placestats

Hours worked (PWT) vs. PISA reading

Fades after adjusting for income

Across 79 countries, Hours worked (PWT) and PISA reading rise and fall together at r = -0.59 (on a scale from −1 to +1, where 0 means no link). Comparing only countries with similar income (GDP per person) shrinks it to -0.32, which could easily be chance (q = 0.43, 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 PISA reading, 394 to 479 PISA points, hours worked (PWT) is 281 hours per year lower at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 201 hours per year.

Link before adjusting (r)-0.592p = 9.3e-9 · 79 countries
After adjusting for national income-0.323p = 0.004 · likely range [-0.51, -0.11]
p, allowing for regions0.159standard error 0.187 · 5 regions
Check for luck (q)0.429across 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.

Hours worked (PWT) · hours per yearlink with income -0.40 · moderate
PISA reading · PISA pointslink with income +0.77 · high

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

Every country as a dot

Hours worked (PWT) · hours per year →PISA reading · PISA points →1,3352,514329543Albania: 2,152 hours per year, 358 PISA pointsUnited Arab Emirates: 2,514 hours per year, 417 PISA pointsArgentina: 1,612 hours per year, 401 PISA pointsAustralia: 1,611 hours per year, 498 PISA pointsAustria: 1,438 hours per year, 480 PISA pointsBelgium: 1,593 hours per year, 479 PISA pointsBulgaria: 1,659 hours per year, 404 PISA pointsBosnia and Herzegovina: 2,122 hours per year, 403 PISA pointsBelarus: 1,875 hours per year, 474 PISA pointsBrazil: 1,994 hours per year, 410 PISA pointsCanada: 1,731 hours per year, 507 PISA pointsSwitzerland: 1,529 hours per year, 483 PISA pointsChile: 1,950 hours per year, 448 PISA pointsColombia: 2,471 hours per year, 409 PISA pointsCosta Rica: 2,177 hours per year, 415 PISA pointsCyprus: 1,840 hours per year, 381 PISA pointsCzechia: 1,774 hours per year, 489 PISA pointsGermany: 1,335 hours per year, 480 PISA pointsDenmark: 1,380 hours per year, 489 PISA pointsDominican Republic: 2,072 hours per year, 351 PISA pointsAlgeria: 2,232 hours per year, 350 PISA pointsSpain: 1,638 hours per year, 474 PISA pointsEstonia: 1,606 hours per year, 511 PISA pointsFinland: 1,497 hours per year, 490 PISA pointsFrance: 1,487 hours per year, 474 PISA pointsUnited Kingdom: 1,523 hours per year, 494 PISA pointsGeorgia: 1,932 hours per year, 374 PISA pointsGreece: 1,893 hours per year, 438 PISA pointsGuatemala: 2,151 hours per year, 374 PISA pointsHong Kong SAR, China: 2,240 hours per year, 500 PISA pointsCroatia: 1,974 hours per year, 475 PISA pointsHungary: 1,668 hours per year, 473 PISA pointsIndonesia: 1,958 hours per year, 359 PISA pointsIreland: 1,654 hours per year, 516 PISA pointsIceland: 1,452 hours per year, 436 PISA pointsIsrael: 1,890 hours per year, 474 PISA pointsItaly: 1,701 hours per year, 482 PISA pointsJamaica: 1,963 hours per year, 410 PISA pointsJordan: 2,483 hours per year, 342 PISA pointsJapan: 1,654 hours per year, 516 PISA pointsKazakhstan: 1,975 hours per year, 386 PISA pointsCambodia: 2,389 hours per year, 329 PISA pointsKorea, Rep.: 1,910 hours per year, 515 PISA pointsLebanon: 2,412 hours per year, 353 PISA pointsLithuania: 1,640 hours per year, 472 PISA pointsLuxembourg: 1,452 hours per year, 470 PISA pointsLatvia: 1,625 hours per year, 475 PISA pointsMorocco: 2,174 hours per year, 339 PISA pointsMoldova: 1,989 hours per year, 411 PISA pointsMexico: 1,629 hours per year, 415 PISA pointsNorth Macedonia: 1,949 hours per year, 359 PISA pointsMalta: 1,848 hours per year, 445 PISA pointsMalaysia: 2,308 hours per year, 388 PISA pointsNetherlands: 1,439 hours per year, 459 PISA pointsNorway: 1,412 hours per year, 477 PISA pointsNew Zealand: 1,708 hours per year, 501 PISA pointsPeru: 2,143 hours per year, 408 PISA pointsPhilippines: 2,096 hours per year, 347 PISA pointsPoland: 1,807 hours per year, 489 PISA pointsPortugal: 1,735 hours per year, 477 PISA pointsParaguay: 2,123 hours per year, 373 PISA pointsQatar: 2,435 hours per year, 419 PISA pointsRomania: 1,826 hours per year, 428 PISA pointsRussian Federation: 2,087 hours per year, 479 PISA pointsSaudi Arabia: 2,125 hours per year, 383 PISA pointsSingapore: 2,283 hours per year, 543 PISA pointsSerbia: 1,995 hours per year, 440 PISA pointsSlovak Republic: 1,621 hours per year, 447 PISA pointsSlovenia: 1,588 hours per year, 469 PISA pointsSweden: 1,432 hours per year, 487 PISA pointsThailand: 2,177 hours per year, 379 PISA pointsTrinidad and Tobago: 1,610 hours per year, 427 PISA pointsTunisia: 2,288 hours per year, 361 PISA pointsTurkiye: 1,747 hours per year, 456 PISA pointsUkraine: 2,045 hours per year, 428 PISA pointsUruguay: 1,481 hours per year, 430 PISA pointsUnited States: 1,789 hours per year, 504 PISA pointsUzbekistan: 2,099 hours per year, 336 PISA pointsViet Nam: 2,160 hours per year, 462 PISA pointsAREARGDEUDNKHKGISLJORKHMLBNSGPSWEURY

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted-0.5929.3e-979
By rank (Spearman), not adjusted-0.5782.4e-879
Standard (Pearson), adjusted for national income-0.3230.00479
By rank (Spearman), adjusted for national income-0.2940.00979

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 79 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: +0.269 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from -0.370 (without SGP) to -0.240 (without QAT). 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: QAT (+0.083).

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 & Pacific12-0.43
Europe & Central Asia42-0.21
Latin America & Caribbean13-0.20

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 third27-0.15
Middle third26-0.28
Richest third26-0.32

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
Christians52-0.12
Muslims15-0.41

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
Spain12+0.04
United Kingdom13-0.60

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
No strong official ideology59-0.13

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
No parties banned65-0.15

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 = -0.323 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 23years. 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 = +0.107, 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 hours worked (PWT) moved did not tend to see their PISA reading move with it.

Across countries (adjusted)-0.323for comparison
Within countries+0.112each country vs itself
…and vs the same year elsewhere+0.107q = 0.468 · 54 countries
Year-on-year changes—q = —
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.

392 country-years (one country in one year), 54 countries, 2000–2022, about 7 years each on average. Share of the variation that happens within countries over time: 9% for Hours worked (PWT), 5% for PISA reading. 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

0.20−0.2-80+10years PISA reading trails Hours worked (PWT) →lag -8: r = -0.108 (n = 247)lag -7: r = -0.108 (n = 247)lag -6: r = -0.051 (n = 247)lag -5: r = -0.026 (n = 333)lag -4: r = 0.013 (n = 333)lag -3: r = 0.009 (n = 333)lag -2: r = -0.005 (n = 328)lag -1: r = 0.039 (n = 392)lag +0: r = 0.107 (n = 392)lag +1: r = 0.135 (n = 391)lag +2: r = 0.057 (n = 390)lag +3: r = 0.114 (n = 390)lag +4: r = 0.108 (n = 389)lag +5: r = 0.147 (n = 370)lag +6: r = 0.140 (n = 366)lag +7: r = 0.114 (n = 366)lag +8: r = 0.083 (n = 364)lag +9: r = 0.060 (n = 362)lag +10: r = 0.034 (n = 362)

Same year (lag 0): +0.107. 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 data


hours per year
PISA points		Years
United Arab Emirates ARE2,5144172023, 2022
Jordan JOR2,4833422023, 2022
Colombia COL2,4714092023, 2022
Qatar QAT2,4354192023, 2022
Lebanon LBN2,4123532023, 2018
Cambodia KHM2,3893292023, 2022
Malaysia MYS2,3083882023, 2022
Tunisia TUN2,2883612023, 2015
Singapore SGP2,2835432023, 2022
Hong Kong SAR, China HKG2,2405002023, 2022
Algeria DZA2,2323502023, 2015
Thailand THA2,1773792023, 2022
Costa Rica CRI2,1774152023, 2022
Morocco MAR2,1743392023, 2022
Viet Nam VNM2,1604622023, 2022

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.
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

Sources

Hours worked (PWT)

Average annual hours worked per person engaged (Penn World Table)

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

Hours actually worked in a year, averaged over everyone with a job, including the self-employed and part-timers. It measures the same thing as the OECD hours measure, and for countries in both the two mostly agree. This one is kept because it reaches much further: about 130 countries each year from 2010 to 2023, where the OECD series has 38 countries and stops in 2016. Before 2000 it covers mainly rich countries. No "better" direction is set.

PISA reading

PISA mean reading score

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

How this was computed

Data used: most recent value in 2010-2025; values come from 2015–2023. 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 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 Hours worked (PWT) and PISA reading

This page shows that two measures go together. It does not show that Hours worked (PWT) changes PISA reading, or the reverse. These figures also describe countries, not individual people. See the ecological fallacy.

More links with Hours worked (PWT) or PISA reading