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Table 1 Returns to skills: international evidence.

From: Skills, earnings, and employment: exploring causality in the estimation of returns to skills

  Pooled Australia Austria Belgium Canada Chile Cyprus Czech R. Denmark Estonia Finland
Baseline (OLS) .200***
(.003)
.205***
(.016)
.182***
(.012)
.151***
(.009)
.204***
(.009)
.367***
(.033)
.141***
(.020)
.122***
(.018)
.135***
(.009)
.177***
(.013)
.140***
(.012)
Measurement error—literacy (2SLS) .221***
(.003)
[61223]
.216***
(.014)
[2824]
.218***
(.013)
[2096]
.169***
(.011)
[3141]
.231***
(.009)
[7334]
.378***
(.029)
[649]
.173***
(.023)
[847]
.159***
(.022)
[581]
.156***
(.009)
[5153]
.168***
(.015)
[3096]
.154***
(.013)
[2812]
Measurement error—second PV (2SLS) .232***
(.003)
[65811]
.250***
(.015)
[2264]
.211***
(.012)
[1859]
.184***
(.011)
[2687]
.242***
(.009)
[5054]
.402***
(.030)
[2238]
.182***
(.024)
[1142]
.149***
(.019)
[1377]
.162***
(.010)
[3346]
.209***
(.015)
[2873]
.164***
(.014)
[2062]
Reverse causality—years school (2SLS) .517***
(.007)
[7569]
.492***
(.039)
[197]
.471***
(.036)
[179]
.322***
(.022)
[324]
.489***
(.023)
[553]
.673***
(.044)
[342]
.752***
(.083)
[93]
.313***
(.040)
[149]
.370***
(.023)
[382]
.450***
(.032)
[369]
.477***
(.036)
[170]
Reverse causality—parents (2SLS) .461***
(.012)
[1862]
.516***
(.083)
[48]
.384***
(.045)
[69]
.315***
(.041)
[79]
.338***
(.032)
[199]
.635***
(.085)
[47]
.502***
(.117)
[38]
.255***
(.056)
[41]
.286***
(.040)
[94]
.487***
(.064)
[95]
.364***
(.080)
[24]
Omitted variables—parents (OLS) .182***
(.003)
.189***
(.017)
.165***
(.012)
.138***
(.010)
.194***
(.009)
.324***
(.034)
.129***
(.021)
.112***
(.019)
.127***
(.010)
.155***
(.015)
.137***
(.012)
Omitted variables—health (OLS) .194***
(.003)
.204***
(.016)
.173***
(.011)
.149***
(.009)
.204***
(.009)
.335***
(.035)
.132***
(.020)
.115***
(.017)
.132***
(.009)
.164***
(.014)
.135***
(.012)
Observations 45064 1433 1115 1221 7197 903 938 1066 1879 1763 1480
  France Germany Greece Indonesia Ireland Israel Italy Japan Korea Lithuania Netherl.
Baseline (OLS) .175***
(.009)
.239***
(.015)
.101***
(.019)
.245***
(.036)
.230***
(.023)
.273***
(.020)
.135***
(.018)
.181***
(.014)
.210***
(.019)
.172***
(.016)
.180***
(.011)
Measurement error—literacy (2SLS) .179***
(.010)
[4326]
.268***
(.015)
[2976]
.106***
(.024)
[601]
.331***
(.049)
[538]
.259***
(.023)
[1583]
.321***
(.021)
[1551]
.154***
(.020)
[1515]
.162***
(.016)
[2778]
.235***
(.017)
[4204]
.169***
(.019)
[1982]
.217***
(.014)
[2252]
Measurement error—second PV (2SLS) .200***
(.010)
[4940]
.274***
(.015)
[2249]
.137***
(.024)
[763]
.306***
(.043)
[661]
.280***
(.021)
[1152]
.320***
(.020)
[2233]
.145***
(.019)
[1535]
.221***
(.017)
[1862]
.249***
(.018)
[2211]
.198***
(.018)
[1590]
.215***
(.014)
[2082]
Reverse causality—years school (2SLS) .361***
(.019)
[524]
.456***
(.030)
[361]
.455***
(.068)
[62]
.747***
(.080)
[190]
.512***
(.042)
[172]
.572***
(.042)
[190]
.423***
(.045)
[220]
.478***
(.037)
[266]
.563***
(.040)
[332]
.600***
(.054)
[156]
.456***
(.039)
[178]
Reverse causality—parents (2SLS) .354***
(.037)
[129]
.370***
(.049)
[86]
.448***
(.146)
[13]
1.381***
(.394)
[12]
.509***
(.074)
[64]
.562***
(.075)
[68]
.466***
(.093)
[51]
.717***
(.131)
[32]
.540***
(.068)
[82]
.401***
(.062)
[67]
.567***
(.096)
[30]
Omitted variables—parents (OLS) .157***
(.010)
.228***
(.017)
.091***
(.019)
.210***
(.034)
.214***
(.025)
.251***
(.021)
.114***
(.020)
.166***
(.015)
.187***
(.019)
.150***
(.017)
.173***
(.012)
Omitted variables—health (OLS) .172***
(.009)
.234***
(.015)
.099***
(.019)
.231***
(.036)
.230***
(.023)
.264***
(.019)
.135***
(.018)
.180***
(.014)
.208***
(.019)
.158***
(.016)
.176***
(.011)
Observations 1715 1296 623 806 1033 908 1019 1319 1441 1260 1012
  New Zealand Norway Poland Singapore Slovak R. Slovenia Spain Sweden Turkey U.K. U.S.
Baseline (OLS) .191***
(.013)
.132***
(.008)
.190***
(.018)
.466***
(.015)
.188***
(.021)
.186***
(.012)
.225***
(.017)
.130***
(.009)
.208***
(.035)
.220***
(.015)
.254***
(.028)
Measurement error—literacy (2SLS) .206***
(.013)
[2848]
.131***
(.008)
[4754]
.250***
(.021)
[1483]
.444***
(.014)
[8089]
.184***
(.023)
[1782]
.222***
(.013)
[3120]
.261***
(.020)
[2265]
.139***
(.010)
[2646]
.273***
(.036)
[509]
.262***
(.016)
[1978]
.278***
(.022)
[2947]
Measurement error—second PV (2SLS) .221***
(.012)
[3184]
.152***
(.009)
[2990]
.221***
(.020)
[1587]
.501***
(.015)
[7153]
.225***
(.023)
[1709]
.224***
(.013)
[2484]
.259***
(.018)
[2350]
.143***
(.009)
[2489]
.246***
(.032)
[703]
.247***
(.015)
[2484]
.274***
(.023)
[3389]
Reverse causality—years school (2SLS) .460***
(.036)
[217]
.330***
(.026)
[257]
.642***
(.055)
[161]
.723***
(.025)
[1055]
.742***
(.071)
[142]
.506***
(.030)
[405]
.653***
(.040)
[322]
.230***
(.023)
[272]
.804***
(.096)
[87]
.606***
(.058)
[117]
.487***
(.033)
[473]
Reverse causality—parents (2SLS) .363***
(.063)
[43]
.278***
(.036)
[82]
.740***
(.133)
[31]
.747***
(.062)
[133]
.654***
(.091)
[66]
.461***
(.043)
[135]
.676***
(.117)
[34]
.201***
(.035)
[55]
.649***
(.149)
[34]
.408***
(.050)
[120]
.443***
(.052)
[131]
Omitted variables—parents (OLS) .182***
(.014)
.120***
(.009)
.168***
(.018)
.445***
(.016)
.148***
(.020)
.157***
(.014)
.206***
(.019)
.127***
(.009)
.193***
(.036)
.188***
(.019)
.213***
(.030)
Omitted variables—health (OLS) .186***
(.013)
.128***
(.008)
.183***
(.018)
.456***
(.015)
.182***
(.021)
.178***
(.013)
.224***
(.018)
.127***
(.008)
.208***
(.035)
.214***
(.014)
.236***
(.027)
Observations 1204 1520 817 1507 1193 1306 1192 1316 674 1787 1121
  1. Dependent variable: log gross hourly wage. Each cell reports the coefficient on numeracy skills from a separate regression. Regressions weighted by sampling weights. Model names indicate bias addressed by the specification; “OLS” refers to ordinary least squares estimations, “2SLS” refers to two-stage least squares estimations. Least squares estimates (except for pooled specification) take into account all 10 plausible values of numeracy skills. Sample: full-time employees aged 35–54 years. All regressions control for a quadratic polynomial in actual work experience and gender. Baseline standard model controlling for work experience and gender. Measurement errorliteracy numeracy skills are instrumented by literacy skills. Measurement errorsecond PV numeracy skills are instrumented by second plausible value of numeracy skills. Reverse causalityyears school numeracy skills are instrumented by years of schooling. Reverse causalityparents numeracy skills are instrumented by parental education (1 neither parent attained upper secondary education, 2 at least one parent attained upper secondary education, 3 at least one parent attained tertiary education). Omitted variablesparents adds control for parental education. Omitted variableshealth adds control for respondent’s health (1 poor, 2 fair, 3 good, 4 very good, 5 excellent). Observations refer to baseline specification. Numeracy skills standardized to SD 1 within country. Pooled specification includes country fixed effects and gives same weight to each country. Robust standard errors (jacknifed in the OLS models due to the complex sampling design) in parentheses. F-statistics of excluded instrument in the first stage of 2SLS models in brackets. Significance levels: * p < 0.10, ** p < 0.05, *** p < 0.01