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Table 2 Employment effects of 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) .079***
(.002)
.081***
(.011)
.042***
(.011)
.057***
(.009)
.083***
(.007)
.103***
(.016)
.080***
(.012)
.048***
(.016)
.105***
(.010)
.087***
(.009)
.080***
(.012)
Measurement error—literacy (2SLS) .079***
(.002)
[131508]
.078***
(.011)
[6472]
.051***
(.011)
[4747]
.065***
(.009)
[6473]
.080***
(.008)
[12005]
.099***
(.016)
[1398]
.069***
(.014)
[2108]
.056***
(.021)
[1210]
.116***
(.010)
[9153]
.089***
(.009)
[6076]
.084***
(.012)
[4372]
Measurement error—second PV (2SLS) .092***
(.002)
[135446]
.101***
(.011)
[6105]
.047***
(.012)
[4548]
.067***
(.009)
[5839]
.094***
(.008)
[9848]
.116***
(.015)
[3360]
.088***
(.013)
[2840]
.056***
(.018)
[2356]
.121***
(.010)
[5725]
.092***
(.009)
[5517]
.099***
(.013)
[3123]
Reverse causality—years school (2SLS) .171***
(.004)
[15746]
.158***
(.021)
[484]
.080***
(.024)
[375]
.141***
(.015)
[676]
.159***
(.014)
[932]
.147***
(.019)
[713]
.243***
(.028)
[296]
.117***
(.029)
[248]
.179***
(.018)
[675]
.191***
(.017)
[715]
.147***
(.021)
[282]
Reverse causality—parents (2SLS) .095***
(.007)
[3873]
.091**
(.042)
[129]
.029
(.038)
[127]
.116***
(.023)
[213]
.141***
(.023)
[283]
.136***
(.041)
[73]
.132***
(.051)
[83]
–.066 (.060)
[72]
.061*
(.034)
[155]
.118***
(.036)
[145]
–.056 (.070)
[29]
Omitted variables—parents (OLS) .075***
(.002)
.074***
(.012)
.040***
(.011)
.051***
(.009)
.071***
(.008)
.105***
(.019)
.078***
(.012)
.047***
(.015)
.106***
(.010)
.084***
(.009)
.079***
(.012)
Omitted variables—health (OLS) .066***
(.002)
.068***
(.011)
.021**
(.011)
.037***
(.008)
.083***
(.007)
.083***
(.017)
.070***
(.012)
.032**
(.016)
.080***
(.009)
.072***
(.009)
.064***
(.011)
Observations 85800 3214 2248 2149 11,583 2018 1810 1865 2747 3091 2044
  France Germany Greece Indonesia Ireland Israel Italy Japan Korea Lithuania Netherl.
Baseline (OLS) .082***
(.008)
.104***
(.010)
.032***
(.012)
.024**
(.011)
.105***
(.011)
.104***
(.010)
.098***
(.014)
.033***
(.009)
.029***
(.010)
.091***
(.012)
.088***
(.010)
Measurement error—literacy (2SLS) .073***
(.010)
[8142]
.108***
(.010)
[5965]
–.004 (.013)
[2848]
.043***
(.012)
[1771]
.103***
(.012)
[4951]
.120***
(.012)
[4057]
.095***
(.013)
[3385]
.006 (.012)
[4755]
.018*
(.010)
[7949]
.060***
(.014)
[3103]
.094***
(.011)
[5077]
Measurement error—second PV (2SLS) .088***
(.009)
[8099]
.115***
(.010)
[6354]
.050***
(.014)
[2309]
.031***
(.011)
[2338]
.121***
(.012)
[3585]
.113***
(.011)
[5501]
.119***
(.013)
[3807]
.042***
(.012)
[3461]
.037***
(.011)
[4880]
.108***
(.014)
[3291]
.095***
(.012)
[4646]
Reverse causality—years school (2SLS) .137***
(.015)
[1178]
.120***
(.016)
[829]
.190***
(.029)
[325]
.050***
(.019)
[576]
.254***
(.022)
[400]
.241***
(.019)
[549]
.248***
(.023)
[458]
.033*
(.019)
[415]
.031*
(.019)
[611]
.218***
(.025)
[312]
.179***
(.019)
[438]
Reverse causality—parents (2SLS) .087***
(.027)
[291]
.070**
(.029)
[188]
.084*
(.049)
[80]
.160**
(.062)
[36]
.177***
(.034)
[199]
.222***
(.032)
[216]
.156***
(.040)
[120]
–.055
(.049)
[71]
–.032
(.040)
[110]
.139***
(.040)
[116]
.081**
(.038)
[112]
Omitted variables—parents (OLS) .078***
(.009)
.105***
(.011)
.029**
(.013)
.023*
(.012)
.101***
(.012)
.088***
(.011)
.093***
(.014)
.036***
(.011)
.031***
(.011)
.083***
(.014)
.086***
(.012)
Omitted variables—health (OLS) .068***
(.008)
.087***
(.010)
.028**
(.012)
.021*
(.012)
.085***
(.010)
.089***
(.011)
.094***
(.013)
.032***
(.010)
.024**
(.010)
.081***
(.013)
.071***
(.010)
Observations 2919 2384 2356 3408 2655 1901 2243 2224 3066 2134 2205
  New Zealand Norway Poland Singapore Slovak R. Slovenia Spain Sweden Turkey U.K. U.S.
Baseline (OLS) .073***
(.009)
.096***
(.011)
.079***
(.012)
.040***
(.010)
.141***
(.010)
.096***
(.011)
.142***
(.010)
.080***
(.011)
.052***
(.014)
.078***
(.009)
.097***
(.010)
Measurement error—literacy (2SLS) .074***
(.010)
[6147]
.094***
(.011)
[7809]
.073***
(.013)
[3374]
.034***
(.009)
[13343]
.129***
(.012)
[4395]
.092***
(.011)
[4956]
.143***
(.011)
[7128]
.087***
(.013)
[5205]
.060***
(.013)
[2753]
.077***
(.010)
[4756]
.103***
(.011)
[6419]
Measurement error—second PV (2SLS) .089***
(.010)
[6390]
.104***
(.011)
[5635]
.093***
(.013)
[3596]
.045***
(.009)
[10787]
.168***
(.012)
[4371]
.108***
(.011)
[4138]
.158***
(.011)
[5549]
.084***
(.013)
[3936]
.060***
(.014)
[2164]
.082***
(.011)
[5262]
.104***
(.011)
[5617]
Reverse causality—years school (2SLS) .138***
(.020)
[496]
.182***
(.020)
[378]
.251***
(.025)
[370]
.060***
(.013)
[1618]
.272***
(.021)
[455]
.195***
(.017)
[743]
.288***
(.018)
[1046]
.134***
(.023)
[472]
.204***
(.025)
[393]
.088***
(.026)
[255]
.139***
(.016)
[656]
Reverse causality—parents (2SLS) .058
(.042)
[92]
.068**
(.032)
[133]
.152***
(.043)
[120]
.002
(.034)
[166]
.212***
(.032)
[195]
.132***
(.026)
[260]
.167***
(.043)
[148]
.045
(.038)
[106]
.199***
(.073)
[24]
.074**
(.031)
[194]
.098***
(.026)
[261]
Omitted variables—parents (OLS) .064***
(.011)
.098***
(.011)
.069***
(.013)
.041***
(.010)
.130***
(.012)
.088***
(.012)
.141***
(.011)
.075***
(.012)
.048***
(.015)
.078***
(.011)
.089***
(.011)
Omitted variables—health (OLS) .060***
(.009)
.074***
(.010)
.060***
(.012)
.040***
(.010)
.121***
(.010)
.079***
(.011)
.134***
(.011)
.069***
(.011)
.052***
(.014)
.057***
(.010)
.066***
(.011)
Observations 2429 2101 1716 2277 2182 2254 2737 1762 2224 3864 1990
  1. Dependent variable is a binary indicator that equals 1 if the respondent reports that she is currently employed, and 0 otherwise. 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: persons aged 35–54 years. All regressions control for a quadratic polynomial in age and gender. Baseline standard model controlling for age and gender. Measurement error 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