Ageing in the labour market: a spatial VAR approach

ABSTRACT

This study examines the effects of ageing on per capita labour income, consumption and wealth of the working population in Italian provinces. Starting from the overlapping generations (OLG) model of perpetual youth, we estimate a spatial vector autoregressive (VAR) model to investigate how ageing affects the model’s dynamics. We find that ageing positively impacts per capita labour income and wealth, consequently having an adverse effect on consumption (over-accumulation). A simple exercise shows that over-accumulation is beneficial to the Italian social security system.

KEYWORDS:

• ageing
• spatial vector autoregressive
• overlapping generations (OLG) models
• labour market

JEL:

• C33
• D15
• H55
• J11

ACKNOWLEDGEMENTS

The authors thank two anonymous referees for helpful and constructive comments. The usual disclaimer applies.

DISCLOSURE STATEMENT

No potential conflict of interest was reported by the authors.

Notes

1 It is assumed that the retirement age is fixed proportionally to population ageing by law.

2 We thank an anonymous referee for this citation.

3 In particular, if labour income decreases with age, the model produces over- rather than under-investment (Acemoglu, 2009, p. 466).

4 Following the suggestion of an anonymous referee, we tried an alternative type of spatial matrix (K-neighbours, with k = 5, 7, 9). The results are barely affected by different assumptions about the spatial matrix.

5 The max eigenvalue of $C$ is 0.871.

6 For more details, see Table B1in Appendix B in the supplemental data online.

7 However, as requested by an anonymous referee, we tested the strict exogeneity according to Wooldridge (2010, section 10.2.2). The exogeneity test confirms our assumptions.

8 In order to give more certainty to workers, the National Social Security Institute (INPS) launched, in 2015, a sort of ‘orange envelope’, as in Sweden. Each worker can view a simulation of his/her future pension benefit by logging onto the individual position in the INPS database.

9 Source: ILO forecast.