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Working While Learning or Learning While Working ? Aviad Tur-Sinai Dmitri Romanov Noam Zussman. March 11, 2008. Subject. Paper investigates empirically whether employment during academic study effects the duration of study and the likelihood of dropping out.
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Working While Learning or Learning While Working ?Aviad Tur-SinaiDmitri RomanovNoam Zussman March 11, 2008
Subject • Paper investigates empirically whether employment during academic study effects the duration of study and the likelihood of dropping out. • Takes advantage of a comperhensive individual-level dataset constructed from administrative files and records – of candidates, students, and recipients of bachelor’s degrees.
Main Findings • The relationship between the extent of students’ employment and duration of their studies depends on their age: • Among students aged 22-26 at the beginning of their studies, the extent of employment has no effect on the duration of studies. • Among the older students there is a strong positiveeffect.
Motivation for Study (1) • Employment is common among first-degree students who come from diverse socioeconomic backgrounds and pursue various academic diciplines. It has considerable implications for the students’ economic situation and on access to the higher-education system and their patterns of study.
Motivation for Study (2) • Clashing conclusions via the literature: • Brunello and Winter-Ember (2003): Employment of students in Europe had no significant effect on the duration of study. • Ehrenberg and Sherman (1987): Employment of male students during the semester prolonged their degree studies and raised their dropout rates.
Motivation for Study (3) • Solving an econometric problem: Endogeneity of the students’ employment (resulting from the positive correlation between unobserved personal characteristics: motivation, social connections...) when investigating the effect of employment on the duration of study. Usual IV doesn’t solve the problem of individual heterogeneity in employment and scholastic achievements(Ruhm, 1997; Light, 2001; Hakkinen, 2006). Therefore – we suggest a solution to solve the individual heterogeneity problem.
The Data: Administrative records of first-degree students at higher education institutions in Israel - who began their studies in the 1999/2000 academic year.
The Data: Education For each first-degree student (6 years follow-up): • Preferences for institutions. • Fields of study at the time of enrollment. • The progression of studies: institution(s), subjects completed. • Scholastic abilities.
The Data: Employment and earning: Matched employee-employer for the years 1999-2005 : • Number of months worked. • Annual gross earnings. • Tenure of employment with employer.
The Data: Demographic data: (source: administrative register of residents) • Sex • Date of Birth • Nationality/Religion • Country of birth • Date of immigration • Marital status • Number of children • Locality of residence • Identity of student’s parents Total population: 24,960 students.
Proportion of students who received degree within 6 years from beginning of studies 82.9% 78.9% 69.4%
Deviation of duration of degree studies from standard years years 3 years 4 years
Proportion of first-degree recipients who began advanced degree studies immediately after first degree(by duration of first-degree studies) %
Measuring Rate of employment & Earnings Rate of employment • A work load index. • Represented by the proportion of employee-wage months in the course of the year out of twelve months. Earnings • Annual earnings from all working places. • No. of months worked during the year. Therefore: we can derive the average monthly wage.
Employment Rate of Fisrt-Degree students % Time preparation for the bar exams
Mean Annual Months Worked by First-Degree Students (by year of employment and Major) months
Monthly Earnings of First-Degree Students(NIS, current prices)
Monthly Earnings of First-Degree Students(NIS, current prices)
Monthly Earnings of First-Degree Students(NIS, current prices)
Average monthly earnings of (graduated) first-degree students(NIS, current prices)
Average monthly earnings of (graduated) first-degree students(NIS, current prices)
Average monthly earnings distribution of students who received degree within 6 years Students without prior employers %
Average monthly earnings distribution of students who received degree within 6 years Students without prior employers %
Occupations of 20-29 age group, by standing in academic studies (year 2006) Source: Central Bureau of Statistics, Household Expenditure survey 2006, data processed by the authors.
Occupations of 20-29 age group, by standing in academic studies (year 2006) Source: Central Bureau of Statistics, Household Expenditure survey 2006, data processed by the authors.
Occupations of 20-29 age group, by standing in academic studies (year 2004) Source: Central Bureau of Statistics, Household Expenditure survey 2006, data processed by the authors.
Occupations of 20-29 age group, by standing in academic studies (year 2004) Source: Central Bureau of Statistics, Household Expenditure survey 2006, data processed by the authors.
The aim: Estimating the correlation of employment during study and patterns of study (duration of study, likelihood of dropping out, likelihood of going on to advanced studies).
The econometric difficulty The need to contend with unobserved heterogeneity in the traits of those who choose to work and the others, traits that correspond both on the decision to work and the likelihood of scholastic success (scholastic abilities, diligence, motivation, etc.).
Let assume: - Duration of study Described by the following model: (1) An array of exogenous controlling variables (sex, ages, ethnic origin, scholastic ability, …) Employment during studies Unobserved personal traits "white noise"
(2) where: Unobserved personal traits that affect labor supply (social connections, job-hunting ability, etc.) An array of variables associated with employment but not with duration of studies "white noise"
However… A positive correlation between and causes the unobserved-heterogeneity problem – which makes the employment variable in eq.(1) endogenous. Therefore… Using the Instrumental Variable Method as correlated with employment during study and not correlated with the variables which influence the likelihood of scholastic success.
What kind of Instrument Variable ? First Suggestion The regional unemployment rate during the term of studies (Ruhm, 1997; Light, 2001; Hakkinen, 2006). Second suggestion A predetermined variable: employment in 1999 Explanation: reflects the individual’s propensity to labor and should not be correlated with the duration of first-degree studies.
Effect of students’ employment on standard deviation of years of study until award of first degree Effect of students’ employment Year of study denote 10%, 5% and 1% significance, respectivety. ***,**, *
Effect of students’ employment on standard deviation of years of study until award of first degree Effect of students’ employment Year of study denote 10%, 5% and 1% significance, respectivety. ***,**, *
Effect of students’ employment on standard deviation of years of study until award of first degree Effect of students’ employment Year of study denote 10%, 5% and 1% significance, respectivety. ***,**, *
Effect of students’ employment on standard deviation of years of study until award of first degreeAge 22-26 (in 2000) vs. All students denote 10%, 5% and 1% significance, respectivety. ***,**, *
Effect of students’ employment on standard deviation of years of study until award of first degreeAge 22-26 (in 2000) vs. All students denote 10%, 5% and 1% significance, respectivety. ***,**, *