How to Fight Unemployment with the Minsky Alternative in Italy and in the EU

Abstract

This chapter examines how to fight structural and short-term unemployment in Europe using the “Employer of Last Resort” (ELR) program originally envisaged by Minsky, by which the State offers a job to anyone willing to work. In replying to the many criticisms it received, we show that ELR is the best suitable alternative in terms of effectiveness in curing unemployment, public finance soundness, social and financial stability, long-term growth and international economic imbalances. Although on the theoretical side laissez-faire policies are not riding high these years, the institutional design of the proposal is the key to its political viability. State accountability and efficiency are vital issues and we try to address them deepening the analogy with lending of last resort. In particular, we propose to set up a State regulator similar to a central bank, to supervise ELR projects along with local controls from below ensuring the cost-effectiveness of the scheme. We also show, operationally, that the cost of an ELR program for Italy and for the EU would be in the range of 1.5–2 % of the GDP, a small fraction of what the EU put in place these years to save its banking system.

The views expressed are those of the author and do not involve the responsibility of the Bank of Italy.

Appendices

Appendix: How Much Would the ELR Cost to Italy and to the EU

In the section Cost and Benefits for the State, we mentioned the empirical literature on ELR. In this appendix, we will conduct a similar appraisal for contemporary Italy. In doing this, we can borrow from a very recent case study on Greece (OESD 2014). This thorough reading on how to tackle the terrible situation of unemployment in Greece after years of austerity, points out that a full-scale ELR program would cost between 1.5 and 5.4 % of GDP; moreover, 40 % of this cost would be recouped by the State in taxes, and so forth. It also estimates that at a current minimum wage, for every ten ELR new jobs, around four indirect jobs are created and that the GDP increase is 2.3 times the cost of the program. Simulation results are based on the Eurostat I-O tables of the country. Comparing the I-O tables of the specific sectors used by the study as ELR jobs creators, we can see that for all the differences between Greek and Italian economies, there is a strong similarity. In fact, these five sectors ¹⁵ have a very similar weight on the economy and their input composition is also similar (see Table A.1). ¹⁶

Table A.1 Input composition of the synthetic sector

Therefore, we can confidently use the multipliers of the original research to simulate the cost of an ELR program for Italy. In particular, we base our analysis on the following assumptions:

Using these coefficients we can simulate the impact of the scheme. We present the data (for 2013) in the following table ¹⁷ :

The gross cost of an ELR program is therefore less than 2 % of the GDP, close to the estimates made by Papadimitriou (2008) for USA and UK. To put this number in context, we should consider that in 2012, the total cost of employment policies for the Italian government was more than €29 billion, of which €23 billion was for unemployment benefits. This means that the ELR labour cost would not increase the gross bill for the State. As for the net cost, considering only the direct GDP growth, the situation would be by far better, as now these benefits are paid without any increase in the GDP, while the economic growth stemming from the ELR could be in the range of €64 billion per year, that means, inter alia, more than €25 billion of new revenues for the State.

What About the EU?

To assess to what extent the calculation we made for Italy could be used for the EU as a whole, we take the first four economies of the area besides Italy (i.e. Germany, France, UK and Spain) and we extend the Table A.1 to them (the last column is the weighted sum of the four countries’ data):

As we can see, also for these countries the results are not much different and the weight of the five ELR sectors is even higher than in Greece. Given that the six countries we discussed so far make more than 70 % of the EU GDP, we will apply the “Greece multipliers” to the EU economy as a whole (see Table A.2). Using these coefficients we can simulate the impact of the scheme. We present the last disposable EU data in the following table ¹⁸ :

Table A.2 ELR program multipliers^a

Table A.3 Results

Table A.4 Input composition of the synthetic sector

Table A.5 Results

The gross cost of an ELR program for the EU would be around 1.5 % of the GDP. To put this number in the European context, we should consider that in the period 2008–2011, the average annual cost of employment policies by EU countries has been more than €61 billion. Around €200 billion per year to fund the program could seem a huge number. However, we should recall that between October 2008 and October 2012, EU countries mobilized €4500 billion to save their banks. This means almost 22 years of ELR funding in just four years. At the end of the day, employment of last resort would be cheaper than lending of last resort and we think at least as important.

Notes

• 1. See for instance, the IMF recent papers listed in the bibliography.

• 2. See Tymoigne (2006), Assenza et al. (2010), Bellofiore et al. (2010), Ferri (2010).

• 3. For further in-depth analyses see Tymoigne (2008) and Tymoigne (2010).

• 4. On the difficulty of implementing self-sustaining growth models, see Minsky (1965a, [1982]). An approach to the fight against poverty as distinct from economic growth is shared by a vast literature (Bell and Wray 2004; Wray 2007b; Tcherneva 2007, Kaboub 2007b; Dodd 2007, section 4).

• 5. http://epthinktank.eu/2014/08/13/in-work-poverty-in-the-eu/.

• 6. For a general analysis see Wray (1998) and his critical assessment by Aspromourgos (2000).

• 7. http://www.jobsletter.org.nz/jbl05210.htm.

• 8. We do not touch the aspect of the kind of works the ELR can bring about as it is an issue addressed in depth by the literature. For instance, a UNPD (2010) study proposes more than 50 different sectors of intervention.

• 9. The supporters of the basic income guarantees believe such measures to be effective against the drift towards job insecurity (Aronowitz and DiFazio 1994; Van Parijs 1995; Widerquist 2004). The debate on these themes is extensively illustrated by Tcherneva (2007).

• 10. For a more detailed examination of these issues, see Mastromatteo (2009) and Wray (2007a, b).

• 11. The importance given by Minsky to this issue does not imply the acceptance of Ricardian equivalence, crowding-out effects or budget constraints. See Arestis and Sawyer (2003, 2004) for more detailed investigation on the issue.

• 12. See, for instance, the documents of UNECE (http://www.unece.org/) and European Commission (2012).

• 13. http://www.newsweek.com/we-are-all-socialists-now-82577.

• 14. Pasinetti (2007) speaks of hyper-integrated human activity.

• 15. Environmental services; Constructions; Security and investigation services; Services to buildings and landscape; Office administrative and support; Education services and Social work.

• 16. The synthetic sector is built using the single sectors data weighted for their share of the total output.

• 17. Source: Bank of Italy Annual Report for 2013, Statistical Appendix (http://www.bancaditalia.it/pubblicazioni/relann/rel13/rel13it/app_13_totale.pdf).

• 18. Source: Eurostat (http://ec.europa.eu/eurostat/web/labour-market).