1. LA CREAZIONE DI POSTI DI LAVORO NEL COMPARTO TURISTICO. QUALE RILEVANZA PER LA STAGIONALITA’? III Workshop PRIN “Frammentazione e Sviluppo Locale: Modelli Interpretativi e Scenari di Politica Economica” Novara 28 giugno 2007 G. Guidetti* e L. Zamparini** * Università degli Studi di Bologna ** Università del Salento

2. Struttura della presentazione Theoretical introduction Theoretical introduction The databases The databases Descriptive statistics Descriptive statistics

3. Dynamic labour demand with adjustment costs Adjustment costs In addition to wages, labour costs are given by hiring and firing expenses. The former include monitoring and training costs; the latter any outlay related to the procedure of lay-off of redundant employees.

4. The shape of the hiring costs curve In standard models, symmetric convex adjustment costs are assumed, with the typical U-shaped profile. However, it seems more plausible (Nickell, 1986) to assume that the profile of hiring and firing curves are different. For low levels of hiring it seems more reasonable to assume that marginal costs are not increasing, whereas when the hiring rates overcome a given threshold, increasing marginal hiring costs can be observed.

5. The shape of firing costs curve As to firing costs, it seems reasonable to assume the same shape as hiring costs, although the non-convex initial profile might be smaller than the one noticeable for hiring costs.

6. The dynamic optimization of the employment level The formal problem of optimization, when adjustment costs are relevant, is given as follows (Nickell, 1986): Max

7. Results of the optimization problem (1) Anderson (1993) shows that, when hiring, the following condition has to hold: The marginal revenue product of labour has to outweigh the real wage plus hiring costs.

8. Results of the optimization problem (2) On the other hand, when firing, the following condition has to hold: The losses due to a decrease in revenues plus firing costs have to be offset by a decrease in wage costs.

9. What happens if these two inequalities hold ? and

10. If both the two previous inequalities hold, then neither hiring nor firing occurs. These two inequalities identify the so-called “no action area”. As a matter of fact, if both inequalities hold it is optimal for the employer to neither hire nor fire. The higher adjustment costs (hiring and firing), the wider the “no action area”.

11. For our purposes, when product demand exhibits a highly seasonal profile, labour demand fluctuations can be assumed to be comparatively predictable, which implies that employers can exploit (decreasing average hiring costs) by implementing standardised and stable procedures to monitor the labour market and to find the suitable employees from both a quantitative and qualitative perspective.

12. Therefore, one can assume that average hiring and firing costs decrease as the level of both hiring and firing rate increases, at least until a given threshold. Non-convex adjustment costs prevail. The higher the degree of predictability of seasonal labour demand the higher the degree of volatility of the level of employment. The same considerations are worth for firing procedures and their related costs.

13. The databases Data about arrivals, tourist nights and number of room in hotels have been provided by local APT and, after their closing down, by local Administrations. Data about arrivals, tourist nights and number of room in hotels have been provided by local APT and, after their closing down, by local Administrations. All data about employment have been provided by INAIL. All data about employment have been provided by INAIL. Empirical analysis refers to the nine Provinces of Emilia-Romagna Empirical analysis refers to the nine Provinces of Emilia-Romagna

14. Tourist nights (Quarterly data) 1

15. Employment in tourism sectors (1)

16. Tourist nights (Quarterly data)- 2

17. Employment in tourism sectors (2)

18. Tourist nights (coefficient of variation)

19. Arrivals (coefficient of variation)

20. Gini coefficient - Arrivals

21. Gini coefficient – Tourist Nights

22. (Occupancy ratio – Quarterly data) -1 (Occupancy ratio – Quarterly data) -1

23. (Occupancy ratio – Quarterly data) -2

24. Ratio of change in FTE employees in hotels and in overall employment - 1

25. Ratio of change in FTE employees in hotels and in overall employment - 2

26. Ratio of change in FTE employees in hotels and in overall employment - 3

27. Coefficient of variation of FTE employees in the nine Provinces of Emilia-Romagna in tourist sectors PiacenzaParma Reggio Emilia ModenaBolognaFerraraRavenna Forl ì Cesena Rimini 20000.0350.1050.0310.0260.0150.1240.3660.3980.578 20010.0570.0950.0270.0400.0130.1520.3610.3410.535 20020.0540.1040.0270.0470.0240.1530.3400.3180.505 20030.0060.0790.0270.0220.0120.1380.3070.2740.414 20040.0500.0770.0410.0320.0170.1260.2750.2240.357 20050.0070.0660.0130.0170.0110.1220.2900.2200.357

28. Few preliminary conclusions The dynamic labour demand model with adjustment costs is consistent with the higher degree of variability of employment in Provinces such as Rimini, Ravenna, Forlì-Cesena and Ferrara. For these Provinces the higher degree of variability of the level of employment in tourism sectors depends on the higher level of seasonal variability, as far as tourist nights and arrivals are concerned

29. A high degree of seasonality in the demand for tourism services favours the implementation of formal and informal tools for monitoring the labour market, training the newly employees and, in general, smoothing transaction costs arising from the management of the workforce. These tools decrease the average costs of hiring and firing procedures, narrowing the “no action area”.

30. Very preliminary analysis of correlation seems to confirm our hypothesis. After using the X11 technique to adjust the time series for both trend and seasonal components we find, at least for Rimini and Forlì-Cesena, a significant correlation between employment and tourist nights.

31. Furthermore, if one correlates change in employment for each quarter, with change in tourist nights lagged by one year, one finds that the higher coefficient of variation of employment, the higher the index of correlation. The provinces where employment shows the highest seasonal fluctuations exhibit the highest correlation between employment and tourist nights → high degree of labour market flexibility.