1. MODELS Meeting Seminar on Labor Market Modeling Brussels 10/11th September 2007 CRSA/ERASME NEMESIS Model

2. PLAN 1. Human Capital Integration in Production Block 2. Labor Market 3. Interactions on Income, Savings and Consumption

3. 1.1 The technical progress in NEMESIS 1.1.1 From R&D to Knowledge stock 1.1.2 Process and Product innovation 1.2 Overview 1.2.1 Neoclassical Framework 1.2.2 Endogenous growth theory 1.2.3 Substitution and Complementarity problems between Human Capital and R&D 1.2.4 “Technological Frontier” approach 1.2.5 Empirical studies Human Capital Integration in Production Block (1/2)

4. Human Capital Integration in Production Block (2/2) 1.3 Human Capital Integration in NEMESIS production block 1.3.1 First Empirical Results 1.3.2 Graphical Analysis 1.3.3 Specification Hypothesis 1.3.4 New Production Function

5. 1.1 The Technical Progress in NEMESIS Two types of innovations – Process – Product (quality) Endogenous technical progress – Learning – R&D Knowledge externalities (Knowledge spillovers) – Inter-sectoral – Inter-national

6. 1.1.1 From R&D to Knowledge Stock

7. 1.1.2 Process and Product Innovation

8. 1.2.1 Neoclassical Framework (1/2) Macro-Mincer Equation Where Yt is the mean of revenues; St is the average years of schooling.

9. 1.2.1 Neoclassical Framework (1/2) Mankiw, Romer, Weil (1992) Where K corresponds to the physical capital, H is the human capital stock Assumptions: - Diminishing returns to scale, - Perfect substitution between skilled and unskilled labor, - Human capital and labor are considered separately.

10. 1.2.2 Endogenous Growth (1/2) Lucas (1988): Education and professional training - H is the human capital; - is the average stock of human capital; - u is time devoted to production.

11. 1.2.2 Endogenous Growth (2/2) Assumption underlying the theory: - No diminishing returns, - The presence of externalities induces a need for education policies, - Substitution/complementarity problems, - No distinction between levels of educational attainment (primary, secondary or tertiary).

12. 1.2.3 Substitution and Complementarity Problems between Human Capital and R&D Nelson and Phelps (1966): - The human capital stock determines the ability to assimilate new technologies. Benhabib and Spiegel (1994): - Their empirical study emphasizes this phenomenon. Golsbee (1998), Romer (2000), Acemoglu and Zilibotti (2002): - More education leads to more investment in R&D. - The more R&D and innovation, the stronger is the demand for education.

13. 1.2.4 “Technological Frontier” Approach The source of technological progress is dual, it results from: - Innovation and imitation activities. Far from the technological frontier, the potential for catching up is very large and so imitation contributes significantly to technological improvement. Close to the frontier, the potential for catching up is very small, innovation and tertiary education are needed for technological progress. There is a proximity threshold above which tertiary education has a growth-enhancing effect. (Vandenbussche, Aghion, Meghir 2004).

14. 1.2.5 Empirical Studies (1/2) Non structural econometric methods: - Barro and Sala-i-Martin (1995): - Three levels of education: primary, secondary, tertiary. - Distinction by gender. - An increase by 0.091 year of the male tertiary education raises the economic growth by 0.5%.

15. 1.2.5 Empirical Studies (2/2) Structural approach: - Benhabib and Spiegel (1994): - An increase of the stock of human capital by 1% increases the growth rate by 0.13%. - Bassanini and Scarpetta (2001): - One more year of schooling raises the level of GDP per capita by 6%.

16. 1.3.1 First Empirical Results (1/2) ERASME (2007): - The panel dataset covers 44 countries between 1960 and 2000. - We run regressions of the total factor productivity (TFP) growth on the stock of skilled human capital and on the proximity to the frontier. - The stock of skilled human capital is assumed to be the skilled fraction of the labor force; - Proximity is measured by the ratio between the TFP in the country and the corresponding variable in the USA.

17. 1.3.1 First Empirical Results (2/2) DATASET : We present results using two education datasets, those of Barro and Lee (2001) and Cohen and Soto (2001). EMPIRICAL RESULTS : - The stock of skilled human capital has a positive and significant impact on the TFP growth in emerging countries. - Moreover, this impact is stronger for emerging countries than for OECD economies which are closer to the frontier.

18. 1.3.2 Graphical Analysis (1/4) Curve derived from the V.A.M. (2004) estimations:

19. 1.3.2 Graphical Analysis (2/4) Where: - dg/dLs is the marginal impact of the stock of skilled (Ls) on the TFP growth (g), - a is the proximity to the frontier, - a* is the proximity threshold above which the skilled human has a growth-enhancing effect.

20. 1.3.2 Graphical Analysis (3/4) Curve derived from ERASME (2007) estimations:

21. 1.3.2 Graphical Analysis (4/4) Where: - from a* to a**, the marginal impact of the stock of skilled human capital on TFP growth is increasing, - a** is the threshold above which dg/dLs decreases, - remark: we do not have sufficient data to estimate this relationship for countries below a*.

22. 1.3.3 Specifications Hypothesis Incorporation of the variable KNOW that is linked to R&D stocks and to spillovers. Separability between production factors. - Fallon and Layard (1975). - Krussell and al. (2000) - Papageorgiou and Saam (2006) Complementarity between skilled labor (Ls) and technological capital (K, KNOW)

23. 1.3.4 New Production Function in NEMESIS (1/2) New Production Block :

24. 1.3.4 New Production Function in NEMESIS (2/2) Old Specification New Specification X M KEL KEL KE X Lu KELuLs M KELs KELs KE

25. 2. Labor Market 2.1 Backgrounds 2.2 Specifications 2.3 Labor Force 2.4 Supply of Skills

26. 2.1 Backgrounds In NEMESIS, we use a wage/price setting framework involving a modified Phillips curve and a price setting equation in level

27. 2.2 Specifications (1/2) An illustration of WS/PS model can be deduced from bargaining models which imply that wages are fixed as a ‘mark-up’ over a reservation wage: W/P = (W/P) R + F s + T s - a.U Where, (W/P) R : the reservation wage, F s : the tax wedge, T s : the trade union density and U: the unemployment rate

28. 2.2 Specifications (2/2) The problem is the determination of the reservation wage. Four approaches exist in the literature: 1. Introduction of a positive trend 2. Unemployment benefits 3. Labor Productivity 4. Lagged real wages (approach kept)

29. 2.3 Labor Force (1/3) 12 different labor force cohorts differenced by: - Age : [15,24]; [25,64] and 65 and over, - Gender: men and women, - Qualification: skilled and unskilled.

30. 2.3 Labor Force (2/3) Labor force by cohorts: i : country index, x: cohort index and t: time index LF : the labor force, T: the participation rate and POP: the population which is exogenous but have structural impacts on labor force.

31. 2.3 Labor Force (3/3) b min and b max are respectively the limits for participation rates, And X i,x,t are factors which impacts on choice to participate on labor market or not (trend, real wage, employment variation, social transfers, population structure, enrolment in studies, …) Participation rate modeled through a logistic curve for each cohorts :

32. 2.4 Supply of Skills Grounded on public and private expenditures on education, and expenditures on training Influenced by expectations of skill needs over future years, extrapolations of past trends, population projection by cohorts

33. 3 Interactions on Income and Savings 3.1 Current state of the model 3.2 Current developments

34. 3.1 Current State of the Model (1/4) In the current version of NEMESIS, disposable income and savings are derived from the households’ agent account No data available for splitting the full sequence Assumptions – Wages and salaries are available (EU-KLEMS) – Mean net income by education level (Eurostat) – When information, applying different taxation rates, calculating capital income… When not, same rates for both categories

35. 3.1 Current State of the Model (2/4) Aggregate consumption depends of – Real disposable income – Population structure – Interest rates – Inflationary pressure Aggregate consumption is then split between the 27 consumption categories using the following structure

36. 3.1 Current State of the model (3/4)

37. 3.1 Current State of the Model (4/4)

38. 3.2 Current Developments (1/2) No data for consumption by educational level but: – By socio-economic category (EU15) – By income quintile (EU15) (our choice) We can then split the consumption functions into two categories (Calibration) for the EU15 still searching data for other countries

39. 3.2 Current Developments (2/2) 4 accounts are distinguished in the model (NFC,FC,GGOV,HH) Public budget already linked in the model – Expenditures : some are exogenous (final consumption), others are partially of fully modelled (subsidies, Compensation of employees..) – Incomes fully endogeneised (taxes, …)