Rory O'Farrell: The idea of an investment stimulus got a boost this week. Though people may disagree over the extent to which this is 'new money', it shows that at the very least, the government want to be seen to be pro-investment stimulus.
Coincidentally, this week I presented a working paper which uses the HERMIN model (used by the EU to measure the effects of cohesion funding) to assess the effect of an investment stimulus.
Two interesting things stand out about the announced stimulus. First is the involvement of the European Investment Bank (EIB). Not only do they bring money to the table, but perhaps more importantly they bring their expertise in assessing projects and an independent pair of eyes. They won't be funding any vanity projects.
The second is the off-the books nature of the funding. With traditional financing, the net cost to Government of an investment is considerably less than the headline cost, about 57%. This is as multiplier effects lead to increased tax revenue. Then over the medium term, the supply side effects of higher GDP and tax revenue more than offset interest payments on a project. However, as the projects are 'off the books' and the tax revenue is 'on the books' there will be an immediate decrease in the reported Government deficit. Though this is playing with accounting rules, it means that the government will about €400 million more room to manoeuvre and staying within Troika limits.
Overall, we can expect 17,000 jobs to be created per €1bn invested in a year, and there is a multiplier of 1.6. When designing a stimulus, it is important to front load the investment, and then phase it out. This allows the export cavalry enough time to come over the hill and save us from long term unemployment and stagnation.
Rory O’Farrell is an economist at the Dept of Economics, OECD, with extensive post-PhD international work experience. His research has been in the area of public policy, labour economics, fiscal policy and monetary policy. He has experience with macroeconomic modelling, calibrating Mortensen-Pissarides matching models and forecasting.