Medium-term macroeconomic projections in a multiregional ... · 5/02/2013 2 plan.be Harmonized Econometric Research for Modelling Economic Systems Analysis of macroeconomic and sectoral

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Medium-term macroeconomic projections in a multiregional state: the case of Belgium

Delphine Bassilière (FPB) – Didier Baudewyns (FPB)

Brussels, 1st February 2013

CMTEA Workshop

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Long tradition of making medium-term forecasts at the Belgian Federal Planning Bureau…

… first at national level…

… since a few years also at regional level

Aim of this presentation: explaining how national and regional medium-term forecasts are generated

Overview:1. National medium-term forecasts: the HERMES model2. Regional medium-term forecasts: the HERMREG model

Medium-term forecasting at the Belgian Federal Planning Bureau

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Harmonized Econometric Research for Modelling Economic Systems

Analysis of macroeconomic and sectoral aspects of the Belgian economy

Yearly sectoral model with a forecasting period of 1 to 6-12 years

Econometric model based on time series analysis with strong theoretical foundations

Demand-driven model + important supply elements

FPB’s national medium-term model: HERMESGeneral Description

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8000 equations of which 600 are econometrically estimated

1200 exogenous variables

15 industries

4 production factors

3 main categories of salaried employment (and 2 sub-categories)

8 main energy products (total of 14)

6 greenhouse gases

15 main consumption categories (total of 24)

5 main institutional sectors (total of 12)

Highly detailed public finances block

FPB’s national medium-term model: HERMESWhich disaggregation?

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Starting point: international environment and demography

For years t and t+1, fully coherent with the short-term MODTRIM model’s results

From industries to national results

Putty-clay production functions for manufacturing

Exogenous technical progress

Use of input-output and transition matrices to determine consumption and sectoral investments

Potential output and output gap are computed ex post using the EC methodology (but applied to our own historical and projected series)

Working Paper “A new version of the HERMES model” to be published in the coming months

FPB’s national medium-term model: HERMESSome characteristics

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FPB’s national medium-term model: HERMESDifferent blocks

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FPB’s national medium-term model: HERMES

An illustration: Real and potential GDP growth

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1981

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1991

1996

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2011

2016

Real GDP growth Potential GDP growth

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• Main uses:Medium-term outlook (unchanged policy scenario, notably

with regard to fiscal and social policies)

Impact of policy measures and exogeneous shocks (impact of higher crude oil prices, effects of various energy taxation policies, effects of new labour policies,…)

• Main users:Social Partners

Federal Government

Parliament, universities, research departments, …

FPB’s national medium-term model: HERMESMain uses and users

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In February: National short-term exercise (year t) for budgetary control produced by MODTRIM (FPB’s national short-term model)

In March: Fully coherent with national short-term forecast, preliminary version of national medium-term exercise, used by the government to draw up SP and NRP, submitted to EC

In May: Final version of national medium-term assessment for Belgian economy

Calendar of FPB’s national and regional forecasts

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In June: Fully coherent with national medium-term outlook, regional medium-term outlook published with our regional partners

In June: Fully coherent with national medium-term outlook, national long term outlook published by the Study Committee on Ageing (MALTESE model)

In September: National short-term exercise (year t and t+1) for the budget of year t+1

In September: Fully coherent with new national short-term exercise, quick update of national and regional medium-term outlook

Calendar of FPB’s national and regional forecasts

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Cooperation (since end 2005) between the three regional research institutes (IBSA, SVR, IWEPS) and FPBWhy HERMREG ?

• Growing importance of Regions for policy making • Since 1970: six State reforms in Belgium• Sixth State reform under way: devolution of even more

responsibilities to the Regions• Regional policy instruments (EU, national, regional levels)

Need for developing tools for policy analysis including a regional dimension

1st step: development of a first top-down macroeconometricmultiregional module (“HERMREG”) coupled to HERMES• Main goal: medium-term forecasting• Top-down (why ?) : severe data restrictions at regional level

Multiregional forecasting: the HERMREG project

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• 3 regions, 13 industries• Time-series macroeconometrics (1980-…)• Public finances by Region and by Community: in HERMES• Credibility of the regional projections: Consistency with the national FPB outlook/projections Collective publications/communication (common press

releases) Close collaboration of experts of FPB and the 3 regions

Transparency: publication of regional projections + database 1995–… available on the FPB website

Use of HERMREG database/projections by national/regional experts, usual “outsiders” (academics, …)

Multiregional forecasting: the HERMREG project

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Top-down HERMREG model

Regional household income accounts

Multiregional shift-share block

Employment, GVA, investments, labour cost: 13 branches

Inter-regional

commuting flows

Employed labour force,

unemployment

National medium-term projections5 agents, 15 industries, 24 consumption

goods/services, 4 production factors, 6 GHGPopulation, regional

labour supply

Regional GHG

emissions +

HERMES

HERMREG

RegionalPublic

Finances

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• Combination of shift-share and regression analysis (similar to REGINA: Koops and Muskens, 2005)

• Multiregional shift-share block: 4 key variables• GVA, investments, wages, employment

• Decomposition of growth rate yij,t (sector i, region j, year t) in two components (in volumes for GVA and investments):

1) national sectoral growth rate yi.,t

2) differential shift: rij,t (= yij,t - yi.,t)so yij,t = yi.,t + rij,t

• rij,t is endogenously determined for the 4 key variables, using OLS-estimated equations• empirical selection of explanatory variables: general-to-

specific strategy

Top-down HERMREG model

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• Coherence with national projections:• Regional projections are used as

“endogenous keys”• Any regional series in current prices: weights applied to the

national forecast• Any regional series in “chained Euros”: calibration to the national

projected value (aggregates in PYP are additive)• 3 regions 6 commuting flows are modelled …

… using push-pull factors: economic conditions in origin and/or destination region (e.g. employment growth, unemployment rate)

• Regional unemployment = labour supply – working populationworking population = employment + (outgoing commuting –incoming commuting) + net-border workers flow

Public accounts of the Communities and RegionsTop-down regional energy-environment (GHG) module

Top-down HERMREG model

kTijkTikTij ryy ,.,, ˆˆ

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• Multiregional multisectoral medium-term projections:GVAInvestmentsWagesEmployment (salaried and self-employed)Labour productivity

• Multiregional medium-term projections:GDPCommuting flows, working population, employment rate, unemployment GHG emissions (CO2, …)Households incomes

Multiregional projections

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Multiregional projections

Regional GDP in volumegrowth rate in %

Regional GDP growth differentialscompared to Flanders, in pp : 5-year moving average

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2010

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2014

2015

2016

2017

Brussels-Capital Region Flemish Region Walloon Region

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2.5

1985

1987

1989

1991

1993

1995

1997

1999

2001

2003

2005

2007

2009

2011

2013

2015

2017

Flemish Region - Brussels-Capital RegionFlemish Region - Walloon Region

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Progressive development of a bottom-up multiregional macroeconometric structural model• Top-down: OK for prevision, not for regional impact analysis• Different regions are influenced differently by national policies Need to model both the supply and the demand sides by region

1st step: a hybrid bottom-up/top down model Supply side regionalised

Two-level CES four-factor production functions

• Demand side: still overwhelmingly national (demand for regional production: top-down determined)

Next steps: regionalisation of demand components Deliveries by regional branch to investments of all the branches

... ... !

Work in progress: the bottom-up approach

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Regions are different: example

Regional unemployment rate% of labour force (broad definition)

Regional employment rate% of working age population(15-64 years)

50.0

52.0

54.0

56.0

58.0

60.0

62.0

64.0

66.0

68.0

70.0

1986

1988

1990

1992

1994

1996

1998

2000

2002

2004

2006

2008

2010

2012

2014

2016

Brussels-Capital Region Flemish Region Walloon Region

0.0

5.0

10.0

15.0

20.0

25.0

1980

1982

1984

1986

1988

1990

1992

1994

1996

1998

2000

2002

2004

2006

2008

2010

2012

2014

2016

Brussels-Capital Region Flemish Region Walloon Region

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For listening

For questions (?)

Thank you !