Differences in Unemployment Dynamics over the Business Cycle across countries: Okun´s Law

Introduction

The 2007 Financial/Economic Crisis has led to a deep decrease in GDP growth and hence to

unprecedented levels of unemployment in most OECD countries. After seven years of recession,

across the OCDE, there are almost 49 million unemployed persons, 16 million more than at 2007,

although the unemployment response to a similar decrease in GDP growth has varied across

countries. Why some countries, such as Spain, have destroyed so many jobs for similar output

reductions? This paper investigates the relation between unemployment rate and output for some

countries, and in particular also, whether such relationship differs depending on the business cycle

phase.

Traditionally, the relationship between changes in unemployment rate and output growth has

been measured through the statistical relationship known as the Okun´s Law. In 1962, the

economist Artur Okun quantified the statistical relationship between unemployment and output.

Okun estimated the following relationship between these two variables using the equation:

Where Δu is the change in unemployment rate, Δy the real GDP growth rate, and k and c are two

parameters that are assumed to be constant (c is also named Okun´s coefficient, which is a key

feature in this paper).The Okun´s law reflects the elasticity of unemployment to output changes,

assuming that that elasticity is constant. This law has been taken by economists as a good point to

start an analysis. The equation is a practical tool whose parameters are often estimated to make

time and cross country comparisons.

Cazes et al. (2013), which is the base reference of this work, argue that “… Knotek (2007)

proposed that Okun ’ s coefficient varies over time in the context of both longer-term trends and

asymmetry over the business cycle. In this literature, asymmetry is used to denote the phenomenon

where the correlation between the two series (change in the unemployment rate and output)

differs over specific phases of the business cycle” (Neftci 1984)[Cazes et al. (2013), page 2].

Cazes et al. (2013) proposes a new methodology to take into account the variability of the Okun’s

coefficient over the business cycle.

Our specific contribution is twofold: On the one hand, we expand the period analyzed by Cazes et

al (2013) including the post-recession data (from 2011 to 2015). Secondly, we also perform a

variant of Cazes et al (2013) analysis, by considering the relationship between changes in the rate

of total hours worked in the country and output growth instead of the unemployment rate used in

the Okun´s law.

We consider a sample of four European countries: Spain, Germany, Sweden and UK. Each of them

represent not only a different cardinal point of Europe but also they are somehow representative

of different European Regions: Spain as the example of a Mediterranean country. Sweden as an

Scandinavian and northern economy. UK because its peculiarities, shared in part with Ireland and

anglo-saxon countries. Germany as a central European strong economy.

The structure of the paper is as follows. Section 2 shows the evolution of GDP and unemployment

rate across the last 25 years, along with data about the evolution of productivity, labor force and

hours worked per worker. In section 3 the Okun´s parameter will be calculated following the

rolling regressions method. In section 4 the previous exercise will be repeated using annual growth

rates in total hours instead of the unemployment rate in the Okun´s equation. Finally, section 5

concludes the paper.

2. Descriptive Evidence – Output and Unemployment changes over

the cycle

Before estimating the relationship between changes in unemployment and output, it is important

to describe the behavior of such variables over time and for each of the countries which enter the

analysis.

2.1Output and Unemployment

Figure 1 reveals a very different evolution of unemployment rates, particularly between Spain and

the other three countries: On the first hand, Spain is the country where Unemployment Rate

decreased to a greatest extent since the mid-nineties to the start of the recession. However, the

increase in unemployment rate is huge from 2008 onwards. On the contrary, if we look at

Germany, it can be seen that unemployment rate has decreased from 2008 onwards. Sweden and

UK experience a mild increase in Unemployment Rates in the first years of the recession, to

decrease slightly after 2010.

Figure 2 shows the evolution of GDP Per Capita for the last 25 years. In the four countries

considered, output per capita grows since mid-nineties until 2008, the start of the actual

recession. From then on, it can be seen that countries like Germany and Sweden seem to have

experienced a quick recovery whereas UK and, specially, Spain are, after 7 years, still unable to

recover the pre-crisis levels.

Unemployment

05

1015

2025

1990 1995 2000 2005 2010 2015Year

Germany Sweden

Spain UK

Une

mpl

. rat

e

GDP per capita

2500

030

000

3500

040

000

4500

0

1990 1995 2000 2005 2010 2015Year

Germany Sweden

Spain UK

GD

P p

. c. (

US

$ o

f 201

0, p

ps)

Figure 1: Unemployment rate of countries of the simple, period 1990q1-2015q1

Figure 2: GDP per capita for the countries in the sample, period 1990q1-2015q1

2.2 Variables related with unemployment and GDP.

It is useful to do a descriptive analysis of additional variables deeply connected with

unemployment and output, such as Productivity, Working Hours and Labour Force. These variables

are not only interesting by themselves, but also allow us to understand some underlying facts

regarding the relationship between output and unemployment. Following Cazes et al. (2013) we

do a decomposition exercise to help the understanding of the underlying relationship between

unemployment and GDP.

Where H means total hours worked in the country, N net employment, LF labor force, and the

results for

are productivity and hours worked per worker respectively.

The evolution of productivity, which is mean output per hour worked, is clearly the most

important variable to relate GDP and unemployment. Regarding this variable, it can be said that in

two countries (Sweden and UK) grow in a continuous and fast way, whereas in Germany such

growth has been more moderate since 2000. Finally, in Spain no productivity growth has taken

place whatsoever until the start of the crisis. Indeed, the lack of productivity growth in Spain

during the 2000-2007 upturn is remarkable. The constant productivity shows that the relation

between output and labor has been constant along time. This apparent constancy is hiding a

dualistic development: when the productivity of some sectors (industry and services) was growing

, most of the employment creation was in the construction sector whose productivity was the

lowest (see Andres et al, 2009). When the recession started the employment destruction in

construction sector made the general productivity to grow, even when the employed workers

weren´t more productive than in the past.

______ Productivity ______Hours per worker ______Labor force

Figure 3: Annual productivity, working hours and labor force growth taking 2000 as the reference year (2000 =0).

Period 1991-2014

Spain

-10

010

20

30

-20

1990 1995 2000 2005 2010 2015Year

Sweden

-20

-10

010

20

30

1990 1995 2000 2005 2010 2015Year

Germany

-20

-10

010

20

30

30

1990 1995 2000 2005 2010 2015Year

UK

-20

-10

010

20

30

1990 1995 2000 2005 2010 2015Year

Average hours of work per worker exhibit a general decrease during the period, with the only

exception of Sweden, and only until 2000. In Germany this decrease is much more pronounced

than in the rest of the countries being around 15% in 25 years (more than an hour per workday).

Finally, with respect to labour force trends, we can see a similar (steady) increase in the UK and in

Sweden. On the contrary, labour force seems to remain relatively constant during the whole

period in Germany. In Spain, the evolution of labour force exhibits large volatility: It increases to a

large extent from 2000 to 2007 due mainly to the immigration boom. From 2008 onwards, labour

force remains relatively constant.

3. Results from the Rolling Regressions of the Okun´s Law

The most important assumption implied in Okun´s law is that the relation between changes in

unemployment rate and output growth rate is linear. Since the year of publication of his paper,

the labor market has changed , and economists argue about its empirical validity. Although all the

shakes in Okun´s parameter (which it is assumed to be constant) can´t be count as structural,

European labor market has been experiencing many drastic reforms that change the relation

between the two variables.

Cazes et al. (2013) mentions that Knotek (2007) proposed that Okun ’ s coefficient varies over time

in the context of both longer-term trends and asymmetry over the business cycle. In the literature,

some dynamic-versions of the Okun´s law have been proposed: lag incorporation (of

unemployment and GDP) in the original Okun´s equation (Pereira, 2013); the so called “dynamic

betas” method, (IMF 2010, Chapter 3) and the rolling regressions method, used in Cazes et al.

(2013) and which will be replicated in this paper.

In the rolling regressions method, instead of calculating a Okun´s parameter with the complete

dataset by Ordinary Least Squares, it takes a specific number observations of one period to

calculate that period´s parameter by OLS, then drops the first observation of the period and takes

the next one to repeat the process… to build a set of parameters instead of one. In this exercise,

we calculate an Okun´s parameter for each period of 40 quarters (10 years, 40 observations)

taking observations for the period 1980q1 to 1989q4, then, another parameter for the period

1980q2 to 1990q1 and so on. Remember that the estimated equation is the standard Okun´s

equation referred at the beginning of the paper:

At this point, it must be reminded that the Okun´s parameter c express how much will decrease

the unemployment rate for every point of growth in the GDP, and k the required GDP increase to

have zero change in unemployment rate. This paper only focuses in c values and their changes

throughout time.

The availability of quarterly data is more limited than annual data. In particular, Quarterly series

for unemployment and GDP (extracted from OECD dataset) start before 1985 for UK and Sweden,

but only from 1986 on in the case of Spain. For Germany, due to the reunification, almost all time

series data begin in 1991.

Germany

Germany shows a low elasticity of unemployment to GDP changes. However, if we compare

different phases of the last business cycle, we can see a slight increase in the upturn, and from

2007 onwards, a slight decrease. Still, the values range from 0.05 to 0.2.

We might think that part of the explanation for this low response of unemployment to changes in

GDP, particularly during downturns, stem from the fact that Germany has a very flexible short-

Okun´s Coefficient

0.2

.4.6

.81

1995 2000 2005 2010 2015Year

Sweden Germany

UK Spain

Figure 4: Okun´s coefficient value for each series of 40 quarters. Period: 1995q1-

2015q1 for UK and Sweden, 2001q1-2015q1 for Germany and 1996q1-2015q1 for

Spain.

time work programs as a way to cope with the recession. This means that an aggregate demand

reduction will be faced with the reduction of the working day instead of firing labor. As a

consequence, the work reduction is faced not as an extensive, but intensive way.

Sweden

Regarding Sweden, we can see a slight increase in the Okun´s coefficient from 1997 to 2003. From

then on, we observe a continuous decrease until the Great Recession. To understand these

changes, we must notice from figure 1 that Sweden suffered an important increase in

unemployment from 1990-1997, but from then on, unemployment rate has stayed reasonably

stable. In addition, GDP per capita has grown continuously and at a high pace for the last 25 years,

except from 2008 to 2010, where an abrupt decrease can be observed. But from 2010 on, Sweden

has faced again a relatively high pace in the growth of GDP per capita. Hence, it looks like Sweden

has been almost no affected by this last Recession quick recovery, and this is probably why we do

not observe a particular change in the relationship between output growth and changes in

unemployment rate during this last recession. As in Germany, after the Great Recession the

Okun’s coefficient is quite constant and its value ranges from 0 to 0.2 .

Spain

Spain is, by no means, the country with a highest and most volatile Okun´s parameter. From 2000

to 2003, Spain faces a very sharp increase in the elasticity of unemployment rate to output

growth, growing from 0.2 to 0.75. From 2003 to 2006, the relationship stays remarkable constant

at 0.6. From then until the start of the Great Recession, the elasticity suffers another sharp

increase, reaching the value of 1. Lastly, from then on until 2015, we appreciate a continuous,

although slight, decrease. At 2015, the elasticity of unemployment to output reaches 0.8. To

understand what is behind such unstable relationship between output growth and unemployment

rate, we must rely on the mechanisms that Spain uses to adjust aggregate demand shocks. Barely

every adjustment to changes in aggregate demand is done through the hiring or firing of

temporary workers, i.e., the extensive margin. There is no adjustment whatsoever at the intensive

margin, i.e., hours per worker. Hence, unemployment changes greatly at aggregate demand

changes.

In particular, the spectacular growth of the Okun´s coefficient since 2000 can be partially

explained by the enormous employment creation in the construction sector, characterized by

being very intensive in labour and with a very high proportion of temporary employment.

However, In 2008, when the economic crisis started hitting the country, a great deal of this

increase in temporary employment is destroyed, unemployment rates grow to unprecedented

levels, and the Okun´s parameters takes the highest values. From then on, the observed slight

decrease might have to do with the two labour market reforms, which took place in 2010 and in

2012, and whose purposes, among others were to increase flexibility in the internal conditions at

the firm level, so as to be able to adjust at the intensive more that at the extensive level.

UK

Finally, Okun´s parameter in the UK shows a continous decrease from 2000s to the start of the

Great Recession. By 2000, the elasticity of unemployment rate to output growth reaches the value

of 0.4, but from then on, we observe a continous decrease until 2007, reaching a value of 0.

However, after a sudden increase at the start of the recession, the parameter stays remarkably

stable at 0.2. Such value is similar to the one observed in Germany and in Sweden. In order to

understand such relatively stability, we may look at the figures displayed before: Although GDP

per capita has experienced a remarkable decrease in the UK in the last recession and still has not

yet reached the pre-recession levels, hours per worker have continuously decreased since then.

This means that adjustment to a decrease in aggregate demand is partly being done at the

intensive level and not so much at the extensive one. This may be part of the reason why we find

such stability and low elasticity of unemployment rate to output since the start of the Great

Recession till nowadays.

Summarizing, we have analyzed a representative sample of European countries and their Okun´s

parameters. Some facts are remarkable: On the first hand, we would stress that in most countries,

we observe a relatively constant Okun´s parameter since the start of the 2007-recession until

nowadays. In spite of the sharp drop in GDP growth, the relationship between unemployment and

output has not experienced a noticeable variation. On the second hand, we should note that UK,

Sweden and Germany show a very similar Okun´s parameter from 2008 until today – around 0.2.

And the parameter shows a slight decrease. This is also interesting given that labour market

institutions differ to a great extent across these countries. However, it looks that these countries

have managed to adapt to aggregate demand changes by adapting at the intensive, more than at

the extensive level. Thirdly, there is a clear difference between northern-central European

countries (Germany, UK and Sweden) and southern countries (Spain). The elasticity of

unemployment to output in Spain is much higher, and this is at least partly given that Spain adapts

to aggregate demand changes exclusively at the extensive, and not intensive level. It would be

interesting to know whether this is also the case for other south-european countries, or rather,

Spain represents an isolated case.

4. Hours worked and Okun´s law

In the previous sections, we have mentioned that the dynamics of the labor force and hours

worked per worker differ across countries. Whereas in Germany, most of the variability is

observed in the hours worked per worker, in Spain employment (and hence unemployment) is

more volatile than hours worked per worker. It seems that the extensive margin in the labor

market in Spain (Germany) is more (less) responsive to output fluctuations than the intensive

margin.

In this section we will estimate the rolling regression using the quarterly increase percentage

change in the total hours worked in the country, this is, the sum of the quarterly hours worked by

each employed person. In this section, the last rolling regression exercise will be repeated using

the following equation:

Where Δ ht is the quarterly increase growth rate in total hours worked in the country (

). To difference this “Okun´s coefficient” c` from the original, it will be called Total Hours

Coefficient.

The use of Changes in Total hours as the dependent variable allows us to measure the total

employment response to changes in output, not only at the extensive, but also at the intensive

level, both of them taken together. In principle, we should notice that c´, total hours coefficient,

should be higher than the original Okun´s one: c´captures not only the extensive but also the

intensive response of employment (and hence to some extent unemployment) to output changes,

whereas the original c would only capture the extensive margin response of labour to changes in

aggregate demand. Moreover, the vertical distance between c´and c tells us about the extent to

which labour market adjustment at changes in aggregate demand are done at the intensive rather

than at the extensive level.

Given that, as we saw before, adjustment of labour to aggregate demand is done differently across

different countries, it is interesting to compare differences between c and c´ for the countries

under consideration. One drawback of using total quarterly hours is the more limited availability

for time series data. The sample begins in 1985 for UK and 1991 for Germany, 1993 for Sweden

and 1995 for Spain, and is more limited for the last two countries.

Germany

-.50

.51

1.5

1995 2000 2005 2010 2015Time

Sweden

-.50

.51

1.5

1995 2000 2005 2010 2015Time

0.5

11.

5

1995 2000 2005 2010 2015Time

Spain

Germany

As expected, the new c´ coefficient is higher than the original one. As we said before, Germany

adapts to aggregate demand changes basically through changes in hours worked per worker, and

not so much through hiring/firing workers. The response of total hours worked to aggregate

demand changes reaches 0.5 and it is relatively stable since the start of the Great Recession until

today. When we compare this coefficient with the original c, we appreciate that the latter has

decreased slightly whereas the “new” one, stays relatively stable and at a clearly higher level.

Sweden

When we compare the magnitude and evolution of the coefficients c´and c for Sweden, we

appreciate the following issues: First, the distance between them is small, and decreases since

2008 onwards. Second, the value of c´ is smaller than the one observed for Germany. This is an

expected result given that as we saw before, in Sweden hours per capita have remained constant

not changed as much as in Germany, and GDP per capita and labor force show a continuous and

relatively constant growth rate. The observed reduction in the differences between both

parameters might be a result of a lower adjustment at the intensive margin (hours worked per

worker) at changes in aggregate demand.

UK-.5

0.5

1

1995 2000 2005 2010 2015Year

Total Hours coef Okun´s coef

Figure 5: Okun´s coefficient and Total Hours Coefficient values for each series of 40 quarters. Periods

for the total hours coefficient:

Spain: 2005q1-2015q1 Germany: 2001q1-2014q4

Sweden: 2003q1-2015q1 UK: 1995q1-2015q1

Spain

When we compare the parameters c and c´for Spain, in particular from the start of the last

recession until today, we observe that the value of c´is above 1 and remains as such for the whole

recession period. When we compare the evolution of the two parameters from 2008 onwards, we

observe that while c diminishes slightly, c´does not do so and hence the vertical distance

increases. This may be at least partly a result of the consequences of the 2010 and 2012 labour

market reforms. Both of them tried to increase internal flexibility at the firm level so as to be able

to adjust to aggregate demand changes through changes in hours per worker (intensive level)

instead of the extensive level. It looks like in the latter years, such change in the adjustment is at

least partly taking place. Still, and besides differences between c´and c, the most remarkable fact

to notice is that the coefficients c and c´for Spain are way above those found for some of our

European neighbors, which denotes the enormous elasticity of employment (and unemployment)

to changes in aggregate demand. Spanish employment and unemployment is too volatile and

something should be done to make it more stable at aggregate demand changes.

UK

Finally, the comparison between c´and c for UK looks weird: On the first hand, from 2002 to 2008,

the Total Hours coefficient is smaller than the original Okun´s one. This is something we cannot

explain. On the second hand, from the start of the recession onwards, it looks like c´ increases

slowly but steadily whereas c remains stable. This increases the vertical distance between c´and c

which tells us that since the start of the recession, adjustment to aggregate demand changes

seems to be increasingly done at the intensive rather than at the extensive level. This is consistent

with the observed decrease in hours worked per worker observed in the UK since the start of the

recession.

Conclusions

This paper has looked at output growth and unemployment rate changes and the relation

between them across a sample of four European countries. The aim of the study is to provide a

deeper understanding about how such relation is determined and how it has changed across time,

focusing in the Great Recession of 2008 and the situation before and after it.

The data has been obtained from the compilation of statistics from national institutes made by the

OECD. In the case of quarterly hours of work series, those have been obtained directly from the

source (INE, SBC, ONS and BCE´s Statistical Data Warehouse for Germany).

An important contribution of this paper is the performance of the original Okun´s exercise using

total hours worked instead of the unemployment rate. Having an indicator that measures the

relation of output and employment could be a necessary complement to the Okun´s approach.

The presence of important differences between both parameters shows the need to take into

account this indicator. The observed differences are very much consistent with the mechanisms

which each country use to adjust labor to aggregate demand changes. In those countries where

adjustment is more focused at the intensive (hours per worker) rather than at the extensive

(number of workers), unemployment rate responses more mildly at recessions. This has happened

in Germany and to some extent in the UK. On the contrary, in other countries, such as Spain,

where most adjustment is done at the extensive level, the elasticity of unemployment to output

changes is very big, and at a deep recession like the 2008, the fall in aggregate demand is coped

with an unbearable increase in unemployment.

One of the lessons to extract from this exercise is that Spain should try to increase the degree of

response of changes in output at the intensive, rather than at the extensive one so as to avoid at

least partly mass dismissals at downturns.

Appendix

Despite the aim of this work is the analysis of the Okun´s parameter and to examine the relation of

elasticity between output and GDP, it will be illuminating to include the other parameter of the

Okun´s equation, named k in (1).

k is the increase in the unemployment rate when the GDP growth is 0. Usually economic analysts

use the value for the opposite situation, the so called output growth threshold, the needed GDP

increase to maintain unemployment rate constant, the value k/c in the cleared version of the

Okun´s equation:

In the alternative Okun´s equation using total hours, the output growth threshold will show the

needed increase in GDP to maintain constant the number of hours worked in the country. Clearing

the equation of total hours:

The results from the replicated rolling regressions exercise show a very high cross country

similarity, at least between Spain, Sweden and UK (Figure 6). These three countries show both

similar absolute values and parallel trends. During the 2000´s both coefficients start to rise slowly

to reach the peak on 2008. Then, with the economic crisis it comes a sudden fall followed with an

slower decrease.

Germany is a case apart. Its parameters are not only lower, but also decrease during the whole

period of the 2000´s, if with the start of the crisis the decrease is more pronounced. In this values

may be part of the explanation of the high employment creation of Germany, simply its output

growth threshold is lower.

Regarding the differences between parameters, again Spain Sweden and UK are very similar. Both

parameters tent to have almost the same values during the 2000´s to start differing after 2008. If

before the crisis the parameter of the total hours equation tent to be a bit higher than Okun´s,

after 2008 its value falls faster, to create a differences in the threshold for hours and for

unemployment rate. Again, Germany is an exception, having an output growth threshold higher

for the working hours than for the unemployment rate.

The interpretation of the values of this parameters is not the aim of this paper, only to show the

data and to make a brief description in this appendix. The explanation of the output growth

thresholds is more related with productivity growth than with the elasticity of unemployment of

output, being it a very different subject.

.2.4

.6.8

10

-.2

1995 2000 2005 2010 2015Time

Spain.8

.20

-.2

.4.6

1

1995 2000 2005 2010 2015Time

Sweden

-.2

0.2

.4.6

.81

1995 2000 2005 2010 2015Time

Germany

.2.4

.6.8

10

-.2

1995 2000 2005 2010 2015Time

UK

Figure 6: Output growth thresholds. k/c (Okun´s ecuation) and k´/c´ (Total Hours ecuation) values for

each series of 40 quarters.

References.

Arthur Okun "Potential GNP: Its Measurement and Significance", 1962. Proceedings of the

Business and Economic Statistics Section of the American Statistical Association. Alexandria, VA:

American Statistical Association

Edward S. Knotek “How usefull is the Okun´s law?”, 2007, quarter 4. Economic review of the

Federal Reserve Bank of Kansas City

J. Andrés, J. E. Boscá, R. Domenech and J. Ferri “Job creation: productivity growth, labor market

reforms or both?”, 2009. BBVA Working Papers, Economic Research department Nº 10/13.

José Daniel Buendía Azorín and María del Mar Sánchez de la Vega,“Estimación de los umbrales de

crecimiento económico para la creación de empleo y la reducción del desempleo con datos de

panel de las provincias españolas” , 2014. International Conference on Regional Science.

Ravi Balakrishnan, Mitali Das,and Prakash Kannnan “Unemployment dynamics during recessions

and recoveries: Okun´s law and beyond”, 2013. IMF World Economic Outlook, April, chapter 3.

Rui M. Pereira “Okun's Law across the Business Cycle and during the Great Recession: A Markov

Switching Analysis”, 2013. College of William and Mary, Department of Economics, Working Paper

Number 139.

Sandrine Cazes, Sher Verick and Fares al Hussami”Why did unemployment respond so differently

to the global finantial crisis across countries?”, 2013. IZA Journal of Labor Policy.

Data Appendix

Time series data about employment and unemployment, GDP and annual hours of work has been

obtained from the OECD webpage http://www.oecd.org/

-Quarterly GDP growth: https://data.oecd.org/gdp/gross-domestic-product-gdp.htm

-Quarterly Unemployment rates: https://data.oecd.org/unemp/harmonised-unemployment-rate-

hur.htm

From http://stats.oecd.org/:

-Net employment and Labor Force: National Accounts/Quarterly National Accounts/

Quarterly National Accounts/ Population and Employment-National Concept.

- GDP per capita: National Accounts/Quarterly National Accounts/ Quarterly National

Accounts/ GDP per Capita.

-Annual hours worked per worker: Labour/Labour Force Statistics/Hours worked/Average

annual hours actually worked per worker.

-Annual total labor force and net employment: Labour/Labour Force Statistics/ Annual

Labour Force Statistics/ Population and Labour Force.

-Real GDP: National Accounts/ Annual National Accounts/ Main Aggregates/Gross

domestic product (GDP)/ GDP, US $, constant prices, constant PPPs, reference year 2010,

millions

-Productivity: Calculated using Real GDP (GDP), Labor Force (LF) and Hours worked per worker (h):

-Total Hours: Calculated using net employment (E) and Hours worked per worker (h):

Data about quarterly hours comes from the following national statistical institutes: INE (Spain),

ONS (UK) and SCB (Sweden). German quarterly hours have been obtained from the ECB Statistical

Data Warehouse:

-Spain: http://www.ine.es/jaxiT3/Tabla.htm?t=9377

-UK: http://www.ons.gov.uk/ons/taxonomy/search/index.html?nscl=Weekly+Hours&nscl-

orig=Weekly+Hours&content-type=Dataset&content-

type=Reference+table&sortDirection=DESCENDING&sortBy=pubdate

-Germany:

http://sdw.ecb.europa.eu/quickview.do?SERIES_KEY=119.ESA.Q.DE.Y.1000.TOTEMP.0000.

TTTT.N.H.A&periodSortOrder=ASC

-Sweden:

http://www.statistikdatabasen.scb.se/pxweb/en/ssd/START__NR__NR0103__NR0103B/N

R0103ENS2010T11Kv/table/tableViewLayout1/?rxid=40de06a9-042c-4542-9d31-

255fcc5d877b