Download ISPE01-Paper-Feld 221503 en

A joint Initiative of Ludwig-Maximilians-Universität and Ifo Institute for Economic Research
Labour Market Institutions and
Public Regulation
– A CESifo and ISPE Conference –
CESifo Conference Centre, Munich
26-27 October 2001
Growth, Unemployment, Investment, and
Employment Protection Legislation: Panel
Evidence for the EU-12 from 1970 to 1996.
Lars P. Feld
CESifo
Poschingerstr. 5, 81679 Munich, Germany
Phone: +49 (89) 9224-1410 - Fax: +49 (89) 9224-1409
E-mail: [email protected]
Internet: http://www.cesifo.de
Growth, Unemployment, Investment, and
Employment Protection Legislation:
Panel Evidence for the EU-12 from 1970 to 1996
by
LARS P. FELD
UNIVERSITY OF ST. GALLEN
SIAW-HSG AND CESIFO
Abstract
The persistence of European unemployment compared to unemployment in the U.S. and the
differences in the share of long term unemployed between both continents are often attributed
to differences in labor market institutions and particularly to employment protection legislation (EPL). In this paper, I use a new set of EPL indicators on individual and collective dismissals, part-time work, temporary work, fixed-term contracts and working time for the EU12 in an annual panel from 1970 to 1996. Using this data set, a macroeconometric model is
estimated with GDP growth, unemployment and private investment as functions of labor market regulations explicitly considering the relationship between these three endogenous variables. The main findings are a relatively robust negative relationship between the strictness of
regulation on dismissals and GDP growth per capita, a positive relationship between dismissals’ regulation and unemployment and virtually no relationship between EPL and investment.
Paper prepared for the CESifo/ISPE conference on ‚Labour Market Institutions and Public
Regulation‘, 26. – 27. October 2001 in Munich (Germany). – Preliminary Version, September
27, 2001. – I would like to thank ANTOINE SANTONI for allowing me to use his data on labor
market regulation. He really did an enormously honorable work.
Keywords: Employment Protection Legislation, Labor Market Adjustment, Unemployment.
JEL Classification: K31, J23.
Mailing Address:
Dr. Lars P. Feld
University of St. Gallen
SIAW-HSG, Institutsgebäude
Dufourstr. 48
CH-9000 St. Gallen
Switzerland
e-mail: Lars.Feld@ unisg.ch
–2–
1.
Introduction
The persistence of European unemployment compared to unemployment in the U.S., in particular the differences in the share of long term unemployed between both continents, is often
attributed to differences in labor market institutions. Quite a number of labor market differences might explain different unemployment rates, but the focus of many economists is on
two categories of labor market institutions: market power of unions and employer organizations on the one hand, and government policies on the other hand. Labor market regulations
and, as a part of these, employment protection legislation (EPL) is particularly accused of being detrimental for employment development in Europe.
However, this view is not unambiguously supported neither from theoretical grounds nor from
empirical evidence. EPL are fixed costs of employment1 and therefore reduce the number of
workers hired in economic upturns, but also those fired in economic downturns. Less workers
become unemployed, although those being laid off may remain unemployed for a longer time
period. Thus, the net impact of EPL on employment during a business cycle is ambiguous.2
BLANCHARD (2000) and BLANCHARD and WOLFERS (2000) argue that EPL explain the differences in unemployment rates between OECD countries and their development across time
mainly in combination with important macroeconomic shocks. During the oil price shocks of
the seventies, firms had no choice but to lay off employees despite high firing costs caused by
EPL. The shocks rendered a non-negligible part of their equipment obsolete such that larger
restructuring efforts were necessary. Though it couldn’t stop the subsequent increase in unemployment, EPL prevented investors from hiring additional employees early in the recovery of
economic activity. Those unemployed up to then suffered from a depreciation of their human
capital that further reduced their attractiveness for firms. They became long-time unemployed
while macroeconomically a persistence of unemployment occurred.
BLANCHARD and WOLFERS (2000) pay strong attention to the role of investors during macroeconomic shocks. As costs of employment, EPL may affect the profitability of investment and
may thus also have an indirect impact on employment. RISAGER and SØRENSEN (1997) show
that the importance of such a relationship depends on the assumptions concerning aggregate
demand on product markets. If the price elasticity of demand of the goods produced by a firm
is high, EPL lead to lower investment and to reduced employment. If demand is relatively
price inelastic, these effects are only moderate. A higher price elasticity reduces the ability of
firms to shift the burden of EPL to consumers and thus decreases the profitability of investment. The extent of the reduction in employment depends in addition on the elasticity of substitution between labor and capital. The more capital substitutes for labor, the more important
are the indirect effects of EPL on employment. According to BERTOLA (1994), such a reduction in the profitability of investment which is caused by EPL will also affect economic
growth. Because of less investment the accumulation rate of capital declines and so does the
growth rate. Whether this only holds in the transition to steady state or leads to persistent
1.
See OI (1962) and ALOGOSKOUFIS, BEAN, BERTOLA, COHEN, DOLADO and SAINT-PAUL (1995),
Chap. 5, but basically already HICKS (1932), p. 228 for such an assessment.
2.
The theoretical papers by LONG and SIEBERT (1983), BERTOLA (1990, 1999), BENTOLILA and
BERTOLA (1990), BURDA (1992), HOPENHAYN and ROGERSON (1992, 1993), FLANAGAN (1993),
BOERI (1999) corroborate this view. See also BERTOLA, BOERI and CAZES (1999) for a survey.
–3–
growth differences depends on the growth model behind this reasoning. In endogenous growth
models, EPL might lead to persistent differences.
SAINT-PAUL (1997) argues that EPL biases optimal international specialization. Strong EPL
increases firing costs such that investors in a country tend to produce relatively ‚secure‘
goods, i.e. mature goods in later stages of the product cycle. If goods in the earlier stages of
the product cycle are more ‚high-tech‘, a negative impact on economic growth results. SAINTPAUL (2001) shows that less innovations therefore occur leading to permanent growth losses.
AGHION and HOWITT (1998, chap. 12, pp. 427) and CABALLERO and HAMMOUR (1998, 2000)
point to the additional possibility that EPL might harm creative destruction in an economy,
thus reducing the profitability of R&D investment and subsequently economic growth. Structural changes in the economy are slowed down and innovations are postponed. Following
these arguments, a particularly detrimental role can be attributed to regulations increasing the
costs for collective dismissals because they reduce the ability of firms to adapt to structural
changes and adopt innovations.
This selection of theoretical arguments and an additional look into the literature illustrate that,
first, the impact of EPL on employment and unemployment is theoretically ambiguous. Second, the impact of EPL on private investment may be negative, positive or negligible depending on price elasticities on product markets, the substitution elasticity between labor and
capital and the interplay between substitution and output effects. Third, and theoretically least
contested, EPL is supposed to have a negative impact on economic growth. However, since
employment and investment affect each other and economic growth as well, EPL may have
direct and indirect effects that may compensate for each other. Whether there really is fire
behind the smoke can thus obviously not be resolved by theoretical arguments. It is eventually
an empirical question as to whether EPL increases unemployment or simply smoothes it during the course of a business cycle, whether it affects private investment and economic growth
at all and to what extent it does.
The recent surveys of GREGG and MANNING (1997), DI TELLA and MACCULLOCH (1999) and
OECD (1999) indicate however that the empirical evidence on the impact of EPL on labor
market outcomes is inconclusive as well. According to GREGG and MANNING (1997) the existing evidence „[is] much less persuasive than is commonly believed“ and that the trust „in
the merits of labor market de-regulation is misplaced“ (p. 395). According to the survey of
OECD (1999), seven out of nine studies find no significant correlation between EPL and unemployment rates. However, most studies conclude that EPL leads to significantly higher
long-term unemployment or a significantly higher duration of unemployment spells. Employment appears to be more stable and the persistence of unemployment increases due to EPL.
These results are corroborated by new empirical results of the OECD (1999) using new indicators of EPL. BLANCHARD and WOLFERS (2000) provide evidence that clearly stands out of
the other studies. They report strong results that EPL lead to increases in unemployment together with important macroeconomic shocks.
However, most empirical studies on the impact of EPL suffer from particular shortcomings.
The indicators of the strictness of EPL in the different countries measure labor market regulations insufficiently. The EPL indicators in most studies are based on at best three to four cross
sections provided by EMERSON (1988) and BERTOLA (1990), GRUBB and WELLS (1993) and
the OECD (1994, 1999) for 1985, an average of the late eighties and of the late nineties, re-
–4–
spectively. These indicators measure regulation on individual and collective dismissals, fixedterm contracts, and temporary work. LAZEAR’s (1990) data are on a yearly basis from 1956 to
1984, but they cover only two aspects of individual dismissals in regular labor contracts, the
legal notice period and severance pay. The OECD and EMERSON’s data thus obtain their main
variation in the cross section domain, particularly if it is taken into account that the variation
of EPL occurred to a considerable extent in the seventies. While the LAZEAR data do measure
developments over time, they are restricted to legal notice period and severance pay only and
do not distinguish between individual dismissal in regular contracts and collective dismissals,
temporary work and fixed-term contracts. The existing panel evidence, e.g. that provided by
NICKELL and LAYARD (1999), is thus to a large extent based on insights from a variable that
does not change much (or not at all) over time. BLANCHARD and WOLFERS (2000) consider
variation over time, but to the costs of having an imperfect indicator for the seventies. In addition to these shortcomings, these imperfect measures may be even more severely biased
because, as BERTOLA, BOERI and CAZES (2000) point out, these indicators only measure the
legal strictness of EPL as provided by the labor code and additional laws without considering
the impact of the courts and labor unions.
A different approach is provided by DI TELLA and MACCULLOCH (1999). They asked managers of firms in different countries as to their assessment of the strictness of EPL. Such an approach bears the advantage that it does not have to struggle with the details of legal provisions
(usually in national languages only) and courts‘ rulings, but offers the subjective assessment
of people being regularly confronted with legal problems due to EPL. This advantage incorporates a disadvantage because subjective responses may suffer from several biases that are not
inherent in revealed behavior. For a panel of 21 OECD countries from 1984 to 1990, these
authors nevertheless find a negative correlation between employment and their EPL indicator
as well as a positive relationship with unemployment and with long-term unemployment.
There are only a few studies analyzing the impact of EPL on economic growth and none investigating private investment and EPL.3 KOEDIJK and KREMERS (1996) study the relationship
between labor and product market regulation and average GDP growth of 11 EU countries
between 1981 and 1993. They find a significant negative relationship between product market
regulation and GDP growth, but no relationship between GDP growth and labor market regulation. Their results suffer however from low reliability due to the small sample of 11 observations. BERGER (1998) estimates the impact of labor market regulation on GDP growth in a
time series analysis for Germany from 1951 to 1991. He uses the number of cases before the
labor courts as an indicator of the strictness of EPL in Germany, but only finds a marginally
significant negative relationship between EPL and growth.
In this paper, I use a new set of EPL indicators on individual and collective dismissals, parttime work, temporary work, fixed-term contracts and working time for the EU-12 in a panel
from 1970 to 1996.4 For the first time, EPL indicators are collected on a yearly basis such that
3.
KANNIAINEN and VESALA (2000) provide cross section evidence for 19 OECD countries that
EPL adversely affect enterprise formation, but do not extend their analysis (and their argument)
to private investment in general.
4.
These data are described in the doctoral dissertation of SANTONI (2001). See also FELD and
SANTONI (2000) and FELD (2001) for brief descriptions of the data. The introduction to that data
set in Section 2 is the first that is provided in English.
–5–
usual panel data methods can be applied. These data particularly allow for the investigation of
the time series domain of these variables. In that respect, I follow the claim of BLANCHARD
and WOLFERS (2000) and BOERI, BERTOLA and CAZES (2000) that more detailed indicators are
necessary. Using this unique data set, a macroeconometric model is used in which real per
capita GDP growth, unemployment and real private investment are estimated as functions of
labor market regulations and standard control variables by explicitly considering the relationship between these three endogenous variables. The evidence presented in this paper is thus
the first panel data evidence on the relationship between economic growth and EPL and between private investment and EPL.
The main findings are a relatively robust negative relationship between the strictness of regulations on dismissals and real per capita GDP growth, a positive relationship between dismissals regulation and unemployment and virtually no relationship between EPL and real private
investment. The paper is organized as follows: In Section 2, the data on employment regulation are briefly described. The econometric model is presented in Section 3 followed by the
empirical results in Section 4. The paper is concluded by some final remarks in Section 5.
2.
Data on Employment Protection Legislation
The EPL indicators used in this paper cover regulation on individual and collective dismissals,
fixed-term contracts, part-time work, temporary work and working time of the twelve EU
member countries, Belgium, Denmark, France, Germany, Greece, Ireland, Italy, Luxembourg,
the Netherlands, Portugal, Spain, and the United Kingdom during the period 1970 to 1996 on
an annual basis.5 About 600 laws and legal notices are summarized in these indexes. The data
used here refer only to written statutes provided in the labor code, the private code or other
laws. Courts’ rulings and contractual self-regulations by unions and employer organizations
are not considered.6 The written statutes can thus be understood as minimum standards only.
They might well underestimate the impact of EPL on economic performance. However, the
advantage of these data lies in the fact that they are generally binding for all employers and
employees. This is particularly important with respect to countries whose labor market is
strongly influenced by collective agreements between employers and employees, but whose
coverage rates are not sufficiently known.
These indicators measure strictness of EPL on an ordinal scale from 0 to 9 and can therefore
not be interpreted quantitatively. They take on the value of ‘0’ when there is no legal restriction in a country at a given point in time, ‘9’ when a regulation precludes certain actions and
the medium scale value ‘5’ when regulations correspond to EU directives or ILO conventions.
For example, regulations for collective dismissals are assessed by finding out first whether
and to what extent a country follows the EU directives of 1975 and 1992 are followed. In addition, equal treatment of blue collar and white collar workers, administrative allowance, the
duty to consult and inform trade unions, severance pay and legal notice periods as well as the
requirement to create a social compensation plan (‘social plan’) are considered. This is done
by a catalogue of criteria that allow for an international comparison. Nevertheless, counter-
5.
SANTONI (2001) is the person who did the enormously honorable task to collect these data from
laws and regulations provided nearly exclusively in the national languages.
6.
I thus follow BERTOLA, BOERI and CAZES (1999, 2000) only with respect to the time variation of
the data, but not with respect to the extension of the data base to courts‘ rulings.
–6–
vailing effects between different indicators and within an indicator may occur. In the Netherlands, for example, regulation on part-time work is relatively loose while individual dismissals are strongly restricted due to the requirement of administrative allowances. The reform of
labor market regulation in Spain in 1994 entailed stricter EPL, because the reasons for the
allowance of fixed-term contracts were tightened, and a relaxation of EPL, because temporary
work agencies were permitted. Table 1 indicates that the U.K., Ireland and Denmark possess
relatively liberal labor market regulations while Germany, France and Belgium have more
restrictive EPL. The strictest EPL are observed in Greece, Italy and Spain.
Table 1:
Comparison of Indexes of Employment Protection Legislation, 12 EUMember Countries
LAZEAR BERTOLA
(1990)
(1990)
OECD
(1999)
Own Indexes Based on
SANTONI
(2001)
1956-84
1985
Late
1980’s
Late
1990’s
Weighted Average
Late
1970-84
1990’s
Average
1985-91
Average
1992-97
Belgium
10
9
13
13
16
6.27
10.75
11
Germany
11
6
14
18
20
8.91
10.54
10.78
Denmark
14
2
7
8
8
8.27
7.5
6.22
France
15
8
10
21
21
8.8
11.25
12.28
Greece
16
–
16
24
24
11.56
12.17
12.33
Italy
19
10
18
23
23
12.91
13
12.5
Ireland
1
–
4
4
5
4.84
7
7.78
Luxembourg
–
–
–
–
–
3.82
4.5
9.28
Netherlands
9
3
11
14
13
11.91
11.29
11.44
Portugal
13
–
19
25
26
4.22
7.71
9.56
Spain
17
–
17
22
22
5
13.46
10.94
U.K.
7
4
2
2
2
4.47
6
5.56
Mean
12.14
6
10.71
14.14
14.71
8.79
10.05
9.97
Median
11
6
11
14
16
8.80
10.75
11
Maximum
19
10
18
23
23
12.91
13
12.50
Minimum
7
2
2
2
2
4.47
6
5.56
Standard
Deviation
4.10
3.11
5.15
7.38
7.61
2.95
2.43
2.86
J.-B.
0.46
0.68
0.24
0.46
0.65
0.29
0.71
1.12
Notes: ‘–‘: Not available. Source: OECD (1999), p. 67. LAZEAR’s index is based on the average of 1956 to
1984. The own indexes are the rank sums of regulations for individual and collective dismissal, fixed-term contracts and temporary work according to SANTONI (2001) averaged over the respective periods for comparability.
J.-B. is the value of the Jarque-Bera-test on normality.
This order of countries is not very surprising for insiders in labor market regulations. The
rankings obtained from the data of LAZEAR (1990), BERTOLA (1990) and the OECD (1994,
1999) are thus not totally different from the data collected by SANTONI (2001). This holds de-
–7–
spite the fact that in contrast to the indicators used here, those authors provide rankings of
countries with ‘1’ for the country with the lowest strictness of labor market regulations and
higher values for lower ranks. No number occurs twice. The message of both kinds of measurement is the same: Higher values reflect stricter EPL, lower values lower strictness of EPL.
In order to enable a comparison of the SANTONI-indexes with existing ones, the rank sums of
regulations for individual and collective dismissal, fixed-term contracts and temporary work
according to SANTONI (2001) are computed and averaged over three different periods. Regulations on part-time work and working time are not considered in this comparison (but in the
empirical analysis) because LAZEAR, BERTOLA and the OECD do not consider them either.
The three periods chosen were 1970 to 1984 for a comparison with LAZEAR’s index which is
averaged over 1956 to 1984, 1985 to 1991 for a comparison with the EMERSON/BERTOLA index and the OECD late eighties index, and finally 1992 to 1997 for a comparison with the unweighted and weighted OECD late nineties indexes.
Table 2:
Spearman Rank Correlations between Indexes of Employment Protection Legislation, 12 EU-Member Countries
LAZEAR
(1990)
BERTOLA
OECD
(1999)
Own Indexes Based on
SANTONI
(2001)
(1990)
1956-84
1985
Late
1980’s
1.000
–
–
–
–
–
–
–
BERTOLA 1985
(1990)
0.464
1.000
–
–
–
–
–
–
OECD
(1999)
Late
1980’s
0.664*
0.679(*)
1.000
–
–
–
–
–
Late
1990’s
0.736** 0.643(*) 0.909**
1.000
–
–
–
–
Weighted Late
1990’s
0.745**
0.786*
1.000
–
–
–
Average
1970-84
0.427
0.250
0.209
0.264
0.218
1.000
–
–
Average 0.755**
1985-91
0.536
0.655*
0.664*
0.645*
0.706*
1.000
–
0.609*
0.643
0.527(*) 0.627*
0.618*
0.741**
0.839**
1.000
LAZEAR
(1990)
Own
Indexes
Based on
SANTONI
(2001)
1956-84
Average
1992-97
Late
Weigh- Average Average Average
1990’s ted Late 1970-84 1985-91 1992-97
1990’s
0.918** 0.991**
Notes: ‘–‘: Not indicated. ‘**’, ‘*’ and ‘(*)’ indicate significance at the 1, 5 or 10 percent level.
Table 1 indicates some differences between the indexes. They are most notable between LAZEAR’s index and the SANTONI index for the period 1970 to 1984, most illustrative in the case
of Spain and Portugal. This difference results from the fact that LAZEAR considers legal notice
periods and severance payments only, while the SANTONI index is more comprehensive.
BERTOLA’s index and the SANTONI index for the period 1985 to 1991 differ also considerably,
while the OECD index for the late eighties appears to be quite close to the latter. The same
–8–
holds with respect to both the OECD late nineties indexes and the SANTONI-index for 1992 to
1997. This assessment is corroborated by the Spearman rank correlation between the indexes
in Table 2. While the SANTONI indexes for the eighties and nineties are significantly associated with the OECD indexes, the SANTONI index for 1970 to 1984 provides additional information. It is neither significantly associated with the OECD nor the BERTOLA and LAZEAR
indexes although the latter appears to be more closely correlated to the early SANTONI index
than any other index. This comparison shows that the strictness of EPL is consistently measured by the SANTONI indexes. The less than perfect association with existing indexes reveals
that there is interesting additional information incorporated in the SANTONI index.
While the additional information for the seventies and early eighties stems from additional
regulation components as compared to LAZEAR, the additional information for the late eighties
and the nineties is obtained by following the development of regulations over time. Focusing
more closely on the time dimension in Table 1, it is obvious that a higher value for a country
in the case of the SANTONI indexes indicates stricter EPL. This strictness of EPL is measured
by consistently comparing regulations across countries and time. This is not obvious from the
indexes of the other authors. They assess the strictness of EPL consistently only across countries. The regulations of France at rank 10 in the late eighties according to OECD (1999) may
hypothetically be accompanied by higher, lower or the same strictness of that EPL measured
by rank 21 in the late nineties. The change in the ranks may simply be the result of regulatory
reforms in other countries that may or may not affect the French economy at both points in
time. It requires assumptions on openness of the country, the extent of international regulatory
competition, globalization and so on to argue that the (hypothetically) same legal provisions in
the late eighties and the late nineties are perceived differently by employers and employees in
a country. Thinking about the meaning of such rank orders clearly reveals that adding them up
across time is not very useful. It is thus a strong advantage of the SANTONI data used here that
a real time dimension is provided.
In addition, these data allow for observing regulation policies over time more closely. They
reveal an average increase of EPL strictness from the seventies to the eighties and a moderate
decline of average EPL strictness in the nineties. The median for the latter time comparison
shows the opposite, i.e. a slight increase in strictness. These summary figures are the result of
quite interesting patterns of EPL developments in different countries. There are strong increases of EPL strictness in France, Portugal and Spain across time although the latter reduces
the strictness between the late eighties and nineties. There are moderate declines in Denmark
and the Netherlands and moderate increases in strictness in Germany, Greece and the U.K.
There are also different patterns of regulation, deregulation and re-regulation. In general, deregulation policies in the 12 EU member countries across time were only moderate in the case
of regulation of individual and collective dismissals, fixed-term contracts, part-time work,
temporary work and working time. While the states with dictatorial regimes, Greece, Portugal
and Spain, started from relatively moderate regulation levels in the beginning of the seventies,
they quickly caught up with their new partner countries after joining the EU (then EC). The
seventies were however also a time period of increasing strictness of EPL for the original EC
member countries. The deregulation discussion in the eighties and nineties influenced regulation outcomes as well. There are deregulations of the laws on individual dismissals in Portugal in 1983, 1988 to 1990 and in France in 1986. Regulations of collective dismissals and
temporary work were relaxed in the Netherlands in 1985 and 1990. There were deregulations
–9–
of fixed-term contracts in Italy, of part-time work in Belgium and Spain and of working time
in France. Many of them were only moderate however and were compensated by an additional
tightening of these provisions later. Examples are the re-regulation of working time in France
in recent years or the regulation of individual dismissals in Germany after the government
change to the coalition of social democrats and greens in 1999.
Figure 1: Index of Regulation on Individual Dismissals in Germany, 1970 to 1996
7
6
5
4
3
2
1
0
70 72 74 76 78 80 82 84 86 88 90 92 94 96
To illustrate this picture of EPL in the EU further, the regulations of dismissals in Germany
and France are compared. Figures 1 and 2 indicate the development of regulations for individual dismissals in Germany and France, while Figures 3 and 4 offer the development of
regulation on collective dismissals in both countries.7 The German regulation of individual
dismissals in regular contracts for permanent workers starts from the general principle of continued existence of a labor contract. The private code distinguishes between ordinary and extraordinary dismissals. Ordinary dismissals are accompanied by specific notice periods and are
regulated by the employment protection regulation. Extraordinary dismissals are only possible
for specific reasons. Regulations on individual dismissals are not valid for firms with five or
less employees (excluding apprentices).
According to Art. 622 BGB of 1970, legal notice periods were different for blue collar and
white collar workers. Blue collar workers had a legal notice period of two weeks only, while
that of white collar workers was up to six months (after 20 years tenure). In addition, there
were differences in the consideration of tenure times, which started at an age of 25 years for
white collar workers, but only at an age of 35 years for blue collar workers. These differences
were ruled unconstitutional by the Constitutional Court in 1982. The legislation was however
not able to present a new law equalizing these differences until 1990. Since 1972, no changes
7.
See again SANTONI (2001) for the following description. For a comparison see OECD (1999),
Chap. 2 and the Appendix in BERTOLA, BOERI and NICOLETTI (2001).
– 10 –
in regulations for individual dismissal therefore occurred. The early change in 1972 resulted
from the introduction of a consultation requirement of labor councils.
As well in 1990, the German Constitutional Court ruled that legal notice periods should be
equalized. Given the long time, the legislature needed to consider the Court’s ruling of 1982,
the legislature was now required to change the law until 1993. This equalization of notice periods increased average notice periods for workers with more than ten years tenure and thus
lead to a tightening of EPL. It was followed by the increase of the employment requirement
for protection against unfair dismissal from 5 to 10 workers in 1996 (relaxing EPL) which was
reduced again to 5 employees in 1999 (leading to a tightening again).
Figure 2: Index of Regulation on Individual Dismissals in France, 1970 to 1996
8
6
4
2
0
70 72 74 76 78 80 82 84 86 88 90 92 94 96
While Germany appears to be a good example that the governments’ discussion of deregulation policies was mere rhetoric and thus is a bad example for the time series dimension in the
data used, the time variation of dismissals regulation in France is much stronger. According to
Art. L 122-4 of the labor code, contract partners can terminate the contract at any time. Already in 1958, a minimum legal notice period was established that worked asymmetrically
against employers. It was a month for employers and eight days for employees. A more important regulation against unfair dismissals stems from 1973 however. It imposed the requirement for a real and serious reason for any dismissal (‚cause réelle et sérieuse‘). The real
and serious reasons were defined by the courts, e.g. for not observing security standards or
working time. In 1975 an even more important regulation for unfair dismissal followed. It
required employers to seek an administrative allowance for (individual and collective) dismissals on economic grounds. Economic grounds were grounds that could not be personally
attributed to employees, but nevertheless led to job destruction. Until the administrations allowed for a dismissal, employees had an entitlement for employment on their job.
– 11 –
In 1982, regulations on unfair dismissals were refined in two minor, but opposite ways. On the
one hand, the guilt of employees was considered, on the other hand discriminatory reasons for
dismissals were precluded. Again more important changes in the labor code occurred in 1986
because the administrative allowance for (individual and collective) dismissals on economic
grounds was abolished. Additional regulations in 1989 increased the role of ‘social plans’ and
introduced a consultation requirement of unions. The statutory requirements about the contents of ‘social plans’ in 1993 was only a minor regulation that did not tighten EPL noticeably.
Summarizing the case of individual dismissals, the strictness of regulations in both countries
appears to be the same in the end of the nineties, but the development across time was quite
different. A similar assessment follows from an analysis of regulations on collective dismissals. Figure 3 broadly corresponds to Figure 1 and Figure 4 to Figure 2.
Figure 3: Index of Regulation on Collective Dismissals in Germany, 1970 to 1996
7
6
5
4
3
2
1
0
70 72 74 76 78 80 82 84 86 88 90 92 94 96
Without providing too many details, several general observations may conclude this section.
First, there are differences in strictness of EPL according to different regulatory components,
dismissals, fixed-term contracts and so on. Second, there are differences in the development
of the different EPL regulations over time. While the temporal pattern of regulation on collective and individual dismissal corresponds in Germany and in France, it does less so in other
countries and for other regulatory components. As mentioned above, regulatory packages, like
all log-rolling decisions in legislatures, contain sometimes countervailing regulations within a
component of EPL or across components. Third, consistently adding the time dimension to the
data provides additional information. While some indicators vary considerable in some countries, others vary less in other countries.
Finally, a kind of convergence of regulatory strictness can be observed from the seventies to
the nineties. In the case of regulations on individual dismissal, the median for the sample of
the 12 EU member countries increased from 3.0 in 1970 to 5.5 in 1996. The median values of
the other indicators for the EU-12 are: regulations on collective dismissals 0 in 1970 and 6.0
in 1996, fixed term contracts 1.5 in 1970 and 4.0 in 1996, part-time work 0 in 1970 and 4.0 in
– 12 –
1996; the strictness of regulation on temporary work increased from 0 to 5.0, that of working
time from 2.0 to 4.5. Thus, a ‘race to the top’ instead of a ‘race to the bottom‘ can be observed. It remains to be investigated whether AGELL’s (1999, 2000) social insurance arguments hold for the data used in this paper as well, or whether SAINT-PAUL’s (2000) political
economy arguments explain this development of EPL over time more precisely. Preliminary
evidence points towards a mixture of both (FELD, 2001).
Figure 4: Index of Regulation on Collective Dismissals in France, 1970 to 1996
10
8
6
4
2
0
70 72 74 76 78 80 82 84 86 88 90 92 94 96
3.
The Econometric Approach
3.1
The Basic Theoretical Considerations
The starting point for the empirical analysis is an underlying endogenous (Schumpeterian)
growth model provided by AGHION and HOWITT (1998, pp. 425).8 They specify a production
function for each sector of an economy with capital and labor as the two production factors.
Innovations are incorporated into capital. They depart from the usual Walrasian labor market
by assuming that labor market frictions exist that stem from positive hiring costs. The positive
hiring costs are the results of employment protection legislation. Workers, whether they are
organized in unions or bargain decentrally, obtain a wage proportional to the recent technological innovation. Each time they hire a worker, firms therefore additionally have to pay setup costs. The cost of labor is thus a function of wages and set-up costs for innovations which
can be attributed to each unit of labor. Besides the user cost of capital necessary to set-up innovations, the latter mainly consists of hiring costs. Together with the unit costs of capital
they determine the firms’ profit and thus labor demand and investment in an economy. Labor
demand and investment together with a specification of the value of innovation, as a function
8.
The model is only briefly summarized in this section. It can be obtained from AGHION and
HOWITT (1998). Specifying the main ingredients of the model is hopefully sufficient to follow the
thoughts behind the econometric approach.
– 13 –
of expected present values of rents accruing until a producer is replaced, and individual lifetime utility, as a function of the path of consumption, determine the steady state growth rate of
the economy. It depends positively on R&D productivity and negatively on hiring costs of
workers. Private investment and employment determine growth in the transition to the steady
state, but also in steady state due to the fact that they incorporate factor prices.
The growth equation can thus be specified as follows:
(1)
∞
∞
∞
i =0
i=0
i =0
g it = ai + ∑ β1iit + ∑ β 2uit + ∑ β 3 EPLit + vit1
where: git
the growth rate of real GDP per capita,
iit
real private investment (in percent of GDP),
uit
the unemployment rate,
EPLit employment protection legislation.
Private investment has a positive impact on economic growth in this model because it incorporates innovations. Innovations may be smaller for some kinds of investment projects, but
higher for others. As long as innovations are not consistently measured across countries and
time, private investment appears to be the best indicator of it. EPL are included because they
directly affect R&D negatively. EPL prevent structural changes from taking place. Given the
setting of an endogenous growth model, labor market regulations may lead to permanent differences in growth rates of GDP per capita between countries. The unemployment rate is included in the model because of a link between employment and investment that is usually
neglected, but emphasized by DAVERI and TABELLINI (2000, p. 60) in a recent paper.9 They
start from the common assumption that savings and investment grow with the marginal product of capital. If the capital stock is below its steady state value, the marginal product of capital is relatively higher than in steady state and the economy grows faster (and vice versa). An
exogenous shock that affects employment leads to adjustments of the steady state capital stock
through the ratio between capital and employed workers. Permanent changes in employment
lead to adjustments to the new steady state as well. For given capital-labor ratios and new
(lower) steady state values of capital, permanent employment reductions induce a lower marginal product of capital. Firms undertake less investment and the economy grows more
slowly. The adjustment process brings about a new steady state with the same capital-labor
ratio, but a smaller capital stock.
This process starts if there is involuntary unemployment that can be interpreted as a permanent change in employment. Because labor market frictions arise due to hiring costs, the labor
market is not cleared such that an involuntary unemployment may in fact result. These frictions can be interpreted to be similar to those that are found in the literature on job matching
(PISSARIDES, 1990). According to matching theory, the flow of workers into unemployment at
each date depends on the frequency of production units’ obsolescence and the number of units
producing, while the flow out of unemployment is the rate at which workers are matched with
plants (AGHION and HOWITT 1998, pp. 126). There is therefore also a feedback effect from
9.
The effect described in the following is independent of the specific OLG-framework chosen by
DAVERI and TABELLINI (2000). It requires only that involuntary unemployment occurs.
– 14 –
EPL and its impact on innovations via growth on unemployment. Introducing creative destruction in the model, a direct effect of innovations on unemployment stems from a creative
destruction effect. An increased growth directly raises the job destruction rate and thus the
unemployment rate. PISSARIDES (1990) discusses an opposite indirect effect, that AGHION and
HOWITT (1998, p. 127) call a capitalization effect: An increase in growth rates raises the returns from creating a new plant and the capitalized values of these returns. This effect encourages additional entry by new plants leading to job creation. Which effect dominates is an empirical question. This reasoning leads us to the unemployment equation:
(2)
∞
∞
∞
∞
∞
i =0
i =0
i =0
i =0
i =0
uit = bi + ∑ β 4iit + ∑ β 5 g it + ∑ β 6 wit + ∑ β 7 rit + ∑ β 8 EPLit + vit2
where: wit
rit
wage rates,
user costs of capital.
The relationship between investment, growth and unemployment has just been described. Investment and growth may have negative impacts on unemployment if the job creation effect
from capitalization dominates the creative destruction effect. Higher costs of labor lead to
higher unemployment, ceteris paribus. The costs of labor have been specified above as a
function of wages and set-up costs for new plants and equipment. These set-up costs consist
of hiring cost of labor and the user cost of capital. It can therefore be expected that higher
wages, higher user costs of capital and higher EPL lead to higher unemployment.
The corresponding reasoning eventually leads to the investment equation:
(3)
∞
∞
∞
∞
∞
i =0
i =0
i =0
i =0
i =0
iit = ci + ∑ β 9uit + ∑ β10 g it + ∑ β11wit + ∑ β12 rit + ∑ β13 EPLit + vit3 .
Unemployment has a negative effect on private investment, again via the adjustment process
to a new steady state after a permanent reduction of unemployment. GDP growth has a positive effect on investment via the capitalization effect. Wages, user costs of capital and hiring
costs (EPL) affect investment negatively.
In equations (1) to (3), β1 to β13 are (vector-valued) coefficients to be estimated and the vit
are the error terms of the equations. ai, bi and ci are country specific fixed effects that consider unobserved heterogeneity of the 12 EU member countries. The macroeconomic model is
estimated for the i = 1, ..., 12 EU countries, Belgium, Denmark, France, Germany, Greece,
Ireland, Italy, Luxembourg, the Netherlands, Portugal, Spain and the U.K. and the years t =
1970, ..., 1996. The year 1970 is used to compute the growth rates.
3.2
The Econometric Strategy
The variables are proxied in various ways. The growth rates of real GDP per capita of the 12
EU member states in the sample are from the SUMMERS and HESTON data set (PWT 6.0). A
specific problem occurs for Germany due to unification. Data for Germany from 1992 to 1996
are from the PWT 6.0 version, those from 1970 to 1990 are from the PWT 5.6 version. The
year 1991 is excluded in the German case instead of introducing a dummy variable for this
year. Real private investment in percent of GDP, standardized unemployment rates, wage
rates (measured by an index of men’s hourly wages) and the real long-term interest rate as a
– 15 –
proxy for the user costs of capital are from the OECD National Accounts statistics (CD ROM
version). The EPL data are the six SANTONI indexes described in Section 2.
In addition to the variables specified in the previous subsection, schooling (the percentage of
secondary school attainment in total population from the BARRO and LEE data set) as a proxy
for human capital, openness in percent of GDP (OECD National Accounts) and lagged real
GDP per capita (SUMMERS and HESTON data set) as a proxy for catch-up effects are included
as the standard controls used in growth equations. They are introduced in all three equations.
The econometric strategy consists in starting first with simple OLS regressions with fixed
country effects (Least Squares Dummy Variables Approach). Thus, the time series dimension
of the data is emphasized. Second, these regressions are varied according to the aggregation of
EPL indicators and the inclusion of additional controls as robustness checks. The aggregation
of EPL is done to level out compensating regulatory changes in the different EPL components,
in particular between regulation on individual and collective dismissals.10 This is also done to
check the robustness of the estimates with respect to multicollinearity problems. The additional controls included in the equations are the revenues from (employers’ and employees’)
social security contributions, personal income taxes, corporate income taxes and indirect taxes
each in percent of GDP (OECD Revenue Statistics). Their inclusion, motivated by results of
DAVERI and TABELLINI (2000), is done in order to correct for a potential omitted variable bias
in the equations. This bias may be particularly severe in the analysis of regulations because
taxes and regulations are different alternative instruments that can be used by governments to
achieve certain goals. There may be a correlation between these different measures. Because
the focus in this paper is not on the effect of taxes, but rather having taxes as an additional
control, it suffices to take tax revenue in percent of GDP instead of using effective tax rates
like DAVERI and TABELLINI. In the case of the growth equation, time dummies instead of fixed
country effects are included to test the robustness of the results with a focus on the cross section variation. The time dummies control for common shocks affecting the 12 EU countries.
Third, the model is estimated by 2SLS correcting for the potential bias due to obvious endogeneity of the three right-hand side variables in equations (1) to (3). Fourth, this procedure
is basically the same for all three equations, although each step is not exactly repeated for the
unemployment and investment equations in order not to bore the reader too much. In the unemployment and investment equations, an additional problem occurs due to the autocorrelation of residuals. They are captured by the introduction of lagged endogenous variables. Although T (the 26 years analyzed) may be sufficiently high to have only a small bias in the estimates and thus obtain consistently estimated coefficients (BALTAGI, 1995, p. 126), the lagged endogenous variables are instrumented by the two periods lagged endogenous variables
(ARELLANO, 1989). Since one of the six EPL components varies for one single country only in
the first two years (but differently across indicators), only the aggregate indexes of EPL can be
used in the 2SLS equations. The focus is on a dismissals’ index as the most important one.
10. The aggregation procedure is the sum of indicators. I do not compute (weighted or unweighted)
averages or medians. The basic effect does not change due to the fact that these ordinal indicators
cannot be interpreted quantitatively. The average is thus only an unimportant scale effect.
– 16 –
Table 3:
Panel Regressions of Real GDP Growth per Capita on Employment Protection Legislation and Controls, 12 EU-Member Countries, 1971 - 1996
Independent Variables
(1)
OLS
LSDV
(2)
OLS
LSDV
(3)
OLS
LSDV
(4)
OLS
LSDV
(5)
OLS
LSDV
(6)
OLS
TD
(7)
2SLS
LSDV
(8)
2SLS
LSDV
Individual Dismissal
- 0.214
(-0.83)
–
–
–
–
–
–
–
Collective Dismissal
- 0.173
(1.10)
–
–
–
–
–
–
–
Fixed-Term Contracts
- 0.244
(1.49)
- 0.242
(1.48)
–
- 0.005
(0.02)
–
–
–
–
Part-Time Work
0.380**
(3.15)
0.380**
(3.14)
–
0.301*
(2.53)
–
- 0.017
(0.29)
–
–
Temporary Work
- 0.031
(0.27)
- 0.034
(0.30)
–
0.016
(0.13)
–
–
–
–
Working Time
- 0.074
(0.31)
-0.072
(0.30)
–
- 0.143
(0.56)
–
–
–
–
Index of Dismissal
Regulation
–
- 0.374*
(2.18)
- 0.403*
(2.48)
-0.369(*)
(1.96)
- 0.345*
(2.00)
Real Private Investment (in % of GDP)
0.251**
(3.51)
0.248**
(3.76)
0.236**
(3.58)
0.172*
(2.56)
0.185**
(2.71)
0.154**
(5.32)
0.165*
(2.30)
0.120(*)
(1.69)
Unemployment Rate
(in %)
0.120
(1.55)
0.118
(1.58)
0.100
(1.29)
0.167*
(2.26)
0.173*
(2.30)
0.107**
(3.05)
0.200*
(2.50)
0.255**
(3.27)
Schooling
- 0.076
(1.47)
-0.076
(1.47)
- 0.030
(0.65)
- 0.052
(0.97)
0.016
(0.33)
-0.006
(0.46)
- 0.079
(1.58)
- 0.010
(0.19)
Openness (in % of
GDP)
0.079**
(3.80)
0.078**
(3.76)
0.055**
(2.66)
0.078**
(4.04)
0.066**
(3.30)
0.014**
(2.90)
0.043*
(2.38)
0.056**
(3.20)
Lagged Per Capita
GDP
- 0.070
(1.13)
-0.069
(1.13)
- 0.037
(0.07)
- 0.076
(1.11)
- 0.013
(0.22)
- 0.007
(0.17)
- 0.029
(0.46)
- 0.029
(0.46)
Social Security Payments (% of GDP)
–
–
–
–
–
- 0.649**
(4.45)
Personal Income Taxes (in % of GDP)
–
–
–
- 0.163
(1.31)
-0.234*
(2.17)
–
–
- 0.258*
(2.22)
Corporate Income
Taxes (% of GDP)
–
–
–
0.462(*)
(1.82)
0.458*
(2.21)
–
–
0.419*
(2.35)
Indirect Taxes (in
% of GDP)
–
–
–
0.182
(1.19)
0.099
(0.69)
–
–
0.101
(0.86)
2.929**
3.492**
–
1.989(*)
–
–
–
–
R2
0.156
0.156
0.132
0.219
0.206
0.425
0.101
0.254
SER
2.512
2.507
2.524
2.429
2.431
2.103
2.738
2.952
D.W.
1.642
1.641
1.621
1.687
1.696
1.571
1.546
1.619
F-Test: EPLIndicators
- 0.586** -0.582**
(3.50)
(3.81)
- 0.148(*) - 0.477** - 0.393**
(1.79)
(3.36)
(2.81)
Number of observations: 311. Instruments are real private investment in percent of GDP, the unemployment rate,
an index of men’s hourly wages and real long-term interest rates, all lagged by one period. LSDV indicates Least
Squares Dummy Variables estimates and TD indicates time dummies. The numbers in parentheses are the absolute
values of the t-statistics based on White-corrected standard errors. ‘**’, ‘*’ and ‘(*)’ indicate significance on the 1,
5 or 10 percent level. The F-statistic is the test statistic on the null hypothesis that the EPL indicators together are
not statistically different from zero. SER is the standard error of the regression. D.W. is the Panel Durbin-Watson
statistic on autocorrelation of the residuals. The Durbin-h statistic is provided for equations with a lagged endogenous variable.
– 17 –
4.
Estimation Results
The results are reported for the growth equation first (Section 4.1), followed by the unemployment (Section 4.2) and investment equations (Section 4.3).
4.1
Growth and Employment Protection Legislation
The results for the growth equation are presented in Table 3. The overall performance of the
model is reasonably well, although less than 20 percent of the variation can be explained. For
growth rates such a low R2 is however not that bad. There is no autocorrelation of the residuals according to the panel Durbin-Watson statistics in any of the specifications for the growth
equation. The standard control variables have the expected signs with two exceptions:
Schooling and the unemployment rate. Real private investment and openness both in percent
of GDP have the expected positive signs and are significant at the 1 percent level. These effects remain stable across all specifications, only the significance of private investment is reduced sometimes. Lagged per capita GDP has the expected negative effect, but is insignificant
in all equations. Schooling has an unexpected negative impact, but is not significant on any
conventional significance level. In addition, this effect is not fully robust across specifications.
It may be the result of the fact that the schooling variable only varies every five years and ends
in 1990, such that the time series approach in this panel data analysis is rather unfair to the
limited time variation of this variable.
Finally, the unemployment rate is consistently and unexpectedly negative, an effect that becomes significant if either public finance variables or time dummies are introduced or a 2SLS
specification is used. This positive effect can be explained by a reliance on creative destruction. If involuntary unemployment occurs due to exogenous changes in EPL and an adjustment process is induced that reduces private investment, it increases the returns from creating
a new plant and leads thus to an opposite positive effect on economic growth. Still, this positive effect in the growth equation comes as a surprise in particular because DAVERI and
TABELLINI (2000) recently presented results with an opposite effect of unemployment on
growth. Since the basic data used are not different, the differences in the results can either
stem from an omitted variable bias in their estimates due to the fact that EPL indicators are
not considered in their growth equation. Or it may be the result of the fact that they use five
years averages, and the model used here insufficiently captures business cycle effects. The
results with time dummies is however speaking against this argument.
The most interesting results in the growth equation are however the impacts of the different
EPL indicators. Remember that the hypothesis on the impact of EPL on growth is a negative
relationship. EPL increases the costs to innovate and thus reduces growth. This hypothesis is
valid for all components of EPL. A look at column (1) of Table 3 reveals, however, that this
hypothesis cannot be rejected only in the case of five of the six indicators used. In the case of
regulations on part-time work, a significant positive impact results. An F-test on the significance of all EPL indicators indicates that the null hypothesis of them together having no impact can be rejected at the 1 percent significance level. Performing an F-Test on the null hypothesis that all EPL indicators together except that on part-time work have no effect on GDP
growth per capita indicates that this hypothesis can be rejected on the 5 percent level (F =
2.494). That none of the EPL indicators except that on part-time work is separately significant
should thus not bother, if their common negative impact is significant.
– 18 –
However, it indicates that there may be compensating regulatory changes that divert the impact of single indicators. In order to find out whether something like that can be found in the
data, the regulation indexes for individual and collective dismissals are aggregated. This aggregate index of dismissal regulation substitutes for the two separate dismissal regulation indexes. Estimating the same model as in column (1) of Table 3 with this aggregate index, the
results presented in column (2) are derived. The aggregate index of dismissals is negatively
affecting GDP growth and significant at the 5 percent level. The significantly positive impact
of the index of part-time work regulation is virtually not changed. The hypothesis that the indexes of regulation on fixed-term contracts, temporary work and working time do not have
any impact on GDP growth can however not be rejected on any conventional significance
level (F = 1.201). That the significantly negative impact of the index of dismissal regulation is
not the result of a multicollinearity with the part-time work regulation is indicated by the results in column (3). Similarly, but not shown in the table, the significantly positive effect of
part-time work regulation obtains if introduced without dismissal regulation.
Both results remain relatively robust to the introduction of public finance variables (column
(4)). Of the four taxation variables, two are at least significant, depending on the specification.
Revenue from social security contributions in percent of GDP has a negative impact in each
specification and is significant at the 1 percent level. Corporate income tax revenue in percent
of GDP is positively affecting growth of GDP per capita, an impact that is significant at least
on the 10 percent level. This impact may result from the fact that corporate income tax revenue is chosen instead of effective tax rates. A reverse causation cannot be ruled out. Since the
results are robust to the exclusion or inclusion of that variable and taxes are not the focus of
this paper, it does not bother further. Personal income tax revenue is negatively affecting
growth, but the significance of this impact depends upon the exclusion of regulation on parttime work (column (5)). Since the impact of part-time work regulation is not robust in sign
and significance to a specification with fixed time effects instead of fixed cross-section effects
(column (6)), an emphasis on this positive impact of the regulation on part-time work on GDP
per capita growth would be misplaced. The negative effect of the index of dismissal regulation
remains however negative and is significant at the 10 percent level in the fixed time effects
equation.
The results indicate that regulation on individual and collective dismissals is consistently and
robustly reducing the growth rate of GDP per capita of 12 EU member countries in the OLS
specification. This effect may be biased however due to potential endogeneity between
growth, unemployment and private investment. Thus, the growth equation is estimated by
2SLS using the lagged values of private investment in percent of GDP, of the unemployment
rate, the wage proxy and real long-term interest rates as instruments. The results in columns
(7) and (8) with and without public finance variables indicates that a robustly significant
negative impact of regulations on individual and collective dismissals prevails.
These results lend support to the view that EPL, in particular the regulations making individual and collective dismissals more expensive, is harmful for economic growth. This impact is
amazingly robust over several specifications. Higher hiring costs appear to increase indeed the
set-up costs for new plants and thus reduce the ability of an economy to innovate and to induce structural changes. It is that effect that is shaping Euro-Sclerosis.
– 19 –
Table 4:
Panel Regressions of the Unemployment Rate on Employment Protection
Legislation and Controls, 12 EU-Member Countries, 1971 - 1996
Independent Variables
(1)
OLS
LSDV
(2)
OLS
LSDV
(3)
OLS
LSDV
(4)
OLS
LSDV
(5)
OLS
LSDV
(6)
OLS
LSDV
(7)
2SLS
LSDV
Individual Dismissal
0.825**
(5.31)
–
–
0.137(*)
(1.86)
–
–
–
Collective Dismissal
0.055
(0.59)
–
–
0.013
(0.27)
–
–
–
Fixed-Term Contracts
0.053
(0.54)
0.015
(0.15)
- 0.032
(0.30)
- 0.053
(1.08)
- 0.058
(1.22)
–
–
Part-Time Work
-0.205*
(2.16)
- 0.203*
(2.13)
- 0.067
(0.74)
0.058
(1.16)
0.060
(1.22)
–
–
Temporary Work
0.212*
(2.59)
0.276**
(3.34)
0.283**
(3.46)
0.081(*)
(1.88)
0.090*
(2.12)
–
–
Working Time
0.298*
(2.02)
0.287(*)
(1.95)
- 0.085
(0.52)
- 0.067
(0.83)
- 0.073
(0.92)
–
–
Index of Dismissal Regulation
–
0.667**
(6.12)
0.655**
(6.01)
–
0.111*
(2.41)
0.133**
(3.04)
0.153**
(3.10)
Lagged Unemployment Rate
–
–
–
0.862**
(34.08)
0.866**
(34.71)
0.872**
(35.52)
0.865**
(29.54)
Index of Men’s Hourly
Wages
0.023**
(4.44)
0.024**
(4.38)
0.025**
(5.00)
0.003
(1.63)
0.003
(1.61)
0.001
(0.58)
0.002
(0.73)
Real Long-Term Interest
Rates
- 0.175**
(4.34)
- 0.193**
(4.68)
- 0.212**
(5.10)
0.013
(0.65)
0.011
(0.55)
0.005
(0.26)
0.001
(0.06)
Real Private Investment (in
% of GDP)
-0.344**
(6.54)
- 0.306**
(5.29)
- 0.282**
(4.76)
- 0.106**
(3.31)
- 0.098**
(3.24)
- 0.086**
(3.16)
- 0.082**
(3.39)
-0.007
(0.17)
- 0.012
(0.26)
- 0.013
(0.29)
- 0.151**
(5.03)
- 0.152**
(5.07)
- 0.150**
(5.14)
- 0.145**
(5.65)
0.183**
(4.05)
0.192**
(4.10)
0.099*
(1.99)
-0.008
(0.35)
-0.008
(0.37)
0.021
(1.08)
0.023
(1.04)
Openness (in % of GDP)
0.013
(0.76)
0.022
(1.32)
0.027(*)
(1.77)
- 0.015*
(2.03)
- 0.014(*)
(1.88)
- 0.015*
(2.47)
- 0.014*
(2.20)
Lagged Per Capita GDP
- 0.108*
(2.20)
- 0.123*
(2.51)
- 0.208**
(3.86)
- 0.026
(1.17)
- 0.028
(1.27)
- 0.006
(0.28)
- 0.012
(0.45)
Social Security Payments (%
of GDP)
–
–
0.291**
(2.61)
0.027
(0.56)
0.028
(0.60)
0.026
(0.59)
0.031
(0.61)
Personal Income Taxes (in %
of GDP)
–
–
0.089
(0.99)
0.055
(1.43)
0.057
(1.50)
0.044
(1.25)
0.016
(0.40)
Corporate Income Taxes (%
of GDP)
–
–
0.127
(0.80)
- 0.202**
(3.35)
- 0.199**
(3.28)
- 0.213**
(4.14)
- 0.211**
(3.50)
Indirect Taxes (in % of
GDP)
–
–
0.349**
(3.30)
0.010
(0.27)
0.012
(0.32)
- 0.019
(0.54)
- 0.019
(0.46)
F-Test: EPL-Indicators
Real GDP Growth per Capita
(in %)
Schooling
17.485**
18.776**
16.169**
3.889**
4.398**
–
–
2
R
0.880
0.876
0.887
0.976
0.976
0.976
0.888
SER
1.672
1.699
1.634
0.749
0.750
0.754
1.080
D.W.
0.454
0.442
0.454
1.123
1.124
1.107
1.153
For notes see Table 3. Instruments are real private investment in percent of GDP, real GDP growth per capita, all
lagged by one period and the unemployment rate lagged by two periods.
– 20 –
Table 5: Panel Regressions of Real Private Investment in Percent of GDP on Employment Protection Legislation and Controls, 12 EU-Member Countries,
1971 - 1996
Independent Variables
(1)
OLS-LSDV
(2)
OLS-LSDV
(3)
OLS-LSDV
(4)
2SLS-LSDV
(5)
2SLS-LSDV
Individual Dismissal
0.952**
(4.35)
–
0.958**
(4.42)
–
–
Collective Dismissal
- 0.382**
(2.94)
–
- 0.327*
(2.46)
–
–
Fixed-Term Contracts
0.181(*)
(1.73)
0.124
(1.26)
0.191(*)
(1.70)
–
–
Part-Time Work
- 0.114
(0.81)
- 0.107
(0.74)
- 0.088
(0.60)
–
–
Temporary Work
0.274*
(1.98)
0.401**
(2.90)
0.271*
(1.99)
–
–
- 0.498**
(2.76)
- 0.584**
(3.19)
- 0.564**
(2.74)
–
–
Index of Dismissal Regulation
–
0.173
(1.53)
–
–
0.069
(0.88)
Index of EPL
–
–
–
0.067
(0.55)
–
Lagged Private Investment (in %
of GDP)
–
–
–
0.816**
(21.77)
0.823**
(22.15)
Index of Men’s Hourly Wages
- 0.003
(0.58)
- 0.004
(0.75)
0.001
(0.06)
- 0.002
(0.65)
- 0.001
(0.42)
Real Long-Term Interest Rates
- 0.120**
(2.73)
- 0.151**
(3.19)
- 0.138**
(3.20)
- 0.116*
(3.44)
- 0.111**
(3.47)
Unemployment Rate (in %)
- 0.433**
(6.91)
- 0.406**
(5.88)
- 0.408**
(6.58)
- 0.134**
(3.03)
- 0.136**
(2.98)
Real GDP Growth per Capita (in
%)
0.104*
(2.38)
0.106*
(2.26)
0.049
(1.11)
0.164**
(4.307)
0.176**
(4.42)
Schooling
0.044
(0.95)
0.052
(1.06)
0.044
(0.81)
0.086*
(2.32)
0.080*
(2.33)
Openness (in % of GDP)
- 0.093**
(4.52)
- 0.086**
(4.17)
- 0.079**
(3.64)
0.190
(0.19)
0.078
(0.08)
Lagged Per Capita GDP
- 0.001
(0.17)
- 0.003
(0.54)
- 0.007
(1.25)
- 0.007(*)
(1.70)
- 0.008(*)
(1.79)
Social Security Payments (% of
GDP)
–
–
- 0.314**
(3.10)
0.127
(1.54)
0.132
(1.60)
Personal Income Taxes (in % of
GDP)
–
–
- 0.143(*)
(1.68)
- 0.140*
(2.30)
- 0.145*
(2.34)
Corporate Income Taxes (% of
GDP)
–
–
0.946
(0.06)
0.060
(0.63)
0.037
(0.39)
Indirect Taxes (in % of GDP)
–
–
0.247*
(2.18)
0.133*
(2.03)
0.157*
(2.28)
Working Time
F-Test: EPL-Indicators
7.977**
7.270**
9.377**
–
–
2
R
0.813
0.795
0.823
0.828
0.827
SER
1.874
1.955
1.835
1.485
1.521
D.W.
0.652
0.608
0.693
0.707
0.735
For notes see Table 3. Instruments are the unemployment rate, real GDP growth per capita, all lagged by one period and private investment in percent of GDP lagged by two periods.
– 21 –
4.2
Unemployment and Employment Protection Legislation
The robust negative effect of dismissal regulation on economic growth is an important result
as such. But it is of interest to analyze how the impact of EPL on unemployment or private
investment is. The results for the unemployment equation are presented in Table 4. The overall performance of the model is better than that of the growth equation. About 90 percent of
the variance of unemployment rates can be explained by the model. However, according to the
panel Durbin-Watson statistics the standard errors of the estimated coefficients may be biased
due to autocorrelation in the error term of the regression. The first three columns in Table 4
are thus only presented for illustrative reasons since the estimation results are not very reliable. Introducing a lagged endogenous variable that successfully corrects for autocorrelation
(according to the panel Durbin-h statistics) strongly changes the estimation results, while they
remain relatively stable as to the estimation by 2SLS. This is the broad picture.
Bearing these caveats in mind, it can be said that the controls perform fairly well. Factor
prices have virtually no significant and robust effect on unemployment. Private investment
across the board and real per capita GDP growth in the more reliable regressions with a lagged
endogenous have a negative impact on unemployment. The PISSARIDES (1990)/AGHION and
HOWITT (1998) capitalization effect appears to dominate the job destruction effect in structural changes. An increase in growth rates raises the returns from creating a new plant and
encourages more entry by new plants leading to job creation. Schooling and lagged real GDP
per capita do not have any robust and significant effect. In the estimations with a lagged endogenous, openness has a significantly negative impact on unemployment at least on the 10
percent level. This is not the usually expected globalization effect on unemployment, but it
indicates that more open (usually also smaller) economies have lower unemployment rates.
The public finance variables that are included for robustness check do not have robust and
significant impacts on unemployment. The exception is corporate income tax revenue in percent of GDP which has a significantly negative impact on unemployment rates in the regressions with a lagged endogenous. These results are no surprise given the difficulties to correctly measure effective tax rates. They should thus not be emphasized too much in comparison with the DAVERI and TABELLINI results. Their focus on labor taxes in the unemployment
equation must be taken with a grain of salt however given these results on corporate income
taxes.
Concerning EPL indicators, the picture is pretty differentiated. The null hypothesis that these
variables together do not have any effect on unemployment rates can be rejected on the 1 percent significance level according to the F-tests presented in Table 4. While it appears to be
that regulations on working time and part-time work significantly affect unemployment rates,
though in opposite directions, their impact vanishes when public finance indicators are introduced and turns around (remaining insignificant) when a lagged endogenous is introduced.
The results that do remain robust are those of regulations on temporary work and again those
of regulations on individual and collective dismissals. Both are significant at least on the 1
percent significance level. Their impact is also driving the results of the F-tests in columns (3)
to (5). The stricter these regulations are, the higher is unemployment over time in the 12 EU
countries. While the index of regulations on temporary work cannot be included in the 2SLS
specifications, because the additional lag renders the index of these regulations for one country time invariant, the effect of dismissal regulation is again robust to the 2SLS specification.
The conclusion that can be drawn from the estimation results of the unemployment equation is
– 22 –
that EPL, in particular dismissal regulation, harms labor market performance. This result is
again amazingly robust across specifications. What appears to be obvious from piecemeal
evidence and discussions with managers from firms in Europe, but is so hard to find in systematic empirical studies, shows up quite clearly in these estimation results: Higher hiring
costs induce higher unemployment. Adding the time dimension consistently to the EPL indicators reveals an effect that remains hidden with cross section variation only.
4.3
Private Investment and Employment Protection Legislation
It remains to be checked whether there is an impact of EPL on investment as well. The results
on the investment equation are presented in Table 5. The overall performance of the investment equation is again relatively well. About 80 percent of private investment in percent of
GDP can be explained. There is however autocorrelation in the error terms according to the
panel Durbin-Watson statistics rendering the first three columns in Table 5 to mere illustrations. Including a lagged endogenous variable removes autocorrelation successfully as indicated by the panel Durbin-h statistics.
With respect to the performance of the control variables, a robust negative correlation of real
long-term interest rates as proxies for the user costs of capital and private investment can be
observed that is significant at least on the 5 percent significance level. In addition the negative
impact of unemployment rates on private investment is significantly different from zero even
on the 1 percent level. It corroborates the view of DAVERI and TABELLINI that a permanently
lower employment induces adjustments of private investment to a new steady state with a
smaller capital stock. This result somehow contradicts that from the growth equation indicating that the presumption of private investment as a good proxy for innovation may be too optimistic. Real GDP growth per capita has a significantly negative impact on the 1 percent significance level in the more reliable 2SLS specifications. Similarly, the marginally significant
negative impact of lagged real GDP per capita corroborates the catch-up hypothesis. Openness
and wages do not have any consistent and robust impact on private investment while schooling is consistently positive and becomes significant on the 5 percent level in the 2SLS specification. Of the public finance variables, personal income tax revenue in percent of GDP has a
robust negative and significant effect on private investment, while the correlation of indirect
tax revenue in percent of GDP and private investment is consistently positive and significant
on the 5 percent level.
The impact of EPL on investment is however virtually non-existent. This is again evidence for
the misplaced optimism that private investment reflects innovation in an economy sufficiently
well. The transmission channel from EPL to private investment mainly runs via investment in
R&D and the high set-up costs of new plants that are induced by higher hiring costs. The estimation results in Table 5 instead indicate that regulations on individual dismissals have a
significantly positive and that on collective dismissals a significantly negative impact on private investment. These effects are already compensating each other in the OLS specification,
but fully vanish in the 2SLS specification (column (5)). The effects in opposite directions can
also be found for the positive impact of regulations on temporary work and fixed-term contracts on the one hand and the negative impact of regulations on working time on the other
hand. The overall effect of the index of EPL in the 2SLS specification is thus far from any
conventional significance level. The conclusions that can be drawn from these results are not
– 23 –
at all clear. Perhaps a disaggregation of investment according to different innovation degrees
would be helpful.
5.
Some Concluding Remarks
Based on some theoretical considerations obtained from an endogenous growth model by
AGHION and HOWITT (1998), the impact of employment protection legislation (EPL) on real
per capita GDP growth, unemployment rates and real private investment in percent of GDP is
econometrically analyzed. The results are obtained for six new indicators on regulation of
individual and collective dismissals, fixed-term contracts, part-time work, temporary work
and working time and a sample of the 12 EU member countries before the latest enlargement,
namely, Belgium, Denmark, France, Germany, Greece, Ireland, Italy, Luxembourg, the Netherlands, Portugal, Spain, and the U.K. with annual data from 1970 to 1996. Since these new
indicators allow for a consistent measurement of strictness of EPL across countries and time,
it is for the first time possible to use standard panel data methods in an analysis of EPL and
economic performance. The EPL indicators are correlated with existing indexes, but reveal
new information to a considerable extent.
The main findings are a relatively robust negative relationship between the strictness of regulations on dismissals and real per capita GDP growth, a positive relationship between dismissals regulation and unemployment and virtually no relationship between EPL and real private
investment. It is not such a big surprise to find a negative effect between unemployment and
dismissal regulation. Given the existing theoretical studies and the struggle with the empirical
evidence, it has been clear that new indicators may shed more light on this relationship.
Somehow, the results presented in this paper therefore follow the claim by BERTOLA, BOERI
and CAZES (2000) that new indicators on EPL are needed. In addition, the theoretically less
contested, but empirically seldom investigated and nearly not established negative effect of
EPL on growth sheds some light on the causes of Euro-sclerosis. Both results are amazingly
robust to different specifications including additional control variables and estimation procedures. In addition to the ones reported in the paper, further robustness tests have been performed using different aggregation steps of the EPL indexes, using additional control variables, and looking for outliers. The statement of robustness obtains including these unreported
robustness checks. However, robustness tests with respect to some additional controls in particular unemployment benefits and labor productivity wait to be performed. An omitted variable bias may still be hiding there.
On the other hand, the non-existent relationship between EPL and private investment poses
the question how the transmission between EPL and growth takes place. The starting point of
the theoretical considerations in this paper is the negative impact of EPL on innovation because higher hiring costs that are due to EPL increase set-up costs of new plants. Innovations
are supposed to be incorporated in capital and thus in private investment. Perhaps total private
investment is too crude a proxy to investigate this relationship. The results of KANNIAINEN
and VESALA (2000) that EPL adversely affect enterprise formation indicate on the other hand
that the basic idea of such a transmission mechanism is not totally wrong. It may still drive the
estimation results of the growth equation. Perhaps this is the most important route for future
investigations. It may shed more light on Euro-Sclerosis.
– 24 –
References
AGELL, J. (1999), On the Benefits from Rigid Labour Markets: Norms, Market Failures, and Social
Insurance, Economic Journal 109 (1999), F143 – F164.
AGELL, J. (2000), On the Determinants of Labour Market Institutions: Rent-Sharing vs. Social Insurance, CESifo Working Paper No. 384, Munich, December 2000.
AGHION, PH. and P. HOWITT (1998), Endogenous Growth Theory, MIT Press, Cambridge 1998.
ALOGOSKOUFIS, G., CH. BEAN, G. BERTOLA, D. COHEN, J. DOLADO and G. SAINT-PAUL (1995), Unemployment: Choices for Europe, Monitoring European Integration 5, CEPR, London 1995.
ARELLANO, M. (1989), A Note on the Anderson-Hsiao Estimator for Panel Data, Economics Letters
31 (1989), 337 – 341.
BALTAGI, B.H. (1995), Econometric Analysis of Panel Data, John Wiley & Sons, New York et al.
1995.
BENTOLILA, S. and G. BERTOLA (1990), Firing Costs and Labour Demand: How Bad Is Eurosclerosis?, Review of Economic Studies 57 (1990), 381 − 402.
BERGER, H. (1998), Regulation in Germany: Some Stylized Facts About its Time Path, Causes, and
Consequences, Zeitschrift für Wirtschafts- und Sozialwissenschaften 118 (1998), 185 – 220.
BERTOLA, G. (1990), Job Security, Employment and Wages, European Economic Review 34 (1990),
851 − 886.
BERTOLA, G. (1994), Flexibility, Investment, and Growth, Journal of Monetary Economics 34 (1994),
215 – 238.
BERTOLA, G. (1999), Microeconomic Perspectives on Aggregate Labor Markets, in: O. ASHENFELTER
and D. CARD (eds.), Handbook of Labor Economics 3C, Elsevier, Amsterdam 1999, 2985 –
3028.
BERTOLA, G., T. BOERI and S. CAZES (1999), Employment Protection and Labour Market Adjustment
in Some OECD Countries: Evolving Institutions and Variable Enforcement, mimeo, European
University Institute, Florence.
BERTOLA, G., T. BOERI and S. CAZES (2000), Employment Protection in Industrialized Countries: The
Case for New Indicators, International Labour Review 139 (2000), 57 – 72.
BERTOLA, G., T. BOERI and G. NICOLETTI (eds.) (2001), Welfare and Employment in a United
Europe, MIT Press, Cambridge 2001.
BLANCHARD, O. (2000), The Economics of Unemployment: Shocks, Institutions, and Interactions,
forthcoming, Oxford University Press, Oxford.
BLANCHARD, O. and J. WOLFERS (2000), The Role of Shocks and Institutions in the Rise of European
Unemployment: The Aggregate Evidence, Economic Journal 110 (2000), C1 – C33.
BOERI, T. (1999), Enforcement of Employment Security Regulations, On-the-Job Search and Unemployment Duration, European Economic Review 43 (1999), 65 – 89.
BURDA, M.C. (1992), A Note on Firing Costs and Severance Benefits in Equilibrium Unemployment,
Scandinavian Journal of Economics 94 (1992), 479 – 489.
– 25 –
CABALLERO, R.J. and M.L. HAMMOUR (1998), Jobless Growth: Appropriability, Factor Substitution,
and Unemployment, Carnegie-Rochester Conference Series on Public Policy 48 (1998), 51 –
94.
CABALLERO, R.J. and M.L. HAMMOUR (2000), Institutions, Restructuring, and Macroeconomic Performance, NBER Working Paper No. 7720, Cambridge, May 2000.
DAVERI, F. and G. TABELLINI (2000), Unemployment, Growth and Taxation in Industrial Countries,
Economic Policy 30 (2000), 47 – 104.
DI TELLA, R. and R. MACCULLOCH (1999), The Consequences of Labour Market Flexibility: Panel
Evidence Based on Survey Data, ZEI Working Paper B2 1999, Rheinische Friedrich-WilhelmsUniversity Bonn 1999.
EMERSON, M. (1988), Regulation or Deregulation of the Labour Market: Policy Regimes for the Recruitment and Dismissal of Employees in the Industrialized Countries, European Economic Review 32 (1988), 775 – 817.
FELD, L.P. (2001), Institutioneller Wettbewerb und Arbeitsmarktinstitutionen in Europa, forthcoming
in: TH. APOLTE and U. VOLLMER (eds.), Arbeitsmärkte und soziale Sicherung: Fehlentwicklungen, Reformpotenziale und Reformerfahrungen, Lucius & Lucius, Stuttgart 2001.
FELD, L.P. and A. SANTONI (2000), Employment Protection Legislation and Economic Growth: Empirical Evidence for 12 EU Member States from 1971 to 1993, mimeo, University of St. Gallen.
FLANAGAN, R.J. (1993), Hiring Behavior and Unemployment, in: CH.F. BUECHTEMANN (ed.), Employment Security and Labor Market Behavior: Interdisciplinary Approaches and International
Evidence, ILR Press, Ithaca 1993, 148 − 159.
GREGG, P. and A. MANNING (1997), Labour Market Regulation and Unemployment, in: D. SNOWER
and G. DE LA DEHESA (eds.), Unemployment Policy: Government Options for the Labour Market, Cambridge University Press, Cambridge 1997, 395 – 424.
GRUBB, D. and W. WELLS (1993), Employment Regulation and Patterns of Work in EC Countries,
OECD Economic Studies 21 (1993), 7 – 58.
HICKS, J.R. (1932), The Theory of Wages, MacMillan, New York 1932, reprinted by Peter Smith,
New York 1948.
HOPENHAYN, H. and R. ROGERSON (1992), A Framework for Assessing Aggregate Consequences of
Labor Market Regulations, in: A. CUKIERMAN, Z. HERCOWITZ and L. LEIDERMAN (eds.), Political Economy, Growth and Business Cycles, MIT Press, Cambridge 1992, 373 – 394.
HOPENHAYN, H. and R. ROGERSON (1993), Job Turnover and Policy Evaluation: A General Equilibrium Analysis, Journal of Political Economy 101 (1993), 915 – 938.
KANNIAINEN, V. and T. VESALA (2000), Enterprise Formation and Labor Market Institutions, CESifo
Working Paper No. 359, Munich, November 2000.
KOEDIJK, K. and J. KREMERS (1996), Market Opening, Regulation and Growth in Europe, Economic
Policy 23 (1996), 445 – 467.
LAZEAR, E.P. (1990), Job Security Provisions and Employment, Quarterly Journal of Economics 105
(1990), 699 – 726.
LONG, N. VAN and H. SIEBERT (1983), Lay-Off Restraints and the Demand for Labor, Journal of Institutional and Theoretical Economics (JITE) 103 (1983), 612 – 624.
– 26 –
NICKELL, ST. and R. LAYARD (1999), Labor Market Institutions and Economic Performance, in: O.
ASHENFELTER and D. CARD (eds.), Handbook of Labor Economics 3C, Elsevier, Amsterdam
1999, 3029 – 3084.
OECD (1994), The OECD Jobs Study: Facts, Analysis, Strategies, OECD, Paris 1994.
OECD (1999), Employment Outlook, June 1999, OECD, Paris 1999.
OI, W.Y. (1962), Labor as a Quasi-Fixed Factor, Journal of Political Economy 70 (1962), 538 – 555.
PISSARIDES, C.A. (1990), Equilibrium Unemployment Theory, Basil Blackwell, Oxford 1990.
RISAGER, O. and J.R. SØRENSEN (1997), On the Effects of Firing Costs When Investment Is Endogenous: An Extension of a Model by Bertola, European Economic Review 41 (1997), 1343 −
1353.
SAINT-PAUL, G. (1997), Is Labour Market Rigidity Harming Europe’s Competitiveness? The Effect of
Job Protection on the Pattern of Trade and Welfare, European Economic Review 41 (1997), 499
− 506.
SAINT-PAUL, G. (2000), The Political Economy of Labour Market Institutions, Oxford University
Press, Oxford 2000.
SAINT-PAUL, G. (2001), Employment Protection, International Specialization, and Innovation, forthcoming in: European Economic Review (2001).
SANTONI, A. (2001), Gesetzliche Arbeitsmarktregulierung in der Europäischen Union und ihre Auswirkungen auf das Wirtschaftswachstum, Doctoral Dissertation, TU Darmstadt 2001.