BeTa

The following detailed assumptions are used in determining the exact input data for the BeTa model:

• training is funded through additional public resources: private resources that are freed through deadweight loss for the public authorities, are reflected in the simulation as higher disposable income for individuals and lower costs of labour for employers;
• no substitution effects with existing public training support schemes: those participating in training would have either not participated in absence of support or done so thanks to individual, private resources;
• additional investment in upskilling activities resulting from voluntary cost-sharing is assumed away;
• given the model is based on the representative agent, individuals are not heterogeneous. The simulation focuses on the EU-average annual value of training undertaken irrespective of any dynamics linked to individual accumulation. Decreasing marginal returns over time are also assumed;
• from a long-term perspective, fixed set up costs are omitted. This is justifiable because from a long-term perspective, one-off costs become negligible. Hence, the focus lies on operational yearly costs;
• the average cost of training for the EU-27 estimate is calculated based on the number of training entitlements redeemed by each target group, in each country, using as deflators for the education sector as per the cost benefit analysis. It is therefore a weighted average which adjusts to the amount of entitlements used by each country and target group.
• input data used for this simulation is based on the middle ground scenario for the take up rate of the training entitlements and considers, as net effects on training participation, all the economically relevant additionality in training undertaken (i.e. all the training which would have not been undertaken without the training entitlements).
• wage levels are left free to fluctuate to ensure macroeconomic coherence in combination with the increases in taxes, monetary transfers (training purchased with public resources that would have been purchased through private ones) and effects on the job matching function. This is necessary as all these factors (taxes, transfers and changes to job finding rates) affect the value wages at equilibrium levels, hence it is impossible to fix them exogenously.

The model inputs consist of a rich and large dataset which is required by the estimation strategy. The data that will be used in the estimation stage are:

• GDP, consumption,
• investment,
• imports,
• exports,
• wages;
• the unemployment rate,
• the rates of change of the price deflators for consumption,
• import,
• export,
• nominal effective exchange rate,
• the domestic and the monetary policy short term interest rate,
• labour force,
• participation rates,
• data on R&D,
• human capital

The model outputs consist of the provision of different socio-economic scenarios. The focus will lie in particular on GDP and employment outcomes as a result of the provision of training entitlements.

Macroeconomic modelling using the BeTa model is able to control for the complex economic interactions which might result from, for example, impacts of additional taxes used to fund the training entitlements. As a forecasting model, it is able to provide an assessment of medium to long-effects on output and employment.