1. Using RHOMOLO model to assess ESF macroeconomic impacts
Amparo ROCA ZAMORA
DG Employment, Social Affairs and Inclusion
Evaluation and Impact Assessment Unit
ESF Evaluation Partnership meeting, 7 December 2017, Brussels

2. Outline 1.Why RHOMOLO? 2.ESF potential uses of RHOMOLO:
Simulations for post MFF Human Capital Impact Assessment.
3. Quick facts about the RHOMOLO model
4. A few caveats and challenges

3. Why RHOMOLO? 2. DG EMPL approach for supporting ESF impact evaluation:
programming period: strict requirements for impact evaluation and demonstrate EU added value of ESF funding.
2. DG EMPL approach for supporting ESF impact evaluation:
-Micro level: counterfactual evaluation (CRIE –JRC-; Admin. Arrangement since 2013 EMPL-CRIE).
-Macro level: RHOMOLO for estimating Aggregated macroeconomic impacts from ESF interventions (JRC Sevilla-DG EMPL).

4. Role of ESF The ESF supports the inclusive growth
European Social Fund
The ESF supports the inclusive growth
strand of the Europe 2020 Strategy (art. 162 TFEU)
The ESF contributes to territorial and social cohesion
(art. 174 and 175 TFEU)

5. ESF potential uses of RHOMOLO
1. Current period (on going needs –e.g. communication-; preparing ex post evaluation) (and check data constraints in order to propose improvements for next period )
3. Post-2020: new MFF proposal in 2018, Impact assessment required : Simulations of alternative funding scenarios; EU added value: the cost of “non-Europe”.
RHOMOLO captures the impact of ESF funding on GDP, Employment, income, consumption, investment and savings.

6. Quick facts about RHOMOLO model
RHOMOLO is the model developed by the JRC for ex-ante, ex post territorial impact assessments of EU Regional Policy, but now extended to other policy areas;(e.g. transport).
Good for analysing policies linked to: infrastructures , investments, HUMAN CAPITAL and innovation.
It is a spatial Computable General Equilibrium (CGE) model; it shows how "policy shocks" are expected to affect economic and social outcomes at the regional level, as deviations from baseline;
It allows policy makers to have an idea of the trade-offs and general equilibrium implications (macroeconomic impacts) of their policy choices. (e.g. post-2020 HC funding scenarios)

7. Structure of RHOMOLO Sector disaggregation
5 NACE 1.1 regional sectors (Agri, Manuf&Construct., Business Serv.,Fin.Serv, Public serv.) + national R&D sector; (new version 10 sectors).
Sectors can be perfectly or imperfectly competitive, the latter with finite number of firms and "small-group" monopolistically competitive pricing strategies.
Geographical coverage
28 EU Member States + ROW
267 NUTS2 regions (French overseas territories are excluded);
Number of equations/prices per year: 831,190.
Time dimension
Base year for calibration: 2010; but now a new model version calibrated 2013!!
Annual frequency (with update of stocks in every period);
Horizon for simulations: years and longer.

8. From ESF spending to Macro Impacts
ESF intervention
TO10 education
TO 8 training for unemployed
POLICY SHOCK
RHOMOLO MODEL
FINAL MACRO
IMPACT
GDP
EMPLOYMENT
Increased labor productivity for low/ medium skilled

9. Production structure

10. Sources of spatial interactions
Imports
Final consumption as
Exports
Other firms' input
Region A
sector 1
Region B sector 2
Taxes and transfers
R&D
Inter-regional activity with spillovers
Investments
Savings cross borders

11. Example: EU impacts by region groups

12. Example: Impact on EU regions' GDP
2007
2015
2030

13. A few caveats and challenges
On model features: (some examples)
Technologies/taste parameters are assumed fixed over the simulation horizon;
There is a scarcity of estimates for elasticities and spill-overs at the regional level (macro literature focuses on national data and innovation literature on specific sectors of geographical areas).
Current specification of labour market inside RHOMOLO doesn't allow estimate all the ESF impacts on LM.
On policy simulation from ESF interventions ("policy shocks")
The model assumes that regions spend the entire envelope of ESF funds
Dozens of specific spending categories are aggregated into a limited number of sources of model shocks;
Challenges on selection of the types of ESF intervention/results better suited to feed the model (e.g. ALMP “access to employment” impacts on participation rates; inside human capital, disentangle impact on low/medium/high skills labour productivity). (Thematic objective –TO- 8, TO 9 and TO 10).
The “quality” of spending is homogeneous across regions and time-invariant.

14. For more information on RHOMOLO:. Website:. https://ec. europa
For more information on RHOMOLO: Website: Web simulation tool: 14