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Large-scale Assessments in Education

An IERI – International Educational Research Institute Journal

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 error—second PV numeracy skills are instrumented by second plausible value of numeracy skills. Reverse causality—years school numeracy skills are instrumented by years of schooling. Reverse causality—parents 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 variables—parents adds control for parental education. Omitted variables—health 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
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