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)

  CZ FIN GR ITA LAT UK

Population

418 481 170 200 142 259 282 020 364 345 115 899

GDP (m Euros)2129.3 2982.8 1524.1 2953.6 592.2 2749.1

Rural Share (%)21.99 58.1 4.28 32.39 41.3 40.5

Urban Share (%)78.01 41.9 95.72 67.61 58.7 59.5

GDP Per Capita (Euros) 5088 16919 10711 10473 1625 23724

Rural GDP Per Capita 4482 14201 14345 6643 1127 15599

Urban GDP per Capita 5289 23047 10593 14470 2361 36731

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

  CZ FIN GR ITA LAT UK

Activities/Industries 15 52 18 23 33 38

Of which Rural 8 23 9 12 17 19

Commodities 15 28 20 19 15 19

Factors of Productions 10 9 10 10 6 10

Of which Rural 5 5 5 5 3 6

Households 5 8 13 4 8 8

Of which Rural 3 4 6 2 4 4

1 Rest of World, 1 Government sector all case study areas

Production structure

Urban/Rural

Urban/Rural

Local/Regional

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

Key Assumptions Each case study area separate labour market Urban-rural labour market integrated within case study areaCapital 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 impactMostly 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

% Impact on Real Gross Domestic Product (GDP)

  CZ FIN GR IT LAT UK

Private Cons. 6.7 4.3 4.2 8.9 3.9 2.6

Investment 16.2 43.6 15.0 14 3.5 25

Reg Exports 6.8 4.2 4.1 8.6 9.3 7.4

Reg Imports 8.4 12.7 6.4 7.4 4.9 8.1

GDP at Factor Cost 6.5 5.3 4.9 8.2 5.6 5.7

Scenario 1 +10% change in total labour supply all areas % Impact on Real Gross Domestic Product (GDP) at Factor Cost

  CZ FIN GR IT LAT UK

Rural 6.4 5.2 1.9 9.0 5.2 3.3

R-primary 6.2 1.3 1.9 6.7 5.5 2.8

R-manufacturing 8.3 6.9 2.9 8.5 8.4 6.1

R-services 4.9 5.7 2.5 9.7 3.8 2.7

Urban 6.9 5.3 5 7.7 5.8 7.3

U-manufacturing 8.6 6.7 8.8 7.8 8.4 8.9

U-services 5.7 4.8 4.2 7.6 4.4 6.9

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

% changes in GDP at Factor Cost

  -20% skilled +20% unskilled

  CZ FIN LAT GR IT UK

Overall -12.6 -5.3 -6.9 4.3 4.8 1.8

Rural -12.2 -4.7 -5.2 2.6 5.2 1.3

R-primary -10.9 -0.7 -7.7 1.4 7.7 1.1

R-manufacturing -15.7 -5.0 -13.4 3.6 7.0 0.8

R-services -9.7 -6.1 -1.4 3.5 3.9 1.5

Urban -13.4 -6.1 -8.0 4.6 4.6 2.1

U-manufacturing -16.4 -5.1 -14.2 8.6 6.9 1.4

U-services -11.4 -6.4 -4.7 3.4 1.5 2.3

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

% Impact on Real Gross Domestic Product (GDP)

  CZ FIN GR IT LAT UK

Private Cons. -6.9 -4.5 -4.3 -9.0 -4.1 -3.1

Investment -17.1 -45.2 -16 -15 -1.4 -29

Reg Exports -7.0 -4.5 -4.3 -8.7 -9.7 -8.8

Reg Imports -8.8 -13 -6.8 -7.6 -5.7 -9.5

GDP at Factor Cost -6.7 -5.5 -5.1 -8.3 -5.9 -6.4