The Wage Premium in Italian Cities

Abstract

In most countries urban workers enjoy higher wages than non urban ones, and this premium increases with the size of the city. In this paper we show that in Italy hourly wages of private-sector workers are 6% higher in urban areas than in non-urban local labor markets (less than 2% controlling for observable workers’ characteristics); this premium is higher for more educated workers and for women. More generally, as the local population grows, hourly wages tend to increase: doubling population increases wages by 2.1% (less than 1% net of workers’ characteristics). Even larger gaps are usually estimated in other developed countries. Using an employer-employee dataset and a standard AKM wage decomposition, we divide Italian wages into two components, one proxying for worker’s skills and the other one proxying for firm’s quality. We find that better workers and better firms both tend to sort themselves in urban areas. Nevertheless, the sorting of workers seems to be more relevant than the sorting of firms, resulting in a larger urban premium for the workers’ component. The sorting of firms is almost entirely explained by a few characteristics of the local labor market, such as higher educational attainment and labor market participation.

Appendices

Appendix 1: Urban Switchers

In regressions on longitudinal data with individual fixed effects, the urban wage premium is estimated only through non urban to urban movers or urban to non urban ones.

Table 13 provides the numbers of stayer in non urban areas and urban ones and the transition flows from one type of LLM to the other one. In each year for which we can compute the transitions there are about 2.5% of workers who switch from a urban to non urban LLM and vice versa, about 33% who stay in a non urban LLM (or switch from a non urban LLM to another non urban LLM) and about 62% who stay in an urban LLM (or switch from an urban LLM to another urban LLM).

Table 13 Transitions of workers from and to urban areas

Appendix 2: Tests of the Exogenous Mobility Assumption

The AKM wage decomposition has been criticized by the literature for failing to account for endogenous mobility.

The error term might be structurally related to the assignment of workers to employers either through search dynamics (Mortensen 2005; Lentz 2010), coordination frictions (Shimer 2005), or learning (Gibbons et al. 2005). In this section we present a series of tests of the exogenous mobility assumption suggested by Card et al. (2013) and Card et al. (2016).

First of all, we verify whether mobility is based on the value of the worker-firm match. If the exogenous mobility assumption is violated due to sorting based on the value of the match, then the wage premium would include a match component that would be specific to each worker-firm pair.

To test for such sorting, we look at wage changes for job movers. We consider all job changers with at least two consecutive years both in the old and in the new firm. We classified firms in every year of analysis (from 2005 to 2014) in quartiles on the basis of the average daily wages. We exclude firms with less than 10 employees in order to avoid that a single worker may affect the average wage in a substantial way. Under the exogenous mobility assumption, workers who move between firms in the same quartile should not experience any wage change. Also, workers who move from a low quartile to a high quartile should experience a wage increase; conversely, workers who move in the opposite direction should have a roughly symmetrical wage reduction. If workers change firms on the basis of a match component, then job changes in the same quartile will be associated with wage increases, and the loss for movers from firms in a high quartile to firms in a low quartile will experience a smaller wage change with respect to movers in the opposite direction.

Table 14 and Fig. 2 show that workers who move from a low-paying firm to a high-paying firm experience wage increases that are increasing with the gap between origin and destination quartiles; workers who move in the opposite direction experience similar wage declines. This symmetry is in line with the predictions of the AKM model.

Fig. 2

Source INPS and INVIND 2005–2014.

Movers from 1st and 4th quartiles

Table 14 Mean wages before and after job change

Then, according to Fig. 3, wages of movers who stay within the same quartile are essentially unchanged. The lack of a mobility premium suggests that idiosyncratic worker-firm match effects are not crucial in order to explain job mobility.

The exogenous mobility assumption would also be violated if the idiosyncratic component of wages is associated with transitions between high-wage and low-wage firms. This would be the case, for instance, if wages of movers showed an upward trend in the years before the move. Table 14 reveals that wages of movers show no systematic trend prior to job change. In other words, wage fluctuations do not predict mobility patterns.

Fig. 3

Source Inps-Invind 2005-2014.

Movers within the same quartile

Another way to test for the importance of idiosyncratic worker-firm match effects is the comparison of the AKM decomposition and a match fixed effects regression. If match effects are important, such a model should perform better than the AKM model in terms of statistical fit. We find that the match fixed effects model has an adjusted R$^2$ that is slightly lower (0.918), and a Root MSE slightly higher (0.139) than those from the AKM regression (0.946 and 0.112). Thus, the match component in wages seems to have no a big relevance in explaining wages.

Finally, we examine residuals from the AKM regression. Following the preceding literature, we form deciles based on the estimated worker and firm effects, and compute average residuals in each cell. The mean residuals by cell are generally very small. In 99 cases out of 100, the mean residual is smaller than 0.01 in magnitude (in line with Macis and Schivardi 2016). The largest deviations appear among the highest-decile workers and the highest-decile firms.