labour reallocation, job tenure, labour flows and labour...

Labour reallocation, job tenure, labour flows and

labour market institutions: Evidence from Spain1

by

Carlos Garcia-Serrano* and Juan F. Jimeno**

DOCUMENTO DE TRABJO 98-07

April 1998

* Universidad de Alcalá.

** Universidad de Alcalá and FEDEA.

http://www.fedea.es/hojas/publicaciones.html#Documentos de Trabajo

1 Paper presented at the Job Tenure and Labour Reallocation Conference, held at the Centre for EconomicPerformance (LSE, London), 24th and 25th April 1998.

FEDEA – D.T. 98-07 by Carlos García-Serrano and Juan F. Jimeno 2

ABSTRACT

The purposes of this paper are to provide an account of the recent trendsin labour reallocation, and to estimate the effects of several labour marketinstitutions on the job tenure distribution and labour market flows from a panelof Spanish sectors and regions. The main motivation for the paper is to learnfrom the Spanish experience, first, to what extent labour reallocation isnowadays higher than in the seventies and eighties, and, secondly, the role oflabour market institutions at easing or hindering the process of labourreallocation. We approach the measurement of labour reallocation from twoperspectives. First, we follow the traditional macroeconomic approach toidentifying reallocation shocks by analysing the dispersion of employmentgrowth across sectors, regions, and occupations. Secondly, we document theevolution of job tenure and workers’ and jobs’ flows. Finally, we estimate, froma panel of regions and sectors that spans from 1987 to 1997, the influence ofsome labour market institutions on workers’ flows, workers’ turnover, and jobtenure. Our main findings are: i) although there seems to be some evidence ofhigher job reallocation during the mid-eighties from the evolution of thedispersion of employment growth across different segments of the labourmarket, during the nineties job reallocation seems to have returned to the levelsof the early and late eighties, ii) mean job tenure has decreased in the last tenyears mainly because a huge increase in the proportion of workers who holdjobs for less than a year, iii) workers’ turnover has noticeably increased,especially when short-term employment and unemployment spells are computedin the workers’ flows, iv) job reallocation (creation and destruction) onlyexplains around one fourth of total worker turnover, being the rest due torotation of workers through a given set of employment positions, and v) there isindirect evidence that firing costs diminish workers’ turnover and increase jobtenure while wage compression increases workers’ turnover.

Keywords: Labour reallocation, workers’ and jobs’ flows, job tenure, labourmarket institutions.JEL Codes: J60, J63


1. Introduction

There is the presumption that, nowadays, most countries face an increasing

necessity of reallocating labour and, as a result, workers face higher job

instability. The two most-often cited culprits of this trend are uneven and biased

technological progress, and the “globalisation” of financial and goods markets.

Supposedly, to adjusting to the changing environment, it is required a

reallocation of jobs across sectors, regions, and other relevant segments of the

labour market (which we refer to as “reshuffling”), a reallocation of jobs within

firms in each segment of the labour market (which we refer to as “turnover”),

and, even, a reallocation of workers across a fixed configuration of jobs (which

we refer to as “churning”). Thus, workers’ job tenure is bound to be lower and

labour flows are to increase.

There is also the presumption that some labour markets (mainly in

Continental Europe) are ill suited to cope with the need to reallocate labour. It is

often argued that labour markets need to be “flexible” to adapt to a higher

intensity of workers and jobs flows and to the changing compositions of these

flows. Thus, some countries have reacted by deregulating their labour markets to

some extent. A higher incidence of reallocation shocks (the shocks that generate

the necessity to reallocate labour) and a more deregulated labour market should

produce a lower mean job tenure, a raise in workers and jobs’ flows, and a

change in the composition of these flows.

Nevertheless, surprisingly as may seem, there is little evidence that the

intensity of labour reallocation has increased. The empirical literature on this

matter has focused on the measurement of workers and jobs’ flows, and on the

analysis of job tenure distributions. The construction of time series for workers

and jobs’ flows is hindered by the lack of availability of microeconomic data

sources at different moments in time. In spite of that, many studies have


documented the volume of gross workers flows across labour market states and

their cyclical properties.2 The main results from these studies are as follows.

First, the magnitude of worker flows is large, but it seems that may have been

higher in the early seventies and steadily declined from then on (Contini et al.,

1995). Secondly, unemployment inflows and outflows move together in the

business cycle and are countercyclical. Thirdly, employment inflows are

procyclical and employment outflows are mildly procyclical or even neutral

(due to the different behaviour of flows from employment to unemployment,

that are countercyclical, and the flows from employment to employment that are

strongly procyclical. Evidence for Spain (García-Fontes and Hopenhayn, 1996;

and Antolín, 1996) suggests that Spanish flows have increased since the mid-

eighties (in particular, job-to-job transitions) but do not adjust completely to

international evidence: the main difference rests on unemployment outflows

because they do not show any clear behaviour with respect to the business cycle.

Recent empirical work on gross job flows has documented the existence of

simultaneous job creation and job destruction within narrowly defined

aggregates in some OECD countries (Leonard, 1987; Dunne et al., 1989;

Blanchard and Diamond, 1990; Davis and Haltiwanger, 1990, 1992; Boeri and

Cramer, 1992; Blanchflower and Burgess, 1993; Konings, 1995; and Dolado

and Gómez, 1995, among others). It has also been documented that the amount

of job reallocation is large, differs among countries (it is larger for non-

European –New Zealand, Australia and Canada- and north-European countries -

Denmark and Sweden-) and does not show any significant upward trend since

the late seventies (OECD, 1996). New evidence coming from databases

incorporating information on the number of hirings and separations at firm-level

also suggests that workers mostly arrive at jobs that existed before and that will

exist after they quit or they are fired; in other words, the rotation component of

2 See, for instance, Clark and Summers (1979), Hall (1982), Akerlof et al. (1988), and Blanchard and Diamond(1990) for the US; Pissarides (1986) and Burgess (1994) for the UK; Burda and Wyplosz (1994) for some


worker accounts for a large portion of total worker turnover (Anderson and

Meyer, 1994; Lane et al., 1996; Hamermesh et al., 1996).

Across countries, there is little correlation between the magnitude of jobs and

workers’ flows and the “flexibility” of the labour market (see Garibaldi et al.,

1994, and Alogoskoufis et al., 1995). As for job tenure distributions, there are

also few changes in the last decades (see Diebold et al., 1994, Farber, 1995,

Booth et al., 1997, and Burgess and Rees, 1996). Furthermore, mean job tenures

are roughly similar in countries with very different labour market institutions

(see, for instance, Burgess et al., 1997, for a comparison between job tenure

distributions in the UK and Italy).

The purposes of this paper are to provide an account of the recent trends in

labour reallocation, and to estimate the effects of several labour market

institutions on labour market flows, turnover, and job tenure, from a panel of

Spanish sectors and regions. The main motivation for the paper is to learn from

the Spanish experience, first, to what extent labour reallocation is nowadays

higher than in the eighties and seventies, and, secondly, the role of labour

market institutions at easing or hindering the process of labour reallocation. In

section 2, we argue that the Spanish experience provides a good deal of

significant changes, both in the distribution of reallocation shocks and in labour

market institutions, which makes this analysis interesting. In section 3, we

follow the traditional macroeconomic approach to identifying reallocation

shocks by analysing the dispersion of employment growth across sectors,

regions, and occupations. Thus, in this section, we measure the time evolution of

“reshuffling”, the first of the three components of labour reallocation. In section

4 we document changes in the job tenure distribution during the last decade by

means of the mean job tenure, and the proportion of workers whose job tenure is

lower than one year and higher than twenty years. In section 5, we provide a

European countries, Japan and the US.


descriptive analysis of the second and third components of labour reallocation,

“turnover” and “churning”, by measuring workers’ and jobs’ flows, using

available data sources (the Labour Force Survey, and other surveys addressed to

firms). In section 6, we estimate, from a panel of regions and sectors that spans

from 1987 to 1997, the influence of some labour market institutions on workers’

flows, workers’ turnover, and job tenure. Finally, section 7 contains some

concluding remarks and a summary of the main findings.

2. The Spanish labour market: Recent general trends

In the last two decades or so, the Spanish labour market has gone through

two large employment crisis (1975-85 and 1991-94) and two expansions with

significant employment creation (1986-90 and 1994-97), together with an

intense labour reallocation process and partial deregulation of the labour market.

The are some Spanish peculiarities in the labour reallocation process of the last

two decades. Spain entered the first oil crisis in political turmoil, with an

obsolete industrial structure and an almost non-existent Welfare State. Thus, the

late seventies and early eighties were years of intense labour reshuffling and the

building up of the Welfare State. Then, Spain entered the EEC in 1986, and

further labour reallocation was required. Not surprisingly, the composition of

employment in Spain has changed in the last two decades in all respects -sectors,

educational levels, skills, occupations, and regions.3 The change has been

especially noticeable in the sectoral dimension. The proportion of agricultural

employment, which was above 20 per cent in the mid-seventies, is currently

around 8 per cent. Employment in the service sector, which amounted to around

40 per cent of total employment in the mid-seventies, is currently above 60 per

cent of total employment; while the proportion of manufacturing employment

has fallen from roughly 27.5 per cent to around 20 per cent in the last two


decades. At present, the sectoral composition of employment in Spain

approximately matches the average for the European Union (see Table 1).

The institutional features of the Spanish labour market have also

undergone through successive reforms. The framework for the current state of

labour market relations dates back to 1980, with the approval of the Workers’

Statute. The main institutional features of this system of labour market relations

that mostly affect the ability to reallocate labour both within and between firms

are:

a) A high degree of employment protection both against dismissals and

functional and geographical mobility, achieved by high firing costs, even for

European standards, and the need for either administrative or courts’

approval of changes in the geographic and functional characteristics of the

job post, and

b) The predominance of collective bargaining at the sectoral level as the means

for establishing wages, working hours, and other employment conditions.

Along the eighties and early nineties, partial reforms have significantly

relaxed some restrictions to both workers’ dismissals and the employer’s

capacity to unilaterally change some employment conditions. The most

significant change in this regard is the liberalisation of fixed-term employment

contracts in the late 1984. This type of employment contracts has become

widespread. Currently, the proportion of fixed-term employment is above 30 per

cent, despite some government interventions, first, to restrict their use by

employers in 1994, and, then, to promote permanent employment contracts in

1997, by means of fiscal incentives and reductions in Social Security

contributions.

3 See Jimeno and Bentolila (1998), for the evolution of Spanish regional labour markets, Garcia-Serrano, Jimenoand Toharia (1995) for the change in skills and occupations, and Blanchard et al. (1995), annex 1, for the change


3. Measuring labour reshuffling and reallocation shocks: A macro

approach

In this section, we follow the traditional macroeconomic approach to the

measurement of reallocation shocks, which has relied mostly on the analysis of

the time evolutions of the dispersion of employment growth across some

relevant segments of the labour market (sectors, regions, occupations). In

particular, following Lilien (1982), it is usual to measure reallocation shocks by

the standard deviation of the rate of growth of employment across industrial

sectors.4 Although by construction this index can only measure the degree of

employment reallocation between firms in different sectors, what we label as

“reshuffling”, it provides a first approximation to the intensity of the labour

reallocation process.

The relationship between the Lilien’s index of employment growth

dispersion and the incidence of reallocation shocks can be grasped from the

following simple model of the labour market. Suppose that the labour market is

composed of N segments, where the labour demand and the wage setting

equations in each sector i are given respectively by:

being n (log) employment, w (log) wages, p (log) prices, u the unemployment

rate, θ labour productivity, and where the index i denotes a segment. Labour

productivity in each segment i, θi, is assumed to have two components, an

aggregate component, θ, and a segment-specific component, θi

s, but the

in the educational attainments of the labour force.4 Weighted by the employment proportion of each sector.

iiii pwnn θαβαβα )1())(1(1, −+−−−= −

ii upw θλλθγµ )1( −++−=−


aggregate component affects to each segment of the labour market in a different

fashion, so that θi =aiθ +θi

s. Thus, ai represents the “cyclical volatility” of the

segment i. For simplicity we will take θ and θi

s to follow random walks with

orthogonal innovations ε and εi, which are i.i.d. with zero mean and variances σ2

and σi

2, respectively. Also, by definition:

being ω the employment weight of each sector. The parameters α, β, γ, λ, µ,

assumed to be positive, are related to some institutional feature of the labour

market. Employment inertia is increasing in α, so that the higher firing costs are,

the higher α is. β is the (long-run) wage elasticity of labour demand; µ is the

mark-up of wages over prices, which sometimes is referred to as “wage

pressure” and is determined by unemployment benefits, workers’ bargaining

power, etc; γ gives the response of real wages to unemployment, and λ, if there

are mobility costs across segments, may be related to the degree of

decentralisation of the wage setting process –the higher λ is, the less

decentralised wage determination is, and the more compressed is the wage

distribution across sectors.5 It is easy to show that the standard deviation of

employment growth across sectors i is given by:

Thus, for a given distribution of shocks, the Lilien’s index of employment

dispersion is decreasing in employment inertia, α, and increasing in the degree

of centralisation of the wage setting process, λ, and in the (long-run) wage

5 In this simple representation of the labour market, the (long-run) equilibrium unemployment rate is given byβµ/(1+βγ).

∑ =N

ii θω

+−

+−+=∆ ∑

=1

22222 )1(1

1)var( σωελβ

αα

∑=

=1

1ω


elasticity of labour demand, β. Thus, as stressed by Bertola and Rogerson

(1997), the intensity of labour reallocation observed in labour markets with low

firing costs and a high degree of decentralisation of the wage-setting process

(low α and λ, as, for instance, in the US) may be similar to that observed in

labour markets with high firing costs and a high degree of centralisation of the

wage setting-process (high α and λ, as in Continental Europe).

However, as shown by the previous equation, the Lilien’s index of

employment growth dispersion is contaminated by cyclical effects if the

different sectors of the labour market differ in their response to aggregate shocks

-or if the parameters of the labour demand and wage setting equations are

correlated with segment specific shocks across labour market segments.

Additionally, some changes in labour market institutions may affect to the

dispersion of employment growth. Thus, to properly measuring the incidence of

reallocation shocks is necessary to take into account the possibility of different

response to aggregate shocks and different dynamics of employment in each

labour market segment. To doing this, we follow Jimeno (1992) and estimate a

bivariate VAR for each segment composed of the rate of growth of aggregate

employment and the rate of growth of employment in segment i, and identifying

segment-specific shocks, εi, as innovations which have no contemporaneous

effects on aggregate employment.6 Additionally, this procedure measures

directly the dispersion of sector-specific shocks, θi

s, and, thus, eliminates the gap

introduced by labour market institutions between this dispersion and the

dispersion of employment growth, as shown by the previous simple model.

Following this approach, we have computed the original and the corrected

version of the Lilien’s index of employment growth dispersion across different

segments of the labour markets: provinces (50), regions (17), sectors, and


occupations (both at a 2 digit level of disaggregation) for the period 1978-97.7

The corrected version of the Lilien’s index is from the residuals of a VAR of

four lags estimated with quarterly data. The results are presented in Table 2 and

Figure 1. According to these indexes, both labour reallocation and the incidence

of labour reallocation shocks was highest during the mid-eighties, independently

of the segmentation of the labour market used for the definitions of the index

(provinces, regions, sectors, occupations). There is also some evidence of a

(slightly) higher incidence of reallocation shocks during the nineties as

compared to the early eighties. The correlation between the original Lilien’s

indexes and their corrected versions are, respectively, .21, -.20 and .20 for

provinces, regions and sectors, respectively. The lack of significant correlation

between the two versions of the Lilien's indexes may be due to either a

significant dispersion of cyclical volatility across labour market segments, or to

changes in the institutional framework of the labour market. However, the

previous conclusions on the intensity of labour reallocation, the incidence of

reallocation shocks, and the relevance of institutional changes must be taken

with caution. As already explained, these indexes can only measure the

reallocation across different labour market segments (“reshuffling”), but not

within each segment of the labour market. The measurement of other

components of labour reallocation (“turnover” and “churning”) requires the use

of microeconomic data, which we do in next section.

6 See Jimeno (1992). The identification hypothesis is less and less controversial as the sectoral disaggregationand the frequency of the data used for the estimation of the VAR increase.7 The data source is the Spanish Labour Force Survey, which have a quarterly frequency. Employment growth isdefined with respect to the same quarter of the previous year. In 1987 and again in 1994, there were twomethodological changes in the classification of occupations that resulted in a raise of the dispersion ofemployment growth across occupations. Thus, we have not computed this dispersion for 1987 and 1988, nor thecorrected Lilien’s index for occupations.


4. Job tenure distribution

Another aspect of the labour reallocation process is its impact on job tenure.

As either “reshuffling”, “turnover” or “churning” increases, jobs last for shorter

spells. Thus, the evolution of job tenure distributions provides some information

on the intensity of the reallocation process. As job tenure depends on workers’ and

jobs’ characteristics, looking at mean tenure may provide an incomplete picture.

Thus, we use the Spanish Labour Survey over the last decade to report on the

evolution of mean job tenure and the proportion of workers who hold jobs for less

than a year and for longer than 20 years, distinguishing by age and sectors.

These statistics of the job tenure distribution are in Table 3. First we refer to

mean job tenure. As can be seen in the Table, mean job tenure has decreased by

more than half a year in the last decade (from 9.7 to 9.1). This fall in mean job

tenure has mostly affected to men (mean job tenure has increased for women). As

for age groups, the reduction has been largest for young workers (16-24 years)

and, to a lesser extent, to workers from 26 to 45 years of age, while mean job

tenure for workers above 46 has remained more or less constant. By sectors, mean

job tenure is higher in manufacturing and public services, plausibly as a result of

the technological and product demand characteristics of these sectors. These two

sectors also show either a non-decreasing mean job tenure (increasing for public

services and more or less constant mean job tenure for manufacturing), while

mean job tenure in agricultural jobs, building jobs, and commercial services has

noticeably decreased.

The rest of Table 3 shows that the evolution of job tenure in the last decade

is not only characterised by a decrease in mean job tenure, as the distribution has

behaved differently in the tails. On the one hand, the proportion of “short jobs”

(those that have lasted by less than a year) has raised by more than 12 percentage

points, which have affected more or less similarly to both men and women. On the


other hand, the proportion of jobs lasting for more than 20 years (the so-called

“lifetime jobs”) has increased by almost three percentage points, and by more for

females than for males. With regards to short jobs, its incidence is relative larger

for young workers and in agriculture and in the building sector. The increasing

trend in the incidence of short jobs is common to all age groups and sectors

(including public services). With regards to “lifetime jobs”, the largest share is in

manufacturing and public services, and there seems to be an increasing trend in the

incidence of “lifetime jobs” in all sectors but agriculture, where it is decreasing,

and building and commercial services, where it has remained more or less

constant.

Taking these three statistics of the job tenure distribution together, the

picture seem to be one of increasing segmentation, with a decrease in mean job

tenure and a raise in “lifetime jobs” whose effect on job tenure has been

countervailed by a huge increase in the proportion of “short jobs”. In the next

section we focus on the intensity of workers’ and jobs’ flows which has marked

the evolution of the job tenure distribution, and in section 6 we estimate to what

extent the evolution of job tenure is driven by changes in technology or in the

volatility of labour demand or, alternatively, by changes in the institutional

framework of the Spanish labour market.


5. Labour turnover and churning: A descriptive analysis

In this section, we report on the magnitude and composition of workers’

and jobs’ flows in the Spanish labour market. We will also put them in

international perspective by comparing available information on workers and

jobs’ flows across OECD countries. The identification of trends in labour market

flows and international comparisons are hindered by the fact that available

information is scattered around different data sets that do not provide

homogeneous information across time nor across countries.

5.1. The size of jobs and workers’ flows

We begin by considering the amount of job creation, job destruction, and

job reallocation for the Spanish economy for the period 1985-95. Data comes

from different sources. First, we use a firms’ survey collected by the Bank of

Spain (Central de Balances del Banco de España, CBBE) which covers the

period 1984-92. Secondly, there is another firms’ survey collected by the

Ministry of Industry and Commerce (Encuesta de Estrategias Empresariales,

ESEE) which covers the period 1991-95.8 The indexes of job reallocation, job

creation and job destruction that can be computed from these data sets (as

proportion of total employment) are plotted in Figure 2. As can be seen in this

figure, there is a (very) slight upwards trend in job reallocation during the 1984-

92 period, while job creation and job destruction show no significant trend, and

mostly follow the business cycle.

As for workers’ flows, we first focus on the transitions of individuals

through jobs, independently of what happens to the employment position

(whether it is either a newly created or a continuing or a destroyed job). Thus,

8 For the estimation of jobs’ flows from the CBBE data set, see Dolado and Gómez (1995). For the estimation ofjobs’ flows from the ESEE data set, see Ruano (1997).


workers’ flows are due to both job reallocation and rotation of workers among

continuing jobs. We use the Labour Force Survey to estimate workers’ flows for

the period 1986-97 (flows are measured as changes of the employment status

taking the previous years as reference). The magnitude of flows from

unemployment to employment, from unemployment to unemployment (with a

short spell of employment in between), from employment to employment, and

from employment to unemployment are plotted in Figures 3 and 4. According to

the data in Figure 3, around 30-35 per cent of the unemployed was able to find a

job a year later. Additionally, 15 per cent of the unemployed reappeared as

unemployed a year later after a short employment spell. In any case, no

significant trend is observed in both cases, except for a drop in the flow from

unemployment to employment in the first half of the nineties.

Figure 4 gives the flows from employment and provides the most

significant trend: a strong increase in the flows from employment to

employment during the last decade. Between 1996 and 1997, one out of six

people employed moved from job-to-job; ten years before, this proportion was a

much lower one out of seventeen. As for the flow to unemployment, the figure

shows both a counter-cyclical pattern and a increasing trend, so that it went up

from about 4 per cent in the second half of the eighties to almost 6 per cent in

the mid-nineties.

From these data, we have computed two indexes of workers’ mobility.

The first one is the proportion of the labour force at the initial period that

changes its employment status from one year to the next (that is, flows from

employment to unemployment and from unemployment to employment). The

second index (labelled “with internal mobility”) is the previous one plus the

proportion of workers that remains in the same employment status and had a

change in status within the year. This second index is a better proxy of the

amount of workers’ reallocation going on within the year. Both indexes are


plotted in Figure 5. The aggregate index without considering “internal” mobility

within the labour force statuses shows values more or less stable around 11-12

per cent of the labour force and only a very slight increasing trend since the

eighties. However, once that we compute an index of workers’ reallocation

which takes into account changes in the employment status within the year, we

find a very noticeable increasing trend. Between 1996 and 1997 more than one

out of four active people changed its status, including job-to-job changes and re-

entries into unemployment; the proportion was one out of seven ten years ago.

Thus, the main conclusion that we draw is that while job reallocation

seems to have remained stable over the last decade, workers’ mobility has

noticeable increased. This raise of workers mobility is mostly due to the

existence of short employment/unemployment spells within the year, which

comes from the rotation of workers among a given set of jobs. This conclusion

is confirmed by Figure 6 that plots job reallocation and workers’ reallocation in

a given sample of large firms.9 As seen in the Figure, job reallocation was

around 3-4 per cent during all the period, while worker mobility increased from

10-15 per cent in 1993 to around 20 per cent in 1996 (this increasing trend

coincided with the economic recovery and the 1994 labour market reform).

Therefore, it seems that job reallocation (creation and destruction) only explains

in average around one fourth of total worker mobility, being the rest due to

rotation of workers through a given set employment positions.

We now focus on the sectoral distribution of workers’ flows. It has been

argued that, although job reallocation might not be higher than in the past, the

sectoral sources and destinations of the flows has drastically changed. In the

fifties and, to a lesser extent, in the sixties and the seventies, workers moved

from the agricultural sector to the manufacturing and the building sectors.

9 The data source is the Encuesta de Coyuntura Laboral, a survey on (non-agriculture) establishments that iscarried out each quarter by the Spanish Ministry of Labour since the second quarter of 1990.


However, there are the presumptions that nowadays the flows are from

manufacturing to the service sector, and this makes the process of labour

reallocation more harmful. In Table 4 we report the sectoral destination of the

moves observed from one period to the next, using information from the Spanish

LFS. As seen in the Table, in the second half of the eighties, about 77 per cent of

the agricultural workers who changed jobs remained in the same sector, a

proportion that is similar for manufacturing workers but about ten points lower

than for workers originally in the building and service sectors. However, in the

1991-97 period, we observe a substantial increase in the proportion of movers

who did not change sectors (about 85 per cent for agricultural workers, 90 per

cent for workers in manufacturing and the building sectors, and close to 95 per

cent for workers in the service sector). Overall, inter-sectoral workers flows

have clearly diminished with respect to the second half of the eighties.

5.2. International comparison

Now we turn to put Spanish labour market flows in international perspective

by comparing the size of workers and jobs’ flows across OECD countries.

Tables 5 and 6 summarise the available information on different components of

jobs and workers’ reallocation on which we rely to perform international

comparisons.

As for job reallocation, on the one hand, we find the job mobility that occurs

as a consequence of job creation and destruction in newly created firms

(openings) and dead firms (closures) in the period of observation. On the other

hand, job reallocation is also generated as a consequence of job creation and

destruction in continuing firms, due to either expansion or contraction during the

period of observation. The source of information in the table is OECD (1996);

we have added the results by Dolado and Gómez (1995) for Spain using the

Bank of Spain Firms’ Survey for the period 1983-92. This permits to evaluate to


what extent the Spanish case shows idiosyncratic features with respect to other

different countries.10 From Table 4 we draw some general conclusions. First, the

aggregate job reallocation rate is high for most countries. In particular, non-

European countries (New Zealand, Australia and Canada) and some north-

European countries (Denmark and Sweden) show job reallocation rates around

30 per cent of total employment. On the other hand, those countries with the

lowest rates (around 15 per cent) are Belgium, Germany and the Netherlands.11

Second, the bulk of job creation and destruction due to openings and closures

varies among countries. In some of them (New Zealand, Australia, France and

the UK), its contribution to total employment is as larger as that of expansions

and contractions of continuing firms.

Given the heterogeneity of databases for the classification of openings and

closures of firms or establishments (see Contini et al., 1995), it may be

convenient to focus the international comparison on job creation and destruction

due to expansions and contractions of continuing firms. In this case, those

countries with the largest job reallocation rate are the same as before. Regarding

Spain, it would be safely classified as a country with low job reallocation rates,

together with Austria, France, Germany and the UK (Belgium and the

Netherlands should also be included, because they are countries with low overall

rates but they cannot be disaggregated between expansion-contraction and

openings-closures). At this respect, it is important to address that the study by

Dolado and Gómez (1995) refers to a sample of large manufacturing firms; thus,

it is likely that the Spanish job reallocation rate, as measured in Table 4, is

biased downwards.12

10 As always, these comparisons must be taken with caution, as the sample period and the characteristics of thedata sets are not homogeneous across countries.11 The low rate for the UK is likely due to the sample period (1985-91). This corresponds to a later period to thatof intense reshuffling process that took place during the first years of Thatcher’s governments.12 A similar result was obtained by García-Serrano (1996) for the Spanish case. Using a sample of large firms(500 or more employees), which is almost a census, of the Encuesta de Coyuntura Laboral, he obtains aquarterly job reallocation rate of 3.3 per cent for the period 1993-94. If we rise that figure to the year, we obtaina 13 per cent, something similar to that obtained previously. Therefore, in accordance with those results, the


After having checked that job reallocation rates vary among the OECD

countries, we will consider the mobility of workers. In order to try to check the

size of worker mobility as percentage of total employment and the importance of

job reallocation in bringing about worker mobility, we have built Table 6. In this

case, the number of countries for which information is available is lower, since

the number of databases with the appropriate information to calculate both

variables is smaller. That information refers to the amount of hirings and

separations taking place at firm level (and, by aggregation, at the economy)

during the corresponding period of observation. An additional feature that must

be taken into account is that information on job reallocation refers only to

continuing firms or establishments, so that total reallocation will be

underestimated as long as job reallocation due to openings and closures is

important.

Data from Table 6 seems to indicate that workers’ mobility is larger in the

US and Canada than in Europe (although the difference is less sizeable than one

might expect though). Spain is at the average of European countries with regard

to workers’ mobility. On the other hand, figures on the participation of job

reallocation on total worker turnover suggest that there is a great deal of

variation across countries. In the US and Denmark, job reallocation amounts to

over 40 per cent of workers’ turnover, while in the rest of the countries this

proportion is around 20-30 per cent. Thus, for most European countries, it is true

that the major component of worker turnover is due to rotation through a given

set of available jobs. As can be seen in the Table, the Spanish economy is

classified in that latter group.

Spanish economy would be classified as a country with low job reallocation rates due to expansion andcontraction of continuing firms.


6. The influence of labour market institutions on job tenure and workers’

flows: Estimation from panel data

We now turn to the estimation of the influence of labour market institutions

on job tenure and the magnitude of workers’ flows from panel data. For this

estimation we have to rely on workers’ flows, as data on jobs’ flows are not

available. We construct a balanced panel of 17 sectors and 17 regions (283

“segments”, after dropping some of them with missing values) for the period

1989-97. For each segment of the labour market we collect data on statistics of

the job tenure distribution, on workers’ flows, and on several labour market

institutions which may affect job tenure and turnover.

Theoretical models stress several determinants of labour market flows.

Matching models (Pissarides, 1990, Pissarides and Mortensen, 1997) focus on

productivity shocks (which affect to the market value of a match between jobs

and workers) and workers’ reservation wages. Thus, the incidence of

idysioncratic/reallocation shocks, possibly the different response of each firm

productivity to aggregate shocks, and the factors that explain workers’

reservation wages (unemployment benefits, the wage distribution, etc.) are the

main determinants of labour market flows. Other models (Lazear, 1990,

Bentolila and Bertola, 1992, Hopenhayn and Rogerson, 1993) have emphasised

the influence of firing restrictions. These models predict that the higher firing

costs are, the smaller the size of labour market flows is, as both hirings and

firings are lower. Bertola and Rogerson (1997) analyse the combined effects of

firing restrictions and wage compression to find that wage compression increase

turnover, as job creation in high productivity firms and job destruction in low

productivity firms are higher, the more compressed the wage structure is.

In order to test some of these implications of theoretical models on the

determinants of labour market flows, we run the following regression:


Xijt = λi + λj + µt + β Zijt + εijt , i=1,2,...,17; j=1,2,...,44;

t=1987,...,1997

where i stands for region, j stands for sector, t stands for time, Xij is either job

tenure or workers’ flows in region i and sector j, λi, λj and µt are, respectively,

regional, sectoral and time fixed effects, and Zij is a vector of institutional

characteristics of the labour market segment ij, which in some cases are defined

over ij, in some cases over i, and, in some cases, over j. The dependent variables

are flows from unemployment to employment (as proportion of employment in

the destination sector), from employment to unemployment (as proportion of

employment in the original sector), from employment to employment (as

proportion of employment in the destination sector) and total turnover

(computed as the sum of the three flows) from one year to the next. We also

introduce the lagged dependent variable as a regressor and allow for serial

correlation in the error term. Labour market institutions in each segment are

measured by the incidence of self-employment and fixed term employment, the

coverage of unemployment benefits in each region, the ratio of non-manual

workers’ earnings to manual workers’ earnings, and the coverage of collective

bargaining at the firm level.13

The estimations are performed with the DPD program (see Arellano and

Bond, 199 ). We estimate in differences and using instrumental variables (the

instruments are two lags of the corresponding dependent variable and of the

endogenous variables in Z from period t-2 to t-3). The results are in Tables 7

(panes a to d) and 8 (panels a to c). In each Table we present four set of

estimations (two for the period 1993-97 which include the ratio of non-manual

workers earnings to manual workers earnings as a regressor, and two for the

period 1990-97 which exclude this regressor).14 For each period, we estimate

13 The definition of the variables and the data sources are in the Appendix.14 The ratio of non-manual workers earnings to manual workers earnings is only available from 1989.


first with time and sectoral dummies, and then with time and regional

dummies.15 The regressors in Zij are: i) Self-employment (Proportion of self-

employees in region i and sector j), ii) Fixed-term employment (Proportion of

fixed-term employment in region i and sector j), iii) Coverage u Benefits

(Proportion of unemployed in region i receiving unemployment benefits), iv)

Wratio (Earnings of non-manual workers in region i over earnings of manual

workers in region i), v) Collective agreements at the region (Proportion of

employees covered by collective bargaining agreements in region i). In the

regressions for job tenure we also include the proportion of workers with above

high-school studies (Secondary and University Studies). Fixed-term employment

is related to the amount of firing costs. We take low values of Wratio as an

indication of a higher degree of wage compression. We also expect that a higher

coverage of collective bargaining increases wage compression. Finally, a higher

proportion of “educated” workers should increase job tenure.

First, we consider workers’ flows from unemployment to employment

(Table 7a). The results show that there is only one regressors whose coefficient

is positive and statistically significant: the incidence of fixed-term employment.

Fixed-term employment may increase the flows from unemployment to

employment for two reasons: i) as the incidence of fixed-term employment is

higher, firing costs are lower and, thus, hirings are higher, ii) fixed-term

employment increases the amount of rotation among a given set of jobs

(“churning”). Without a direct measure of firing costs in each segment of the

labour market, we cannot distinguish the relative importance of these two

explanations. Secondly, as for flows from employment to unemployment, we

find that, except for the proportion of self-employment, whose coefficient is

negative and barely significant, and fixed term employment, whose coefficient is

also marginally significant when regional and sectoral fixed effects are included

15 After dropping segments with missing values, we are left with some regions in which there are data only forone sector. Thus, we cannot perform estimations including both sectoral and regional dummies simultaneously.


simultaneously, no variable have significant effects on separations (Table 7b).

As for flows from employment to employment, as seen in Table 7c, the

coefficient of fixed-term employment is positive and very significant. In this

case, the coverage of unemployment benefits and the incidence of collective

bargaining reduce the flows. Finally, we focus on the determinants of workers’

turnover, defined as the flows from unemployment to employment and from

employment to either unemployment or employment (Table 7d). Our results

show that self-employment seem to reduce turnover (although the effect is not

statistically significant) while fixed-term employment substantially increases it.

The coverage of unemployment collective benefits and the incidence of

collective bargaining have, in some specifications, a negative effect on turnover

that is marginally significant. Overall, the results in Tables 7a to 7d suggest that

the main labour market institution behind workers’ flows is the incidence of

fixed term employment. To the extent that fixed-term employment are

negatively related to firing costs and that a higher coverage of collective

bargaining yields a more compressed wage structure, these results can be taken

as supporting evidence of models of labour market turnover which stress the role

of labour market institutions (as Bentolila and Bertola, 1990, and Bertola and

Rogerson, 1997).

The effects of labour market institutions on job tenure are reported in Table 8

(panels a to c). As for mean tenure, we find than self-employment increases job

tenure, while fixed term employment decreases it (a raise of one percentage

point in fixed term employment is estimated to decrease mean job tenure by 2

per cent). The proportion of workers with secondary and/or university studies

also increases job tenure, while, in some specifications, the incidence of

collective bargaining decreases job tenure. As for the incidence of “short jobs”

(the proportion of workers whose job tenure is less than one year) we find

similar results: self-employment and fixed term employment increase the

incidence of “short jobs” while an educational attainment reduces it. Finally, as


for jobs lasting more than 10 years, we also find a positive effect of self-

employment, and a negative effect of fixed term employment.

7. Concluding remarks

In the last three decades, the composition of the Spanish employment has

experimented huge changes in many dimensions (sectors, occupations, and

regions). At the same time, there also have been several labour market reforms.

In this paper we have tried to examine the main recent trends in labour

reallocation ant to estimate the effects of several labour market institutions on

labour market flows and turnover. Our main findings have been as follows:

a) Although there seems to be some evidence of higher job reallocation during

the mid-eighties from the evolution of the dispersion of employment growth

across different segments of the labour market (sectors, occupations,

regions), during the nineties job reallocation seems to have returned to the

levels of the early and late eighties.

b) Mean job tenure has decreased substantially in the last decade. This has

mostly affected to young workers, as the main reason for that decrease has

been a huge raise in the proportion of job lasting for less than a year,

especially among youngsters.

c) Workers’ mobility has noticeably increased, especially when short-term

employment and unemployment spells are computed in the workers’ flows.

While one out of seven active people changed its status (including job-to-job

changes and re-entries into unemployment) within a year between 1986 and

1987, that proportion is more than one out of four ten years later.


d) Job reallocation (creation and destruction) has remained more or less stable

during the eighties and nineties and only explains around one fourth of total

worker mobility, being the rest due to rotation of workers through a given set

of employment positions.

e) Fixed-term employment is one of the main variables influencing workers’

flows, affecting positively to the inflows into employment and to overall

turnover. Therefore, there is indirect evidence that firing costs (that are

negatively related to fixed-term employment) diminish workers’ turnover.

These results can be taken as supporting evidence of models of labour market

turnover which stress the role of labour market institutions.

f) Job tenure is also mainly affected by the incidence of fixed term

employment. A raise of one percentage point in fixed term employment is

estimated to decrease mean job tenure by approximately 2 per cent. The

incidence of “short jobs” is positively related to the incidence of fixed term

employment while the incidence of jobs lasting for ten years or more is

negatively related to fixed term employment (although the coefficients, in

this case, are not always statistically significant). Thus, we are left to

conclude that the main factor at changing the shape of the job tenure

distribution over the last decade has been fixed term employment.


APPENDIX

The definition and data sources of the variables used in the panelestimation in section 6 are the following:

1.- Dependent variables:

-Transitions from unemployment to employment in region i and sector j (asproportion of employment). Reference period: second quarters of twoconsecutive years. Source: Labour Force Survey.-Transitions from employment (region i, sector j) to unemployment (asproportion of employment). Reference period: second quarters of twoconsecutive years Source: Labour Force Survey.-Transitions from employment to employment in region i and sector j (asproportion of employment in the receiving sector). Reference period: secondquarters of two consecutive years. Source: Labour Force Survey.-Turnover in region i and sector j: Sum of the transition rates from employmentto unemployment, from unemployment to employment and from employment toemployment. Source: Labour Force Survey.-Mean job tenure. Source: Labour Force Survey.-Proportion of workers whose job tenure is less than a year. Source: LabourForce Survey.-Proportion of workers whose job tenure is ten years or more. Source: LabourForce Survey

2.- Independent variables:

-Self-employment: Proportion of self-employees in region i and sector j. Source:Labour Force Survey.-Fixed-term employment: Proportion of fixed-term employment in region i andsector j. Source: Labour Force Survey.-Ucoverage: Proportion of unemployed in region i receiving unemploymentbenefits. Source: Labour Force Survey.-Wratio: Earnings of non-manual workers in region i over earnings of manualworkers in region i. Source: Earnings Survey.-Collective agreement at the region: Proportion of employees covered bycollective bargaining agreements in region i. Source: Statistics on CollectiveBargaining.-Secondary and University Studies: Proportion of workers in sector j and regioni with high-school studies and above. Source: Labour Force Survey.


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Table 1: Sectoral composition of employment (%). Spain and EU, 1994.

Spain EU

Agriculture and fishing 9.9 5.4

Manufacturing 20.9 22.2

Mining 0.2 0.2

Electricity, gas and water distribution 0.7 1

Oil, gas and nuclear products 0.1 0.1

Mineral products 1.5 1

Food, drink and tobacco 3.2 2.1

Textiles 3.1 2

Paper and printing 1.4 1.8

Chemical products 1.1 1.7

Rubber and plastics 0.7 1

Equipment 2.1 3.9

Instruments 0.2 0.5

Metal products 2.6 3

Vehicles and transport materials 2 2.4

Wood and furniture 2.1 1.5

Construction 9.1 7.8

Services 60.1 64.6

Trade 17.2 14

Hotels and restaurants 6.1 4

Transportation 4.5 4

Mail and telecommunications 1.3 2

Financial and Real Estate 2.6 3.2

Services to firms 5.2 8

General administration 6.4 8

Educational and research 5.5 6.7

Health and social services 9.6 13

Recreational services 1.7 1.7

Source: European Economy.


Table 2. Dispersion of employment growth (%)*

Across provinces Across regions Across sectors Acrossoccupations

L LC L LC L LC L1979-84 4.03 .46 1.88 .46 4.20 .68 6.741985-90 4.76 .64 2.47 .47 5.24 .78 15.45 (1)1991-97 4.20 .42 2.33 .44 4.65 .44 7.45 (2)

*Averages of the standard deviations of growth rates. L: Lilien’s index. LC: Lilien’s index correctedfor cyclical effects. (1) Excludes 1987:2-1989:1. (2) 1991-93.


Table 3. Mean job tenure, proportion of employees in jobs lasting one year or less and proportion ofemployees in jobs lasting twenty years or more, Spain 1987-97

MEAN JOB TENURE1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997

Total 9.7 9.3 8.9 8.6 8.6 8.7 9.1 8.9 8.9 9.1 9.1Men 10.7 10.3 9.9 9.6 9.6 9.8 10.1 9.9 9.8 10.1 9.9Women 7.0 6.8 6.6 6.5 6.4 6.6 7.0 7.0 7.1 7.4 7.516-25 2.0 1.8 1.5 1.4 1.4 1.3 1.4 1.2 1.1 1.1 1.126-45 8.6 8.4 8.0 7.8 7.6 7.7 7.8 7.6 7.5 7.5 7.445-64 17.0 16.8 16.7 16.3 16.6 16.7 17.0 16.7 16.5 16.8 16.9Agriculture 9.8 8.8 8.6 7.5 7.7 7.2 6.6 6.2 6.0 6.3 5.7Extrac/Metal 13.0 12.6 12.0 11.5 11.7 12.0 12.8 12.7 12.6 12.6 12.3Other manufacturing 9.5 9.2 9.2 9.2 9.2 9.0 10.0 9.6 9.2 9.4 9.5Building 6.4 5.7 5.3 4.8 4.9 4.9 5.0 5.1 4.8 5.0 5.0Commercial services 8.6 8.3 7.8 7.6 7.6 7.9 7.9 7.7 7.6 7.8 7.7Public services 10.2 10.2 10.1 9.8 9.5 9.6 10.5 10.3 10.7 11.1 11.5

PROPORTION OF WORKERS IN EMPLOYMENT SPELLS LASTING LESS THAN 1 YEAR1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997

Total 24.2 27.4 31.0 32.7 32.5 35.3 33.3 34.8 36.7 35.9 36.6Men 22.6 25.6 29.2 30.7 29.4 32.3 30.4 32.3 34.4 34.0 34.7Women 28.3 31.7 35.1 37.2 38.8 41.4 38.9 39.5 40.9 39.3 39.916-25 56.0 63.9 69.6 70.1 69.2 76.1 74.4 77.5 81.2 81.2 80.926-45 19.0 20.8 24.2 26.6 26.7 30.1 29.4 31.3 33.1 33.3 33.945-64 10.1 11.3 12.3 13.6 13.0 14.3 13.5 14.9 16.2 15.5 15.9Agriculture 38.1 45.3 48.6 51.8 51.4 51.9 52.3 54.5 57.6 55.5 58.5Extrac/Metal 13.6 16.5 21.8 23.2 21.3 25.1 20.9 21.6 25.8 27.0 28.6Other manufacturing 24.2 28.1 28.9 31.5 31.0 35.9 32.0 34.9 38.8 36.9 38.0Building 45.2 49.7 55.3 56.5 53.4 57.6 56.6 59.1 62.5 61.7 60.6Commercial services 25.7 29.1 33.4 34.7 34.4 37.8 37.3 39.2 40.7 40.6 41.2Public services 16.6 17.6 19.7 21.5 23.8 25.8 22.2 22.9 22.0 21.0 20.3

PROPORTION OF WORKERS IN EMPLOYMENT SPELLS LASTING MORE THAN 20 YEARS1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997

Total 16.5 15.5 15.1 14.6 14.9 15.7 16.8 17.1 18.2 19.0 19.1Men 20.1 19.1 18.7 18.1 18.5 19.2 20.4 20.7 21.7 22.4 22.2Women 7.6 7.1 7.0 7.0 7.4 8.7 9.7 10.4 11.8 12.9 13.526-45 8.3 7.8 7.2 7.3 7.5 8.3 8.9 9.3 10.5 10.5 10.245-64 43.0 42.1 43.0 41.6 43.2 43.1 44.6 44.8 45.7 47.2 48.1Agriculture 22.0 18.9 19.4 15.7 16.7 14.6 12.4 12.0 11.4 12.1 10.8Extrac/Metal 25.9 24.7 23.9 22.7 23.8 26.6 29.1 30.4 33.0 32.8 31.6Other manufacturing 14.8 13.9 15.2 15.8 17.1 16.6 19.3 20.2 20.8 21.5 22.1Building 10.6 8.6 8.8 7.7 8.3 7.9 8.1 8.7 8.9 10.2 10.0Commercial services 13.5 12.9 12.0 11.9 12.6 13.5 13.3 13.4 14.3 14.8 14.8Public services 16.2 16.0 15.7 15.2 14.4 15.1 18.0 18.2 20.0 21.5 22.9

Source: Labour Force Survey, second quarters.


Table 4. Sectoral distribution of the employment-to-employment flows*

1986-90 Agriculture Manufacturing Building ServicesAgriculture 77.1 5.0 9.4 8.6Manufacturing 2.2 78.1 3.6 16.2Building 3.0 4.7 85.4 6.9Services 2.1 7.3 3.6 87.0

1991-97 Agriculture Manufacturing Building ServicesAgriculture 84.6 3.4 5.6 6.4Manufacturing 1.0 89.1 2.2 7.8Building 2.1 2.1 90.6 5.2Services 1.0 2.9 1.6 94.5*Proportion of workers who have changed jobs from one year to the next who are employed in eachsector. Source: LFS, second quarters, annual averages).


Table 5. Job creation and destruction in OECD countries *

Australia1984-85

Austria1991-93

Belgium1983-85

Canada1983-91

Denmark1983-89

Finland1986-91

France1984-91

Germany1983-90

Ireland1984-85

Gross job gains 16.1 - 7.7 14.5 16.0 10.4 12.7 9.0 8.8

Openings (1) 9.0 - - 3.2 6.1 3.9 6.1 2.5 2.7

Expansions (2) 7.1 5.7 - 11.2 9.9 6.5 6.6 6.5 6.1

Gross job losses 13.2 - 7.5 11.9 13.8 12.0 11.8 7.5 12.7

Closures (3) 8.7 - - 3.1 5.0 3.4 5.5 1.9 4.6

Contractions (4) 4.6 6.2 - 8.8 8.8 8.7 6.3 5.6 8.1

Net employment change 2.9 - 0.2 2.6 2.2 -1.6 0.9 1.5 -3.9

Net entry (1)-(3) 0.3 - - 0.1 1.1 0.5 0.6 0.6 -1.9

Net expansion (2)-(4) 2.5 - - 2.4 1.1 -2.2 0.3 0.9 -2.0

Job reallocation (1 to 4) 29.3 - 15.2 26.3 29.8 22.4 24.4 16.5 21.4

Openings-closures (1)+(3) 17.6 - - 6.3 11.1 7.2 11.5 4.4 7.3

Expansion-contraction (2)+(4) 11.7 11.9 - 20.0 18.7 15.2 12.9 12.1 14.1

Italy1987-92

Japan1985-92

Holland1984-91

NewZealand1987-92

Norway1985-92

Sweden1985-92

UK1985-91

USA1984-88

Spain1983-92

Gross job gains 11.0 - 8.2 15.7 8.1 14.5 8.7 8.2 -

Openings (1) 3.8 - - 7.4 2.1 6.5 2.7 1.4 -

Expansions (2) 7.3 8.6 - 8.3 6.0 8.0 6.0 6.7 3.1

Gross job losses 10.0 - 7.2 19.8 10.6 14.6 6.6 10.4 -

Closures (3) 3.8 - - 8.5 3.1 5.0 3.9 7.3 -

Contractions (4) 6.2 5.3 - 11.3 7.5 9.6 2.7 7.7 4.0

Net employment change 1.0 - 1.0 -4.1 -2.5 -0.1 2.1 -2.2 -

Net entry (1-3) 0.0 - - -1.1 -1.0 1.5 -1.2 -1.3 -

Net expansion (2-4) 1.1 3.3 - -3.0 -1.5 -1.6 3.3 -1.0 -1.0

Job reallocation (1 to 4) 21.0 - 15.4 35.5 18.7 29.1 15.3 18.6 -

Openings-closures (1+3) 6.5 - - 15.8 5.2 11.5 6.6 4.2 -

Expansion-contraction (2+4) 13.5 13.9 - 19.7 13.5 17.6 8.7 14.4 7.1* Sample periods are yearly averages, except for Germany, Denmark, Ireland, Italy, Holland, New Zealand, Sweden, the UK and the US, for which data refer to specific months. Information for

Austria, Belgium, Canada, France, Italy, Holland and the UK refer to firms. Data for Australia, Ireland, Holland, Norway and the US come from the manufacturing sector. Source: OECD(1996), and Dolado and Gómez (1995).


Table 6. Total worker turnover and job turnover for OECD countries *

Country Period Workers’mobility(1=2+3)

Hirings (2) Separations

(3)

Jobturnover

(4)

Jobs/Workers’turnover(4)/(1)

Surveys

Japan 1987 18.0 9.3 8.7

USA 1985 51.8 25.3 26.5

Administrative data

France 1987 59.6 28.9 30.7

Germany 1987 43.8 22.3 21.5

UK 1987 13.2 6.7 6.6

Spain 40.7 19.8 20.9

Establishment-level (yearly) data

Canada 1987-88 92.6 48.2 44.4 22.1 23.8

Denmark 1984-91 57.9 29.0 29.0 23.2 40.1

Finland 1986-88 77.0 40.0 37.0 19.5 25.3

France 1990-91 58.0 - - 12.9 22.4

Germany 1985-90 62.0 31.6 30.4 16.0 25.9

Italy 1985-91 68.1 34.5 33.6 22.8 33.5

Japan 1988-92 39.1 20.2 18.9 8.2 21.0

Netherlands 1988-90 22.0 11.9 10.1 7.0 31.8

Establishment-level (quarterly) data

USA 1979-83 31.6 16.1 15.5 13.4 42.4

Spain 1993-94 13.8 6.7 7.1 3.3 23.9 * Job reallocation (4) and total worker turnover (1) are given as percentage of total employment.Information refers to continuing firms or establishments. Source: Burda and Wyplosz (1994), OECD(1996), and García-Serrano (1996).


Table 7a. Estimation of the determinants of workers’ flows (I)*

Dependent variable: Flows from unemployment to employment(as proportion of employment in the receiving sector)

(1) (2) (3) (4)Constant -1.300

(.339)-1.214(.407)

-1.714(.339)

-1.609(.414)

Lagged dep. variable -.093(.031)

-.116(.035)

-0.97(.029)

-.120(.037)

Self-employment (%) .015(.063)

-.017(.049)

.015(.074)

-.009(.055)

Fixed-term employment (%) .243(.104)

.236(.123)

.241(.099)

-261(.123)

Coverage u Benefits (%) .048(.049)

.039(.054)

.041(.052)

.031(.058)

w ratio -- 1.734(3.008)

-- 3.553(3.169)

% Collective agreement at the region .014(.031)

.026(.034)

.014(.031)

.022(.034)

TIME DUMMIES YES YES YES YES

REGION AND SECTORALDUMMIES

NO NO YES YES

Sargan test (p-value) 43.25 (.056) 47.21(.172) 41.78 (.075) 48.40 (.144)

m1 .000 .000 .000 .000

m2 .561 .970 .613 .907

Sample period 1990-97 1993-97 1990-97 1993-97

* GMM IV estimation in differences, treating Self-employment and Fixed-term employment asendogenous. Instruments are lags of the endogenous variables from periods t-2 to t-3. Standard errorsare robust to heteroskedasticity and serial correlation.


Table 7b. Estimation of the determinants of workers’ flows (II)*

Dependent variable: Flows from employment to unemployment(as proportion of employment in the original sector).

(1) (2) (3) (4)Constant -.912

(.586)-.001(.388)

-1.037(.539)

.185(.375)

Lagged dep. variable -- -- -- --

Self-employment (%) -.069(.046)

-.094(.059)

-.082(.063)

-0.083(.064)


.151(.142)

.129(.086)

.163(.125)

Coverage u Benefits (%) .031(.028)

.036(.048)

.027(.030)

.035(.051)

w ratio -- -.156(4.038)

-- 0.061(4.218)

% Collective agreement at the region -.002(.027)

.020(.032)

-.001(.027)

.021(.031)



NO NO YES YES

Sargan test (p-value) 37.26 (0.24) 36.66 (.262) 31.78 (.201)

m1 0.000 0.000 0.000

m2 0.541 0.578 0.796

Sample period 1990-97 1993-97 1990-97 1993-97

* GMM IV estimation in differences, treating Self-employment and Fixed-term employment asendogenous. Instruments are lags of the endogenous variables from periods t-2 to t-3. Standard errorsare robust to heteroskedasticity and serial correlation.


Table 7c. Estimation of the determinants of workers’ flows (III)*

Dependent variable: Flows from employment to employment(as proportion of employment in the receiving sector).

(1) (2) (3) (4)Constant 1.937

(.731)1.085(.669)

1.523(.679)

.774(.190)


.009(.180)

.008(.183)

.033(.190)


.264(.197)

-332(.172)

.342(.199)

Coverage u Benefits (%) -.079(.049)

-.166(.063)

-.085(.052)

-.171(.068)

w ratio -- 1.354(4.894)

-- 3.093(5.111)

% Collective agreement at the region -.050(.036)

-.012(.044)

-.047(.037)

-.005(.046)



NO NO YES YES

Sargan test (p-value) 32.90 (.423) 26.63 (.429) 31.61 (.486) 28.01 (.358)

m1 .000 .000 .000 .000

m2 .652 .278 .646 .270

Sample period 1990-97 1993-97 1990-97 1993-97* GMM IV estimation in differences, treating Self-employment and Fixed-term employment asendogenous. Instruments are lags of the endogenous variables from periods t-2 to t-3. Standard errorsare robust to heteroskedasticity and serial correlation.


Table 7d. Estimation of the determinants of workers’ turnover*

Dependent variable: Sum of dependent variables in Tables 7a-7c.(1) (2) (3) (4)

Constant 1.010(1.357)

.098(.672)

.567(1.323)

-.259(.733)

Lagged dep. variable .018(.045)

-.020(.052)

.045(.050)

-.001(.058)


-.106(.203)

-.070(.220)

-.067(.214)


.553(.434)

.503(.348)

.670(.449)

Coverage u Benefits (%) -.029(.060)

-.082(.078)

-.045(.068)

-.105(.085)

w ratio -- 3.981(7.631)

-- 7.942(7.973)

% Collective agreement at the region -052(.040)

.027(.051)

-.057(.042)

.027(.052)



NO NO YES YES

Sargan test (p-value) 56.04 (.199) 48.12 47.81 (.480) 38.00 (.515)

m1 .000 .000 .000 .000

m2 .876 .877 .738 .952

Sample period 1990-97 1993-97 1990-97 1990-97* GMM IV estimation in differences, treating Self-employment and Fixed-term employment asendogenous. Instruments are lags of the endogenous variables from periods t-2 to t-3. Standard errorsrobust to heteroskedasticity and serial correlation.


Table 8a. Estimation of the determinants of job tenure*

Dependent variable: Mean job tenure (in logs)(1) (2) (3) (4)

Constant .029(.017)

.034(.015)

.046(.017)

.043(.017)


.067(.037)

.091(.031)

.093(.041)

Self-employment .435(.264)

.331(.308)

.439(.257)

.292(.306)

Fixed-term employment -2.106(3.25)

-2.305(.369)

-2.071(.301)

-2.282(.384)

Coverage u Benefits -.156(.127)

.080(.188)

-.193(.124)

.063(.192)

Collective agreement at the region -.047(.098)

-.200(.109)

-.033(.097)

-.191(.114)

Secondary and University Studies .569(.197)

.474(.242)

.378(.195)

.320(.249)

w ratio -- .110(.147)

-- .048(.155)



NO NO YES YES

Sargan test (p-value) 101.16(.064)

66.37 (.464) 99.95 (.075) 69.77 (.352)

m1 .000 .000 .000 .000

m2 .482 .259 .738 .350

Sample period 1990-97 1993-97 1990-97 1993-97* GMM IV estimation in differences, treating Self-employment, Fixed-term employment andSecondary and University Studies as endogenous. Instruments are lags of the endogenous variablesfrom periods t-2 to t-3. Standard errors are robust to heteroskedasticity and serial correlation.


Table 8b. Estimation of the determinants of job tenure*

Dependent variable: Workers with job tenure lower than one year(as proportion of total employment)

(1) (2) (3) (4)Constant .357

(.607)-1.374(.530)

-.131(.606)

-1.847(.570)


.120(.040)

.088(.035)

.121(.035)

Self-employment .159(.063)

.202(.077)

.196(.071)

.260(.096)

Fixed-term employment .779(.113)

.793(.119)

.817(.103)

.834(.111)

Coverage u Benefits .044(.045)

-.018(.059)

.040(.045)

-.044(.062)


-0.21(.041)

-.015(.034)

-.031(.043)

Secondary and University Studies -.172(.062)

-.132(.079)

-.116(.056)

-.075(.077)

w ratio -- -6.515(4.686)

-- -3.995(5.070)



NO NO YES YES


m1 .000 .000 .000 .000

m2 .591 .870 .789 .827



Table 8c. Estimation of the determinants of job tenure*

Dependent variable: Workers with job tenure higher than ten years(as proportion of total employment)

(1) (2) (3) (4)Constant -.016

(1.345)-.669(.771)

.159(1.110)

-.667(.765)


.280(.048)

.149(.059)

.220(.044)

Self-employment -.371(.175)

-.383(.194)

-.106(.195)

-.226(.168)

Fixed-term employment -.230(.144)

-.256(.169)

-.075(.134)

-.142(.169)

Coverage u Benefits -.035(.059)

.003(.076)

-.005(.060)

.020(.079)


-.038(.054)

-.066(.044)

-.027(.057)

Secundary and University Studies .059(.152)

.039(.165)

.098(145)

.082(.148)

w ratio -- 7.944(6.197)

-- 9.225(6.478)



NO NO YES YES


m1 .000 .000 .000 .000

m2 .242 .183 .118 .108



Figure 1a. Dispersion of employment growth across several segments of the Spanish (Lilien’s index)

Figure 1b. Dispersion of employment growth across several segments of the Spanish (Lilien’s index,corrected for cyclical effects and dynamics).

0.0125

0.0225

0.0325

0.0425

0.0525

0.0625

0.0725

0.0825

1978

1980

1982

1984

1986

1988

1990

1992

1994

1996

provinces regions occupations sectors

0.002

0.003

0.004

0.005

0.006

0.007

0.008

0.009

0.01

1979

1981

1983

1985

1987

1989

1991

1993

1995

1997

provinces regions sectors


0,0

2,0

4,0

6,0

8,0

10,0

12,0

14,0

16,0

84 85 86 87 88 89 90 91 92 93 94 95

Years

Per

cent

age

of to

tal e

mpl

oym

ent

JR

JR

JPOS

JPOS

JNEG

JNEG

Figure 2a. Job turnover as percentage of total employment. CBBE (1984-92) and ESEE (1991-95).


0,0

2,0

4,0

6,0

8,0

10,0

12,0

85 86 87 88 89 90 91 92 93 94 95

Years

Per

cent

age

of p

erm

anen

t em

ploy

men

t

JR

JR

JPOS

JPOS

JNEG

JNEG

Figure 2b. Job turnover for permanent contracts as percentage of total permanent employment. CBBE(1985-92) and ESEE (1991-95).

0,0

5,0

10,0

15,0

20,0

25,0

30,0

35,0

40,0

45,0

85 86 87 88 89 90 91 92 93 94 95

Years

Per

cent

age

of fi

xed-

term

em

ploy

men

t

JR

JR

JPOS

JPOS

JNEG

JNEG

Figure 2c. Job turnover for fixed-term contracts as percentage of total fixed-term employment. CBBE(1985-92) and ESEE (1991-95).


0,0

5,0

10,0

15,0

20,0

25,0

30,0

35,0

40,0

86/8

7

87/8

8

88/8

9

89/9

0

90/9

1

91/9

2

92/9

3

93/9

4

94/9

5

95/9

6

96/9

7

Years

Per

cent

age

of u

nem

ploy

men

t in

t-1

U->E

U->U

Figure 3a. Turnover of unemployed people as percentage of total unemployment in the previous year.LFS (1987-97), second quarters.

0,0

2,0

4,0

6,0

8,0

10,0

12,0

14,0

16,0

18,0

86/8

7

87/8

8

88/8

9

89/9

0

90/9

1

91/9

2

92/9

3

93/9

4

94/9

5

95/9

6

96/9

7

Years

Per

cent

age

of e

mpl

oym

ent i

n t-

1

E->E

E->U

Figure 3b. Turnover of employed people as percentage of total employment in the previous year. LFS(1987-97), second quarters.


0,0

5,0

10,0

15,0

20,0

25,0

30,0

86/8

7

87/8

8

88/8

9

89/9

0

90/9

1

91/9

2

92/9

3

93/9

4

94/9

5

95/9

6

96/9

7

Years

Per

cent

age

of la

bour

forc

e in

t-1

With"internal"mobility

Without"internal"mobility

Figure 3c. Worker turnover as percentage of total labour force in the previous year. LFS (1987-97), secondquarters.


0,00

2,00

4,00

6,00

8,00

10,00

12,00

14,00

93-1

93-2

93-3

93-4

94-1

94-2

94-3

94-4

95-1

95-2

95-3

95-4

96-1

96-2

96-3

Quarters

Per

cent

age

WPOS

WNEG

JPOS

JNEG

Figure 4a. Job creation, job destruction, and worker mobility as percentage of total employment. ECL (1993-96).

0,00

5,00

10,00

15,00

20,00

25,00

30,00

93-1

93-2

93-3

93-4

94-1

94-2

94-3

94-4

95-1

95-2

95-3

95-4

96-1

96-2

96-3

Quarters

Per

cent

age

of e

mpl

oym

ent

WR

JR

Figure 4b. Worker and job turnover as percentage of total employment. ECL (1993-96).

labour reallocation, job tenure, labour flows and labour...

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