• Nem Talált Eredményt

GENDER AND RACE IN THE LABOR MARKET

N/A
N/A
Protected

Academic year: 2022

Ossza meg "GENDER AND RACE IN THE LABOR MARKET"

Copied!
14
0
0

Teljes szövegt

(1)

GENDER AND RACE IN THE LABOR MARKET

Sponsored by a Grant TÁMOP-4.1.2-08/2/A/KMR-2009-0041 Course Material Developed by Department of Economics,

Faculty of Social Sciences, Eötvös Loránd University Budapest (ELTE) Department of Economics, Eötvös Loránd University Budapest

Institute of Economics, Hungarian Academy of Sciences Balassi Kiadó, Budapest

(2)

2

Author: Anna Lovász Supervised by Anna Lovász

June 2011

Week 11

Roma in the labor market II: schooling Literature for next week: employment policy

• Fleck–Messing (2009)

• Ringold et al. (2005)

Labor market situation of the Roma

• Last lecture (Kertesi–Kézdi 2010): significant labor market disadvantage of the Roma

• Employment: decline after the transition, 40 percentage point disadvantage

• Wages: roughly 30 percentage point gap ( as a comparison: female-male gap is about 17)

• Reasons for the differences

• Role of low schooling, family background

(3)

3

• The social benefit of Roma integration

• Abilities: differences in test scores, causes

• School segregation

Kertesi–Kézdi 2010: Children of uneducated parents and Roma youth in secondary

schools

• Employment rates of 18–35 year olds who are no longer enrolled in school, 2006–

2009, percentages

• Compared to the EU average, the majority of the disadvantage in employment is seen among the unskilled.

• Without secondary schooling, permanent unemployment is the norm.

Roma and secondary school graduation

• Secondary schooling is critical for employment and life paths, its type is critical for income possibilities.

• Roma and disadvantaged people rarely receive higher education than vocational schooling, often not even that.

• Main cause: dropouts

• Goal: more precise evaluation of secondary school failures

• Data: Life path survey, panel data

• 10,000, students finishing 8th grade in 2006

(4)

4

• 1st wave: family structure, financial background, childhood, health, schooling history, plans for further education

• Further waves (2007–2009): schooling outcomes

Schooling outcomes by group

• 7-8% of Roma do not continue studies after the 8th grade, <1% of non-Roma students.

• For low-skilled parents: 10 and 2-3%

• In the fourth year of secondary school, 62% of Roma students, and 95% of non- Roma students continue their studies.

• 40% of Roma students are in secondary schooling and have not been kept back a year, 80% of non-Roma.

• For low-skilled parents: 30 and 60%

Role of basic skills – Roma and non-Roma

• Stronger correlation between low competence and continuing education for Roma students

• They go to lower level schools even if they have better skills, very rarely continue to high schools.

(5)

5

Summary: Roma and secondary schooling

• The rate of dropping out is especially high among Roma students, even compared to other students with similarly low-skilled family backgrounds.

• The relative disadvantage of the Roma population in terms of schooling is being reproduced after the transition.

• Secondary school failures are correlated with the serious omissions in terms of basic skills in elementary schools.

• Elementary schools fail to endow 20-25% of students with the basic skills necessary for secondary schooling.

Kertesi–Kézdi (2010): The Roma/non-Roma Test Score Gap in Hungary

• Test scores of Roma and non-Roma students are different on average: what are the causes of this difference?

• Similar to black/white results in the USA

• There: increases with age, with controls, reduces to about 0.

• Explanatory variables of the decomposition: health status, home environment, school fixed effects, schooling of parents, and income status

• Comparison to the black/white results

(6)

6

Statistics on the situation of the Roma and blacks in the USA

Differences in test scores

(7)

7

Control variables

• Health status

• Low birth weight

• Teenage height

• Self-evaluation

• Home environment

• Retrospective questions: how often they read stories, went to the theatre or hiking

• Standardized HOME measures

• School fixed effects (+class level)

• Family background (living with parents, number of books, internet), parents’

schooling

• Permanent income effects: employment of parents, number of years of employment, household income, size, poverty measures

(8)

8

Results: Roma non-Roma test score differential

Differences in health status/home environment

• Raw differences are significant.

• With controls they are much smaller.

Not innate differences, consequences of poverty and low schooling

(9)

9

Kertesi–Kézdi (2006): budgetary benefits of helping disadvantaged and Roma reach

secondary school graduation

• Estimation of the benefit from an investment in the education of Roma children – Highly educated people contribute more to the budget and receive less in

transfers.

– The estimated discounted long-term gain is about 19 million Forints, 7-9 million by the most conservative estimates.

(10)

10

Kertesi–Kézdi (2009): Segregation in primary schools in Hungary

• Detailed analysis of between- and within-school segregation

• Regional differences

• Comparison to the USA

• National Assessment of Basic Competences 2006

• All students nationally

• On average can give us trustworthy estimates

Measuring segregation

• Exposure index for majority (T) and minority (K):

• Where

(11)

11

• Segregation index:

• Does not depend on the ratio of minority students regional comparison

Results: national averages

(12)

12

Results by region and by settlement type

(13)

13

(14)

14

Comparison to the USA: determinants of segregation

Hivatkozások

KAPCSOLÓDÓ DOKUMENTUMOK

– Activity: differences in the ratio of active jobseekers within various groups – Employment: differences in the ratio of employed within various groups – Occupations:

• If the ratio of discriminatory employers is high enough, there will be some minority workers employed at those firms, and there will be a wage differential.. • Discriminatory

• Heckman correction: estimate the probability of entry into the labor market based on individual characteristics (family status, etc.), then include in wage equation

• Do differences in the relative productivity of various worker groups explain their wage differentials. (For example, the gender

The effect on the employment chances of women is identified from differences between orchestras and rounds, and the changes over time in hiring processes. •

round : Player 2 receives the game description, the name and decision of Player 1, and the (tripled) amount sent to him/her. Decides how much to send back to

above the reservation wage differential, more workers are willing to e=accept the dangerous job as the wage grows. • Equilibrium: positive wage differential, since

• – Empirical results: time spent on housework impacts wages negatively (compensating wage differentials for flexible jobs).. • Different expectations and labor market ties