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Labour Economics 8 2001 103–129
www.elsevier.nlrlocatereconbase
Widening differences in Italian regional
unemployment
qGiorgio Brunello
a,b,c, Claudio Lupi
d, Patrizia Ordine
e,) aFaculty of Economics, UniÕersity of PadoÕa, PadoÕa, Italy
b
IZA, Bonn, Germany
c
CESifo, Munich, Germany
d
ISAE-Istituto di Studi e Analisi Economica, Rome, Italy
e ( )
Department of Economics, UniÕersity of Calabria, I-87036 ArcaÕacata di Rende CS , Italy
Received 8 June 1999; received in revised form 25 April 2000; accepted 19 September 2000
Abstract
Regional unemployment differentials among Italian regions have widened since the mid 1980s, especially between the leading Northern and Central areas and the less developed South. We suggest that the following elements are important to explain the observed
Ž .
phenomenon: a employment performance in the South has worsened considerably in the Ž .
presence of sustained labor force growth; b labor mobility from the South to the North–Central areas has sensibly declined with the reduction in earnings differentials and
Ž .
with the increase in social transfers per head; c real wages in the South are not affected by local unemployment conditions but depend on the unemployment rate prevailing in the
Ž .
leading areas; d the labor share increased particularly fast in the South during the 1970s,
q
Preliminary versions of this paper were presented at the ConferenceAThe Impact of Increased Economic Integration on Italy and the Rest of EuropeB, Washington, Georgetown University, 30 April–2 May 1999 and circulated as Fondazione Eni Enrico Mattei FEEM WP 54.99. We are grateful to Luigi Bonatti, Daniele Checchi, Annalisa Cristini, Miriam Golden, Juan Jimeno, Peter Lange, Paolo Leon, Jacques Melitz, Barbara Petrongolo and Chiara Saraceno for comments and suggestions and to Antonio Rigon of Sistemi Operativi and Giulio Fettarappa of Banco di Sardegna for having provided most of the data. Detailed comments from two anonymous referees helped us in significantly improving on the previous versions of the paper. The views expressed in this paper are solely the responsibility of the authors and do not involve ISAE or its staff. The usual disclaimer applies.
)Corresponding author. Tel.:q39-984-492-458; fax:q39-984-492-421.
Ž . Ž .
E-mail addresses: [email protected] G. Brunello , [email protected] C. Lupi ,
Ž .
[email protected] P. Ordine .
0927-5371r01r$ - see front matterq2001 Elsevier Science B.V. All rights reserved.
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mainly as a consequence of the elimination of institutions that allowed the presence of Ž .
significant wage differentials; e a parsimonious description of the increase in regional unemployment differentials is that the Northern and the Southern areas responded in an asymmetric way both to the increase in real social transfers per head and to the reduction in the real price of energy.q2001 Elsevier Science B.V. All rights reserved.
JEL classification: J61; J64
Keywords: Regional unemployment; Labor mobility; Italy
1. Introduction
Regional unemployment disparities are a well-documented feature of the Italian economy.1A relatively novel feature is that these disparities have widened rather sharply since the mid 1980s, mainly because of the rapid increase of Southern
2 Ž .
unemployment see Fig. 1 .
Different factors may have contributed to this result. On the one hand, long run regional unemployment differentials have varied asymmetrically with the increase in real social transfers per head and in the tax wedge and with the reduction in the real price of energy experienced by the Italian economy since the mid-1980s. On the other hand, poor employment performance in the South is not necessarily the outcome of negative and contemporaneous idiosyncratic shocks only, but can also be interpreted as the delayed response of firms to the removal of institutions allowing for regional differentials in collective labor contracts at the end of the 1960s, that increased sharply the southern labor share during most of the 1970s. This paper shows that, despite growing unemployment in the South, labor mobility from the South to the North has remained low and relative wages have not adjusted to reflect worsened local labor market conditions. This has happened because the North–Central areas of the country have acted as a leading region in wage settlements. We consider this as a crucial aspect, also in view of the new
Ž .
issues posed by the European Union. Following Saint Paul 1997 , we argue that if in a politically integrated area characterized by economic asymmetries wage formation is dominated by the economic interests of a leading region, then the conditions exist for regional unemployment disparities to be exacerbated. More generally, since regional unemployment mismatch is a widespread feature among and within European countries, we believe that interesting lessons can be learned by looking at the Italian emblematic experience. The study of the nature and
1 Ž . Ž .
See Attanasio and Padoa Schioppa 1991 and Bodo and Sestito 1991 .
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causes of widening disequilibria is fundamental for the implementation of national and super-national policies aimed at reducing regional disparities.
The paper is organized as follows: the next section is devoted to the discussion of some key features of local labor markets in Italy. Section 3 investigates the role of adverse shocks and asymmetric responses in shaping regional unemployment differentials. The relationship between regional wage determination and unem-ployment is the subject of Section 4. Labor and firm mobility issues are treated in Section 5. Section 6 concludes. An Appendix reports data sources.
2. Regional labor markets in Italy
When studying labor markets, the measurement of unemployment is an un-avoidable problem. The definition of unemployment used in this paper coincides with the ISTAT3definition until 1992. According to this definition, jobless people are considered as unemployed if they declare themselves as being without work and having looked for a job, independently of a real search having been carried out and of the time elapsed since the last search action. In practice, wait unemploy-ment is included in the unemployunemploy-ment measure. This definition is wider than the standard set by ILO in the Thirteenth International Conference of Labour
Statisti-Ž .
cians 1982 and may be more appropriate in those circumstances Awhere the
w x
conventional means of seeking work are of limited relevance, or where the labor
w x 4
market is largely unorganized or of limited scope ...B. On empirical grounds,
Ž .
Jones and Riddell 1999 find that the waiting sub-category of the non-employed displays a behavior similar to the unemployed and therefore they can be both considered in a single homogeneous measure of joblessness. With reference to the
Ž .
focus of the present paper, we note that both regional wide-sense unemployment rates and non-employment rates diverged in a similar way in Italy since the
Ž .
mid-1960s, with a dramatic burst after the early 1980s see Fig. 2 .
Table 1 reports the average annual changes of unemployment rates and the percentage changes of total employment and the labor force in four Italian geographical areas. This decomposition is performed for two sub-periods, 1970– 1979 and 1980–1994. While the former sub-period follows the wage push of the late 1960s, the second sub-period starts with Italian participation to the EMS and with the substantial reduction of union power in industrial relations.
Consider first the industrialized North–West. Compared to the 1970s, unem-ployment increased during the 1980s and 1990s at about the same pace, as a consequence of the contemporaneous slowdown both of labor force and of
3 Ž .
ISTAT Istituto Nazionale di Statistica is the Italian Central Statistical Office.
4
Resolution concerning statistics of the economically active population, employment, unemploy-ment and underemployunemploy-ment, adopted by the Thirteenth International Conference of Labour Statisticians
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G. Brunello et al.rLabour Economics 8 2001 103–129
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Decomposition of average annual changes of unemployment rates in four areas of the country
Du DN% DFL%
1970 – 1979
North–West 0.19 0.34 0.53
North–East 0.19 0.74 0.94
Center 0.21 0.32 0.55
South–West 0.41 0.67 1.13
South–East 0.25 0.85 1.12
North–Center 0.20 0.40 0.61
South 0.36 0.72 1.13
1980 – 1994
North–West 0.22 y0.09 0.14
North–East 0.11 0.50 0.61
Center 0.30 0.14 0.47
South–West 0.96 y0.29 0.91
South–East 0.75 y0.40 0.46
North–Center 0.23 0.11 0.36
South 0.90 y0.32 0.78
u is the unemployment rate. N and FL are the employees and labor force, respectively. Source:
historical statistics based on the Quarterly Labor Force Survey. See Appendix for details.
employment growth. In the North–East, unemployment growth was slower during the second sub-period, because labor force growth slowed down in the presence of sustained employment growth. In either period, employment growth has remained relatively fast, at close to 0.6% a year. In the central regions, employment slowed down more than the labor force in the second period, resulting in faster unemploy-ment rate growth. In the South, employunemploy-ment growth plummeted from more than 0.7% a year during the 1970s to negative growth in the 1980s and later. Since labor force growth remained relatively fast in the two periods, unemployment increased at a rate close to 1 percentage point a year.
A more detailed account is offered in Fig. 3, which makes it clear that the relative increase in unemployment differentials in the South compared to the rest
Ž . 5
of the country has been associated to: a faster labor force growth in the South; Ž .b slower employment growth in the 1980s and more serious job destruction in the 1990s. Although northeastern regions outperform the rest of the country in terms of employment growth since the mid-1980s, a comparison of employment rates shows a close pattern in the northern and central regions and growing
Ž .
differences with respect to the South see Fig. 4 .
These numbers point to the existence of important and widening unemployment differentials among Italian regions. A further and to some extent surprising aspect
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Table 2
Unit root tests of relative regional unemployment rates: P-values
Region WS ADF Z Region WS ADF Z
Piemonte 0.088 0.207 0.340 Lazio 0.702 0.451 0.757
Lombardia 0.208 0.887 0.599 Abruzzo 0.949 0.147 0.396
Trentino 0.489 0.668 0.385 Molise 0.257 0.224 0.299
Veneto 0.303 0.330 0.620 Campania 0.174 0.086 0.332
Friuli 0.817 0.193 0.340 Puglia 0.853 0.464 0.598
Liguria 0.203 0.380 0.153 Basilicata 0.090 0.238 0.125
Emilia 0.283 0.625 0.711 Calabria 0.049 0.156 0.143
Toscana 0.458 0.280 0.190 Sicilia 0.184 0.768 0.893
Umbria 0.434 0.351 0.184 Sardegna 0.789 0.903 0.602
Marche 0.163 0.185 0.403
Relative unemployment rates are defined as uiruITA, where u is the unemployment rate of region ii
Ž
and uITA is the national unemployment rate. WS is the Weighted Symmetric test see Pantula et al.,
. Ž .
1994 ; ADF is the augmented Dickey–Fuller test Said and Dickey, 1984 ; Z is the Phillips–Perron test
ŽPhillips and Perron, 1988 . All the tests include the constant and a drift: the number of lags is selected.
by using the AIC criterion.
of the data is that not only unemployment differentials exist, but they also diverge in a nonstationary way. In other words, there are no signs of a reversion of the observed diverging tendency towards a common equilibrium. This conclusion is formally supported by the results of tests for unit roots in regional relative unemployment rates. In no instance it is possible to reject the null hypothesis that uiruITAhas a unit root, when u is the regional unemployment rate and ui ITAis the
Ž .
nationwide unemployment rate see Table 2 . Interestingly, this outcome is
Ž .
squarely different from the results obtained by Eichengreen 1993 , who finds instead no evidence against stationarity. This difference can be easily explained with the choice of the sample period. Eichengreen’s data stop in the mid 1980s, before the real action starts.
3. Adverse shocks and asymmetric adjustments
Widening differences in regional unemployment rates can be explained either by the fact that regional shocks are more important than common aggregate shocks or by the fact that regional employment and unemployment respond asymmetri-cally to common aggregate shocks. Clearly, these are not mutually exclusive hypotheses, but we try to assess empirically their relative importance.
We start by investigating employment data using the regional accounts.
Follow-Ž . Ž .
ing Blanchard and Katz 1992 and Jimeno and Bentolila 1998 , we estimate the following empirical model for each region
1
Dln N
Ž
i t.
saiqÝ
b Dln Ni jŽ
i tyj.
q´i tŽ .
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Responsiveness of regional employment to aggregated shocks
a 2
Region R AR Norm b tbs0 Hbs1
P-values P-values P-values P-values
Piemonte 0.496 0.867 0.284 1.097 0.000 0.580
Lombardia 0.516 0.603 0.910 0.920 0.000 0.639
Trentino A. Adige 0.392 0.710 0.809 1.484 0.000 0.177
Veneto 0.380 0.058 0.121 0.876 0.000 0.563
Friuli V. Giulia 0.549 0.508 0.319 1.452 0.000 0.080
Liguria 0.171 0.403 0.035 0.683 0.023 0.275
Emilia Romagna 0.550 0.900 0.042 1.025 0.000 0.889
b
Toscana 0.440 0.008 0.000 1.149 0.000 0.559
Umbria 0.475 0.118 0.988 1.319 0.000 0.234
Marche 0.464 0.606 0.248 1.426 0.000 0.153
Lazio 0.152 0.100 0.490 0.551 0.033 0.080
Abruzzo 0.339 0.560 0.708 1.024 0.001 0.930
Molise 0.065 0.137 0.512 0.901 0.175 –
Campania 0.166 0.315 0.476 0.678 0.025 0.271
Puglia 0.285 0.083 0.036 1.084 0.002 0.798
Basilicata 0.045 0.817 0.299 0.773 0.262 –
Calabria 0.014 0.007 0.072 0.307 0.535 –
Sicilia 0.080 0.216 0.708 0.396 0.142 –
Sardegna 0.280 0.188 0.375 1.085 0.003 0.799
a Ž .
The table reports the results from the estimation of Eq. 1 . AR is the test for residual autocorrelation up to the second order. Norm is the normality test for residuals.b is the estimated coefficient. tbs0 is the marginal significance of the parameter. Hbs1 is the test forbs1; this test is carried out only for significant estimated parameters.
b
Toscana is the only region for which Ni ty1 is significant and has been added to the regression.b
Ž
and tbs0 in this case, refer to the sum of the coefficients on N and Ni t i ty1 tbs0 in this case, is the
.
P-value of the joint F-test .
where i is for region, t is for time, Ni t is regional employment in the private sector, measured by standard labor units, and N is aggregate employment in thei t private sector, region i excluded.6 The R2 of these regressions is an indicator of how much of the variation over time in regional employment is accounted for by
Ž .
variations in aggregate employment. The estimates of Eq. 1 are presented in Table 3 for the period 1965–1994. The table shows that the R2 is much lower in the South than in the rest of the country. This result suggests that idiosyncratic shocks are relatively more important in southern regions. The presence of persis-tent and widening unemployment differentials also points to the possibility that common trends among regional unemployment rates exist. Given p)2 variables, the existence of one common trend implies that there are py1 cointegrating
Ž . Ž .
vectors. Using Johansen’s approach see Johansen, 1995 , we find see Table 4
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Table 4
Ž . Ž .
Cointegration analysis of log- regional unemployment rates P-values
Geographical area p rs0 rF1 rF2 rF3 rF4
North–West 3 0.010 0.212 0.803
North–East 3 0.284 0.463 0.658
Center 5 0.125 0.242 0.360 0.579 0.968
South–West 5 0.211 0.798 0.867 0.959 0.907
South–East 3 0.145 0.247 0.689
p is the number of regions in the area; r is the cointegration rank. The P-values are from MacKinnon
Ž .
et al. 1996 .
that in none of the geographical areas is it possible to find only one common trend. The view that there are clusters of regions where unemployment rates follow a common long run path might be too simple. At the same time, the idea that idiosyncratic shocks are important seems reasonable.
Next, we describe in a parsimonious way the long run evolution of regional
Ž .
unemployment rates ui t by associating them to the movements of variables affecting both the supply and the demand for labor. We capture labor demand
Ž .
variations with the changes over time in the tax wedge ti t and in the real price of
Ž .
imported energy and materials PM . In the presence of real wage resistance, ant increase in the tax wedge leads to an increase of labor costs and to a reduction of labor demand. Changes in the price of raw materials also affect production costs and shift labor demand. Further, they may also affect local unemployment through changes in competitiveness, depending on local industrial structure. Labor supply
Ž .
variations are captured instead by government social transfers per head zi t . The
Ž .
bulk of these transfers consists of pension payments 79.6% of the total in 1991 , because the share of unemployment related benefits is very low by international
Ž .
standards see Peracchi and Rossi, 1995 . As remarked in the literature, one potential reason for the persistently high unemployment rate in the South is the presence of income transfers within southern households, from the employed and
Ž
the retired to the young unemployed see Attanasio and Padoa Schioppa, 1991; .
Bentolila and Ichino, 1998; Faini et al., 1996 . These transfers finance wait Ž
unemployment and maintain high reservation wages in the South see Brunello, .
1992; Mazzotta, 1998 . We do not have a direct measure of intra-household transfers, but we expect the size of these transfers to be influenced by government social transfers per head.7Social transfers affect labor supply because they have a significant role in shaping regional migration flows and individual participation decisions in the labor market. Notice that real social transfers per head could also affect regional labor demand when the production of goods and services is not
7
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symmetrically distributed across regions. In this case, higher social transfers increase household income and expenditure in all regions, but affect mainly the Žderived demand for labor in the regions where production is concentrated..
We carry out the analysis using the standard non-stationary VAR framework, as
Ž .
described by Johansen 1995 . For each region i we estimate the following VAR
Xi tsmiqPi ,1Xi , ty1q. . .qPi , kXi , tykq´i , t
Ž
is1, . . . ,19.
Ž .
2Ž . Ž . Ž . Ž .4
where Xi t' ln ui t , ln ti t , ln zi t , ln PMt . Given that the sample size is small Ž1964–1994 , we are forced to use a very parsimonious representation. Notice,. however, that cointegrating vectors are invariant to variable addition. Moreover, as
Ž .
shown by Abadir et al. 1999 , finite sample estimator biases in a purely nonstationary VARs are proportional to the dimension of the system and the addition of irrelevant variables has more serious consequences than in the standard
Ž .
stationary case. Lag length selection in Eq. 2 is accomplished for each region by initially setting ks4 and by sequential simplification, checking at each stage the standard system diagnostics.8 Using a 5% confidence level, we find at least one cointegrating vector for most of the regions, the only exception being Molise, a small region.
We summarize our results on cointegrating vectors in Table 5.9 Perhaps the strongest result is that real social transfers per head are positively associated to the rate of unemployment in most of the South and negatively associated in the North–Center. The positive association found in the South10 induces us to think that, by increasing household income and the opportunities for intra-household transfers, the main effect of higher social transfers per head in these areas of the country has been both to reduce the incentive to migrate of the young unemployed and to increase their reservation wages, thus encouraging wait unemployment and queueing for public sector jobs. In the North–Center, instead, the prevailing factor behind the increase in social transfers per head has been employment substitution of the retiring old with young labor market entrants, especially in the manufactur-ing industry durmanufactur-ing the second part of the 1980s, a process described asAyoung in,
Ž .
old outB by Contini and Rapiti 1994 . Compared to the South, labor force outflows due to retirement in the North–Center have been accompanied by employment inflows rather than by wait unemployment. We also speculate that real social transfers per head have affected regional labor demand in an
asymmet-8
The main diagnostics and the tests for cointegration rank in the selected models are available from the authors upon request.
9
When more than one cointegrating vector is present for a specific region, the table reports only the first vector. The other cointegrating vectors and the loading factors are available from the authors upon request.
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Table 5
Trentino A. Adige y19.710 4.464 y1.523 0.366
)
Veneto y17.500 4.370 y0.690 0.724
) )
Friuli V. Giulia y11.030 1.686 y1.557 0.793
)
Liguria 0.000 y0.370 0.000 0.601
Emilia Romagna y5.357 0.982 y1.024 0.109
) on the right of a coefficient indicates that the corresponding variable is weakly exogenous with respect to the long run parameters. P-restr is the P-value of the restrictions imposed for each region on the cointegrating vectors and the loading factors.
ric way, because the induced higher consumer expenditure is not equally dis-tributed across regions. Since the production of goods and services is more concentrated in the North–Center, the positive effect on local labor demand has been stronger in these areas and weaker in the South, where the negative labor supply effects on regional unemployment have prevailed.
We also find a positive association between the tax wedge and regional unemployment. This association is particularly strong in the North–Center and can be explained both by the greater importance in these areas of local bargaining and insider power, that increase real wage resistance,11 and by the presence in the South of a larger share of the underground economy, that insulates labor costs from changes in labor taxes. Finally, there is evidence of a positive long run association between the real price of energy and imported materials and regional unemployment in the industrialized areas of the North–Center and of a negative association in the South. Since labor and energy can be either substitutes or complements in production, depending on the technology, this finding could be
11
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driven by the fact that the composition of value added differ in the two areas. While manufacturing is more important in the North–Center, both agriculture and public services are more important in the South. These differences in productive structure can influence unemployment also via the price wedge in opposite directions in the North and in the South.12
While average tax rates have increased during the 1980s and 1990s, the real price of imported energy has significantly declined. On the other hand, real social transfers per head have increased both in the North–Center and in the South. The uncovered asymmetries in the long run association of social transfers per head, the real price of energy and the tax wedge with regional unemployment suggest that the positive association of regional unemployment differentials with higher real social transfers per head and with the lower real prices of energy has prevailed over the negative association between these differentials and the increase in the tax wedge.
4. Wages and unemployment
Poor employment performance in the South during the 1980s and the 1990s is not necessarily the exclusive outcome of negative idiosyncratic shocks taking place during the same period, but could also be the lagged response of firms to negative shocks that occurred much earlier. It is tempting to extend to the Italian South a recent interpretation of high European unemployment in the 1980s and 1990s, that views it as the result of the lagged response of capital to the Aappropriation pushBof the 1970s, when union pressure increased significantly the labor share. In a nutshell, the story goes as follows. With a putty-clay technology, capital is difficult to adjust in the short run, but in the long run both the substitution of capital to labor and the development of more capital intensive technologies can reduce employment and increase the profit share to values even
Ž .
higher than before the appropriation push Caballero and Hammour, 1998 . A
12
where i indicates the region North, South , c is the competitiveness, pi m is the price of imported energy and materials, p) is a world price index, p is the price index of the region, and e stands for
i
the exchange rate.ai and bi are proportional to the external exposure and to the dependence of the economy on imported materials, respectively. IfEerEp)andEp)rEp)are small, thenEPWr
imported energy and materials bi with respect to the openness to foreign markets ai, the higher is the probability of findingEPWr
Ep)-0. If this is the case, a rise in p) should imply a reduction in
i m m
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Table 6
Percentage changes in labor productivity, labor cost, labor share, and capitalroutput ratio Productivity Labor cost Labor share Capitalroutput
1970 – 1979
North–West 3.36 2.92 y0.43 2.25
North–East 3.10 2.79 y0.30 0.24
Center 3.55 3.83 0.27 1.44
South–West 3.04 4.23 1.15 5.59
South–East 3.48 4.90 1.36 3.10
North–Center 3.40 3.20 y0.20 1.58
South 3.16 4.40 1.20 4.82
1980 – 1994
North–West 2.69 1.40 y1.26 0.44
North–East 2.54 1.10 y1.40 0.03
Center 2.33 1.22 y1.08 0.73
South–West 2.15 0.53 y1.58 0.97
South–East 2.69 1.17 y1.48 0.36
North–Center 2.53 1.28 y1.23 0.48
South 2.31 0.72 y1.56 0.78
closely related story is that, while adverse labor supply shifts have been important for the increase of unemployment during the 1970s, wage moderation and rising capital shares can be consistent with high and rising unemployment in the 1980s
Ž .
only in the presence of negative labor demand shocks Blanchard, 1998 .
To illustrate the Italian experience, Table 6 shows the percentage changes in the labor share and in labor productivity in the private sector between 1970 and 1979 and between 1979 and 1994 for the different geographical areas.13 Furthermore, Fig. 5 shows that the divergence of regional unemployment rates was accompanied by nationwide convergence of labor costs, productivity, and capitalroutput ratios. As shown by Table 6, the labor share increased during the 1970s in the South and remained nearly constant on average in the Northern and Central regions. During the same period, the unemployment rate increased by close to 3.5 percentage
13
It is well known that the relationship between real wages and the labor share depends on the production technology. When the technology is Cobb Douglas, the labor share is constant and does not vary with changes in labor costs. When the technology is CES, however, the labor share sL varies with the capital–output ratio according to
´
sL ts1yŽAkt.
where k is the capital–output ratio and A is a measure of disembodied technical progress. See
Ž .
Bentolila and Saint Paul 1998 . In this case, real wages can affect the labor share only by affecting the capital–output ratio. Even when higher wages lead to a higher k, the labor share increases only if labor
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Fig. 5. Regional convergence of unemployment, labor cost, productivity, capitalroutput ratio over the period 1970–1994. Solid lines are the result of a robust
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Ž points in the South and by about 2 percentage points in the North–Center see
.
Table 1 . Interestingly, the increase in the labor share in the South was accompa-nied by positive employment growth, that limited the expansion of the rate of unemployment. During the 1980s and 1990s, the labor share fell faster in the southern than in other regions and unemployment boomed to its currently very high levels. While employment growth remained positive in the North–Center, it turned negative in the South where, at the end of the 15-year-period, employment was lower than in 1979. Since labor force growth remained high, unemployment had to increase.
The labor share in the South increased relatively to the national average during most of the 1970s and started to decrease in the early 1980s. The increase in the
Ž .
1970s was the result of the rapid growth of relative to the North wages, which
Ž .
was not compensated by relative labor productivity growth. As discussed in
Ž .
detail by Faini 1993 , an important event that hit specifically the South at the end of the 1960s was the elimination of institutional rules allowing for the existence of
Ž .
regional wage differentials in union contracts gabbie salariali . Following this Ž
event, only partially compensated by specific payroll tax breaks fiscalizzazione .
degli oneri sociali e sgraÕi contributiÕi , relative labor costs surged in the South
and the labor share increased. As unemployment started to increase, the share partially declined. The rapid increase of the capital stock in the South during this period was induced not only by the increase in labor costs, but also by political reasons. Therefore, the productivity of newly installed capital in the South was generally lower than in the North–Central regions and, while regional productivity converged at a nationwide level, productivity differentials remained important, and even increased, between the North–Center and the South.
The arguments above do not explain why regional unemployment differentials persist. From a theoretical standpoint, differences in regional unemployment can increase and persist when local wages are not sensitive to local economic conditions. This is the case when wage setting is relatively centralized and wage determination is influenced mainly by the economic conditions prevailing in the leading economic areas of the economy. When a negative shock increases
Ž .
unemployment in a backward region the South , wages are not significantly affected and higher unemployment can persist in the absence of other adjustment
Ž .
factors. When the same shock hits the leading region the North–Center , how-ever, wages are negatively affected and the decline in wage growth can contribute to reduce unemployment.14
When regions characterized by economic asymmetries are politically integrated, as in Germany and in Italy, national wage formation can be dominated by the
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economic interests of the leading regions.15 In this case, the failure of regional wages to respond to regional local conditions in some areas of the country can exacerbate unemployment differentials by eliminating an important adjustment mechanism. We empirically investigate this possibility by pooling regional data for 18 Italian regions during the period 1970–1994 and by estimating the following empirical model16
Dlnwi ts
Ý
aiDiqbTqdDln ui tqhDlnPMtqglnwi ty1i
quln uN ty1qsln ui ty1q´i t
Ž .
3where wi t is the real gross wage in region i, uN t is the unemployment rate prevailing in the North–Center, T is a linear trend, D is a set of regionali dummies, and ´i t is the error term. Since changes in the current regional unemployment rate are likely to be endogenous, we use 2SLS estimates. Our selected instruments are the lagged change in regional unemployment, changes in the national rate of unemployment and the first lag of a cyclical indicator, obtained as the residual from fitting regional real GNP on a quadratic trend.17
If the leading region hypothesis is correct, we expect to find that, conditional on the local unemployment rate, unemployment in the North–Center attracts a significant coefficient. In the extreme version of the Aleading areaB hypothesis, local unemployment does not affect local wages, which depend only on unemploy-ment in the leading area. Our estimates are presented in Table 7, where we show the long run elasticities of the real wage both to regional unemployment,hwu, and to unemployment in the leading area,hwun. When we consider all the regions, both regional unemployment and unemployment in the North–Center attract a signifi-cant and negative coefficient in the wage equation. Moreover, the long run wage elasticity of regional unemployment is about half as large as the long run wage elasticity of unemployment in the leading area. This finding confirms that unem-ployment in the North–Center plays a key role in Italian regional wage determina-tion. When we focus on the southern labor market, however, we find no evidence that regional unemployment significantly affect regional wages after controlling
15 Ž .
See Saint Paul 1997 for a discussion.
16 Ž .
In previous work Brunello et al., 2000 we have investigated the question by using aggregate data. Our evidence can be summarized with the following two points: 1. aggregate wage setting in Italy depends only on the rate of unemployment prevailing in the Northern and Central areas of the country. Southern unemployment does not affect wage pressure. 2. There is evidence of a long-run cointegrating relationship between unemployment in the Northern and Central areas, the tax wedge, the real interest rate and a measure of union power.
17
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Table 7
Elasticity of real wages to regional and North–Center unemployment in the private sector
Variable All regions Southern regions
Dependent variable: Dlnw. Sample period: 1970–1994. One asterisk and two asterisks when the coefficients are significant at the 10% and at the 5% level of confidence, respectively. White consistent standard errors.
for unemployment in the leading area. This result clearly supports the view that wage setting is not affected by southern unemployment.18
5. Labor and firm mobility
Much of the recent debate on Italian unemployment has been concerned with the role of labor and firm mobility. In this section we argue that although both these aspects are relevant, they are not sufficient to explain the dramatic widening of unemployment differentials among Italian regions.
Most discussions of unemployment disparities in Italy emphasize the substantial decline of labor migration from the Southern to the North–Center regions that occurred since the early 1970s.19 The basic facts are illustrated in Fig. 6, where we plot net wages in the South relative to net wages in the North–Center, the migration rate from Southern regions to the rest of the country and real govern-ment social transfers per head in the South. Relative net wages increased steeply during the 1970s but remained nearly constant during the 1980s and the 1990s. The out-migration rate from the South fell substantially in the early 1970s and remained low during the 1980s and the 1990s. Government social transfers per
Ž .
head prestazioni sociali , both in money and in kind, which include unemploy-ment benefits, social assistance, regular and invalidity pensions and health pay-ments, increased almost monotonously during most of the sample period.
18 Ž . Ž .
See also the evidence in Casavola et al. 1995 and Manacorda and Petrongolo 1999 .
19 Ž .
Spain has experienced a very similar situation. See Jimeno and Bentolila 1998 . The classic
Ž . Ž .
references for Italy are Attanasio and Padoa Schioppa 1991 , Bodo and Sestito 1991 , Faini et al.
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Table 8
Dependent variable: DM, Anderson–Hsiao estimates. Instruments: DMy2, My2, 1970–1993. Two asterisks indicate that the coefficient is significant at the 5% level of confidence. The regressions include constant and regional dummies.
Attanasio and Padoa Schioppa have used data for six areas of the country ŽNorth–West, North–East, Center, Rome, South–West and South–East and for. the period 1960–1986 to estimate an empirical model that associates net immigra-tion flows to local wages, naimmigra-tional wages, local and naimmigra-tional unemployment.20 In this section, we add to the existing evidence by estimating migration outflows from the eight Southern regions to the remaining Italian regions, using data that cover a more recent time period, 1970–1993. The available regional data are pooled together and we use fixed effects methods to control for region-specific unobservable variables. Our empirical error correction model is
Wi ty1 DMi ts
Ý
biDiqaDMi ty1qgMi ty1qdlnž
/
WN ty1 i
qqln ui ty1qkzi tq´i t
Ž .
4 where Mi t is the percentage of labor outflows with respect to the regional population in the previous year, and W and Wi t N t are the regional net wages and the average net wage prevailing in the North–Center. Our results are presented in Table 8. Given the dynamic nature of the panel of regions, we use the Anderson– Hsiao estimator. In particular, the lagged value of the change in the migration rate is instrumented by the second lag of the change and of the level of the same variable. Our evidence is that the rapid increase both of relative wages and of social transfers per head during the 1970s and the 1980s has significantly reduced migration flows, more than compensating the opposite effects on migration of higher regional unemployment. According to our estimates, a 1 percentage point increase in relative wages and in social transfers per head reduces migration outflows respectively by 2.786 and by 0.345 percentage points. On the other hand,20 Ž .
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a 1% increase in regional unemployment increases out-migration from the South by 0.185%.
An interesting thought experiment is to estimate the size of migration flows under the assumption that relative wages and real social transfers per head in 1993 are equal to their 1972 levels rather than being at their current levels. Given the low elasticity of migration to regional unemployment, an approximateAback of the envelopeB calculation suggests that outmigration from Campania, one of the largest Southern regions, would have increased from about three to about eight individuals out of a thousand per year. Assuming that all the additional migrants flow out of unemployment and of the labor force, the adjusted unemployment rate in 1993 would have been 20.5% rather than 25.5%. This experiment suggests that migration is only part of the story and that even resuming migration flows to the
Ž .
levels experienced in the early 1960s nine individuals out of a thousand would not solve the Southern unemployment problem.21
Non-convergence of unemployment rates may also arise if in the presence of increasing returns from localization both expected wages and expected profits depend positively on the number of firms operating in a given area. Apart from technological spillovers and availability of specialized inputs and services, labor pooling phenomena may induce localization by increasing wage flexibility and easing employment reallocation when uncertainty and idiosyncratic shocks are
Ž .
allowed Krugman, 1993 .
We have already seen that, in the Italian experience, the abolition of Agabbie
Ž .
salarialiB wage cages at the end of the 1960s led to the progressive convergence both of net and of gross wages among the North–Center and the South. This permanent regional supply shock could have induced firms to switch localization away from the South and in favor of the North–Center. In the presence of increasing returns from geographical concentration, regional disparities in net firm growth and net job creation could also have increased, and this trend could have only partially been tempered by the reduction in labor migration flows across regions. The dramatic increase of unemployment disparities among regions after the mid-1980s could be the result of this kind of process.
We use administrative data on firm and job creation at the provincial level22 to show that localization has played, if any, an equilibrating role. Fig. 7 portraits the result of a standard convergence analysis of Italian provinces in terms of firm and job creation, and shows that, both for enterprises and for employees, there are no signs of divergence.23 We conclude that localization issues have played only a
21
We are aware that the experiment illustrated in the text would need careful investigation of the exogeneity conditions. We are confident, however, that the main message is robust.
22
To focus on the private sector, we eliminate sectors where the public presence has been dominant. Results are robust to an extension to the full sample.
23
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Ž . Ž .
Fig. 7. Convergence of firm and job creation in Italian provinces 1985–1993 . The solid line is the result of a robust line fitting Tuckey, 1977 . Different symbols are used to represent provinces according to the geographical areas: circles indentify the provinces in the North–West; squares, North–East;
Ž . Ž .
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minor role, if any at all, in the widening of regional disparities between the North–Center and the South, at least since the mid 1980s, when unemployment divergence phenomena were stronger.
6. Conclusions
Regional unemployment differentials among Italian regions have widened since the mid 1980s, especially between the leading North–Center and the less devel-oped South. The empirical evidence reported in this paper suggests that the following elements are important to understand the observed phenomenon.
Ž .1 Employment performance in the South has worsened considerably in the presence of sustained labor force growth. Regional shocks have been more important than common shocks in this poor performance. A parsimonious descrip-tion of long run regional unemployment differentials is that unemployment in the North–Center and the South have varied asymmetrically with the increase in real social transfers per head and in the tax wedge and with the reduction in the real price of energy experienced by the Italian economy since the mid 1980s.
Ž .2 The labor share increased particularly fast in the South during the 1970s, mainly as a consequence of the elimination of institutions that allowed the presence of significant regional wage differentials. The significant relative slow-down of employment growth in the 1980s and 1990s in the South can be interpreted at least in part as the delayed response to the appropriation push of the 1970s, which was particularly strong in the area.
Ž .3 Real wages in the South are not affected by local unemployment conditions but depend on the unemployment rate prevailing in the leading North–Center. Hence, regional unemployment in the South is not tied down by regional wage dynamics.
Ž .4 Labor mobility from the South to the North–Center have sensibly declined with the reduction in earnings differentials and with the increase in social transfers per head. Limited mobility, however, is at best only part of the whole story. Firm localization also seems to have played a minor role.
In our analysis, social policy and wage determination play a key role. Both aspects have been recently singled out as important areas of policy action to improve labor market performance and reduce unemployment disparities in Eu-rope. In a recent report to the British and Italian Prime Ministers, Boeri et al. Ž2000 consider the British and the Italian experiences and come up with two.
Ž .
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Appendix A. Data sources
Most of the data used in this paper are drawn from regional accounts and from labor force surveys. The sample period is 1960–1994. Italian regions and
geo-Ž .
graphical areas are listed in Table 9 . The available time series have been built by Banco di Sardegna and Sistemi Operativi under the supervision of Giorgio Brunello and Gianni Toniolo. The main sources used in this task are as follows.
A.1. Regional accounts data
v ISTAT, Conti economici regionali. Anni 1980–1994.
v SVIMEZ, I conti economici del Centro-Nord e del Mezzogiorno nel
venten-nio 1970–1989, Il Mulino, 1993.
v ISTAT, Annuario di contabilita nazionale, 1986.
`
v Unioncamere, I dati regionali 1963–1974, Franco Angeli Editore, Milano,
1976.
v Tirloni, C. and Veronese, G., Banca dati regionali 1960–1991, Fondazione
ENI Enrico Mattei.
v CRENOS, Base dati per le regioni italiane 1960–1993, Cagliari 1997.
v Picci, L., Lo stock di capitale nelle regioni italiane, Working paper 229,
Dipartimento di Scienze Economiche, Universita’ di Bologna.
v Rossi, N., Sorgato, A. and Toniolo, G., I conti economici italiani: una
ricostruzione statistica 1890–1990, in Rivista di Storia Economica, n.10, 1993.
Table 9
Regions and geographical areas
Region Area Region Area
Piemonte North–West Marche Center
a
Valle d’Aosta North–West Lazio Center
Lombardia North–West Abruzzo South–East
Trentino Alto Adige North–East Molise South–East
Veneto North–East Campania South–West
Friuli Venezia Giulia North–East Puglia South–East
Liguria North–West Basilicata South–West
Emilia Romagna Center Calabria South–West
Toscana Center Sicilia South–West
Umbria Center Sardegna South–West
a
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A.2. Labor force data
v ISTAT, Statistiche del Lavoro, vol. 26, 1986.
v ISTAT, Occupazione e redditi da lavoro dipendente 1980–1994, 1995.
v ISTAT; Indagine sulle forze di lavoro medie annuali .Ž .
Additional data used in the paper have been provided by the Bank of Italy.
A.3. Variables
Ž .
PMsreal price of imported materials and energy. See Brunello et al. 2000 . UPsunionization rate. Data kindly provided by Daniele Checchi.
tsaverage tax wedge. The wedge is the ratio of payroll and income taxes
Ž .
over average wages. See Brunello et al. 2000 .
References
Abadir, K.M., Hadri, K., Tzavalis, E., 1999. The influence of VAR dimensions on estimator biases. Econometrica 67, 163–181.
Attanasio, O., Padoa Schioppa, F., 1991. Regional inequalities, migration and mismatch in Italy,
Ž .
1960–1986. In: Padoa Schioppa, F. Ed. , Mismatch and Labor Mobility. Cambridge Univ. Press, Cambridge.
Bentolila, S., Ichino, A., 1998.AHow Painful Is Unemployment?BEUI, mimeo.
Bentolila, S., Saint Paul, G., 1998.AExplaining Movements in the Labor Share.B CEPR Discussion Paper no. 1958.
Blanchard, O.J., 1998.ARevisiting European unemployment: unemployment, capital accumulation and factor prices.BNBER Working Paper no. 6566.
Blanchard, O.J., Katz, L., 1992. Regional evolutions. Brookings Papers on Economic Activity 1, 1–77. Bodo, G., Sestito, P., 1991. Le vie dello sviluppo. Il Mulino, Bologna.
Boeri, T., Layard, R., Nickell, S., 2000. AWelfare-to-Work and the Fight Against Long Term Unemployment.BReport to Prime Ministers Blair and D’Alema, mimeo.
Brunello, G., 1992. Un modello generazionale del mercato del lavoro italiano. Politica Economica 4, 61–100.
Brunello, G., Lupi, C., Ordine, P., 2000. Regional disparities and the Italian NAIRU. Oxford Economic Papers 52, 146–177.
Caballero, R., Hammour, M., 1998. Jobless Growth: Appropriability, Factor Substitution and Unem-ployment. Carnegie–Rochester Conference on Public Policy vol. 48, pp. 51–94.
Casavola, P., Gavosto, A., Sestito, P., 1995. Salari e mercati del lavoro locali. Lavoro e Relazioni Industriali 2, 39–83.
Contini, B., Rapiti, F., 1994. Young In Old Out: nuovi pattern di mobilita nell’economia italiana.`
Lavoro e Relazioni Industriali 1, 51–76.
Eichengreen, B., 1993. Labor markets and European monetary unification. In: Masson, P., Taylor, M.
( )
G. Brunello et al.rLabour Economics 8 2001 103–129 129
Faini, R., 1993. Stesso lavoro diverso salario? In: Galimberti, F., Giavazzi, F., Penati, F., Tabellini, G.
ŽEds. , Nuove Frontiere della Politica Economica. Milano: Il Sole 24 ore..
Faini, R., Galli, G., Rossi, F., 1996. AMobilita e disoccupazione in Italia: un’analisi dell’offerta di`
lavoro.BCentro Studi Confindustria, Working Paper no. 6.
Ž .
Jimeno, J., Bentolila, S., 1998. Regional unemployment persistence Spain 1976–1994 . Labour
Ž .
Economics 5 1 , 25–52.
Johansen, S., 1995. Likelihood-Based Inference in Cointegrated Vector Autoregressive Models. Oxford Univ. Press, Oxford.
Jones, S.R., Riddell, W.C., 1999. The measurement of unemployment: an empirical approach. Econometrica 67, 147–161.
Krugman, P., 1993. Geography and Trade. MIT Press, Cambridge, MA.
MacKinnon, J.G., Haug, A.A., Michelis, L., 1996.ANumerical Distribution Functions of Likelihood Ratio tests for Cointegration.BGREQAM, mimeo.
Manacorda, M., Petrongolo, B., 1999.AChanges in Unemployment and Wage Differentials Across Italian Regions. Demand Shocks or Excess Wage Pressure?BMimeo.
Mazzotta, F., 1998. Salario di riserva e probabilita di successo della ricerca di lavoro in Italia: una`
stima sul nuovo panel ISTAT. Lavoro e Relazioni Industriali 5, 115–174.
Pantula, S.G., Gonzalez-Farias, G., Fuller, W.A., 1994. A comparison of unit-root tests criteria. Journal of Business and Economic Statistics 12, 449–459.
Peracchi, F., Rossi, N., 1995.ANonostante tutto e una riforma.` BUniversity of Rome II, mimeo. Phillips, P.C.B., Perron, P., 1988. Testing for a unit root in time series regression. Biometrika 75,
335–346.
Said, S.E., Dickey, D.A., 1984. Testing for unit roots in autoregressive-moving average models of unknown order. Biometrika 71, 599–607.
Saint Paul, G., 1997.AEconomic Integration, Factor Mobility and Wage Convergence.B CEPRrDiscus-sion Paper no. 1597.
