Subjective and Objective Education Mismatches in Turkey

Anıl Duman & İdil Göksel Yaşar University & İEÜ June, 2015

Outline

• • • • • • Motivation Overview Contribution Literature Review Methodology & Results Conclusion

Motivation

• • • • • • There is a rich literature measuring the skill and education mismatches in the labor markets and their impact on wage determination, yet there are very few studies on Turkey.

We try to contribute by providing the analysis of the Turkish case where education and skill mismatches are argued to be large. – For instance, 55.7% of the employees see skill deficits as a primary challenge in Turkey (WEF, 2014) and the incidence of overeducation is around 17.6% (ILO, 2014).

However, the required level of skills and education can be defined subjectively or objectively, and depending on the choice of the method the incidence of mismatch can differ significantly.

Thus, we first try to measure the education mismatches in Turkey employing both approaches.

Then we look at the impact of education mismatches on wage determination in Turkey.

Our findings reveal that there are substantial mismatches by both measures, and the mismatches are treated differently across public and private sectors.

Overview

• Subjective approach: The respondents are asked about their perceptions of the extent their education or skills are used in their job – 28% over skilled – No difference across genders – Over skilling doesn't increase with education – Among the ISCO-08 1-digit level occupational categories craft and related workers are the most over skilled

28% over skilled

Underskilled Matched Overskilled

No Gender Difference

Male Female 0 Underskilled Matched Overskilled 0 Overskilled

Over Skilling vs Education

Primary Basic Primary High

Overview

• • • • • • Objective approach: The overeducated are those with education level higher by some ad-hoc value than the mean or mode of the sample within a given occupation.

We use both mean measure and mode measure and find higher overeducation with the mode measure, which is in line with the literature. There are important differences across occupations both by the mean and mode measures.

– 93.42% match for professionals but 31.52% overeducation for technicians and associate professions. The higher the educational attainment the higher the share of overeducation.

No big difference across genders There is a major sectoral divergence between public and private sectors both in terms of education mismatch and wages.

Mean Measure

0 Overeduc Undereduc Required educ

Mode Measure

0 Overeduc Undereduc Required educ

No Gender Difference

Public vs Private

Public vs Private

Public Private 0 2 4 6 0 lnhrwage Density kdensity lnhrwage 2 4 6

• • • • •

Literature Review

Flisi et al. (2014): The relationship between overeducation and overskilling in EU-17 is very loose and only for a minor fraction of people are overskilled and overeducated at the same time. Meroni et al. (2014): In some countries like Italy and Japan, overeducation is persistent while in others like Turkey, UK and Belgium, it does not lead to further overeducation for the recent graduates. El-Hamidi (2008): The incidence of education-occupation mismatch has declined from 51% to 42%, and the percentage of over-educated workers while the share of under-educated workers in Egypt decreased between 1998 and 2006.

ILO (2014): There is a large range in overeducation and undereducation shares across countries but the incidence of mismatch remained stable. The lowest incidence of overeducation was 10.5% in Kosovo, and the highest incidence was 20.1% in Slovakia. Mercan et al. (2015): High levels of undereducation and overeducation problems in many sectoral job groups exist in Turkey. Even occupations such as subsistence agricultural and fishery workers group are found to have substantial mismatches.

Literature Review

• • • • • Herrera-Idarraga et al (2013): The returns to required education in the informal sector are not only lower, but the penalty that informal workers face due to educational mismatches in terms of wages are considerable higher than their counterparts in the formal sector. Korpi and Tahlin (2007): No evidence that the rate of wage growth is higher among overeducated workers than others in Sweden. Overeducated are penalized early on by an inferior rate of return to schooling and they are not able to recover later on. Santos & Sequeira (2014): In several European countries, over-skilled people tend to have a wage penalty and under-skilled people tend to have a premium. Turkish over and under-skilled workers have lower wages compared to the workers with matched skills. Filiztekin (2011): The incidence of overeducation in Turkey is less than developed countries, and they are paid significantly less than whose education match their job. Allen et al. (2013): Education mismatches have different effects across public and private sectors. While the wage setting institutions explain the observed wage differences in the public sector, the wages in the private sector are mostly based on productivity (actual skills).

Contribution

• • • Most of the studies cover only developed countries, and there are only very few analyses focusing on Turkey.

Public-private sector distinction is not discussed at length although the distribution of education and wages are quite divergent. We looked into these sectors separately and consider the selection issues for public-private employment choices (see Tansel, 2005).

Data

• • Subjective mismatch: European Working Conditions Survey, 2010 – 2045 individuals, 75.35% male, 24.65% female – Self-assessment of skills Objective mismatch: Household Labour Force Survey, 2010 – 81458 individual, 77.39% male, 22.61% female – Wage, education and control variables are derived from the survey – Mode measure of mismatch is the difference between the actual years of schooling and required years of schooling (mode) at ISCO-88 1-digit level – Mean measure of mismatch is the difference between the actual years of schooling and required years of schooling (mean+-sd) at ISCO-88 1-digit level

Methodology

• • Mincerian model: – LnHrWage i =α₀+α₁X characteristics, i +α₂Y i +α₃E i +ε i where X is a vector of individual and household Y is a vector of job characteristics, E is years of schooling, and ε is the error term.

Duncan and Hoffman model: – LnHrWage i =α₀+α₁X i +α₂Y i +α₃RE i + α 4 OE i + α 5 UE i + ε i where RE is required years of education, OE is years of overeducation and UE is years of overeducation.

Heckman Selection

• Heckman Selection model: – – Base: LnHrWagePub i =α₀+α₁X i +α₂Y i +α₃RE i + α 4 OE i + α 5 UE i + ε i Selection: Public i = Z

i γ +

(ε,u) ~ N(0,0,σ 2 ε , σ 2

u

,ρ εu )

u i

We developed and instrumental (spousepub) variable for the selection model.

– Spousepub = 1 if parents or spouse is employed in the public sector.

– This is argued to affect the public employment but not wages.

Gender Age Married Experience Experience 2 Private Fulltime Firm size Permanent Urban Social Security School RegEducy OverEducy UnderEducy Constant Region Dummies Sectors # of Observations Adjusted R 2

OLS Regression Results

Mincerian

0.0380 (0.0037) 0.0076 (0.0002) *** 0.1156 (0.0039) *** 0.0213 (0.0006) *** -0.0004 (0.0000) *** -0.4772 (0.0048) *** -0.3578 (0.0083) *** 0.0473 (0.0011) *** -0.0381 (0.0061) *** 0.0535 (0.0041) *** 0.1921 (0.0043) *** 0.0576 (0.0004) *** 1.0202 (0.0137) *** X X 81458 0.6185

Mean

-0.0042 (0.0040) 0.0047 (0.0002) *** 0.0668 (0.0043) *** 0.0221 (0.0007) *** -0.0004 (0.0000) *** -0.6103 (0.0051) *** -0.3514 (0.0091) *** 0.0602 (0.0012) *** -0.0038 (0.0066) 0.09178 (0.0045) *** 0.2710 (0.0046) *** 0.0181 (0.0004) *** 0.0891 (0.0024) *** 0.0003 (0.0024) 1.5271 (0.0144) *** X X 81458 0.5500

Private

0.0188 (0.0047) *** 0.0063 (0.0002) *** 0.0543 (0.0048) *** 0.0200 (0.0008) *** -0.0002 (0.0000) *** -0.3905 (0.0113) *** 0.0700 (0.0014) *** -0.0756 (0.0071) *** 0.0742 (0.0053) *** 0.2343 (0.0049) *** 0.0124 (0.0005) *** 0.0800 (0.0028) *** -0.0096 (0.0027) *** 1.0503 (0.0161) *** X X 60958 0.2910

Public

-0.0383 (0.0069) *** -0.0023 (0.0005) *** 0.0474 (0.0085) *** 0.0187 (0.0011) *** -0.0002 (0.0000) *** -0.3165 (0.0139) *** 0.0351 (0.0022) *** 0.6248 (0.0174) *** 0.1055 (0.0078) *** 0.8599 (0.0167) *** 0.0217 (0.0005) *** 0.0883 (0.0039) *** 0.0228 (0.0049) *** 0.4609 (0.0309) *** X X 20500 0.3804

Gender Age Married Experience Experience 2 Fulltime Firm size Permanent Urban Social Security RegEducy OverEducy UnderEducy Constant Mills Lambda Region Dummies Sectors # of Observations Wald chi 2

Heckman Selection

Public

-0.0995 (0.0081) *** -0.0011 (0.0005) ** 0.0511 (0.0085) *** 0.0178 (0.0011) *** -0.0002 (0.0000) *** -0.3447 (0.0141) *** 0.0348 (0.0021) *** 0.6193 (0.0174) *** 0.0908 (0.0078) *** 0.9282 (0.0173) *** 0.0212 (0.0005) *** 0.0847 (0.0039) *** 0.0209 (0.0048) *** 0.3766 (0.0314) (0.0057) *** 0.7719 *** X X 81458 12827.03

Private

0.0247 (0.0048) *** 0.0068 (0.0003) *** 0.0534 (0.0048) *** 0.0200 (0.0008) *** -0.0002 (0.0000) *** -0.3968 (0.0114) *** 0.0700 (0.0014) *** -0.0705 (0.0072) *** 0.0694 (0.0054) *** 0.2457 (0.0053) *** 0.0124 (0.0005) *** 0.0779 (0.0028) *** -0.0094 (0.0027) *** 1.0351 (0.0163) (0.0182) *** -0.2235 *** X X 81458 21550.40

Results

• • • • Schooling is positively rewarded in the Turkish labor market.

Overeducation also increases the wages for the entire sample, while the effect of undereducation is positive but insignificant.

Both human capital and the job competition models are rejected. However, the relationship between mismatch and wages are distinct across sectors. – Undereducation is negative and significant in the private sector but it is positive and significant in the private sector. – In other words, human capital theory is applicable to the private sector.

Results

• • • • The decision to be in the public sector need to be controlled for. According to our findings, the effects of mismatch on wages continue to be stable after considering for selection.

In the public sector, the workers with education less than their occupational requirements are not penalized.

The private sector wage determination is more in line with the standard models, and the wages are negatively relaed to the years of undereducation.

Conclusions

• • • • • The education mismatches are more costly for developing countries like Turkey.

Coordination between the labor market and the schooling system could be beneficial.

Public sector wage determination is different than the private sector, and could not be explained by occupation-education matches. Future research is needed in understanding the relationship between skill mismatches and education mismatches for Turkey. Also, persistence of mismatches can be analyzed especially for different educational categories.

Thank You!