The TERA CGE models: analysing labour migration in diverse regional economies in the EU
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The TERA CGE models: analysing labour migration in diverse regional economies in the EU Euan Phimister (University of Aberdeen, UK). SAM & General Equilibrium models Major Part of TERA project This Presentation and Next Complementary Aim - motivation, implementation, usefulness

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The TERA CGE models: analysing labour migration in diverse regional economies in the EU

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The TERA CGE models: analysing labour migration in diverse regional economies in the EU

Euan Phimister (University of Aberdeen, UK)


SAM & General Equilibrium models

  • Major Part of TERA project

  • This Presentation and Next Complementary

  • Aim - motivation, implementation, usefulness

    Structure

  • Background

  • Case Study Areas

  • Modelling Approach SAMs and CGE Models

  • Model Structure

  • Using Models - labour migration.


Background

TERA: Economic development in remote rural areas

Aims:

  • Role territorial factors which influence development

  • review whether existing policies take account of factors

  • propose new policy interventions.

    “The trends and choices that affect rural areas cannot be studied in isolation from what is going on in non-rural areas” (Saraceno, 1994)


Approach

  • Regional/Local

  • Modelling within region rural-urban linkages

    6 Case Study areas. Reflect different

  • Economic and Institutional Context

  • Spatial Scale

  • Rural-urban relationship


OECD Rural Classification


Case Study Differences

Spatial Scale NUTS3 to NUTS 4/5

Population levels 110K – 400K

Rural Pop Densities - 9.5 - 125 persons/km squared (Finland) –(Italy)

Economic Size 0.5bn - 2bn euros/year

GDP per capita. Developed (UK) – less developed (Latvia)

Rural share of GDP – 5% (Greece) to 60%(Finland)


CASE Study Areas: Summary Statistics


Modelling

  • Social Accounting Matrices (SAM) - all transactions given point in time

  • SAM - basis for Computable Equilibrium Model (CGE)

    SAM Construction - each study area

  • Existing secondary sources, e.g. national input-output tables

  • Primary Data collection

  • Survey of Households and Business survey, interviews with key informants


Computable Equilibrium Model (CGE)

Behaviour of representative agents in economy

  • Producers and Traders – maximise profits

  • Consumers – maximise their well-being (have demand curves)

  • Government collects taxes and makes transfers (tax rates and transfers are exogenously set)

    Model Closure rules – assumptions on how markets operate e.g. labour

    All transactions in “economy” accounted for.

    TERA-CGE Models

  • IFPRI Standard CGE Model (Lofgren et al) (www.ifpri.org/pubs/microcom/micro5.htm )

  • Disaggregation of Accounts allows rural-urban analysis


Level of Disaggregation


Production structure

Local/Regional

Urban/Rural

Urban/Rural

Local/Regional


Factors and Households


CGE Model Estimation

  • Each case study area

  • Data - SAM plus other literature estimates

  • Procedure - calibrate CGE models so each CGE replicates Case study SAM

    CGE Model Usefulness

  • Full Picture of case-study economic transactions

  • Controlled experiments – what if ?

    Example Simple Scenario – labour migration

  • How different are the effects of large labour inflow/outflows in case study areas?


Case Study Areas Evidence

  • Significant Growth Greek, Scottish Study areas

  • Decline Finnish and Latvian areas

    Composition effect ?

  • Finland - outmigration of highly educated people

  • Scotland- in migrants (skilled) but work in low skilled occupations

    Scenario 1

    + 10% change in total labour supply all areas

    Scenario 2

  • -20% skilled labour category Czech R, Finland, Latvia

  • +20% unskilled labour category Greece, Italy, UK

    Key Assumptions

    Each case study area separate labour market

    Urban-rural labour market integrated within case study area

    Capital fixed by sector, Government spending fixed


Scenario 1 +10% change in total labour supply all areas

Aggregate level (GDP) broadly similar effects across case study areas

+10% positive impact 5-8% (-10% approximately same negative effect)

Components of GDP - Larger differences

Rural-urban decomposition +10% positive impact

Rural GDP effects 2-9%

Mostly Rural same or less than Urban effect (except Italy)

Largest differences GR, UK

Rural-urban sectoral decomposition +10% positive impact

Mostly Rural sectoral effect same or less than Urban effect(except Italy)

Largest differences GR, UK


Scenario 1 +10% change in total labour supply all areas


Scenario 1 +10% change in total labour supply all areas


Scenario 2a) -20% skilled labour category Czech R, Finland, Latvia b) +20% unskilled labour category Greece, Italy, UK

Areas losing skilled labour

Big differences in overall loss 5-12.6%

Urban areas worst hit

Broadly, impact by sector comparable

Areas gaining unskilled labour

Some differences in overall gains 2-4%

No clear pattern whether Urban or rural areas gain most

Differential sectoral impact by rural-urban

Ratio Skilled: unskilled wages increases both losing & gaining areas


Scenario 2a) -20% skilled labour category Czech R, Finland, Latvia b) +20% unskilled labour category Greece, Italy, UK


Summary & Conclusions

  • Modelling Approach SAMs and CGE

  • CGE Models capture Case Study areas differences (?)

  • Labour migration

    General – Rural GDP case study area differences

    Urban effect often bigger than Rural

    Skills mix-differential losses and gains

  • Example CGE - What if?

  • Further simulations – tailored to specific circumstances of each case study area

  • Range simulations envisaged – Tourism, Transport, Agric Policy


Scenario 1 -10% change in total labour supply all areas


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