ben gardiner fabio manca human capital and skills · 2014. 11. 4. · cz dk de fr fi gr it lt lv mt...

Regional Holistic Model: RHOMOLORegional Holistic Model: RHOMOLO

Skillsnet Technical Workshop, 14-15 June 2010, Thessaloniki

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Ben Gardiner and Fabio Manca

European Commission European Commission –– DG Joint Research Centre (IPTS)DG Joint Research Centre (IPTS)Regional Regional EconomicEconomic ModellingModelling (REMO)(REMO)

The views expressed are purely those of the authors and may not in any circumstances be regarded as stating an official position of the European Commission.

Human Capital and Skills in a Regionally Integrated Model



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Contents

Background to and purpose of RHOMOLO modelSkills and training in Cohesion policyNeed for more integrated modelling approach

Outline of RHOMOLO modelMeasuring human capital/skillsSupply, demand, interaction effectsExpected impacts of increased human capital/skills expenditure

Can we improve RHOMOLO in this area?Work undertaken by CEDEFOP on modeling skills supply and demand (SkillsNet group)Some applicability to scenario / impact analysis as well?



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Background to Cohesion Policy and Related Funds (2007-13)

Three main objectivesConvergence (Obj1)Regional competitiveness and employment (Obj2)Territorial cooperation (Obj3)

Two main fundsCohesion Fund (CF)Structural Funds (SF)

European Social Fund (ESF)European Regional Development Fund (ERDF)

How the numbers add up…CF + SF = €348bn (30% of EU budget c.f. 50% to agriculture)

0

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Funds Objectives

€bn

(200

7-13

)

CF

ERDF

ESF Convergence

Regional comp and empl

Territorial cooperation

0

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150

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300

350

Funds Objectives

€bn

(200

7-13

)

CF

ERDF

ESF Convergence

Regional comp and empl

Territorial cooperation



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Education and Training within Cohesion Policy

ESF supportEducation and training

System reformsHE networkingRaising awarenessLLL participationSupporting PG studies

Workers and new skillsImproved access to trainingIdentify future occupational/skills requirements

Transnational cooperationImproving human capital and educational systems

ERDF supportEducational infrastructure

CZ

DK

FR

GRHU

IR

IT

PL

PT

ROUK

ATBE

BGCY

DE

EEESFI

LT LVLXMT

NLSE SISV

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8000

0 10 20 30 40 50 60 70 80

% of ESF budget -> 'Improving Human Capital'

€m (2

007-

13)

BGCY

EEES

HU

IR

LX

PT

ATBE

CZ

DEDKFIFR

GR

ITLT

LVMT

NL

PLROSE

SI

SV

UK0

200

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600

800

1000

1200

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0 10 20 30 40 50 60 70 80

% of ESF budget -> 'Improving Human Capital'

€ pe

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ad o

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ive

popu

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n (2

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The Need for a New Tool to Model Cohesion Policy Impacts

Modelling of:Research Policy

Industrial structuresEIT-KICs

Education PolicyCohesion policy

Climate change

Microeconomic foundations(R&D, Human Capital, People)

• Trade• Investment• Employment

Multi-Country

RegionsRHOMOLO

(Computable general equilibrium)

Agriculturee.g. CAPRI

Transport

Energye.g. POLESLand use

Macro-economic Models

e.g. QUEST

Our ambition: An economic computable general equilibrium model for the evaluation of European Cohesion policy (ECP) that covers the economy at a NUTS1/2 regional level with sufficient sectoral detail (waste, water, R&D incl. among 23 NACE sectors)



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Human capital in the RHOMOLO - SCGE framework

Human capital affects different dimensions of the RHOMOLO model:

the labour market conditions (relative wages and migration decisions)the households' time-investment decisions (whether to spend time receiving education, working or leisure) the technological capabilities of firms and regions to produce or implement technology.

The main objective is to be able to analyze the effects of Cohesion Policies expenditures on the creation of new stock of human capital and, eventually, to check how the newly produced human capital impacts productivity differentials across Europeanregions



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“Empirical” Human capital and Skills

As we know, Human Capital is an Intangible Asset and for this reason it is usually proxied by either:

Educational attainment levels (as shares of population)“Years of education”Skills are nested within human capital and are much harder to capture

RHOMOLO computes the “empirical” proxy for human capital as:

HK = P*6 + S*10 + T*14 P, S and T are share of labour with Primary, Secondary and Tertiary education over total region population



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The Law Motion for the accumulation of HK(SCGE-model) Human capital accumulates over time according to the following law:

Where:

is the depreciation rate of HK each period of time (if =1 HK depreciates in 1 period)

is the share of investment in educationby household and education type ofregional and national governments

is the time devoted to acquire education

redred

red

Hktred

Hktriktri

thktrithedth

Htredredtred

SHECGRCG

CshareHOUSTLSHAHLSH

,,

,

,,,,,,

,,,,)1(

1,,,,,

)

()(

νδ

δ

−−−

−−

−

⋅++

⋅⋅⋅= ∑

redH ,δ

ktriktrith

ktrithedth CGRCGCshareHOUST −−− ++⋅∑ ,,,,,,,,

redHktredSHE ,

,,ν

−



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Model Overview – Labour Demand and Supply-Demand Interactions



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Human Capital and Technology diffusionIn RHOMOLO regions lagging behind the technological level of the innovative leader (in termsof TFP levels) can potentially catch-up with it by technology transfers (spillovers):

Human capital is fundamental in enhancing technology catching-up proxying for the region absorptive capacity--Abramovitz (1986), Behnabib and Spiegel (1994,2005)

RHOMOLO makes use of the empirical specification proposed by Behnabib and Spiegel(2005) in order to estimate the impact of human capital on the process of technology catch-up and convergence at the regional level

Human capital plays a double-role here:

It affects positively the productivity growth of each region productivity “per se” ( )

It affects the absorptive capacity of the region, making it easier to implement the technology discoveredin the leader region (l).The bigger the TFP gap and the higher the number of “inventions” which can be “absorbed” by thefollower regionAt the same time, if 2 regions (r1 and r2) are at the same distance from the frontier BUT differ in their HK endowment, the one with better HK will catch-up relatively faster ( )

ir

lrrr TFP

TFPHKHKbTFP εββ +⎟⎟⎠

⎞⎜⎜⎝

⎛++=∆ *lnln 21

01 >β

02>β



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Links, Skills and Productivity

Cohesion policy

Improving accessto employment

Improving social inclusion

Increasing Stock of Human Capital

Job Creation:

Skills specificdemand

TFP Growth

GDP Growth

Direct investments: educational policies



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Improving the Modelling of Human Capital/Skills

Definition of skillsSimilar in both modelling exercises (3 broad educational classifications)

Supply of skillsLack of appropriate skills acting as a bottleneck for funding and preventing maximum benefits of CPFunding for training and skills is an explicit part of CPMigration effects

Demand for skillsMeasuring attributes and capabilities that are not quite the same as educational attainment (a counterpart that helps define human capital)Use of SIC-SOC matrix as go-between for sector employment and worker qualifications

Interaction between supply and demand (of labour)

TFP effects on the supply-side of the model

Work undertaken by CEDEFOP on modeling skills supply and demandPrimarily a forecasting exercise looking at identifying mis-matchSome applicability to scenario / impact analysis as well

ben gardiner fabio manca human capital and skills · 2014. 11. 4. · cz dk de fr fi gr it lt lv mt...

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