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The role of labor markets in business cycle
statistics
Jennifer Evans* and Irina Stanga
June 14, 2012
Supervisor: Stefano Gnocchi
Abstract
This paper investigates cross-country heterogeneity in business cycle moments
over the past 30 years to assess whether recent developments are global phenom-
ena, or limited to the case of United States. Furthermore, we consider if labor mar-
ket flexibility, a proposed driver of these developments, is relevant for other OECD
countries. While there is a substantial degree of heterogeneity across countries, we
find a number of statistical similarities between Italy and the United States. We
profile the labor market in each country, and cast doubt on the ability of the labor
market to account for the correlation of productivity with unemployment. How-
ever, our analysis finds evidence that the labor market can explain the vanishing
procyclicality of productivity.
JEL: E24, E32
Keywords: Great Moderation, macroeconomic volatility, labor market
Barcelona GSE, Universitat Pompeu Fabra and Universitat Autonoma de Barcelona
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Contents
1 Introduction 1
2 Literature Review 3
3 Data and Methodology 6
4 Results 7
4.1 Comparisons across countries . . . . . . . . . . . . . . . . . . . . . . . . . . 7
4.1.1 Country groups . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
4.2 Labor markets profiles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
4.2.1 Temporary workers . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
4.2.2 Decline of unionization rate . . . . . . . . . . . . . . . . . . . . . . . 11
4.2.3 Sectoral shift from manufacturing to services . . . . . . . . . . . . . 13
4.2.4 Labor market conclusions . . . . . . . . . . . . . . . . . . . . . . . . 13
4.3 Additional business cycle moments . . . . . . . . . . . . . . . . . . . . . . . 14
5 Conclusion 16
6 Appendix 20
6.1 Robustness check . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
6.2 Figures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21
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1 Introduction
Business cycle statistics in the United States have changed considerably over the past 30
years. Three developments in particular have captured the attention of the economics
profession: (i) a sign shift in the unconditional correlation between productivity and
unemployment, (ii) a decrease in the procyclicality of productivity and (iii) an increase
in the volatility of employment and hours relative to output, and the decline in volatility
of other macroeconomic series, known as the Great Moderation.
While separate theories have been proposed to explain these shifts, structural changes
in the labor market are a common theme. For example, Gali and van Rens (2010) point
to authors who argue that the Great Moderation may have been driven at least in part
by increased wage flexibility.1 Both Gali and van Rens (2010) and Barnichon (2010) find
that the shifts in correlation and procyclicality can be explained in part by a reduction in
labor market frictions. Gali and van Rens (2010) find a common thread in their paper by
using a structural model to show how a reduction in labor market frictions can increasewage flexibility, finding evidence to link all three developments to the labor market.
However, these business cycle developments have been documented for US only.
The scope of this paper is to investigate the cross-country heterogeneity in these busi-
ness cycle moments in order to assess whether the facts emphasized by Gali and van
Rens (2010) and Barnichon (2010) are global phenomena, or limited to the case of US. We
focus on the unconditional sample moments for the cyclical component of key macroe-
conomic variables across 10 OECD countries (including the United States, for compari-
son purposes). Furthermore, we consider if the theories proposed to explain these facts,
which fit well with developments in the US economy, are relevant for other OECD coun-
tries. More specifically, in the first part of the analysis we assess the evolution of the
1See Gourio (2007), Champagne and Kurmann (2010), Nucci and Riggi (2009)
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correlation between productivity and unemployment in order to uncover any similari-
ties across countries and form groups. Thereafter, we focus on the group that includes
US and consider whether the explanations based on labor market flexibility are sup-
ported by empirical evidence, i.e. whether countries that belong to the same group had
similar developments related to the degree of labor market rigidities. Finally, we ana-
lyze additional business cycle statistics, such as the cyclicality of labor productivity and
the volatilities of macroeconomic series, in order to determine whether the three devel-
opments listed above are consistent and reflect the characteristics of the labor market
within our group of interest.
Our paper finds a substantial degree of heterogeneity in the patters of correlations
between labor productivity and unemployment across OECD economies. A few coun-
tries, such as Canada and Finland, display unique patterns, while the others can be
grouped according to the sign of the correlation or the timing of the sign switch. Sur-
prisingly, we find that the countries most comparable to the US are Italy and Norway.
By profiling the labor markets of the United States and Italy, we cast doubt on the ability
of the labor market to account for the correlation of productivity with unemployment
and output, but find evidence that the evolutions on the labor markets are consistent
with the vanishing procyclicality of productivity.
First we place our paper in the literature, and discuss the outcomes of previous stud-
ies into the Great Moderation and additional business cycle developments. Thereafter
we present the data and our methodology. We then focus on our results and a discus-
sion of labor market characteristics in the United States and Italy from the 1970s. Finally,
we conclude.
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2 Literature Review
The studies that document the three business cycle developments considered above
point towards two main explanations. The first one is related to a change in the relative
importance between technology shocks and non-technology shocks and the second one
is represented by the decrease in the rigidities on the labor market. We further discuss
in detail the theories presented in the literature and the basic mechanisms that account
for these changes.
Barnichon (2010) documents a sign switch of the correlation between unemployment
and productivity in the mid 80s and estimates a VAR in order to trace the impact of a
technology and non-technology shock on these two variables. Based on the empirical
evidence, he points towards two main explanations for the sign switch. First, since a
positive technology shock leads to a positive correlation between the variables, while a
non-technology shock generates a negative one, the sign shift could be explained by a
change in the relative size of the shocks. Second, the evidence indicates a decrease inthe pro-cyclicality of productivity after the mid 80s based on structural changes in the
labor market.
Barnichon (2010) provides a structural interpretation using a New-Keynesian model
with sticky prices, search and matching frictions and variable labor effort. In this con-
text, a non-technology shock is interpreted as an aggregate demand shock that deter-
mines firms to raise the labor input in order to be able to satisfy the increase in demand.
Since employment cannot be adjusted immediately due to hiring costs, firms increase
hours and effort leading to a rise in productivity. However, the use of the intensive mar-
gin is limited because the disutility of workers increases in hours and effort, therefore
firms will start to post vacancies and unemployment will decrease. This is the mecha-
nism through which a positive non-technology shock leads to a negative productivity-
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unemployment correlation.
In contrast, a positive technology shock generates an increase in productivity, which
leads firms to lower hours and effort initially, because employment is subject to fric-
tions and hence they face firing costs. This reduction leads to a decrease in the value
of a marginal worker and therefore firms will post fewer vacancies and unemployment
will increase. As a consequence, a technology shock leads to a positive productivity-
unemployment correlation.
In line with this evidence, the two events that explain the correlation sign switch
are an increase in the size of technology shocks relative to other types of shocks and
a decline in the response of productivity to non-technology shocks after the mid 80s.
In the model, the declining procyclicality of productivity is explained through a more
flexible labor market due to smaller hiring frictions and an increased elasticity of hours
per worker. The empirical evidence that could support these developments consists of a
rising share of temporary workers, a decline in the unionization rate and the emergence
of online recruitment sites in the last two decades.
The results of the model indicate that about 40% of the increase in the correlation is
due to changes in the sizes of the shocks and approximately 60% can be associated with
the structural changes. Our purpose is to analyze whether these facts are valid for all
the countries where the switch in the sign of the correlation took place and therefore
determine whether they provide a comprehensive explanation or the evidence can be
extended by considering other factors.
Gali and Gambetti (2008) estimate a structural time varying VAR on output, hours
and labor productivity and find evidence for a decline in the cyclical response of la-
bor productivity to non-technology shocks. Furthermore, the authors document a drop
in the correlation between total hours worked and productivity conditional on non-
technology shocks.
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The potential explanation for these findings could be related to the variations in ef-
fort that take place due to the high adjustments costs in employment. Since it is costly
to hire or fire new people when faced with fluctuations in demand, variations in effort
represent a tool for the firms to easily adjust effective labor input. In this context, the
measured hours fluctuate less than their effective counterpart and therefore labor pro-
ductivity will tend to be procyclical. An increase in the flexibility of the labor markets
leads to a decrease in the variations in effort and would therefore explain a decline in
the procyclicality of labor productivity following an aggregate demand shock.
These changes in conditional moments are synchronized with the decline in output
volatility from the early 1980s, however it has not been established whether they share
a common explanation based on structural modifications in the labor market.
On the basis of a similar explanation related to a reduction in hiring costs, Gali and
van Rens (2010) also find evidence for a vanishing procyclicality of labor productivity
and a relative increase in the volatility of employment and the real wage with respect
to output. The mechanism is illustrated through a model with labor market frictions,
variable effort, and endogenous wage rigidities in which effort is considered as a factor
input which is not subject to rigidities and can partly substitute labor. Since frictions
on the labor market create difficulties in adjusting employment, a reduction in frictions
leads to a drop in the volatility of this input and an increase in the one of employment
relative to output. Hence, the procyclicality of productivity is influenced by variations
in effort.
The present study focuses on providing empirical evidence for the explanation based
on an increased flexibility in the labor markets and we leave for future research the con-
sideration of the relative importance of the technology and aggregate demand shocks.
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3 Data and Methodology
Our analysis is based on the following macroeconomic time series at the individual
country level: real GDP, average hours per worker, employment, unemployment and
productivity. We consider quarterly, seasonally-adjusted data for the period 1970Q1-
2011Q42 for Australia, Canada, Finland, France, Italy, Japan, Norway, Sweden, United
Kingdom and the United States. There is extensive research related to business cycle
developments in the United States, and we include it as a benchmark with which to
compare other OECD countries. The main data source is the OECD, although some
OECD series were extracted from the FRED database of the St. Louis Federal Reserve
Bank.
To profile the labor markets in our countries of interest, we focus explicitly on tem-
porary workers, unionization rates and sectoral shifts from manufacturing to services.
The main source of this indicators is the CEP-OECD Institutions Data Set (See Nickell
(2006)).Following Barnichon (2010), all series were de-trended with the HP-filter and a
smoothing parameter of 16003 and our calculations are performed on the deviations
of each series from its trend. Labor productivity is based on our own calculations, and
is computed as real GDP divided by the total hours worked. The correlation of produc-
tivity with unemployment and with output, and the volatilities of relevant times series
are computed as 10 year rolling windows over the sample.
2Exceptions: Finland 1970:Q1-2010:Q4; UK 1972:Q1-2011:Q43Our results are robust when data is transformed with the fourth-difference operator used in Stock
and Watson (2002). See the Appendix, section 6.1
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4 Results
In the first part of the analysis we present our results regarding the patterns of correla-
tions between unemployment and labor productivity for each country. Thereafter we
propose a grouping based on similarities regarding the signs and breaks. In the second
part of the analysis we zoom in on the group of countries that includes US in order to
make a a brief and qualitative assessment of whether explanations based on the labor
market, as cited in Barnichon (2010) and Gali and van Rens (2010), are consistent with
the empirical facts in each country. Furthermore, we enrich our analysis by examin-
ing the volatility of employment and hours relative to output and the procyclicality of
productivity for the selected group of countries.
4.1 Comparisons across countries
The most striking result from our analysis is the parallel sign shifts experienced by the
United States and Italy (See figures 3,6-7 in the Appendix, section 6.2). The first signif-
icant break in the data occurs for both countries in the mid-1980s, when the correlation
became significantly positive. After 1993, both countries display a second break, and
the correlation becomes zero for the United States and significantly negative for Italy.
Norway experiences a significant sign shift slightly later than the US and Italy. It
breaks from a zero correlation in the beginning of the sample to significantly positive
starting in the late 1980s.
New Zealand, Sweden, UK and Australia display a switch in correlation in the late
70s. Previously, the correlation for New Zealand and Sweden was negative, while in the
UK and Australia the correlation was not significantly different from zero. In the late
70s, the correlations become positive for New Zealand, Sweden and Australia, but the
positive correlation is not significant over the full length of the sample. The correlation
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became negative for the UK in the late 90s, although not significantly different from
zero.
The correlations for France and Japan are significantly negative after the 1980s and
do not display any switch in the sign (figure 8). In both countries there are brief periods
in which the correlation is not significantly different from zero.
Canada is the only country for which the switch in correlation is from positive to
negative (See figure 1). The date of this change is in the first quarter of 1983 and is
characterized by a trend instead of a sharp break. The correlation for Finland is not
statistically different from zero along the entire sample (figure 9).
Italy, Norway and the US are the only countries that exhibit sharp breaks over the
sample period. In the case of Australia, Canada, Finland, France, Japan, New Zealand,
Sweden and the UK, the correlation is relatively smooth.
The evolution of the correlation in each individual country can be seen in figures 1-6
in the Appendix, section 6.2.
4.1.1 Country groups
While some countries display similar traits to the United States over the period of in-
vestigation, we also find significant heterogeneity in both the sign of the correlation and
the approximate date of the shift. Furthermore, some countries displayed a sharp break,
and for others the sign shift was characterized by a trend instead of a sharp break. We
classify the countries according to i) the presence of a sign shift, ii) the approximate date
of the shift and iii) the shape of correlation over time.
1) United States, Italy and Norway
2) UK, Sweden, New Zealand, Australia
3) France and Japan
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4) Canada and Finland4
In the next section, we will focus on the empirical evidence regarding the labor mar-
ket and additional business cycle moments in the United States and Italy. We are in-
terested in these two countries in particular because their correlations have a similar
shape, exhibit the same sign shift and break at the same date. In addition, there are no
immediately apparent reasons why the correlation should be so similar between these
countries. They do not share a common labor market or currency union and have dif-
ferent political systems.
4.2 Labor markets profiles
To explain the sign switch in the correlation between productivity and unemployment,
the literature has offered up a number of explanations, including the changing relative
importance of technology shocks and shocks to aggregate demand, an improvement in
monetary policy and a decrease in labor market frictions 5. In the absence of a structural
model, we will focus on the hypothesis that labor market frictions drove the change in
the correlation of unemployment and productivity. We will limit our comparison to the
United States and Italy, two countries that at first glance do not seem to have very much
in common in terms of labor market flexibility.
Barnichon (2010) offers insight into why decreasing labor market frictions would
affect the correlation between unemployment and productivity. He suggests that if hir-
ing costs decline, it is easier for firms to adjust the number of workers in response to
fluctuations in demand. As a result, hours per worker and effort6 fluctuate less. Barni-
4See figures 7 - 9 in the Appendix5See Barnichon (2010), Gali and Gambetti (2008), Gali and van Rens (2010)6Effort, which may be measured as approximate labor utilization by the number of hours per em-
ployee, overtime hours, the ratio of production to non-production workers, accident rates, and materialsinput growth (Marchetti and Nucci (2006)) is not included in our analysis
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chon (2010) also finds that the elasticity of hours per worker has increased leading to an
increased volatility of hours per worker.
Gali and van Rens (2010) and Gali and Gambetti (2008) offer similar explanations
to explain the shift in correlation between productivity and output. Gali and van Rens
(2010) suggest that labor market frictions make it costly to adjust employment, which
implies firms rely more on the intensive margins (hours and effort) in response to de-
mand. As a result of their structural model analysis, they find that as frictions fall,
it becomes optimal to adjust labor more through employment and less through effort.
Furthermore, they state that recent evidence points to a rise in the elasticity of labor
input with respect to output.
Following Barnichon (2010), we should expect to see similar characteristics and tim-
ing in the United States and Italy along the following dimensions:
1) a rising share of temporary workers
2) a decline in the unionization rate
3) a sectoral shift from manufacturing to services7
We focus here on a comparison between United States and Italy according to these
three points and the additional moments.
4.2.1 Temporary workers
Temporary workers is a difficult dimension on which to compare the United States and
Italy, in large part because several definitions of what it means to be a temporary worker
exist.8 However, in the United States it is clear that temporary workers played a bigger
7The connection between the sectoral shift from manufacturing to services and labor market flexibilitymay not be immediately obvious. However, DAgostino et al. (2006) find that institutional frameworksaffecting the degree of flexibility in the labor market play an important role in the level of service sectoremployment. For example, in their econometric analysis of the determinants of service sector employ-ment, they find a negative effect of the rate of national union density on the service sector employmentshare. They report similar results for the effect of national employment protection legislation.
8See Osterman (2001) for a full list of definitions.
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role in the US economy starting in the late 70s and early 80s. According to Osterman
(2001), from "1979 to 1995 the temporary help supply industry grew at a rate of 11.2
percent a year, five times the rate for total U.S. non-farm employment". In addition,
Osterman (2001) shows that, according to Census data, between "1988 and 1996 fully 22
percent were in business services and engineering/management services, i.e. the two
sectors, which supply contract and contingent labour".
The series for temporary workers in Italy also displays an upward trend starting
with the mid 80s (figure 11).9 The slope of the trend becomes more pronounced after
1993, when a series of labor market reforms were implemented in Italy. According to
this criterion, the two countries seem to have a similar evolution.
4.2.2 Decline of unionization rate
The evolutions of the trade union densities are presented in figure 11 in the Appendix.
The rate of union membership in the United States experienced a "modest and concen-
trated decline in the 1979 to 1984 period" (Gosling and Lemieux (2004)), with the peak of
union membership in absolute terms in 1979 with 21 million (Mayer (2004)). However
by 2003 union membership stood at 15.8 million (Mayer (2004)). In terms of propor-
tion, only 11.5% of employed workers were union members in 2003 (Mayer (2004)). In
addition to a decrease in membership, unions also became less relevant for setting em-
ployment terms. Union wage setting in the 1990s is described as decentralized with
"unions [having] little influence over pay in the private sector" (Gosling and Lemieux
(2004)).
The evolution of the trade union density in Italy displays a declining trend starting
with the beginning of the 80s. The pattern is very similar to the one of US, although in
9Unfortunately we lack data before 1983 so we cant assess whether there was a structural break in themid 80s or the increase started much earlier.
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absolute terms the unionization rate for US is much lower than the one in Italy over the
entire sample period. However, in order to accurately compare the two countries along
this dimension we need to consider as well the evolution of the coverage rate in Italy,
since for US the two indicators coincide. In the case of Italy, the coverage and unioniza-
tion rates differ because the impact of the policies adopted by the members of the union
extend to all the workers and not just to union members. The coverage ratio has de-
creased since the beginning of the 1970s until 2000 and displays two main shifts in the
trend, one in the mid 80s and the other one at the beginning of the 90s. These changes
can be associated with the two breaks in the correlation between unemployment and
productivity observed in our data, as well as two labor market reforms that took place
in Italy, one in the mid 1980s and one in 1993 (Jimenez-Rodriguez and Russo, 2010).
The process of deregulation from 1984 consisted mainly of the introduction of part-
time contracts and the abolishment of the mechanism of automatic wage indexation,
characterized by uniform wage adjustments to inflation across workers. The reforms
implemented in 1993 regarded a broad range of issues and established a new institu-
tional framework for bargaining procedures, union representations and general em-
ployment policies. The agreements provided a foundation for a better representation of
employees and collective bargaining (OECD (2004) ; Visser (2008)). The Income Policy
Agreement from 1993 created a new bargaining system which incorporated a national
and regional level. The former is meant to protect the purchasing power of wages,
while the second aims at coordinating the additional wage components with firm per-
formance and therefore improves the flexibility of the wage determination by making
it more market driven and sensitive to the economic conditions (Devicienti, Maida, and
Pacelli, 2006).
Although the reforms implemented in 1993 were meant to increase the flexibility of
the labor market, it is not clear to what extent they were implemented in an efficient
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manner and whether the objective was achieved. However, assuming that these insti-
tutional changes lead to a certain extent to a decrease in the rigidities, according to our
data these effects are associated with a negative correlation between unemployment
and productivity and not a positive one.
4.2.3 Sectoral shift from manufacturing to services
According to Kutscher and Personick (1986), a substantial shift in employment between
the manufacturing and service sectors can be observed beginning in the late 1970s:
the goods-producing sector lost 3 million jobs between 1979 and 1983, "while service-
producing jobs increased every year during that time span, by a total of 4.1 million"
(1986). While the goods-producing sector recovered slightly in the mid-1980s, the "gain
was dwarfed by the almost 3.0 million new service-producing jobs added in that single
year" (Kutscher and Personick (1986)). See figure 10 in the Appendix for the evolution
in employment shares in the US.
The sectoral shift from manufacturing to services took place in Italy as well, in very
similar proportions with the one in the US. We can notice from figure 10 that the propor-
tion of workers in the service sector relative to manufacturing increased between 1970
and 2011, with a more pronounced upper trend in the mid 80s.
4.2.4 Labor market conclusions
Empirical evidence points towards some similarities across the labor markets in US and
Italy, such as a common evolution of temporary workers and a sectoral shift from man-
ufacturing to services. However, these features are common to many industrialized
countries. More importantly, there are substantial differences regarding the role played
by labor unions in each country. Therefore, while the countries display similar trends
towards flexibility since the 1970s, the evidence points to a more flexible market in US.
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Business Cycle Statistics: United States and Italy
Italy
All Sample 1970-1983 1983-1993 1993-2011
Corr (Unemployment, productivity) -0.06 -0.07 0.44 -0.50
Corr (Unemployment, productivity) -0.06 -0.05 -0.07
Corr (Productivity, output) 0.81 0.88 0.73 0.78
Vol: Employment to output 0.50 0.44 0.56
Vol: Hours relative to output 0.44 0.31 0.55
US
All Sample 1970-1983 1983-2011
Corr (Unemployment, productivity) -0.01 -0.35 0.24
Corr (Productivity, output) 0.39 0.64 0.20
Vol: Employment to output 0.70 0.64 0.78
Vol: Hours relative to output 0.29 0.24 0.36
In terms of the procyclicality of productivity, the US and Italy display different be-
havior. In the United States, the strength of this correlation falls significantly in the
second half of the sample, while it remains constant in Italy. We find the US labor mar-
ket to be more flexible than its Italian counterpart thus reinforcing for the claim made
by Gali and van Rens (2010) that increased labor market flexibility is responsible for the
vanishing procyclicality of productivity. However, both Italy and the United States haveexperienced a relative increase in the volatility of employment and hours with respect
to output over the second half of the sample. In their paper, Gali and van Rens (2010)
attribute this increase in labor input volatility to firms increasing reliance on labor input
adjustments in order to meet changes in output, and find that as labor market frictions
decrease in their model, the volatility of employment relative to output increases as
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well.
Furthermore, Barnichon (2010) attributes 60% of the switch in the correlation be-
tween labor productivity and unemployment to structural changes related to the labor
market and monetary policy, which suggests the correlation pattern should reflect the
degree of labor market flexibility to some extent. The similarity in the pattern of the
correlation between the United States and Italy suggests that labor market flexibility is
not likely to be the only relevant explanation for the developments in the evolutions of
correlations. However, he does not denote which of the two structural changes are more
important, so our conclusion is only tentative and further research is needed.
5 Conclusion
Recent developments in business cycle statistics have been documented only for US. In
this paper, we address (i) the sign shift in the unconditional correlation between produc-
tivity and unemployment, (ii) a decrease in the procyclicality of productivity and (iii)
an increase in the volatility of employment and hours relative to output for 10 OECD
countries. Barnichon (2010) provides two main explanations for these developments,
one consisting of an increase in the size of technology shocks relative to other shocks
and another based on a increase in labor market flexibility. The purpose of this paper is
twofold. First, we extend the analysis to other OECD countries in order to investigate
whether the changes in correlations remain valid and group the countries according
to similar evolutions of the series. Second, we investigate whether the degree of labor
market flexibility could be a valid explanation for similar developments and patterns in
the group formed by US and Italy. In order to asses this assumption we look at empiri-
cal evidence regarding the evolution of temporary workers, unionization rates, sectoral
shifts. Finally, we analyze additional business cycle statistics, such as the cyclicality of
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labor productivity and the volatilities of macroeconomic series, in order to determine
whether the three developments listed above are consistent and reflect the characteris-
tics of the labor market within our group of interest.
We find that there are significant differences in the flexibility and evolution of the
labor markets in US and Italy despite the high similarities in the patterns of correlations
between unemployment and labor productivity. The two countries display similarities
only in terms of the evolution of temporary workers and sectoral shifts from manufac-
turing to services, the latter being a common feature of most industrialized countries.
However, the role played by the unions point to a more flexible market in US. Fur-
thermore, the effects of the reforms implemented in Italy at the beginning of the 90s
are associated with a switch in the correlation from positive to negative and not vice
versa. Finally, the procyclicality of productivity declined only in US and not in Italy,
which provides evidence for Gali and van Rens (2010) claim that increased labor mar-
ket flexibility is responsible for the vanishing procyclicality of productivity. However,
we consider that labor market flexibility is not likely to be the only relevant explanation
for the developments in the evolutions of correlations between labor productivity and
unemployment, and the increase in the volatility of employment and hours relative to
output. We do not assess here the explanation based on the relative evolution of tech-
nology and non-technology shocks, therefore this hypothesis remains as a ground for
future research.
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Economic Effects of British Economic Reforms, 1980-2000 June.
Jimenez-Rodriguez, R. and G. Russo (2010). Aggregate Employment Dynamics and
(Partial) Labor Market Reforms? Center for Studies in Economics and Finance Working
Paper (260).
Kutscher, R. and V. Personick (1986). Deindustrialization and the shift to services.
Monthly Labor Review June.
Marchetti, D. and F. Nucci (May 2006). Labor effort over the business cycle. Banca
DItalia: Temi di discussione del Servizio Studi 625.
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Mayer, G. (2004). Union Membership Trends in the United States. Congressional Research
Service: CRS Report for Congress August.
Nickell, W. (2006). The Cep-Oecd Institutions Data Set. CEP Discussion Paper 759.
OECD (2004). Wage-setting Institutions and Outcomes. OECD Employment Outlook,
127181.
Osterman, P. (2001). Flexibility and Commitment in the United States Labour Market.
International Labour Organisation, Research Programme: "Adjustment of labour markets toeconomic and structural change: labour market flexibility, security and labour market poli-
cies 18.
Stat, O. (2012). Real gdp, average hours per worker, employment, unemployment.
Statistics.
Stock, J. H. and M. W. Watson (2002). Has the Business Cycle Changed and Why? NBER
Macroeconomics Annual 17, 159218.
Visser, J. (2008). The Quality of Industrial Relations and the Lisbon Strategy. European
Commission, Industrial relations in Europe.
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6 Appendix
6.1 Robustness check
Robustness Check, Business Cycle Statistics: United States and Italy
Italy
All Sample 1970-1983 1983-1993 1993-2011
Corr (Unemployment, productivity) -0.02 -0.05 0.32 -0.29
Corr (Unemployment, productivity) -0.02 -0.05 0.01
Corr (Productivity and output) 0.77 0.88 0.68 0.73
Vol: Employment to output 0.53 0.45 0.60
Vol: Hours to output 0.47 0.33 0.62
US
All Sample 1970-1983 1983-2011
Corr (Unemployment, productivity) -0.08 -0.38 0.12
Corr (Productivity and output) 0.55 0.71 0.44
Vol: Employment to output 0.65 0.61 0.70
Vol: Hours to output 0.28 0.23 0.35
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6.2 Figures
Figure 1: 10 year rolling correlations between unemployment and productivity
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Figure 2: 10 year rolling correlations between unemployment and productivity
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Figure 3: 10 year rolling correlations between unemployment and productivity
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Figure 4: 10 year rolling correlations between unemployment and productivity
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Figure 5: 10 year rolling correlations between unemployment and productivity
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Figure 6: 10 year rolling correlations between unemployment and productivity
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Figure 7: 10 year rolling correlations between unemployment and productivity
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Figure 8: 10 year rolling correlations between unemployment and productivity
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Figure 9: 10 year rolling correlations between unemployment and productivity
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Figure 10: Sectoral shift from manufacturing to services
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Figure 11: Temporary workers and Trade Union Density
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Figure 12: Evolution of volatilities: Focus group
-0.01
0
0.01
0.02
0.03
0.04
Q11970
Q31971
Q11973
Q31974
Q11976
Q31977
Q11979
Q31980
Q11982
Q31983
Q11985
Q31986
Q11988
Q31989
Q11991
Q31992
Q11994
Q31995
Q11997
Q31998
Q12000
Q32001
US: 10-year rolling standard deviation of output
Output
0
0.005
0.01
0.015
0.02
0.025
Q11970
Q21971
Q31972
Q41973
Q11975
Q21976
Q31977
Q41978
Q11980
Q21981
Q31982
Q41983
Q11985
Q21986
Q31987
Q41988
Q11990
Q21991
Q31992
Q41993
Q11995
Q21996
Q31997
Q41998
Q12000
Q22001
US: 10-year rolling standard deviation ofemployment
Employment
0
0.001
0.002
0.003
0.004
0.005
0.006
0.007
11970
21971
31972
41973
11975
21976
31977
41978
11980
21981
31982
41983
11985
21986
31987
41988
11990
21991
31992
41993
11995
21996
31997
41998
12000
22001
US: 10-year rolling standard deviation of hours
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Figure 13: Evolution of volatilities: Focus group
0
0.002
0.004
0.0060.008
0.01
0.012
0.014
Q11970
Q21971
Q31972
Q41973
Q11975
Q21976
Q31977
Q41978
Q11980
Q21981
Q31982
Q41983
Q11985
Q21986
Q31987
Q41988
Q11990
Q21991
Q31992
Q41993
Q11995
Q21996
Q31997
Q41998
Q12000
Q22001
US: 10-year rolling standard deviation of
productivity
Productivity
0
0.005
0.01
0.015
0.02
0.025
Q1
1970
Q2
1971
Q3
1972
Q4
1973
Q1
1975
Q2
1976
Q3
1977
Q4
1978
Q1
1980
Q2
1981
Q3
1982
Q4
1983
Q1
1985
Q2
1986
Q3
1987
Q4
1988
Q1
1990
Q2
1991
Q3
1992
Q4
1993
Q1
1995
Q2
1996
Q3
1997
Q4
1998
Q1
2000
Q2
2001
Italy: 10-year rolling standard deviation ofproductivity
Productivity
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Figure 15: The cyclicality of productivity
-0.04
-0.03
-0.02
-0.01
0
0.01
0.02
0.03
0.04
0.05
Q11970
Q31971
Q11973
Q31974
Q11976
Q31977
Q11979
Q31980
Q11982
Q31983
Q11985
Q31986
Q11988
Q31989
Q11991
Q31992
Q11994
Q31995
Q11997
Q31998
Q12000
Q32001
Q12003
Q32004
Q12006
Q32007
Q12009
Q32010
The procyclicality of productivity in Italy,1970Q1-2011Q4
Real GDP: Deviations from trend Productivity: Deviations from trend
-0.06
-0.05
-0.04
-0.03
-0.02
-0.01
0
0.01
0.02
0.03
0.04
0.05
Q11970
Q31971
Q11973
Q31974
Q11976
Q31977
Q11979
Q31980
Q11982
Q31983
Q11985
Q31986
Q11988
Q31989
Q11991
Q31992
Q11994
Q31995
Q11997
Q31998
Q12000
Q32001
Q12003
Q32004
Q12006
Q32007
Q12009
Q32010
The procyclicality of productivity in the US,
1970Q1-2011Q4
Real GDP: Deviations from trend Productivity: Deviations from trend
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Figure 16: Volatility ratios: Focus group
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
Q119
70
Q219
71
Q319
72
Q419
73
Q119
75
Q219
76
Q319
77
Q419
78
Q119
80
Q219
81
Q319
82
Q419
83
Q119
85
Q219
86
Q319
87
Q419
88
Q119
90
Q219
91
Q319
92
Q419
93
Q119
95
Q219
96
Q319
97
Q419
98
Q120
00
Q220
01
Italy: Volatility ratios over time
Employment/Output Hours/Output
0
0.1
0.2
0.3
0.40.5
0.6
0.7
0.8
0.9
1
Q11970
Q21971
Q31972
Q41973
Q11975
Q21976
Q31977
Q41978
Q11980
Q21981
Q31982
Q41983
Q11985
Q21986
Q31987
Q41988
Q11990
Q21991
Q31992
Q41993
Q11995
Q21996
Q31997
Q41998
Q12000
Q22001
US: Volatility ratios over time
Employment/Output Hours/Output
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Figure 17: Volatilities
0
0.002
0.004
0.006
0.008
0.01
0.012
0.014
0.016
0.018
Q11970
Q31971
Q11973
Q31974
Q11976
Q31977
Q11979
Q31980
Q11982
Q31983
Q11985
Q31986
Q11988
Q31989
Q11991
Q31992
Q11994
Q31995
Q11997
Q31998
Q12000
Q32001
Australia: 10-year rolling
standard deviations
Employment Lab prod1 Real GDP Hours
0
0.005
0.01
0.015
0.02
0.025
Q11970
Q31971
Q11973
Q31974
Q11976
Q31977
Q11979
Q31980
Q11982
Q31983
Q11985
Q31986
Q11988
Q31989
Q11991
Q31992
Q11994
Q31995
Q11997
Q31998
Q12000
Q32001
Canada: 10-year rolling standard
deviations
Real GDP Employment Lab prod1 Hours
0
0.005
0.01
0.015
0.02
0.025
0.03
0.035
1970
1971
1972
1973
1975
1976
1977
1978
1980
1981
1982
1983
1985
1986
1987
1988
1990
1991
1992
1993
1995
1996
1997
1998
2000
Finland: 10-year rolling standard
deviations
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Figure 18: Volatilities
0
0.005
0.01
0.015
0.02
Q11970
Q31971
Q11973
Q31974
Q11976
Q31977
Q11979
Q31980
Q11982
Q31983
Q11985
Q31986
Q11988
Q31989
Q11991
Q31992
Q11994
Q31995
Q11997
Q31998
Q12000
Q32001
France: 10-year rolling standard deviations
Real GDP Employment Lab prod1 Hours
0
0.005
0.01
0.015
0.02
0.025
Q11970
Q31971
Q11973
Q31974
Q11976
Q31977
Q11979
Q31980
Q11982
Q31983
Q11985
Q31986
Q11988
Q31989
Q11991
Q31992
Q11994
Q31995
Q11997
Q31998
Q12000
Q32001
Italy: 10-year rolling standard deviations
Real GDP Employment Lab prod1 Hours
0
0.005
0.01
0.015
0.02
0.025
11972
21973
31974
1975
11977
21978
31979
1980
11982
21983
31984
1985
11987
21988
31989
1990
11992
21993
31994
1995
11997
21998
31999
2000
Norway: 10-year rolling standard
deviations
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Figure 19: Volatilities
0
0.01
0.02
0.03
0.04
0.05
Q11970
Q21971
Q31972
Q41973
Q11975
Q21976
Q31977
Q41978
Q11980
Q21981
Q31982
Q41983
Q11985
Q21986
Q31987
Q41988
Q11990
Q21991
Q31992
Q41993
Q11995
Q21996
Q31997
Q41998
Q12000
Q22001
New Zealand: 10-year rolling standard
deviations
Real GDP Employment Lab prod1 Hours
0
0.005
0.01
0.015
0.02
0.025
1970
1971
1973
1974
1976
1977
1979
1980
1982
1983
1985
1986
1988
1989
1991
1992
1994
1995
1997
1998
2000
2001
Sweden: 10-year rolling standard
deviations
0
0.005
0.01
0.015
0.02
0.025
Q11970
Q31971
Q11973
Q31974
Q11976
Q31977
Q11979
Q31980
Q11982
Q31983
Q11985
Q31986
Q11988
Q31989
Q11991
Q31992
Q11994
Q31995
Q11997
Q31998
Q12000
Q32001
Japan: 10-year rolling standard deviations
Real GDP Employment Lab prod1 Hours
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Figure 20: Volatilities
0
0.005
0.01
0.015
0.02
0.025
Q11971
Q21972
Q31973
Q41974
Q11976
Q21977
Q31978
Q41979
Q11981
Q21982
Q31983
Q41984
Q11986
Q21987
Q31988
Q41989
Q11991
Q21992
Q31993
Q41994
Q11996
Q21997
Q31998
Q41999
Q12001
UK: 10-year rolling standard deviations
Real GDP Employment Lab prod1 Hours
0
0.005
0.01
0.015
0.02
0.025
0.03
Q11970
Q31971
Q11973
Q31974
Q11976
Q31977
Q11979
Q31980
Q11982
Q31983
Q11985
Q31986
Q11988
Q31989
Q11991
Q31992
Q11994
Q31995
Q11997
Q31998
Q12000
Q32001
US: 10-year rolling standard deviations
Real GDP Employment Lab prod1 Hours
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Figure 21: Volatilities
0
0.05
0.1
0.15
0.2
Q11970
Q31971
Q11973
Q31974
Q11976
Q31977
Q11979
Q31980
Q11982
Q31983
Q11985
Q31986
Q11988
Q31989
Q11991
Q31992
Q11994
Q31995
Q11997
Q31998
Q12000
Q32001
Australia: 10-year rollingstandard deviations
Unemployment
0
0.02
0.04
0.06
0.08
0.1
0.12
0.14
Q11970
Q31971
Q11973
Q31974
Q11976
Q31977
Q11979
Q31980
Q11982
Q31983
Q11985
Q31986
Q11988
Q31989
Q11991
Q31992
Q11994
Q31995
Q11997
Q31998
Q12000
Q32001
Canada: 10-year rolling
standard deviations
Unemployment
0
0.05
0.1
0.15
0.2
0.25
0.3
1970
1971
1972
1973
1975
1976
1977
1978
1980
1981
1982
1983
1985
1986
1987
1988
1990
1991
1992
1993
1995
1996
1997
1998
2000
Finland: 10-year rolling standard
deviations
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Figure 22: Volatilities
0
0.02
0.04
0.06
0.08
0.1
Q11970
Q31971
Q11973
Q31974
Q11976
Q31977
Q11979
Q31980
Q11982
Q31983
Q11985
Q31986
Q11988
Q31989
Q11991
Q31992
Q11994
Q31995
Q11997
Q31998
Q12000
Q32001
France: 10-year rolling standard
deviations
Unemployment
0
0.01
0.02
0.03
0.040.05
0.06
0.07
0.08
0.09
Q11970
Q31971
Q11973
Q31974
Q11976
Q31977
Q11979
Q31980
Q11982
Q31983
Q11985
Q31986
Q11988
Q31989
Q11991
Q31992
Q11994
Q31995
Q11997
Q31998
Q12000
Q32001
Italy: 10-year rolling standard deviations
Unemployment
0
0.05
0.1
0.15
0.2
0.25
1972
1973
1974
1975
1977
1978
1979
1980
1982
1983
1984
1985
1987
1988
1989
1990
1992
1993
1994
1995
1997
1998
1999
2000
Norway: 10-year rolling standard
deviations
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Figure 23: Volatilities
0
0.1
0.2
0.3
0.4
0.5
0.6
Q11970
Q21971
Q31972
Q41973
Q11975
Q21976
Q31977
Q41978
Q11980
Q21981
Q31982
Q41983
Q11985
Q21986
Q31987
Q41988
Q11990
Q21991
Q31992
Q41993
Q11995
Q21996
Q31997
Q41998
Q12000
Q22001
New Zealand: 10-year rolling standard
deviations
Unemployment
0
0.05
0.1
0.15
0.2
0.25
1970
1971
1973
1974
1976
1977
1979
1980
1982
1983
1985
1986
1988
1989
1991
1992
1994
1995
1997
1998
2000
2001
Sweden: 10-year rolling standard
deviations
0
0.02
0.04
0.06
0.08
0.1
Q11970
Q31971
Q11973
Q31974
Q11976
Q31977
Q11979
Q31980
Q11982
Q31983
Q11985
Q31986
Q11988
Q31989
Q11991
Q31992
Q11994
Q31995
Q11997
Q31998
Q12000
Q32001
Japan: 10-year rolling standard deviations
Unemployment
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Figure 24: Volatilities
0
0.02
0.04
0.06
0.08
0.1
0.12
Q11970
Q21971
Q31972
Q41973
Q11975
Q21976
Q31977
Q41978
Q11980
Q21981
Q31982
Q41983
Q11985
Q21986
Q31987
Q41988
Q11990
Q21991
Q31992
Q41993
Q11995
Q21996
Q31997
Q41998
Q12000
UK: 10-year rolling standard deviations
Unemployment
0
0.02
0.04
0.06
0.08
0.1
0.12
0.14
0.16
Q11970
Q31971
Q11973
Q31974
Q11976
Q31977
Q11979
Q31980
Q11982
Q31983
Q11985
Q31986
Q11988
Q31989
Q11991
Q31992
Q11994
Q31995
Q11997
Q31998
Q12000
Q32001
US: 10-year rolling standard deviations
Unemployment