina: $261,176, 18.1% of employmentBelarus: $354,810, 6.33% of employmentBelize: $78,567, 29.8% of employmentBolivia: $53,381, 62.7% of employmentBrazil: $172,608, 26.1% of employmentBarbados: $213,881, 18.8% of employmentBrunei Darussalam: $1,365,080, 4.48% of employmentBhutan: $236,135, 69% of employmentBotswana: $179,626, 25.6% of employmentCentral African Republic: $26,131, 79.4% of employmentCanada: $524,837, 9.56% of employmentSwitzerland: $713,606, 9.6% of employmentChile: $243,644, 20.9% of employmentChina: $228,804, 33.4% of employmentCote d'Ivoire: $40,246, 69.4% of employmentCameroon: $32,971, 67.6% of employmentCongo, Dem. Rep.: $10,352, 81.5% of employmentCongo, Rep.: $142,120, 75.9% of employmentColombia: $133,012, 43% of employmentComoros: $61,490, 56.8% of employmentCabo Verde: $108,256, 34.3% of employmentCosta Rica: $199,425, 23.4% of employmentCyprus: $598,680, 8.38% of employmentCzechia: $532,563, 13.5% of employmentGermany: $456,143, 4.34% of employmentDjibouti: $140,439, 30.3% of employmentDenmark: $624,134, 5.4% of employmentDominican Republic: $248,222, 38% of employmentAlgeria: $250,240, 25.6% of employmentEcuador: $173,936, 50.1% of employmentEgypt, Arab Rep.: $111,080, 23.9% of employmentSpain: $645,774, 10.1% of employmentEstonia: $440,113, 7.09% of employmentEthiopia: $15,427, 84.1% of employmentFinland: $666,233, 9.46% of employmentFiji: $98,132, 32.8% of employmentFrance: $697,343, 8.5% of employmentGabon: $159,764, 29.8% of employmentUnited Kingdom: $512,292, 11.5% of employmentGeorgia: $431,753, 42.4% of employmentGhana: $46,135, 60% of employmentGuinea: $22,150, 79.2% of employmentGambia, The: $21,269, 63.5% of employmentGuinea-Bissau: $12,239, 74.9% of employmentEquatorial Guinea: $191,691, 23.1% of employmentGreece: $528,005, 23.1% of employmentGuatemala: $111,294, 36.2% of employmentHong Kong SAR, China: $667,472, 5.76% of employmentHonduras: $82,123, 33.9% of employmentCroatia: $436,860, 6.35% of employmentHaiti: $98,654, 76% of employmentHungary: $425,172, 7.83% of employmentIndonesia: $183,833, 50% of employmentIndia: $77,306, 71.6% of employmentIreland: $916,129, 9.64% of employmentIran, Islamic Rep.: $326,799, 39.5% of employmentIraq: $157,848, 27.1% of employmentIceland: $663,692, 8.4% of employmentIsrael: $312,643, 7.7% of employmentItaly: $772,186, 14.3% of employmentJamaica: $127,828, 31.6% of employmentJordan: $285,736, 7.86% of employmentJapan: $443,290, 7.49% of employmentKazakhstan: $240,251, 24.8% of employmentKenya: $36,351, 63.8% of employmentKyrgyz Republic: $75,165, 29% of employmentCambodia: $57,014, 52.3% of employmentKorea, Rep.: $524,597, 17.7% of employmentKuwait: $295,624, 2.4% of employmentLao PDR: $60,622, 76.4% of employmentLebanon: $263,237, 19.4% of employmentLiberia: $18,430, 76.9% of employmentSt. Lucia: $227,662, 22% of employmentSri Lanka: $135,884, 39.2% of employmentLesotho: $51,675, 32.6% of employmentLithuania: $351,583, 10.4% of employmentLuxembourg: $630,742, 6.95% of employmentLatvia: $567,433, 8.62% of employmentMacao SAR, China: $580,196, 3.33% of employmentMorocco: $121,741, 35.5% of employmentMoldova: $150,878, 58.6% of employmentMadagascar: $9,126, 84.4% of employmentMaldives: $272,395, 16.9% of employmentMexico: $182,229, 25.3% of employmentNorth Macedonia: $246,047, 12.3% of employmentMali: $13,542, 75.8% of employmentMalta: $303,203, 10.1% of employmentMyanmar: $69,944, 62.9% of employmentMontenegro: $230,861, 14.3% of employmentMongolia: $161,137, 38.4% of employmentMozambique: $20,903, 83.7% of employmentMauritania: $103,000, 53.3% of employmentMauritius: $213,172, 14.9% of employmentMalawi: $4,669, 59.9% of employmentMalaysia: $277,072, 21.9% of employmentNamibia: $151,136, 29.9% of employmentNiger: $16,530, 83.7% of employmentNigeria: $124,033, 66.5% of employmentNicaragua: $83,527, 38.9% of employmentNetherlands: $552,270, 13.4% of employmentNorway: $771,357, 4.17% of employmentNepal: $31,796, 77% of employmentNew Zealand: $260,787, 12.6% of employmentOman: $448,887, 3.81% of employmentPakistan: $31,616, 55.5% of employmentPanama: $444,149, 37.9% of employmentPeru: $123,770, 47.5% of employmentPhilippines: $96,960, 33.6% of employmentPoland: $217,393, 15% of employmentPortugal: $546,974, 9.66% of employmentParaguay: $162,503, 36.1% of employmentWest Bank and Gaza: $154,071, 18.4% of employmentQatar: $955,762, 0.456% of employmentRomania: $306,456, 13% of employmentRussian Federation: $535,814, 4.93% of employmentRwanda: $14,359, 39.4% of employmentSaudi Arabia: $558,363, 1.66% of employmentSudan: $40,014, 39.7% of employmentSenegal: $39,760, 63% of employmentSingapore: $659,201, 9.3% of employmentSierra Leone: $11,451, 86% of employmentEl Salvador: $118,273, 30.8% of employmentSerbia: $242,243, 23.9% of employmentSao Tome and Principe: $56,209, 35% of employmentSuriname: $257,115, 18.4% of employmentSlovak Republic: $356,502, 11.8% of employmentSlovenia: $534,480, 10.6% of employmentSweden: $568,885, 6.87% of employmentEswatini: $109,028, 28.4% of employmentSyrian Arab Republic: $12,902, 38.9% of employmentChad: $14,253, 90.2% of employmentTogo: $23,596, 75% of employmentThailand: $154,578, 48% of employmentTajikistan: $275,734, 28% of employmentTurkmenistan: $247,867, 28.3% of employmentTrinidad and Tobago: $428,237, 21.2% of employmentTunisia: $136,199, 17.9% of employmentTurkiye: $310,440, 23.9% of employmentTanzania: $33,612, 83.7% of employmentUganda: $21,690, 74.4% of employmentUkraine: $640,898, 19% of employmentUruguay: $250,173, 24.4% of employmentUnited States: $482,411, 3.81% of employmentUzbekistan: $153,548, 33.3% of employmentSt. Vincent and the Grenadines: $354,818, 22% of employmentViet Nam: $88,517, 51.4% of employmentSouth Africa: $161,442, 11.7% of employmentZambia: $48,746, 70.2% of employmentZimbabwe: $21,641, 68.2% of employmentAREBGRBRNIRLMDGQATSLETCDTUNZAF

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted-0.7353.0e-29165
By rank (Spearman), not adjusted-0.8793.1e-54165
Standard (Pearson), adjusted for national income-0.1160.140165
By rank (Spearman), adjusted for national income-0.3729.5e-7165

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 165 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: +0.619 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from -0.132 (without IRL) to -0.098 (without TJK). 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: TJK (+0.018).

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
East Asia & Pacific19-0.16
Europe & Central Asia48-0.24
Latin America & Caribbean26+0.00
Middle East, North Africa, Afghanistan & Pakistan20-0.21
Sub-Saharan Africa44-0.45

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 third55-0.51
Middle third55-0.29
Richest third55-0.13

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
Christians97+0.01
Muslims46-0.16

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
France25-0.50
Never a European colony20-0.50
Spain19-0.06
United Kingdom48-0.08

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.

nr
Nationalist25-0.26
No strong official ideology108-0.06

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.

nr
A few parties banned25-0.40
No parties banned114-0.08

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 = -0.131 after dropping 1 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 33years. 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 = +0.043, 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 capital per worker moved did not tend to see their vulnerable employment move with it.

Across countries (adjusted)-0.116for comparison
Within countries-0.307each country vs itself
…and vs the same year elsewhere+0.043q = 0.600 · 167 countries
Year-on-year changes+0.010q = 0.729
Read with care.
  • Almost all of the second indicator's variation is between countries, so the within-country estimate rests on a small part of the data.
  • 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.

5,507 country-years (one country in one year), 167 countries, 1991–2023, about 33 years each on average. Share of the variation that happens within countries over time: 20% for Capital per worker, 2% for Vulnerable employment. 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

0.10−0.1-100+10years Vulnerable employment trails Capital per worker →lag -10: r = 0.012 (n = 3,841)lag -9: r = 0.009 (n = 4,008)lag -8: r = 0.010 (n = 4,175)lag -7: r = 0.013 (n = 4,342)lag -6: r = 0.016 (n = 4,509)lag -5: r = 0.020 (n = 4,676)lag -4: r = 0.026 (n = 4,843)lag -3: r = 0.030 (n = 5,010)lag -2: r = 0.035 (n = 5,177)lag -1: r = 0.040 (n = 5,343)lag +0: r = 0.043 (n = 5,507)lag +1: r = 0.044 (n = 5,670)lag +2: r = 0.048 (n = 5,666)lag +3: r = 0.047 (n = 5,499)lag +4: r = 0.046 (n = 5,332)lag +5: r = 0.044 (n = 5,165)lag +6: r = 0.042 (n = 4,998)lag +7: r = 0.044 (n = 4,831)lag +8: r = 0.049 (n = 4,664)lag +9: r = 0.052 (n = 4,497)lag +10: r = 0.056 (n = 4,330)

Same year (lag 0): +0.043. 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


2021 international $ per worker
% of employment		Years
Brunei Darussalam BRN$1,365,0804.48%2023, 2025
United Arab Emirates ARE$960,1971.5%2023, 2025
Qatar QAT$955,7620.456%2023, 2025
Ireland IRL$916,1299.64%2023, 2025
Belgium BEL$788,01611%2023, 2025
Italy ITA$772,18614.3%2023, 2025
Norway NOR$771,3574.17%2023, 2025
Switzerland CHE$713,6069.6%2023, 2025
France FRA$697,3438.5%2023, 2025
Austria AUT$691,7577.85%2023, 2025
Hong Kong SAR, China HKG$667,4725.76%2023, 2025
Finland FIN$666,2339.46%2023, 2025
Iceland ISL$663,6928.4%2023, 2025
Singapore SGP$659,2019.3%2023, 2025
Bahrain BHR$656,0180.749%2023, 2025

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.
World Bank, World Development Indicators

Sources

Capital per worker

Capital stock per person engaged, at current PPPs (Penn World Table)

Groningen Growth and Development Centre, University of Groningen · via DataverseNL · CC BY 4.0 · updated irregular (new versions every few years)

The value of a country's buildings, machines, roads and other equipment, divided by the number of people working. It is in dollars adjusted for what money buys in each country, and it is best for comparing countries in the same year. The Penn World Table builds it by adding up past investment and taking off wear and tear, so it is linked to the investment share by construction. Where it is used for adjusting, it is measured in percentage terms (on a log scale), like income. No "better" direction is set.

Vulnerable employment

Vulnerable employment, total (% of total employment)

International Labour Organization · CC BY 4.0 · updated quarterly

Self-employed workers and unpaid family workers, who have no employer and usually no protection. The ILO estimates it with a model for every country and year, which is why it is complete where surveys are not.

How this was computed

Data used: most recent value in 2010-2025; values come from 2021–2025. 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 Capital per worker and Vulnerable employment

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

More links with Capital per worker or Vulnerable employment