Labour market adjustments in Europe and the US : how different?
Date: 2015-07-10
Institutions: European Central Bank
Subjects: Europe, United States, labour market, labour mobility, migration

Working Paper Series 

Robert C. M. Beyer  
and Frank Smets 

Labour market adjustments 
in Europe and the US: 

How different? 

No 1767 / March 2015 

Note: This Working Paper should not be reported as representing the views of the European Central Bank (ECB). 
The views expressed are those of the authors and do not necessarily reflect those of the ECB 

 
Acknowledgements 
The views expressed in this paper are our own and not necessarily those of the European Central Bank or its Governing Council. We 
are grateful to Nicola Fuchs-Schündeln, Michele Lenza, Giuseppe Bertola, Domenico Giannone, Ana Lamo, Jens Suedekum, Renata 
Hofmeister, four anonymous referees, to the participants of the 2013 ECB-CEPR conference on ’Heterogeneity in currency areas and 
macroeconomic policies’ at the European Central Bank, and to seminar and workshop participants at Goethe Universität, DIW, and 
Deutsche Bundesbank for helpful comments. Paper presented at the 60th Panel Meeting of Economic Policy in October 2014. 

Robert C. M. Beyer 
Goethe University Frankfurt; e-mail: robert.beyer@hof.uni-frankfurt.de 

Frank Smets 
European Central Bank, KU Leuven; e-mail: frank.smets@ecb.int 

© European Central Bank, 2015 

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ISSN 
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978-92-899-1580-9 
QB-AR-15-007-EN-N 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
Abstract

We compare the labour market response to region-speciﬁc shocks in Europe and the US

and to national shocks in Europe and investigate changes over time. We employ a multi-level

factor model to decompose regional labour market variables and then estimate the dynamic

response of the employment level, the employment rate and the participation rate using the

region-speciﬁc variables and the country factors. We ﬁnd that both in Europe and the US

labour mobility accounts for about 50% of the long run adjustment to region-speciﬁc labour

demand shocks and only a little more in the US than in Europe, where adjustment takes twice

as long. In Europe labour mobility is a less important adjustment mechanism in response to

country-speciﬁc labour demand shocks that cause stronger and more persistent reactions of the

employment and the participation rate. However, we detect a convergence of the adjustment

processes in Europe and the US, reﬂecting both a fall in interstate migration in the US and a

rise in the role of migration in Europe. Finally, we show that part of the diﬀerence between

Europe and the US in previous studies may be due to the use of diﬀerent data sources.

JEL Classiﬁcation: F2, J6, R23, R30

Keywords: labour mobility, regional labour markets, migration, European integration

ECB Working Paper 1767, March 20151Non-technical Summary: Since the outbreak of the ﬁnancial crisis, high and diverging unem-

ployment rates across European countries and regions have become an increasingly important

concern for European policy makers. Heterogeneity is large not only between countries but

also within countries. For example, in France, Belgium and Spain the highest regional unem-

ployment rates are twice as high as the lowest. These diﬀerences in unemployment rates across

regions and countries have put the role of migration in labour market adjustment back on the

European policy agenda. Migration can cushion the negative impact of adverse labour demand

shocks on unemployment and thereby smooth the adjustment to heterogeneous macroeconomic

developments.

We investigate how labour markets adjust to region- and country-speciﬁc labour demand

shocks and whether migration contributes substantially to this adjustment. Looking at the full

sample from 1976 to 2013 we ﬁnd that both in Europe and the US labour mobility accounts

for about 50% of the long run adjustment to region-speciﬁc labour demand shocks. The other

50% is accounted for by a reallocation of jobs across regions. But in Europe it takes longer (10

years) than in the US (5 years) for this adjustment process to be completed. And due to the

greater rigidity of labour markets, the temporary response of the unemployment rate is more

important and more persistent in European regional labour market adjustment.

We next show that in Europe labour mobility is a less important adjustment mechanism in

response to country-speciﬁc labour demand shocks. In this case, both the unemployment rate

and the participation rate play a larger and more persistent role in the adjustment process. This

underlines the remaining cultural, language and institutional barriers to labour mobility across

European countries and provides support to European policy initiatives to further facilitate

migration across countries.

Our sample covers 38 years, which allows us to investigate whether the adjustment process

has changed over time. Since the early 1990s European integration has continued to proceed

in a number of areas which should facilitate the regional adjustment process. There is, for

example, evidence that migration between European countries has increased due to the Schen-

gen Agreement and the introduction of the euro (Beine et al., 2013). In contrast, interstate

migration in the US has been decreasing since the 1980s and has dropped during the crisis to

the lowest values since World War II (Frey, 2009). It is therefore interesting to see whether

this has led to a convergence of the regional labour market adjustment process in Europe and

the United States.

In line with Dao, Furceri and Loungani (2014), we ﬁnd that the role of migration in the

regional adjustment process has decreased in the US. In contrast, in Europe migration has

become a more powerful adjustment factor in response to both regional- and country-speciﬁc

labour demand shocks. This suggests that the acceleration of the European integration pro-

cess after the early 1990s has led to more labour mobility across regions and countries. The

adjustment processes in Europe and the US have consequently converged reﬂecting both a fall

in interstate migration in the US and a rise in the role of migration in Europe.

Our ﬁndings can inform the policy debate in at least two dimensions. First, most of the

ECB Working Paper 1767, March 20152diﬀerences in the role of migration in the regional labour market adjustment process between

the US and Europe are due to remaining barriers connected with country borders. It is therefore

right for European policy makers to focus on how to facilitate labour mobility across countries

in Europe. However, our analysis also reveals that the diﬀerences with the United States, a

monetary union with a quite homogenous culture and a well-functioning labour market, are

not that large. Given that cultural and language barriers are likely to persist in Europe, it is

therefore important to be realistic about what increased labour mobility can achieve.

ECB Working Paper 1767, March 201531

Introduction

Since the outbreak of the ﬁnancial crisis in 2008, high and diverging unemployment rates across
European countries and regions have become an increasingly important concern for European policy
makers. In 2013 the unemployment rate in Spain was above 25%, but only around 5% in Germany.
Heterogeneity is large not only between countries but also within countries. For example, in France,
Belgium and Spain the highest regional unemployment rates were twice as high as the lowest. In
Italy, as an extreme example, the unemployment rate in Veneto was just a third of the unemploy-
ment rates in Campania or Sardinia. Moreover, this regional heterogeneity has increased since 2008
(Marelli, Patuelli, and Signorelli, 2012).

These diﬀerences in unemployment rates across regions and countries have put the role of mi-
gration in labour market adjustment back on the European policy agenda. Migration can cushion
the negative impact of adverse labour demand shocks on unemployment and thereby smooth the
adjustment to heterogeneous macroeconomic developments. This is particularly important within
a monetary union, in which relative wage adjustments may be slow due to the absence of nominal
In 2013 the Commission adopted a proposal for a directive on new
exchange rate adjustments.
measures to facilitate labour mobility and the European Council agreed on measures to ﬁght youth
unemployment aiming, among other things, at increasing the mobility of young workers.

In this paper we contribute to this policy debate by empirically investigating how labour markets
adjust to asymmetric labour demand developments and whether migration contributes substantially
to this adjustment, using a modiﬁed version of the methodology of Blanchard and Katz (1992).
In particular, we compare regional and country labour market adjustment in Europe with state
adjustment in the US. The US is a natural benchmark for such a comparison because it is a large
monetary union of similar size with a well-functioning, quite homogenous labour market. The US
benchmark may therefore give an idea of how much scope there is for increased labour mobility and
migration to play a role in labour market adjustment in Europe.

We are not the ﬁrst ones to make this comparison. In particular, Decressin and Fat´as (1995) and
Obstfeld and Peri (1998) also applied the methodology of Blanchard and Katz (1992) to compare
regional labour market adjustment in Europe and the United States.1 Overall, they found that the
regional adjustment process is faster in the United States due to higher labour mobility. There are
at least three reasons why it is important to update and reﬁne this analysis.

First, we have a much longer sample (38 years rather than 13 years in Decressin and Fat´as
(1995)). This allows us to investigate the robustness of their ﬁndings and, more importantly,
whether the adjustment process has changed over time. Since the early 1990s European integration
has continued to proceed in a number of areas which should facilitate the regional adjustment
process. There is, for example, evidence that migration between European countries has increased

1See Section 2 for a more detailed overview of the literature.

ECB Working Paper 1767, March 20154due to the Schengen Agreement and the introduction of the euro (Beine, Bourgeon, and Bricogne,
2013). Some of these changes have become quite visible since the outbreak of the ﬁnancial crisis.
For example, net migration between Germany and the crisis countries (Spain, Portugal, Italy and
Greece) has risen from minus 10.000 in 2009 to 70.000 in 2012. In contrast, interstate migration
in the US has been decreasing since the 1980s and has dropped during the crisis to the lowest
values since World War II (Frey, 2009). It is therefore interesting to see whether this has led to a
convergence of the regional labour market adjustment process in Europe and the United States.

Secondly, when comparing Europe and the United States, Decressin and Fat´as (1995) did not
make a distinction between regional labour market adjustment within countries and between coun-
tries, while Obstfeld and Peri (1998) only focused on adjustment within countries. In this paper, we
use the common factor methodology of Greenaway-McGrevy and Hood (2013) to ﬁlter out country
factors and analyse the adjustment of countries to national labour demand shocks, which is likely
to be hampered by bigger cultural, language and institutional diﬀerences. This allows us to investi-
gate whether any convergence with the US is due to a smoother working of the adjustment process
within or between countries.

Thirdly, a straightforward comparison of the European and US results was hampered by the
diﬀerent data sources being used in those studies. We show that the diﬀerences are less pronounced
when similar data sources are used.

The following ﬁndings are worth highlighting. First, looking at the full sample we ﬁnd that
both in Europe and the US labour mobility accounts for about 50% of the long run adjustment
to region-speciﬁc labour demand shocks. The other 50% is accounted for by a reallocation of jobs
across regions. But, in Europe it takes longer (10 years) than in the United States (5 years) for
this adjustment process to be completed. And due to the greater rigidity of labour markets,the
temporary response of the unemployment rate is more important and more persistent in European
regional labour market adjustment. Second, we show that in Europe labour mobility is a less
important adjustment mechanism in response to country-speciﬁc labour demand shocks. In this
case, both the unemployment rate and the participation rate play a larger and more persistent role in
the adjustment process. This underlines the remaining cultural, language and institutional barriers
to labour mobility across European countries and provides support to European policy initiatives to
further facilitate migration across countries. Third, in line with Dao, Furceri and Loungani (2014),
we ﬁnd that the role of migration in the regional adjustment process has decreased in the US. In
contrast, in Europe migration has become a more powerful adjustment factor in response to both
regional- and country-speciﬁc labour demand shocks in the second half of the sample (1990-2013
versus 1977-1999). This suggests that the acceleration of the European integration process after
the early 1990s has led to more labour mobility across regions and countries.

In the rest of the paper, we ﬁrst brieﬂy review in Section 2 how migration is typically analysed in
the literature. Section 3, presenting the Blanchard-Katz methodology and our modiﬁcations, may

ECB Working Paper 1767, March 20155be skipped by readers only interested in the results. The data is presented and discussed in Section
4 and Section 5 contains the main empirical analysis. Section 6 links our results to Blanchard and
Katz (1992) and is not relevant for the main message. Finally, Section 7 discusses some policy
implications.

2 Studying Migration

The importance of labour migration in facilitating adjustment to asymmetric shocks in a monetary
union has been recognised at least since the seminal research on optimal currency areas of Mundell
(1961). The empirical analysis of migration has, however, been hampered by the lack of reliable
data. Recently an increasing number of papers have started to analyse migration patterns directly.
Molloy, Smith and Wozniak (2011) analyse changes in the US over the last 30 years and detect a
widespread decline in movements across all distances and across all population sub-groups. Frey
(2009) shows that migration rates in the US recently reached their lowest value since World War
II and that the decline was strongest for interstate migration. Reasons for the decline in mobility
remain, however, unclear.2 Beine et al. (2013) with a new dataset containing 30 countries and
covering the period 1980-2010 come to contrary conclusions regarding migration in Europe. They
ﬁnd that both the Schengen Agreement and the introduction of the Euro have increased migration
between the member countries. However, migration between countries covers only a small part of
all movements. In Germany, for example, roughly twice as many people move every year within
Germany from one state to another than from Germany to another country.

Due to a lack of reliable data to analyse regional labour mobility directly, a large part of the
In their
literature has pursued the indirect approach proposed by Blanchard and Katz (1992).
seminal paper on regional evolutions they develop a small model of regional labour markets (in
the following: BK model) and suggest estimating the joint behaviour of the employment growth,
the employment rate and the participations rate to analyse regional labour market adjustments to
regional labour demand shocks. The respective reduced-form vector autoregression model (VAR)
that they derive from their theoretical model oﬀers an indirect approach to study migration because
all employment changes unexplained by either the participation or the employment rate must
originate from a change in population, which is identiﬁed with migration.

Applying the methodology to US states, Blanchard and Katz (1992) ﬁnd that as of the ﬁrst
year migration plays a dominant role in the adjustment process following a shock to regional labour
demand. Decressin and Fat´as (1995) analyse large Western European regions and compare them

2Demographics and an aging of the population, increasing home ownership rates and an increasing share of women
in the labour force may matter. Glaesser and Tobio (2007) discuss the role played by very long-term adjustment
processes over many centuries that may have been concluded. Dao et al. (2014) point to a decreasing dispersion of
regional labour markets. Earlier papers detecting a decline include Greenwood (1997) and Long (1988). The recent
decline in migration in the US may be somewhat overestimated (Kaplan and Schulhofer-Wohl, 2012).

ECB Working Paper 1767, March 20156to US states and ﬁnd that in Europe the participation rate is the major force driving adjustment.
Obstfeld and Peri (1998) analyse how regions in the US, Canada, the UK, Germany and Italy react
to asymmetric labour demand shocks and show, ﬁrst, that regional real exchange rates play a minor
role in the regional adjustment process and, second, that the US adjustment process is the fastest
due to the highest labour mobility.

The methodology of Blanchard and Katz (1992) has been applied in many other studies and
has become the standard model to analyse regional labour market adjustment mechanisms and to
approach migration patterns indirectly.3 Greenaway-McGrevy and Hood (2013) apply the model to
metropolitan areas in the US and ﬁnd that the adjustment to location-speciﬁc and aggregate shocks
diﬀer considerably. Our paper shares their main modiﬁcation, namely the use of a factor structure
to separate region-speciﬁc from common shocks. Dao et al. (2014) reassess the adjustment of US
states and ﬁnd that the contribution of migration has decreased since 1980 and link it to a declining
trend in the dispersion of unemployment rates across states. In addition, they show that migration
contributes more in aggregate downturns and sketch some diﬀerences between the US and Europe.
For our purposes there is no alternative to inferring migration indirectly as in the Blanchard and
Katz (1992) methodology. But we acknowledge that the chosen approach comes with drawbacks,
including weak micro-foundations and a debatable identiﬁcation of the labour demand shocks. Due
to the availability of more and better regional data economic geography oﬀers an increasingly
feasible alternative. Counterfactual analyses in spatial general equilibrium models – as in Redding
(2012), Ahlfeld, Redding, Strum, and Wolf (2013), or Behrens, Mion, Murata, and S¨udekum (2013)
– could be used to understand how individuals relocate after a shock and where they move. An
alternative approach is to look at how mobility response to well-identiﬁed shocks. Both in the
US and Germany trade shocks, for example, have been shown to induce relatively small mobility
responses (Autor, Dorn, and Hanson, 2013; Dauth, Findeisen, and S¨udekum, 2014).

3 Empirical Strategy

3.1

Intuition of the BK Model

In this section, we provide some intuition behind the BK model. For a full model description,
we refer the interested reader to the original paper of Blanchard and Katz (1992). Starting from
the observation that region-speciﬁc labour demand shocks have permanent eﬀects on employment,
but only temporary eﬀects on the employment rate, the participation rate and wages, Blanchard
and Katz (1992) develop a simple model of regional labour market dynamics that is based on two

3Numerous other papers rely on the BK model: Jimeno and Bentotila (1998) adapt the methodology to study
Spanish regions; Fredriksson (1999) looks at Swedish regions; Bertola (2000) and Tani (2003) at European regions,
Fidrmuc (2004), G´acs and Huber (2005), Bornhorst and Commander (2006) focus on regions in Central and Eastern
Europe. Recently, Sala and Triv´ın (2013) study Spanish regions.

ECB Working Paper 1767, March 20157basic features. First, regions are assumed to produce distinct bundles of goods that are sold in
an aggregate goods market and, second, labour and capital are assumed to be perfectly mobile
in the long run. In this model, state-speciﬁc shocks to labour demand result in short-lived mean
deviations of wages, but cause permanent changes of the employment level. An adverse shock to
labour demand, for example, increases unemployment and lowers wages, which induces some workers
to leave the region. Since workers move out of the region until wages are back to equilibrium, lost
jobs after an adverse demand shock are not fully recovered. Similarly, when region-speciﬁc labour
demand increases, relative wages tend to increase. This leads some ﬁrms to relocate at least part
of their production outside the region and thus reduces employment compensating for some of the
newly created jobs. However, higher wages also cause inward migration of workers so that some
of the newly created jobs remain permanently in the region. The relative sensitivities of labour
demand and supply determine how large the permanent eﬀect of the labour demand shock is on
regional employment. In the short run, changes in the unemployment and the participation rate
can also contribute to the change in employment.

In order to implement this model empirically and in the absence of reliable regional wage data,
Blanchard and Katz (1992) propose to estimate the joint behaviour of employment growth, the
employment rate and the participation rate. The short and long run adjustment of the regional
labour market can then be analysed by tracing out the impact of a shock to the employment growth
equation.

3.2 Region-Speciﬁc Variables

Blanchard and Katz (1992) measure region-speciﬁc variables as simple diﬀerences between the
regional variables and their aggregate continental counterpart. Let Eit stand for the number of
persons employed, Lit for the labour force in persons and Pit for the population in persons, in
region i, at time t; let Xit = [∆ log Eit, log Eit
, log Lit
] contain the regional employment growth,
Pit
Lit
employment rate and participation rate; and let X Cont
stand for the respective continental data.
Then the region-speciﬁc variables – denoted by xit – are given by

t

xit = Xit − X Cont

t

(1)

This deﬁnition of a region-speciﬁc variable boils down to conditioning each of the variables on one
common factor (the continental aggregate variable) and to restricting the loading on that factor
to be equal to one.4 Such a transformation will identify the adjustment to region-speciﬁc shocks
only if all regions respond identically to aggregate ﬂuctuations. But in a regression of regional

4For large cross-sections the idiosyncratic components average out so that the aggregate converges to the common
factor (Forni and Reichlin, 1998 and Pesaran, 2006). For a large sample this is hence identical to including a common
time trend. The aggregate most often refers to national variables (as in Blanchard and Katz, 1992 or in Obstfeld
and Peri, 1998) but continental variables can also be used (as in Decressin and Fat´as, 1995).

ECB Working Paper 1767, March 20158variables on their aggregate counterparts most coeﬃcients are quite diﬀerent from one, suggesting
that regions react quite heterogeneously to aggregate business cycles (see Hamilton and Owyang
2012).5 In this case, the simple transformation like in equation (1) will estimate a mixture of the
adjustment to local and aggregate shocks. One advantage of the simple diﬀerence transformation
is that one does not need to identify local and aggregate shocks. This may still be justiﬁed if the
regional dynamics is independent of the local or aggregate origin of the shock.

There may, however, be reasons why regions adjust diﬀerently following aggregate versus idiosyn-
cratic shocks. For example, using the BK methodology Dao et al. (2014) ﬁnd that the regional
adjustment diﬀers depending on aggregate conditions. One explanation may be that job-churnings
are pro-cyclical, i.e. they decrease during an economic bust and increase in good times (Fallick
and Fleischman, 2001; Caballero and Hammour, 2005; Molloy, Smith and Wozniak, 2011; Davis,
Faberman, and Haltiwanger, 2011). As a result, when a region is hit by an idiosyncratic negative
labour demand shock and the labour market in other regions is not aﬀected, it may be easier to
ﬁnd a job there and the incentive to migrate may be higher. In contrast, when the whole country
is negatively aﬀected but one region worse than another, it may be more diﬃcult to ﬁnd a job in
the region that is less hit, dampening the incentives for migration.

Greenaway-McGrevy and Hood (2013) show how a factor model can be embedded into the
structural innovations of the original BK model in order to distinguish between the adjustment to
aggregate and local shocks. Region-speciﬁc variables are then deﬁned as residuals of a factor model:

xit = Xit − (L1

i f 1

t + · · · + Lk

i f k

t ),

(2)

where f j

t , j = 1, . . . , k, are the factors and Lj
i , j = 1, . . . , k, are constant but region-speciﬁc
loadings.
Intuitively, regions are allowed to respond to two diﬀerent processes, namely a local,
idiosyncratic shock process and a set of common or aggregate shock processes, with potentially
diﬀerent responses. The data is modeled as the sum of these two processes. Strong-form dependence
in the panel allows consistent identiﬁcation of the factors justifying their use in linear regressions
(Bai and Ng, 2006; Bai, 2009; Greenaway-McGrevy and Hood, 2013). Greenaway-McGrevy and
Hood (2013) show that the adjustment processes of MSAs are diﬀerent after location-speciﬁc and
In the former case migration is rapid but relatively weak. Conversely, the
aggregate shocks.
adjustment after common shocks is driven by more prolonged and larger migration.

5Decressin and Fat´as (1995) reject a unity reaction of regions to aggregate shocks for most regions as well. They
suggest using the estimated coeﬃcients as weights when diﬀerencing, so that regions are allowed to react with a
diﬀerent sign and magnitude to aggregate movements. They thus condition on one common factor per variable,
but allow for diﬀerent weights. These variables, so called β-diﬀerences, are uncorrelated with aggregate variables
and, if there were only one common factor per variable, would indeed enable a separation of regional and aggregate
ﬂuctuations. Sala and Triv´ın (2013) also employ this methodology.

ECB Working Paper 1767, March 201593.3 Estimation Procedure

Our estimation proceeds in two steps:6 In the ﬁrst step, we decompose the regional variables in three
orthogonal components: the contribution of a continent-wide factor, of a country (or area) factor
and a region-speciﬁc variable. This is done by estimating a multi-level factor model. In the second
step, we separately estimate a pooled VAR in the region-speciﬁc variables and the country factors to
investigate and compare the labour market response to region-speciﬁc7 and country-speciﬁc shocks
respectively.

3.3.1 The Factor Model

We estimate a separate multi-level factor model for Europe and the US. We include one continental
factor, country factors in Europe and area factors in the US. In Europe, we include a German (G),
French (F), Italian (I), Spanish (SP) and British (GB) factor, and in the US we include the four
US areas Northeast (NE), Midwest (MW), South (S), and West (W).8 We restrict the loadings so
that only regions belonging to a particular country (area) are able to load on the respective country
(area) factor.9 Accordingly, the following factor model is estimated for Europe and the United
States separately:

Xi,a,con,t = xit + Lcon

i

fcon,t + La

i fa,t,

(3)

where i denotes the region, a the country in Europe the region belongs to or the area the
state in the US belongs to, and con is the continent (Europe or US). The idiosyncratic component
xit contains the region-speciﬁc variables. The loadings represent the sensitivity of the regional
series to the country, area or continental factors and since they are region-speciﬁc, they allow for
heterogeneous eﬀects of those factors.

Since principal-components methods cannot account for a hierarchical factor structure, we es-
timate the factors with the quasi-maximum likelihood approach suggested by Doz, Giannone, and
Reichlin (2012). They show that maximum likelihood is suitable to estimate the common factors in
large cross-sections of time series. We implement the QML estimator using the Kalman smoother
and the EM algorithm.10

6Because in this model also the data vector follows a factor structure the factor model can be estimated before

the VAR.

7We use the terms region-speciﬁc, idiosyncratic and local shock interchangeably.
8Diﬀerent factor structures are, of course, possible. The results are not changing importantly for diﬀerent

structures.

9We impose a structure on the factors in order to capture the variables’ pervasive covariation for the diﬀerent
geographical entities. In Europe it is important to account for country factors. Using the ABC criterion of Alessi,
Barigozzi and Capasso (2010), we ﬁnd indeed strong evidence for more than one common factor per series.

10Forni, Hallin, Lippi, and Reichlin (2000) and Stock and Watson (2002) propose to estimate common factors
using principal components. Principal components are indeed easy to compute and consistent for any path of the
cross-section and sample length (Bai and Ng, 2002; Forni, Giannone, Lippi, and Reichlin, 2009). Yet, with principal

ECB Working Paper 1767, March 2015103.3.2 The Vector Autoregression Model

We then separately estimate the following panel VARs and pool over diﬀerent subsamples:

xi,t = φi0 + φ1(L)xi,t−1 + (cid:15)i,t,

fa,t = φa0 + φ1(L)fa,t−1 + (cid:15)i,t,

(4)

(5)

where the region- or country-speciﬁc constants represent regional or country ﬁxed eﬀects that
allow for diﬀerent long-term averages. Given our large cross-section and modest sample length
the two-step procedure does not cause a generated regressor problem (Pagan, 1984; Bernanke and
Boivin, 2003; Bai and Ng, 2006) so that we can indeed treat the region- and country-speciﬁc
variables as observations (Bai, 2003; Giannone and Lenza, 2009).

The short and long run adjustment of the regional labour market can then be analysed by tracing
out the impact of a shock to the employment growth equation on the other variables. The identifying
assumption is that this shock captures unexpected changes in regional labour demand meaning
that contemporaneous employment growth is weakly exogenous in the other equations of the VAR.
The Choleski decomposition implies that current changes in employment aﬀect both employment
and participation rates but not vice versa. There are examples that violate this assumption, for
example changing fertility rates, but we assume these changes are small relative to the labour
demand shocks.11

A region-speciﬁc labour demand shock is a change in labour demand in a region that is un-
correlated with national and continental labour demand. Think for example of a change in local
government spending, the bankruptcy of a big company with many employees in one particular
region, or a regional natural catastrophe like a storm tide. Examples of shocks to country-speciﬁc
labour demand could result from a change in military spending, oil prices, a national banking crisis
or changes in national policies.

components it is not possible to restrict the factor structure as we intend. Other authors working with structural
factors include: Forni and Reichlin (2001); Bernanke, Boivin, and Eliasz (2005); and Boivin and Giannoni (2006).
Also Kose, Otrok, and Whiteman (2003) apply a likelihood based estimator. The QML approach of Doz, Giannone,
and Reichlin (2012) assumes that all series are I(0). In our case, however, some series are I(1). Principal components
deliver consistent estimates also in this case (Bai and Ng, 2004). We re-estimate the three global factors using
principal components and the structural factors of the remaining unexplained ﬂuctuations – that all turn out to be
I(0) – with the QML approach. The factors are very similar. Doing the factor analysis in two steps underestimates
the errors, because the QML estimation uses estimated data. However, in the VAR we treat the region-speciﬁc
variables and factors in any case as observations (Bai, 2003; Giannone and Lenza, 2009).

11Dao et al. (2014) in a recent working paper test the assumption for the US and conclude that identiﬁcation with
an instrument reveals a lower contribution of migration. We are not fully convinced that the only eﬀect of the IV
identiﬁcation is a clearer demand shock, as it may also change the type of the adjustment. Because the IV approach
is very diﬃcult to implement in Europe also Dao et al. (2014) rely on our assumption for their European analysis.

ECB Working Paper 1767, March 201511Note that

Eit =

Eit
Lit

Lit
Pit

Pit.

When we take the logarithm and ﬁrst diﬀerences, rearranging leads to

∆ log Pit = ∆ log Eit − ∆ log

Eit
Lit

− ∆ log

Lit
Pit

.

(6)

(7)

The change in population is a linear combination of the variables in the VAR. We can distil the
population response since any employment change that is not explained by the employment rate or
the participation rates is attributed to a change of the population. Following Blanchard and Katz
(1992), we will assume that these changes are due to migration.

4 Data, Descriptive Statistics, Variance Decomposition

4.1 Regional Disaggregation and Data Sources

The regional disaggregation follows Blanchard and Katz (1992) for the US and is similar to Decressin
and Fat´as (1995) for Europe. For the US, the disaggregation is straightforward: we count each state
plus the District of Columbia as a region so that there is a total of 51 US regions. In Europe entities
of comparable size refer less strictly to administrative divisions. Yet, all regions in the sample
can be understood as consisting of one or more NUTS2-regions. We include eight French, seven
German, eleven Italian, seven Spanish, and eight British regions, as well as Belgium, Denmark,
Greece, Ireland, the Netherlands and Portugal. While Decressin and Fat´as (1995) classify the small
countries as regions, they are treated as countries in our set-up. For a list of all regions see Table
A.1 in the Appendix.

We use data on the population, labour force and employment, from which we compute the
employment growth, the (un)employment rate, as well as the participation rate. Our time series
starts in 1976 and ends in 2013 so that it covers 38 years. The primary European data sources
are the national Labour Force Surveys. We apply some data modiﬁcations to ﬁll in missing data
points and replace data of obviously bad quality using data from diﬀerent international and national
sources. The data from diﬀerent sources is linked using adjusted growth rates of the working-age
population, the unemployment and the participation rates. They are then used to extend the most
recent data backwards. We compared diﬀerent ways to link the data and found that diﬀerences are
minor. For European regions we restrict the sample to the working-age population so that all series
cover only persons between 15 and 64 years old.

For the US we use the Current Population Survey (CPS) as our main data source because it
is comparable to the European Labour Force Surveys. In section 6 below, we also use Local Area

ECB Working Paper 1767, March 201512Unemployment Statistics (LAUS) from the Bureau of Labor Statistics as an alternative data source
for investigating the US adjustment mechanism because these are based on establishment data and
therefore are closer to the data used by Blanchard and Katz (1992). All US series include all persons
older than 15 years.

4.2 Descriptive Statistics

In 2013 the average regional population in the US was 4.8 million with a standard deviation of
5.4 million leading to a coeﬃcient of variation of 1.1. With 30 million California was the biggest
region in the US and with less than half a million Wyoming was the smallest. The average regional
working-age population in Europe is very similar and equal to 4.6 million but the standard deviation
is with 2.4 million smaller, resulting in a smaller coeﬃcient of variation, 0.5. Nordrhein-Westfalen in
Germany is the largest region with a working-age population of 12 million in 2013, whereas Abruzzi-
Molise in Italy is the smallest with only 1 million inhabitants. The total population covered in 2013
was 240 million in the US and 220 million in Europe.

The average unemployment rate in a US region in 2013 was 6.8% with a standard deviation of
1.6%. In Europe the average unemployment rate was nearly twice as high, namely 12.5%, and the
regions were much more heterogeneous, as indicated by a standard deviation of 7.9%. Over the
whole sample the average unemployment rate was 6% in the US and 10% in Europe.

Employment growth ﬂuctuates strongly, in particular in the US. While employment growth was
on average higher in the US than in Europe in the earlier part of the sample, growth rates have
become more similar since then. The unemployment rate is less volatile and returns to its mean
roughly every ten years. During most of the sample the unemployment rate is higher in Europe
than in the United States. The participation rate in Europe shows a clear upward trend throughout
the sample, whereas in the US the participation rate increased until 2000, and started to decline
afterwards.12

Figure 1 plots the standard deviation of regional unemployment rates over time.

In Europe
regions diverged until 1998. Coinciding with the introduction of the euro in 1999, however, the trend
reversed and they converged fast.13 Since 2008 regional unemployment rates are again diverging
strongly. As a result, in 2013 the dispersion reached its maximum over the sample period. Beyer
and Stemmer (2014) analyse the distribution of European regional unemployment at the NUTS2
level and show that inner distributional trends have reversed as well. Regions that experienced
strongly decreasing unemployment rates before 2008 were hit hardest by the recent events.

Note that regional unemployment dispersion is considerably lower in the US than in Europe,

12Figure B.1 in the Appendix plots the continental means of employment growth, the unemployment rate and the

participation rate over the period 1977 till 2013 in the US and Europe.

13In the same period the standard deviation of unemployment rates of other developed countries decreased as

well, but less than in Europe (Estrada, Gal´ı and L´opez-Salido, 2013).

ECB Working Paper 1767, March 201513Figure 1: Standard deviation of regional unemployment rates

conﬁrming that US regions are more homogenous than European ones. Also note that in the US
regions diverge particularly in recessions: the three steepest increases of the standard deviation –
in the early eighties, the early nineties, and between 2008 and 2010 – all coincide with recessions.14

4.3 Variance Decomposition

Next we estimate the multi-level factor model (3) to extract the common factors from the data.

Table 1: Variance Decomposition

Employment Growth
Employment Rate
Participation Rate

Employment Growth
Employment Rate
Participation Rate

EU Country Region

28
41
69

US

38
65
54

29
36
16

43
23
16

Area

State

14
15
18

49
20
29

Table 1 reports the proportion of variance explained by each level for each variable. The common
European factor explains 28% of the employment growth ﬂuctuations, 41% of ﬂuctuations in the
employment rate and 69% of ﬂuctuations in the participation rate. Country factors are nearly
as important for the ﬁrst two series, but matter less for changes in the participation rate. The
importance of the country factors in Europe supports our strategy to estimate a multi-level factor

14The connection between increasing standard deviations and recessions is also discussed in Greenaway-McGrevy

and Hood (2014) as well as in Dao et al. (2014).

	  0 1 2 3 4 5 6 7 8 9 1977 1980 1983 1986 1989 1992 1995 1998 2001 2004 2007 2010 2013 Europe US ECB Working Paper 1767, March 201514model. Together the EU and country factors capture between 57% of the variance in employment
growth and 84% of the variance in the participation rate.
Idiosyncratic ﬂuctuations are most
important for the employment growth rate.

The greater homogeneity of the US economy is reﬂected in the fact that the US factor plays a
more important role in accounting for both employment growth and employment rate ﬂuctuations.
As expected, US states are thus more correlated and their business cycles more aligned than regions
in Europe. The area factors, on the other hand, explain less than half of the variance that is captured
by the country factors, clearly showing that country factors are more important in Europe. The
contributions of region-speciﬁc shocks are similar to the ones in Europe with a slightly higher
contribution for the employment growth.

5 Labour Market Adjustments

In this section, we compare the labour market adjustment of regions to region-speciﬁc shocks
in Europe and the US, and analyse as well the country adjustment in Europe. Moreover, we
analyse changes in the role of labour mobility over time. In each case, the ﬁgures below report
impulse responses of the employment level, the employment rate and the participation rate to a
positive one standard deviation shock to labour demand. Note that deviations of the employment
rate are approximately equal to negative deviations of the unemployment rate. The responses
show percentage deviations from region-speciﬁc means. In addition, we include tables showing the
adjustment in the ﬁrst ﬁve years and in the long run to a normalised initial increase of 100 jobs.
Each table reports in the ﬁrst line the number of newly created jobs and in the lines below it
decomposes the new jobs. Some of the new jobs are ﬁlled with formerly unemployed, others with
people previously not forming part of the labour force and the remaining jobs are ﬁlled with people
moving into the region.

5.1 Regional Adjustment to Region-Speciﬁc Shocks

First we discuss the adjustment of regions to region-speciﬁc changes in labour demand and compare
the adjustment in Europe and the US. We estimate (4) and allow for two lags.15 We test for unit
roots and conﬁrm that all series are stationary so that the model speciﬁcation is appropriate.16

Figure 2 shows the impulse responses for Europe in the left and for the US in the right panel
and Table 2 translates the impulse responses in contributions of workers by the employment rate,
the participation rate and migration. Note, ﬁrst, that following a positive labour demand shock the
employment level increases on impact, then falls back towards its initial level, but remains above it

15Two lags are usually used in the literature. We estimate the model also with only one and four lags and ﬁnd

that the results are very similar.

16We use the panel unit root test of Harris and Tzvalis (1999) and reject a unit root for all series at the 1% level.

ECB Working Paper 1767, March 201515(a) Europe

(b) United States

Figure 2: Regional adjustment to region-speciﬁc shock

in the long run. The fact that some but not all of the initial increase in employment remains in the
long run suggests that both labour migration and job destruction and creation play a role in the
adjustment process. If no jobs disappeared, the permanent eﬀect would be the size of the initial
increase. If, on the contrary, no migrants were moving into the region, the permanent eﬀect on
employment would be zero. Since in the long run the unemployment and participation rates revert
to their pre-shock baseline, the permanent change in employment must stem from migration. The
permanent change in employment relative to the initial increase thus reveals the relative importance
of job destruction and creation versus migration of employees. Due to the normalization the number
of workers migrating in the long run reported in the tables can be interpreted as the long-run
contribution of migration as percentage of the initial increase in employment.

Table 2: Regional adjustment to region-speciﬁc shock

Europe

United States

Years

1

2

3

4

5

10

1

2

3

4

5

10

Employment
Employment rate
Participation rate
Migration

100
20
41
39

83
18
18
47

73
16
15
42

64
11
11
43

59
7
8
44

50
1
2
47

100
13
44
43

92
9
30
54

72
5
12
56

62
1
4
57

59
0
2
57

57
0
0
57

A number of points are worth making. First, the adjustment towards the new steady state is
faster in the US than in Europe. Employment reaches its long run level after 10 years in Europe and
after ﬁve years in the US. After three years both the employment and participation rate continue

ECB Working Paper 1767, March 201516to contribute substantially in Europe, but not in the US. After four years they still contribute
more than 20 per cent in Europe, but only ﬁve in the US. The employment rate (or unemployment
rate) reacts much stronger in Europe and contributes a lot more to the adjustment than in the US.
Migration, on the other hand, contributes a bit less in Europe over the whole adjustment period.
Overall, a shock changing employment initially by 100 workers leads to 47 immigrants in Europe
and 57 in the US. In other words, due to migration 47% of the initial increase of employment
becomes permanent in Europe and 57% remain in the US. While migration is higher in the US, the
diﬀerences are not large.

Summarizing, there are diﬀerences between the regional adjustment mechanisms in Europe and
the US – in Europe it is more persistent, employment rates contribute more, and migration a little
less – but the diﬀerences are smaller than previous work suggests. Compared to Decressin and
Fat´as (1995), we ﬁnd a faster adjustment mechanism, a more important role for job creation (and
consequently a less important role for migration), and smaller diﬀerences between Europe and the
US.

5.2 The National Adjustment Mechanisms in Europe

Next we investigate the role of migration in labour market adjustment across countries. The costs
of migrating across countries are likely to be higher than those of migrating between regions due to
the larger distance, greater language and other cultural barriers, and other institutional obstacles
like the limited portability of pension and other social security rights. We should therefore expect a
lower contribution of migration to the adjustment process following country-speciﬁc labour demand
shocks.

We use the ﬁve country factors from (3) and add our small countries so that we have a cross-
section of 11 countries. We estimate (5) and due to the smaller cross-section now allow for only
one lag. Again we conﬁrm the empirical validity of the VAR speciﬁcation.17

Table 3: National adjustment to country-speciﬁc shock

Country

Years

1

2

3

4

5

20

Employment
Employment rate
Participation rate
Migration

100
42
40
18

115
52
41
22

109
45
37
27

99
35
33
31

89
26
28
34

40
-2
0
43

17Here we test for unit roots using the test developed by Levin, Lin and Chu (2002). A unit root is rejected at

the 1% level for the employment growth, the participation rate, and for the employment rate.

ECB Working Paper 1767, March 201517(a) Countries

(b) Number of Migrants

Figure 3: National adjustment to country-speciﬁc shock

The left panel in Figure 3 shows the impulses responses of a one standard error positive labour

demand shock as before. Note that the standard errors are now larger as the cross-section is smaller.

The employment and participation rate contribute nearly equally in all years and need 15 years

to return to their pre-shock level. As a result, the adjustment process takes longer in response to

country-speciﬁc shocks than in response to region-speciﬁc shocks. The right panel compares the

number of migrants in the ﬁrst ﬁve years after an initial employment change of 100 workers for the

diﬀerent adjustment mechanisms. From before we know that the number of migrants is somewhat

lower after a region-speciﬁc shock in Europe compared to the US. Migration is much lower after a

country-speciﬁc shock, in particular in the ﬁrst years after the shock. The employment rate, on the

other hand, reacts much stronger. Part of the recent increase of the heterogeneity in Europe may
indeed result from the stronger contribution of the employment rate in Europe.18

Table 3 contains again the decomposition into workers for an unexpected increase of 100 jobs.

Following such a country-speciﬁc shock, only 18 workers migrate to a country experiencing an

unexpected increase of the employment level by 100 jobs, whereas around 40 workers migrate after

a region-speciﬁc shock of that size in Europe and the US. These diﬀerences become smaller over

time. Migration also contributes less to the change in employment relative to the participation and

employment rate. In the ﬁrst three years it contributes on average 51% to the regional employment

change in Europe after a local shock but only 21% to the national adjustment after a country
shock.19

Summarizing, we ﬁnd that migration plays a less important role in the adjustment to country-

speciﬁc shocks. Since in Section 5.1. we found that the regional adjustment processes in Europe and

18Note, however, that without the surprisingly strong migration response after region-speciﬁc shocks, diﬀerences

in regional labour market conditions would be even larger.

19We have also estimated the national adjustment mechanism with the country series instead of the factors.

Results are very similar.

	  0 10 20 30 40 50 60 1 2 3 4 5 National Adjustment in Europe Regional Adjustment in Europe Regional Adjustment in US the US are not very diﬀerent, it follows that it is mostly lower labour mobility between European
countries that slows down adjustment in Europe. This ﬁnding is in line with Bartz and Fuchs-
Sch¨undeln (2012), who also show that country borders impede labour market integration in Europe.

5.3 Changes over time

In the previous sections we reported the full-sample results. Given the evidence of changes in labour
mobility discussed in the introduction, in this section we analyse whether the role of migration has
changed over time. To do so, we estimate the VARs of equations (4) and (5) for two subsamples
separately (1977-1999 and 1990-2013). While this obviously shortens the sample, we still have 23
observations per subsample and thus nearly twice as many observations as Blanchard and Katz
(1992) and Decressin and Fat´as (1995). Still, we reduce the lag length to one and focus mainly
on the ﬁrst ﬁve years in order to minimize issues related to sample length. Note that our samples
overlap so that changes originate in diﬀerences in the adjustment in the ﬁrst and last 13 years.

Figure 4 shows the changes of the regional migration response in Europe and the US, as well
as the national migration response in Europe. The left panel plots the total number of migrants
after a shock of 100 workers in the ﬁrst ﬁve years. The dashed lines show the numbers of migrants
between 1977 and 1999 and the solid lines the numbers between 1990 and 2013. In addition, we use
pie charts to report the average percentage contributions of the employment and participation rate
and of migration to the employment change in the ﬁrst three years. This allows us to see whether
migration has become relatively more important or not.

The upper panel reports the changes in the regional adjustment in Europe. The total number
of migrants has risen in all years and also the percentage contribution of migration has increased.
Molloy, Smith and Wozniak (2011) analyse inter-NUTS2 mobility in Europe using a LFS question
asking whether respondents moved in the previous year. In line with our results, they ﬁnd that
mobility rates were either ﬂat or slightly increasing in the early 2000s.

The increase of migration in Europe detected by Beine et al. (2013) refers to migration between
countries and not regions. As discussed in the introduction, recent divergence in unemployment
rates across European countries has led to increased migration in Europe. It is thus interesting to
see whether we can also detect changes in the adjustment to country shocks using our methodology.
The middle panel of Figure 4 shows the changes in the country adjustment mechanism. As expected,
the total number of migrants in response to an initial increase in employment of 100 has indeed
increased. After three years, for example, it increased from 31 in the ﬁrst subsample to 45 in the
second subsample. And also the permanent eﬀect of a country shock on migration has become
more important. Although not directly comparable, our results therefore qualitatively conﬁrm the
ﬁndings of Beine et al. (2013). In sum, we ﬁnd that in the most recent subsample country-speciﬁc
changes in labour demand set in motion more cross-country movement in workers and that this

ECB Working Paper 1767, March 201519Figure 4: Change of Migration

migration contributes more relative to the employment and participation rate. At the same time,

the role of migration between countries remains lower than its role between regions.

Finally, the lower panel shows changes in the role of migration in the US. The total number

of migrants after a region-speciﬁc shock has notably decreased in all years. Three years after the

shock the number of migrants has decreased from 56 to 44. As the pie charts show, the percentage

contribution has declined as well and is compensated by a more ﬂexible labour force. For the US

our results are thus in line with Dao et al. (2014) and relate nicely to the literature on declining

labour mobility in the US.

          34 38 28 Employment Rate Participation Rate Migration Regional Adjustment in Europe   National Adjustment in Europe   Regional Adjustment in the US   20 40 60 1 2 3 4 5 1977-1999 1990-2013 21 28 51 1977-1999 15 24 60 1990-2013 20 40 60 1 2 3 4 5 30 39 30 41 24 35 20 40 60 1 2 3 4 5 9 36 54 11 38 51 (a) Europe

(b) United States

Figure 5: Regional adjustment with simple diﬀerences

6 Relation to Blanchard and Katz (1992)

In this section, we apply the original methodology of Blanchard and Katz (1992), who deﬁne
regional variables as simple diﬀerences from the continent-wide mean to our data. This is useful for
two reasons. First, our results diﬀer quite importantly from those of Blanchard and Katz (1992)
and Decressin and Fat´as (1995) who ﬁnd a much slower adjustment process and a greater role for
migration. In this section, we want to investigate whether these diﬀerences are mainly due to the
change in methodology or also due to use of diﬀerent data sets. Second, one might argue that the
policy maker is interested in the regional adjustment to diﬀerences independent of the type of the
shock. This may be captured somewhat better by analysing simple mean diﬀerences.

6.1 The adjustment with simple diﬀerences

Figure 5 plots the impulse response functions for Europe and the US using simple diﬀerences
computed as speciﬁed in (1) and Table 4 contains again the breakdown as before. While this
speciﬁcation results in stationary series in the US, in Europe we can reject a unit root neither in the
employment rate nor in the participation rate so that that this ﬁltering strategy is not appropriate
for European regions.20 As discussed before, our factor-based methodology of identifying region-
speciﬁc variables results in stationary series.

In Europe, the employment level exhibits a hump-shaped response and migration is initially
lower than for region-speciﬁc shocks. The number of migrants in the ﬁrst years drops from 39
to 27, but is identical in the long run. The participation rate is now much more persistent and

20With Harris-Tzvalis test we reject a unit root in the US for all series at the 1% level. In Europe only the employ-
ment growth is stationary - we reject a unit root at the 1% level – but both for the employment and participation
rate we cannot reject the unit root at any level.

ECB Working Paper 1767, March 201521Table 4: Regional adjustment with simple diﬀerences

Europe

United States

Years

1

2

3

4

5

20

1

2

3

4

5

20

Employment
Employment rate
Participation rate
Migration

100
34
40
27

118
45
36
37

124
49
38
37

119
44
36
39

111
36
34
41

57
-6
16
47

100
16
47
37

108
16
45
48

99
11
32
56

93
7
27
59

88
4
22
61

63
0
0
63

is considerably above the pre-shock level even 20 years after the shock. The employment rate
contributes stronger and is more persistent as well.21

Overall, it looks like the original BK methodology mixes the adjustment to region-speciﬁc shocks
with the adjustment to country-speciﬁc shocks. This results in a more persistent adjustment process
with a larger role for unemployment and a signiﬁcantly smaller role for migration in the ﬁrst years.
Accordingly, in the US the diﬀerences are smaller and the responses look generally similar to
the ones after region-speciﬁc shocks. But again the process now takes longer to be completed and
in particular the contribution of the participation rate is more persistent. Using simple diﬀerences,
migration is a little lower initially, in the ﬁrst year we see 37 instead of 43 migrants, and a little
higher in the long run with 63 instead of 57 migrants. The general conclusions from Section 5.1 are
thus conﬁrmed.

Next, we repeat the estimation for the same subsamples as before with simple diﬀerences. Figure
6 reports again the number of migrants after a shock of 100 workers in the left panel and the average
percentage contributions in the ﬁrst three years in the right panel.

From 1977-1999 to 1990-2013 the total number of migrants has again gone up in Europe, though
only from the third year onwards. The average percentage contribution in the ﬁrst three years is
nearly the same but would increase if we added more years. As before, the number of migrants has
clearly decreased in the US and also the percentage contribution in the ﬁrst three years has gone
down. Our results from Section 5.3 are thus also conﬁrmed.

6.2 Local-Area Unemployment Statistics

While using simple diﬀerences brings the US impulse responses closer to the ones in Blanchard
and Katz (1992), we still neither observe the strong hump-shaped response that characterises their
responses nor the related permanent eﬀect on migration of around 100%. In this section, we analyse
whether the diﬀerent data source may be the reason for this. We estimate the adjustment process

21We also estimated the regional adjustment with β-diﬀerences (see footnote 5) and ﬁnd very similar results.

ECB Working Paper 1767, March 201522Figure 6: Change of Migration

(4) for the US using simple diﬀerences and the LAUS dataset, which is based on establishment data

closer to the data used by Blanchard and Katz (1992). Figure 7 shows the impulse responses to a
positive one standard deviation shock.22

In this case, the impulse responses look very similar to the responses reported in Blanchard and

Katz (1992) and more recently in Dao et al. (2014). Above all, the impulse response now is strongly

hump-shaped and migration is more than twice as important in the long run and above 100%.

We can only speculate about the reasons for the large diﬀerences with our results and the larger

contribution of migration in the long run. Since migration is identiﬁed as the residual of the VAR,

i.e. migration is given by the change of the employment level that cannot be explained by changes in

either the employment or the participation rate, the quality of the data series may be very important.

Inconsistent data series may result in a larger contribution of the residual and hence of migration.

Employment data from LAUS is based on establishment data and there are important diﬀerences

between household and establishment series resulting from diﬀerent deﬁnitions, coverages, and

estimation procedures. For example, CPS employment includes self-employed persons, unpaid

workers in family-operated businesses, and agricultural workers; establishment-based employment

data from the Current Employment Statistics does not. Unpaid absences from work are diﬀerently

accounted for and persons working in more than one establishment are counted more than once

22The Harris-Tzvalis test rejects a unit root at 1% for employment growth and the employment rate and at 5%

for the participation rate.

Europe with simple differences   	  US with simple differences    20 40 60 1 2 3 4 5 1977-1999 1990-2013 34 37 30 1977-1999 45 26 29 1990-2013 34 38 28 Employment Rate Participation Rate Migration 20 40 60 1 2 3 4 5 15 39 46 14 47 39 Figure 7: Regional adjustment with simple diﬀerences and LAUS data

with establishment-based data. The latter inconsistency clearly matters: Blanchard and Katz
(1992) overestimate migration because they rely on establishment-based employment data, but
on CPS data for unemployment and persons out of labour force so that some of the unexplained
employment changes may result from changes in dual job holding and not migration. With LAUS
data the same might happen.

7 Conclusion

7.1 Summary

In this paper we revisit the role of labour mobility in regional labour market adjustments in Europe
and the US. We study 41 European and 51 US regions over a period of 38 years. We use a factor
model to distinguish between the regional adjustment to region-speciﬁc idiosyncratic shocks and
the country adjustment to country-speciﬁc shocks. We show that distinguishing between whether
migration takes place between regions or between countries matters for the relative importance of
both migration and unemployment.

In particular, we ﬁnd that, once we control for country factors, the regional adjustment process
in Europe is not that diﬀerent from the one in the United States. In both areas, migration plays a
relatively important role in the long run, but in European countries the adjustment process takes
somewhat longer and is accompanied by larger changes in unemployment reﬂecting more rigid
labour markets.

What makes a diﬀerence is the cross-country adjustment process in Europe. Due to remaining
diﬀerences in language, cultural factors and institutional diﬀerences, the role of migration is much
less important when a country is hit by a labour demand shock. At the same time, changes in the
employment rate are more important reﬂecting diﬀerent national labour market institutions. If one

ECB Working Paper 1767, March 201524does not account for the country factors, the diﬀerences in regional adjustment between Europe
and the US become much larger. Using a much longer data set, we also ﬁnd that the adjustment
processes in Europe and the US have further converged over the past decades. This reﬂects both
a fall in interstate migration in the US and a rise in the role of migration in Europe as European
integration proceeds. The latter shows up most strikingly in an increased role of migration in the
cross-country adjustment. Finally, we show that part of the diﬀerence between Europe and the US
in previous studies may in addition be due to the use of diﬀerent data sources.

7.2 Policy Implications

Our ﬁndings can inform the policy debate in at least two dimensions. First, most of the diﬀerences
in the role of migration in the regional labour market adjustment process between the US and
It is therefore right for
Europe are due to remaining barriers connected with country borders.
European policy makers to focus on how to facilitate labour mobility across countries in Europe.
Our empirical investigation shows that measures taken in the past such as the Schengen agreement,
initiatives to bring down cultural barriers through exchange programmes such as the Erasmus
programme or eﬀorts like the Bologna process to harmonize educational standards may already
have contributed to a greater role for labour mobility in labour market adjustment. And there
is scope for additional measures to further reduce the persistence of labour market adjustment
to country-speciﬁc shocks and alleviate the associated social costs. A variety of measures can
be considered including promoting more ﬂexible housing markets, increasing the compatibility of
school systems, improving language education, harmonizing pension systems and promoting the
portability of pension and other social security rights, and changing the general attitude towards
migrants. The recent initiatives of the European Commission and Council may hence help to foster
adjustment to country-speciﬁc shocks.

However, our analysis also reveals that the diﬀerences with the United States, a monetary union
with a quite homogenous culture and a well-functioning labour market, are not that large. Given
that cultural and language barriers are likely to persist in Europe, it is therefore important to
be realistic about what increased labour mobility can achieve. The diﬀerences in the importance
of migration in Europe and the US are smaller than has previously been argued, so that labour
mobility might not hamper the functioning of the Euro Area as strongly as some argue.

To become more speciﬁc is diﬃcult given the positive nature of our analysis. This would require
a more structural and normative approach. In this context, one should also recall that there are
also costs to migration, in particular when it involves high-skilled migration that may tend to
exacerbate rather than alleviate regional disparities. Moreover, large-scale migration in Europe
could be socially disruptive (Emerson, 1992; Obstfeld and Peri, 1998). Moreover, from a normative
perspective it is not clear whether adjustment through workers or jobs is preferable. An acceleration

ECB Working Paper 1767, March 201525of the labour market adjustment through job creation may in any case often be desirable. It may
be achieved by more ﬂexible wages – also increasing workers’ mobility – and, equally important,
a higher wage elasticity of jobs. In this context, it is also worth mentioning the role of regional
policies and a banking union in Europe. Regional policies may be used to encourage job-creation
in depressed regions, for example by oﬀering tax deductions to ﬁrms moving in. In addition, the
implementation of a banking union in Europe will foster adjustment through job creation. Morgan,
Rime, and Strahan (2004) show that increased interstate banking in the US stabilised ﬂuctuations
within states and reduced divergence between them.

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ECB Working Paper 1767, March 201530Appendix

Table A.1: Sample

Germany

France

Italy

Spain

United Kingdom

Baden-W¨urttemb.
Bayern
Hessen
Nieders. & Bremen
Nord.-Westfalen
R.-Pfalz & Saarl.
S.Holst. & Hamb.

Bassin Parisien
Centre-Est
Est
Ile de France
Mediterrane
Nord-Pas-de-Cal.
Ouest
Sud-Ouest

Canarias
Centro
Este

Abruzzi-Molise
Campania
Centro
Emilia-Romagna Madrid
Noreste
Lazio
Noroeste
Lombardia
Nord-Est
Sur
Nord-Ovest
Sardegna
Sicilia
Sud

East Midlands
East of England
Northern Ireland
Scotland
South-West
Wales
West Midlands
York and Humb.

US Northeast

US Midwest

US South

US West

Connecticut
Maine
Massachusetts
New Hampshire
New Jersey
New York
Pennsylvania
Rhode Island
Vermont

Illinois
Indiana
Iowa
Kansas
Michigan
Minnesota
Missouri
Nebraska
North Dakota
Ohio
South Dakota
Wisconsin

Alaska
Arizona
California
Colorado
Hawaii
Idaho
Montana
Nevada
New Mexico
Oregon
Utah
Washington

Alabama
Arkansas
DC
Delaware
Florida
Georgia
Kentucky
Louisiana
Maryland
Mississippi
North Carolina
Oklahoma
South Carolina Wyoming
Tennessee
Texas
Virginia
West Virginia

ECB Working Paper 1767, March 201531Figure B.1: Means of original variables

Employment Growth  Unemployment Rate  Participation Rate  -4 -3 -2 -1 0 1 2 3 4 1977 1980 1983 1986 1989 1992 1995 1998 2001 2004 2007 2010 2013 Europe US 0 2 4 6 8 10 12 14 1977 1980 1983 1986 1989 1992 1995 1998 2001 2004 2007 2010 2013 56 59 62 65 68 71 74 1977 1980 1983 1986 1989 1992 1995 1998 2001 2004 2007 2010 2013