Future development of the educational level in Switzerland

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Future development of the educational level in Switzerland Dr. Jacques Babel 18 Feb 2011

Contents Overview of the FSO s education forecasts Educational level forecast Model Main results Which flow of new graduates? Combined forecasts for both the educational system and the educational level Closing remarks 2

Overview of the FSO s education forecasts Goal : Assist educational planning in Switzerland (at national, regional and institutional levels) Highly detailed modelling of flows in the education and training system Data sources: FSO's comprehensive surveys Yearly; horizon: 10 years Output: school students/university students, diplomas/degrees, human resources, indicators Universities: MAPE < 2% for the first 4 years of projection 3

Some consequences of this work Better understanding of the education and training system and its "dynamics" (structural effects, reforms, "upgrade", trends, ) 35% 30% 25% 20% 15% Tertiary-type A graduation rate Scenario "trend" Forecasts Total Universities Universities of applied sciences Forecasts of the future flow of new graduates 10% 5% 0% 2000 2005 2010 2015 4

Educational level forecasts Model Part of FSO population forecasts 2010-2060 Demographic forecasts Educational level forecasts Economically active population forecasts Model for the educational level: hierarchical multistate model. States/strata: age, sex, nationality (Swiss, foreign), educational attainment (4 levels) taking account of migration flows by educational level Data: Labour Force Survey (LFS) for the stock and the transition probabilities (flow) => coherence 5

Educational level forecasts - Model Transition matrix Low Medium High (5B) High (5A, 6) Population forecasts Foreign-nationality population Swiss nationality population Calibration, adjustment Stock: foreign-nationality population naturalisations Stock: Swiss nationality population emigration mortality immigration emigration mortality By demographic forecasts (except distribution by qualification level) Modelled in the project Not included in the model because of small impact => implicitly independent of the qualification level immigration 6

Taking account of migration flows by educational level Why? Since 2003, substantial immigration to Switzerland with approx. 60% with a tertiary-level degree Influence on the structure of the foreign population in Switzerland Model: Immigrants, educational level: LFS Emigrants, educational level not measurable => determined by modelling the foreign population 7

Structure of emigration: based on the educational level of the foreign population Proportion of the foreign population in Switzerland with a high educational level Comparison between forecasts and observations for different hypotheses regarding the emigration structure 50% 40% 30% 20% 2009: LFS 2003: LFS (basis) 2009: Model A. Same structure as the mean foreign population B. Same structure as the immigration (min.) C: Mixed model of A and B 10% 0% 15 18 21 24 27 30 33 36 39 42 Age 45 48 Good constraints by modelisation emigration structure ~ immigration structure 51 54 57 60 63 66 69 8

Import of high qualifications Flow of high qualifications 3500 Persons, mean 2004-2009, by age 3000 2500 2000 1500 Immigration, Total 25-64 =48000 1000 500 Emigration (model), Total 25-64 =21000 0-500 15 18 21 24 27 30 33 36 39 42 45 48 51 54 57 60 63 Net balance, Total 25-64 =28000-1000 -1500 Net balance = 28000 / Y. To be compared with the approx. 50000/Y degrees awarded. 2004-2009: impact of approx. 1.5 % points on the proportion of tertiary education graduates 9

2010-2060 forecasts : Main results high qual. medium low Whole population of Switzerland Foreign population of Switzerland => Large increase of the % of persons with high qualifications 10

Comparison between SFO forecasts and those of CEDEFOP 60 Percentage of high-qualification in the Swiss population, by age In % 50 40 30 20 2009: Cedefop 2011 2020: Cedefop 2011 2009: SFSO 2010 2020: SFSO 2010 (reference scenario) 10 0 25-64 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64 Age -Global results for 2020 are in very good agreement - Differences in age structure. Interpretation: CEDEFOP-2011 flow by age for CH not totally coherent with the stock 11

Preliminary conclusion Model and projections However How does the educational level that people say they have compare with the one we think they have (according to standard definitions)? What exactly are we talking about? Not only a methodological issue. => Detailed analyses of the flow of new graduates are necessary 12

Determining the flow: Methods Longitudinal analyses LFS-T : based on LFS by "differentiating" the stock Advantages Coherent with the stock by definition Disadvantages Difficulty of isolating appropriate populations, possible biases, applicable only for 3 levels. LFS-L : based on the LFS panel EduSys : based on education system data Other Direct determination of the flow based on the panel. In principle coherent with the stock. Applicable to a large number of levels. "Objective" determination of the flow. Comprehensive data. Additional information for subpopulations Potential problems in the panel (e.g. interviews, weighting) Not necessarily coherent with stock (potential problems with coverage, definition), potential doublecounting problems Problems of coherence 13

Comparison of methods I. From low to medium qualification Number of degrees awarded in the upper secondary programmes (ISCED 3/4, medium qualification) 80000 Total 2006-2008, swiss nationality population Number of degrees 70000 60000 50000 40000 30000 20000 10000 0 15 17 19 21 23 25 27 29-10000 Age LFS(L): Longitudinal micro (N=485) LFS(T) : Longitudinal macro EduSys: education system data Good agreement Some uncertainty on the % of the population who do not graduate 14

Comparison of methods II. To high qualifications (Universities, ISCED 5A/6) Number of first degrees awarded in the swiss universities (ISCED 5A/6, high qualification) 10000 Total 2006-2008, swiss nationality, moving average (5) Number of first degrees 9000 8000 7000 6000 5000 4000 3000 2000 1000 0 15 25 35 45 55 65 Age LFS(L) : from sec. II to 5A (Total: 79192, N=196) Edusys (eucation system data): from sec. II to 5a (Total/N: 72492) LFS(L) : from 5B to 5A (Total: 29772, N=96) Good agreement for the transition from ISCED 3/4 to 5A/6 (diff. < 9%) From LFS(L): large number of transitions from 5B to 5A/6 (but N=96 ). Cause: continuing education? 15

Comparison of methods III. To high qualifications (ISCED 5B, Professional Education and Training) Number of first degrees from professional education and training programmes (ISCED 5B, high qualification) 3500 Total 2006-2007, swiss nationality, moving average (5) 3000 Number of first degrees 2500 2000 1500 1000 Edusys: 2006-2007 (estimation), (Total / N: 40200) LFS (L) : (2006-2008)*2/3, (Total: 57400, N =250) 500 0 15 20 25 30 35 40 45 50 55 60 65 Age 40% more graduates in LFS (L), not the same age distribution. 5B: complex and important domain in Switzerland (difficult to measure). Continuing education? Analyses underway 16

Next step Coherent global forecasts for the education system and educational level Why? Allows connecting developments in the education system, its output and the population structure Better hypotheses/forecasts, deeper understanding, more usable by the stakeholders Future evolution of the education system: Future evolution of the educational level : Which number of students? Which skills supply? Migration 17

Combined forecasts for the education system and the educational level Education system forecasts Flow of degrees Transition matrix Low High (5B) Medium High (5A, 6) Population forecasts Foreign nationality population Swiss nationality population Stock: foreign nationality population Flow naturalisations Stock: Swiss nationality population Flow emigration mortality immigration emigration mortality By demographic forecasts (except distribution by qualification level) Modelled in the project Not included in the model because impact is negligible => implicitly independent of the qualification level Calibration, adjustment immigration 18

Preliminary results: 70% 60% 50% 40% 30% Level of education of the population of Switzerland as a function of the datasource used for the flow Group: population with swiss nationality, aged 25-64, model without migrations/naturalisations Low qualification Medium qualification High qualification Low qualification (LFS- L) Medium qualification High qualification (LFS- L) Low qualification (EduSys) Medium qualification High qualification (EduSys) Universities (LFS-L) 20% Universities (EduSys) 10% "Continuing education" in 5A/5B? 0% 1995 2000 2005 2010 2015 2020 Transitions from 5B to 5A/6, "continuing education"? Part of the past/future evolution of the educational level could be due to continuing education. 19

Closing remarks - Model and quality OK - Very good agreement for the educational level 2020 with CEDEFOP (2011) (apart from the age structure) - Comparisons between LFS and number of degrees awarded => number of implications, including improvement of sources - For long-term projections it is important to make global, and thus coherent, forecasts both for the educational level and the education system: Skills supply Number of students 20

Thank you for your attention! Contact E-mail: jacques.babell@bfs.admin.ch Web: www.eduperspectives-stat.admin.ch 21