Download PRODUCTIVITY IN SERVICES: FINLAND IN AN INTERNATIONAL

Growth and Productivity in the Finnish Trade
Industry, 1975-2003: A National Comparative
Perspective
Working paper nr. 2
Jukka Jalava
EU KLEMS WORKING
PAPER SERIES
Growth and Productivity in the Finnish Trade
Industry, 1975-2003: A National Comparative
Perspective
Working paper nr. 2
Jukka Jalava
EU KLEMS Project
Productivity in the European Union: A Comparative
Industry Approach
January 2005
This project is funded by the European Commission,
Research Directorate General as part of the 6th Framework
Programme, Priority 8, "Policy Support and Anticipating
Scientific and Technological Needs".
Growth and Productivity in the Finnish Trade Industry, 1975-2003: A
National Comparative Perspective*
Jukka Jalava**
Abstract:
We analyse the growth and productivity in trade in comparison with the rest of the Finnish economy.
Economic growth shifted into a faster gear in the post-1995 era compared to earlier periods. Aggregate labour productivity change slowed down due to lacking contributions from capital deepening but
aggregate multi-factor productivity growth stayed level. For the trade industries the post-recession
period looked good. Trade joined the growth clubs in value added, labour productivity and multifactor productivity. Unit labour cost growth was moderate and profits were high. However, vis-à-vis
the level of labour productivity only wholesale trade was above the national average. Overall, the
post-1995 productivity change was more concentrated than before as fewer industries than previously
contributed to aggregate productivity growth.
Key words: growth, productivity, trade
*
Financial support from Kesko is gratefully acknowledged. The opinions expressed are those of the author and
do not necessarily represent the views of Statistics Finland. I thank Matti Pohjola and seminar participants in
Jyväskylä for helpful comments without implicating them for any remaining errors.
**
Economic Statistics, Statistics Finland, BOX 6C, FIN-00022 Statistics Finland, Finland. E-mail:
[email protected]
1. Introduction
What is a service? The casual answer to this question is that a service is something that is not a good
(which is perceived as tangible), i.e. a service is something intangible. This is a misconception. In fact
goods can be both tangible and intangible. Intangible goods are the results of creative and innovative
endeavors, such as literary, scientific, and educational writings, musical compositions, computer
software etc. (Hill, 1999). We find that Hill (1977) comprehensively defines what a service is:
‘A service may be defined as a change in the condition of a person, or of a good belonging to some economic unit, which is brought about as the result of the activity of some
other economic unit, with the prior agreement of the former person or economic unit’.
Finland trails leading economies in the productivity of services. The labour productivity (LP) in
wholesale and retail trade was according to some calculations (van Ark and Timmer, 2001) only 56
per cent and in transport and communication 86 per cent of the US level in 1990. It is, however, unclear how much (and for what reasons) we presently are behind leading countries in services productivity. Are there barriers to adopting best practices due to a lack of competition or regulations? The
objective of this paper is to compare the productivity development in trade with that of the rest of the
economy. This topic is important since the share of services in production is ever increasing and the
so called Baumol’s disease predicts that overall productivity growth will slow down as resources shift
to service industries whose productivity growth is slower than that of e.g. manufacturing. In the U.S.
close to three quarters of GDP stems from total services, whereas the share of services in Finnish
GDP was almost two thirds in 2001 (OECD, 2003). The good news is that Mankinen, Rouvinen and
Ylä-Anttila (2002) found in an international comparison that - unlike in manufacturing – there is not
necessarily a negative correlation between the share of employment and productivity in services. The
detailed quantitative account of productivity in the Finnish trade sector is, however, still missing. A
gap that this paper tries to fill. We start by taking a broad look at the growth in trade and the rest of
the economy within the framework of national accounts. We also calculate the changes in and levels
of labour productivity. Then the impact of structural change on LP is determined and finally the
growth of multi-factor productivity (MFP) is estimated. With structural change is in this context
meant the shift of labour into industries with either a higher level of or higher growth rate of LP. In
manufacturing the impact of this creative destruction has been significant in Finland since the mid1980s (Maliranta, 2003). In the case of services it is unclear what the impact of creative destruction
has been. Perhaps it is still to happen? What are the reasons for the low productivity in Finnish services? The reasons cannot be connected to education or infrastructure, since these factors also affect
secondary production. Therefore the reason – or culprit – must be the level of efficiency and MFP. It
would seem that, for some reason or other Finnish service companies do not use the best possible
technology. Since this technology – at least in principle – is readily available, there must be some
practical obstacles preventing its adoption. It might simply be the case that companies do not have
incentives or compulsion to adopt best technology. Lack of competition might also be an explanation,
which could be due to the smallness of the market. Lately competition has become more intense as
Kappahl (in 1990), IKEA (in 1996), H&M (in 1997), Bauhaus (in 2000), Clas Ohlson (in 2002) and
Lidl (in 2002) among others have entered the Finnish market.
Productivity measurement requires the decomposition of production into value, quantity and price.
2
This is particularly difficult when studying productivity in services, since for instance average earnings indexes are being used in some industries as proxies for price changes of service output. The
development work on service statistics is ongoing both in international fora and in Statistics Finland.
The focus of the development work is on the methods used compiling producer price indexes for the
service sector1, on the classification of service products and on statistics on service production by
products. In this paper the main focus is in a national comparative perspective on the trade industry,
which is an interesting industry that is dependent on the production and import of tradeable goods on
one hand and the demand for these goods on the other hand. As wholesalers and retailers are service
providers the gross output of trade industries is the trade margin which is the difference between the
price paid and the price at which a good or service is sold. And not as in the usual case where the
gross output of an industry consists of the goods or services produced by its establishments and the
prices paid for goods or services are separately recorded as intermediate consumption. In this paper
the trade sector is divided into three sub-industries: industry ISIC 50 Sale, repair and maintenance of
motor vehicles; service stations, industry ISIC 51 Wholesale trade and commission trade and industry
ISIC 52 Retail trade; repair of household goods.
The outline of the paper is the following. In section 2 we briefly survey previous research. Sections 3
and 4 look at the growth and productivity in trade and the rest of the economy. Section 5 concludes.
1
In October 2004 Statistics Finland will start publishing producer price indexes for: hotelling services, legal
activities, accounting, bookkeeping and auditing activities, letting of business premises, renting and maintenance of textiles and technical testing and analysis.
3
2. Previous research
Baumol’s (1967) hypothesis of unbalanced growth is central in any discussion of productivity in services. According to Baumol productivity growth in the whole economy will slow down as resources
shift to service industries whose productivity growth is slower than that of e.g. manufacturing. Oulton
(2001), showed that this is only the case for those service industries that produce final goods, and not
for the industries producing intermediate goods. Another important hypothesis was Griliches’ (1992)
concern that when the difficult to measure industries share of the economy grows, it will lead to a
slowdown in aggregate productivity. In a recent paper Gordon (2002) states that the post-1972 slowdown in US productivity is not due to the increasing share of difficult to measure industries in the
economy, in addition Gordon is of the opinion that the step-up in US productivity in the late 1990s is
not connected to output measurement problems. The large share of services in US output is not necessarily a drag on aggregate growth as Baily and Lawrence (2001) show that industries using information and communication technology (ICT) have performed better than the private sector on average in
the US in 1995-99. In a similar vein van Ark (2001) noted in an analysis of ten industrialized countries, that the contribution to aggregate LP of service industries using ICT increased in all countries
(except Japan) from the early 1990s to 1995-99. Jalava and Pohjola (2002) observed that ICTproducing industries contributed one third of Finnish market sector output growth in 1995-99 and
Jalava (2003) pointed out that the level of labour productivity declined from 1975 to 2001 in those
Finnish industries that neither produced nor used ICT. What is new in international productivity comparisons of service branches is represented by Baily and Zitzewitz (2001), who report of the
McKinsey Global Institutes projects (e.g. McKinsey, 1992) which quite innovatively strive to determine the international levels of productivity in service industries. For instance in retailing Baily and
Zitzewitz calculated productivity by weighing the absolute productivity of different retailing formats
(mass merchandising, out-of-town specialized chains, in-town specialized chains, department stores,
mail order and traditional stores) with their share of employment. This takes into account the fact that
the trend in retailing is that specialized chains come up with innovations that discounters copy and
offer at lower prices to consumers.
The classic account of growth and productivity in the Finnish trade industry is Forssell (1979).
Forssell’s work was part of the historical national accounting effort that was carried out under the
auspices of the Bank of Finland’s Growth Studies Committee. Forssell (1979) was the tenth monograph in a series that started in 1966 with a study on Finnish agricultural production and ended in
1988 with monograph number thirteen that presented a consistent historical national accounting view
on Finnish economic growth and structural change from 1860 onwards (Hjerppe, 1988). Forssell estimated the volume of value added in 1860-1900 based on the number of persons engaged in trade.
The series from 1900-1960 are more complete and contain data on employment, average wages and
salaries, volume of sales, price of sales and labour productivity in trade. Forssell was not content with
simply presenting the results of the arduous compilation of the historical series. He also used regression analysis to model developments in trade sector value added. Explanatory variables were average
population, share of urban population in total population and real GDP per capita.
A more recent look at Finnish service sector productivity is Mankinen, Rouvinen and Ylä-Anttila
(2002). They used growth accounting tools to analyze how services have performed in a national perspective. The good news is that they found a positive correlation between the level of productivity and
4
the employment share in services, quite contrary to manufacturing. Thus a post-industrial country
need not necessarily face lower productivity growth. For both wholesale trade and retail trade Mankinen, Rouvinen and Ylä-Anttila (2002) reported a step-up in both volume of value added and multifactor productivity in 1995-2000 compared to the 1975-95 period.
5
3. Growth…
The importance of services to Finnish GDP increased rapidly in the latter part of the 19th century as
trade was liberalized, railways were built and Finland was electrified. For commerce the important
milestones were the permission to open up stores in the countryside in 1859, the reduced regulation of
trading licenses in 1868 and the full freedom of trade in 1879 (Forssell, 1979). Hence the share of
trade in GDP increased from a meager 3 per cent in 1860 to almost 7 per cent in 1900 and 10 per cent
in 1950, a level which has remained constant for half a century. Characteristic to the Finnish long run
economic transformation was that industrialization started late and that services increased directly at
the expense of primary production, as the share of secondary production in GDP did not decrease until
the 1970s (figure 1). This is in contrast with the classical view of historical development in many
developed countries where the main contributor to economic growth first shifts from primary production to secondary production during the process of industrialization, and subsequently from secondary
production to tertiary production as the post-industrial stage is entered.2
Figure 1 Value added as a share of GDP, 1860-2003*
100 %
80 %
TERTIARY
PRODUCTION
60 %
SECONDARY
PRODUCTION
40 %
PRIMARY
PRODUCTION
20 %
1992
1980
1968
1956
1944
1932
1920
1908
1896
1884
1872
1860
0%
*=Preliminary estimate.
Sources: Hjerppe (1988); Statistics Finland.
3.1 From gross output to value added
In this paper the trade industry is broken down into three sub-industries. Industry ISIC 50 Sale, repair
and maintenance of motor vehicles; service stations contains all wholesale, brokerage and retail sale
of new and used motor vehicles and retail sales of fuel and lubricants as well as the maintenance and
repair of motor vehicles and the installation, repair and studding of tires other than during manufacture. Industry ISIC 51 Wholesale trade and commission trade consists of the resale of new and used
goods to retailers and other wholesalers and allows the industry both to acquire ownership of the
goods, which is wholesaling, or not, which is commission trade. Industry ISIC 52 Retail trade; repair
of household goods consists of the sale to consumers for personal and household use of new and second-hand goods as well as the repair as a principal activity of footwear, household electrical appli2
This view has been challenged by Broadberry (1998) who argues that Germany and the United States surpassed Britain’s level of aggregate labour productivity by shifting resources out of agriculture and improving
the productivity of services rather than manufacturing.
6
ances, watches, clocks, jewelry, etc. The gross output of trade industries is the trade margin which is
the difference between the price paid and the price at which a good or service is sold. The ideology is
that wholesalers and retailers are thought of as service providers (SNA93, para. 6.110). The goods
purchased for resale are not treated as intermediate consumption but are directly deducted from the
gross output. Included in intermediate consumption is external services, leasing and other rents as
well as other fixed or variable expenses. The output and intermediate consumption of trade in Finnish
national accounts is calculated by combining data from the business register3 and the structural business statistics4. The structure of estimates is obtained from structural business statistics (e.g. the percentage of output in turnover) and the levels are obtained from the business register (turnover and
wage and salary levels) with the establishment as the unit.
The statistical unit in structural business statistics is the enterprise as the statistical unit used by national accounts is the establishment. An establishment is a production unit belonging to an individual
non-financial corporation or quasi-corporation, situated in a single place and mainly producing one
type of good or service. Thus an enterprise with many establishments can have its economic activity
recorded in various industries depending on the main activity of each establishment. Establishments
are sometimes called local kind of activity units.
In order to ascertain changes in the structure of gross output in trade we look at the input coefficients
from the most recent input-output studies.5 The input coefficients are from the part of the symmetric
industry by industry input-output tables that record the direct inputs from other industries required to
produce one unit of gross output in each industry. To save space and to clarify the analysis we only
show the columns for trade in table 1. Thus e.g. for the gross output of 20,778 million Euros in trading
142 million Euros worth of outputs from hotels & restaurants were needed as inputs in 2000. This
means that the input coefficient is 0.7 per cent (=142/20,778). From 1980 to 1989 the share of intermediate consumption in the trade sector gross output decreased from 40 to 33 per cent. The decline
stemmed from the use of domestic products as all domestic sectors’, except the financial sector’s and
real estate & business services’, relative shares decreased. The step-up in the share of value added
went to the compensation of employees (from 45 to 50 per cent) and consumption of fixed capital
(from 5 to 8 per cent) as the net operating surplus actually shrank to 8 per cent (having been 11 per
cent). In 1989 the use of domestic products constituted 30 per cent of gross output. Real estate &
business services supplied 11 percentage points of the domestic inputs, transport & communications
10 percentage points, total manufacturing 3 percentage points and the financial sector and trade itself
2 percentage points, respectively. The share of imports was only 3 per cent. In 2000 the share of the
use of domestic products in the trade sector’s gross output was 36 per cent. Total manufacturing contributed 10 percentage points of it as did transport & communication. Trade and real estate & business
3
The business register covers all enterprises, self-employed persons and non-profit corporations in the capacity
of employers, recorded in the Value Added Tax Payment Register or the PAYE Register (pay-as-youearn/Employee’s Advance Tax Declaration Register).
4
The structural business statistics contains combined enterprise data from the business register, the business tax
register and direct survey data.
5
They are for the statistical years 1980, 1982, 1985, 1989, 1992, 1993, 1995, and 2000. As these studies were
made 1 to 21 years ago the earlier ones do not exactly match the current national accounting data due to changes
in the international national accounting standard. E.g. the earlier years’ shares of value added in gross output
shown in table 3 are not exactly the same as those calculated using the most recent data in table 2.
7
services supplied inputs worth 6 percent of gross output, respectively. As also imports increased to 8
per cent the share of intermediate consumption was 45 per cent which is the highest observation
throughout our observation period. The high share of intermediate consumption naturally implies a
low share of value added. However, as especially the share of compensation of employees but also
consumption of fixed capital actually declined (to 33 per cent and 6 per cent) the net operating surplus
was a record 15 per cent of output.
In addition to the direct input requirements as portrayed by the input coefficients there are also indirect impacts. The indirect impacts stem from the fact that in addition to the primary inputs required to
produce the gross output secondary inputs are required to produce the primary inputs, tertiary inputs
to produce the secondary ones and so on ad infinitum. The Leontief inverse matrix L takes into account all these direct and indirect effects. It is calculated by subtracting from the identity matrix I the
input coefficient matrix IC and taking the inverse of the thus calculated matrix (see the Appendix for a
clarifying example and Statistics Finland, 2003, for the exact definition):
(1)
L = (I-IC)-1.
Table 1 also contains the column for trade from the Leontief inverse matrix. The column total shows
the total domestic inputs needed to produce one unit of output. As the columns in the inverse matrix
show the multiplier effects backwards they are often used for analytical purposes. The rows would
have shown also the downstream impacts but rows have been omitted for the economy of exposition.
In 1980 were 1.562 units of inputs needed to produce one unit of trade output. In 1989 only 1.447
inputs were needed per trading output. Now it only took 0.1 units of manufacturing goods to produce
one unit of trade goods compared to 0.2 in 1980. In 2000 more inputs (1.571) were needed per output.
It took 0.01 unit of primary production, 0.183 units of total manufacturing, 0.011 units of construction, 1.086 units of trade, 0.011 units of hotels & restaurants, 0.131 units of transport & communications, 0.015 units of financial sector inputs, 0.088 real estate & business services inputs and 0.036
other services inputs to produce one unit of trade output. Alternatively we could think that if trade
output was to increase by one unit these would be the impacts on the industries supplying inputs for
trade.
8
Table 1 Input coefficients and inverse matrixes for trade in selected years, %
Source: Own calculations, data from Statistics Finland (1983, 1985, 1988, 1992, 1996, and 2003).
Table 2 Value added by industry as a share of gross output, %-share
*=Preliminary estimate.
Source: Own calculations, data from Statistics Finland.
9
The aggregate share of value added in gross output increased from 1975 to 1990, as agriculture, total
manufacturing, trade, and transport & communication managed to extract more value added per unit
of gross output (table 2). During the 1990s an increasing share of the economic activity was outsourced either to other domestic producers or substituted with imports. This was the case also in the
trade industries where the share of intermediate consumption in gross output increased by 3 to 6 per
cent when comparing 2003 with 1975.
In 1975 Finland’s gross domestic product (GDP) at basic prices, or the sum of all industries’ value
added, was 16.1 billion Euros (Table 3). Half of the value of GDP was still generated in primary and
secondary production. The value of the goods and services generated in the whole economy increased
by a factor of 7.7 from 1975 as GDP was 123.3 billion Euro in 2003. By 2003 the combined share of
primary and secondary production dwindled to one third with especially agriculture and construction
but also total manufacturing losing ground. Among the service industries real estate & business activities significantly increased its share from more than 10 per cent in 1975 to 19 per cent in 2003. Other
big gainers were the transport & communication industry and health & social work. All service industries increased their share of the economy with the exception of the trade industry and hotels & restaurants. Within trade wholesale trade and the sale of motor vehicles (including service stations) held
their ground but retail trade decreased by more than a percentage point. FISIM, or financial intermediation services indirectly measured, is shown separately as it has not been allocated by industry as
yet.6 Nominal value added in service industries grew the fastest. That is, in all service industries except the sale of motor vehicles, retail trade and hotels and restaurants. Trade matched the national
growth of current price value added until 1989-90. The recession was especially severe in the sale of
motor vehicles and wholesale trade. Wholesale and retail trade regained their 1990 levels in 1996 as
did the sale of motor vehicles the following year. However, of the trade industries only wholesale
trade could reclaim its position relative to the national average. That happened as late as 2002.
The growth in nominal gross value added can be decomposed into price7 and volume components
(table 4). Thus, e.g. the growth of 5.4 p.p.a. in nominal value added in the trade industry in 1995-2003
can be decomposed into a price component of 1.0 p.p.a. and a volume component of 4.4 p.p.a. as
shown in table 6 (due to rounding and averages the components do not always exactly sum to the
totals). The implication of a slower price growth is that given a nominal growth rate the slower the
price growth is the higher the growth of real value added will be. In 2003 the quantity of GDP is twice
the size it was in 1975. In the 1975-1990 period seven industries managed to match or surpass the
average growth rate, wholesale trade was one of them, but in 1995-2003 only six as health & social
and other services work fell behind. Retail trade managed to join the rapidly growing industries.
6
FISIM is services provided by financial intermediaries to their customers that they only indirectly are charged
for by receiving a lower interest on deposits than the interest rate charged for loans. The Commission (Regulation no. 1889/2002) stipulated that FISIM shall be allocated by industry starting from the statistical year 1995.
When this allocation is performed the value added of the industries will change depending on which institutional
sector is the user of the FISIM. For companies FISIM is intermediate consumption, for households and government FISIM is final consumption and for non-residents it is exports.
7
As the prices used in national accounts ideally are indicators of pure price changes the quality improvements
are reflected in the volume growth.
10
The price index of GDP grew during the observation period at an annual average rate of 4.7 per cent8
which means that prices were 3.7 times higher in 2003 than they were in 1975. Of the service industries only the prices in sale of motor vehicles, retail trade and the financial sector grew slower than the
national mean. The GDP inflation rate slowed down in the 1990s as the average growth of the price of
GDP slowed down from 7.2 per cent per annum (p.p.a.) in 1975-90 to 2.4 p.p.a. in 1990-95 and to 1.4
p.p.a. in 1995-2003. The prices in trade grew at an average rate in 1975-90, above average in 1990-95
(3.8 p.p.a. due to the 5.7 p.p.a. growth in wholesale trade) and below average in 1995-2003 (1.0 p.p.a.,
with retail trade showing price decreases of 0.1 p.p.a.). Price growth was only in primary and secondary production and the financial sector slower post-1995 than in retail trade.
8
In this paper the growth rates are expressed logarithmically. Thus growth is defined as: 100*[ln(xt )/ln(xt-1 )].
11
Table 3 Value added by industry as a share of GDP, %-share and value in million Euro
*=Preliminary estimate.
Source: Own calculations, data from Statistics Finland.
12
Table 4 Average growth of value, quantity and price of value added by industry, 2000=100, ln-%
Value
A Agriculture, forestry & hunt.
B Fishing
CDE Total manufacturing
F Construction
G Trade
Sale of motor veh.; serv. stat.
Wholesale trade
Retail trade
H Hotels & restaurants
I Transport, storage & comm.
J Financial interm. & insurance
K Real estate & business act.
L Admin., comp. soc. serv.
M Education
N Health & social work
O Other comm., soc. & pers. s.
P Household service activities
FISIM
Quantity
Price
1975-1990
1990-1995
1995-2003*
1975-1990
1990-1995
1995-2003*
19751990
1990-1995
1995-2003*
7.4
6.7
9.4
9.2
10.1
10.7
10.4
9.5
11.4
11.3
13.6
11.6
11.5
11.1
13.3
13.1
7.9
13.2
-5.2
2.5
4.1
-10.6
-0.6
-3.0
-0.2
-0.1
-1.7
3.0
-1.7
5.9
1.9
2.7
2.4
1.7
8.9
-2.9
1.3
-3.3
3.4
6.9
5.4
6.0
6.3
3.8
4.7
6.3
2.0
7.2
4.1
4.4
4.8
4.6
11.4
1.5
0.4
1.8
3.7
1.5
3.0
2.6
3.5
2.3
2.7
3.4
5.7
4.2
2.4
2.1
4.0
4.0
-5.3
5.7
-0.6
6.5
2.2
-9.9
-4.4
-2.9
-5.9
-2.2
-2.1
1.6
-7.0
2.1
-0.8
0.2
-1.6
-1.0
9.4
-3.8
2.0
-1.4
4.6
2.9
4.4
5.1
4.5
3.8
2.8
4.9
4.2
4.0
1.1
1.8
2.0
2.5
10.1
6.4
7.0
4.9
5.7
7.7
7.2
8.1
7.0
7.3
8.8
7.9
7.9
7.5
9.0
9.0
9.3
9.1
13.2
7.5
-4.6
-3.9
1.9
-0.7
3.8
0.0
5.7
2.1
0.3
1.3
5.3
3.9
2.7
2.6
4.0
2.7
-0.5
0.9
-0.7
-1.9
-1.2
4.0
1.0
0.9
1.8
-0.1
1.9
1.5
-2.2
3.2
3.0
2.5
2.8
2.0
1.4
-4.9
1.7
4.9
3.1
-0.7
3.6
7.2
2.4
1.4
GDP at bp
10.4
*=Preliminary estimate.
Source: Own calculations, data from Statistics Finland.
13
3.2 Hours worked and employment
The hours worked in the Finnish economy have declined from 4.4 billion hours in 1975 to 4.1 billion
in 2003 (table 5). During the early 1990s economic recession the labour input went as low as 3.6 billion hours in 1993-4. As was the case with value added also the labour input of primary and secondary
production declined the most while nearly all service industries increased their hours worked. In 1975
more than half of the hours worked of the whole economy were in primary and secondary production
but in 2003 only one third. Agriculture suffered the biggest loss with the share of hours worked declining by 12 percentage points to 7.0 per cent. Total manufacturing lost 6 percentage points ending at
18.4 per cent. Other industries whose shares declined were construction (from 10.3 to 8.1 per cent),
trade (from 13.7 to 12.8 per cent, due to decreases in retail trade), financial intermediation & insurance (from 1.9 per cent to 1.5 per cent) and fishing (from 0.7 to 0.4 per cent). The largest gainers were
health & social work and real estate & business activities that ended up at 12.9 and 9.9 per cent of the
hours worked in 2003, respectively.
A good measure of the effectiveness of labour input in a time-series perspective is how many worked
hours are required per one million Euro at constant year 2000 prices. As expected the labour input
required in primary production to generate one million Euro of value added was markedly higher than
in either secondary or tertiary production (table 6). The most effective industry in 1975 was the real
estate & business services industry that needed only 19,500 hours per unit of value added. The second
and third most effective industries were the education and the financial intermediation & insurance
industries that needed 39,000 and 43,300 hours to achieve the same feat. In 1975 the trade industry
was more effective with 84,800 hours worked per unit of value added than the 89,400 hours required
in total manufacturing but less effective than construction (67,100 hours). Wholesale trade was the
most effective trade industry (50,900 hours) followed by the sale of motor vehicles (84,600 hours) and
retail trade (143,000 hours). In 2003 the hours worked required for one million of value added at the
level of the whole economy were 34,200. Primary production, hotels & restaurants and household
service activities still failed to reach the national average. A new feature was that administration and
personal services (industries L through O) and construction and trade failed to do so too. The trade
industry was not far off the mark (41,000 hours) with wholesale trade reaching 26,400 hours. The
most effective industries were financial intermediation & insurance (14,000 hours), real estate &
business activities (19,200 hours), total manufacturing (22,200 hours) and transport & communication
(24,400 hours).
14
Table 5 Hours worked by industry as a share of total, %-share and quantity in 100,000h
*=Preliminary estimate.
Source: Own calculations, data from Statistics Finland.
Table 6 Hours worked per one million Euro of value added at 2000 prices
*=Preliminary estimate.
Source: Own calculations, data from Statistics Finland.
15
Total employment, the aggregate number of employees and self-employed, has fluctuated during our
observation period between 2 and 2.5 million persons (table 7), when the population of Finland has
increased from 4.7 million persons to 5.2 million persons. In 1975 employment was 2.3 million and
the unemployment rate was at a record low level: 2.6 per cent. Employment increased steadily – with
the exception of a temporary hiccup at the end of the 1970s – reaching the 2.5 million mark at the
close of the 1980s, when unemployment went close to 3 per cent. As a result of the early 1990s recession the amount of employees and self-employed dwindled to 2.0 million by 1994 and unemployment
soared to 16.6 per cent. The post-1995 economic boom increased employment which rebounded to 2.4
million in 2003, but the unemployment rate only decreased to 9.0 per cent. Primary and secondary
productions were big losers in employment. Agriculture’s share declined from 14.9 per cent in 1975
to 5.1 per cent in 2003, total manufacturing’s share from 26.2 to 19.6 per cent and construction’s
share from 9.3 to 6.5 per cent. Of the service industries trade lost almost one percentage point (due to
a reduction in retail trade) ending up at 12.8 per cent and financial intermediation & insurance shed
half a percentage point. All other service industries increased their relative shares. More than 6 percentage points gains were experienced in real estate & business activities and health & social work.
When looking at employees and self-employed separately the main difference with the development
in total employment is that the self-employed failed to regain their pre-recession level in absolute
terms as there were 430,000 self-employed in 1975 and 280,000 in 2003 (tables 8 and 9). Another
difference in self-employment, when contrasting with total employment and the case of the employees, is that it did not peak prior to the 1990s recession. In self-employment the main story is one of a
massive decline in agricultural self-employment while all other industries except fishing and the three
that do not have self-employment (financial intermediation & insurance, administration and household service activities) have increased their relative shares. The trade industry increased its share by
three percentage points to 10.2 per cent of all self-employed in 2003. The share of services in selfemployment is likely to keep increasing as Rouvinen and Ylä-Anttila (2004) found that in 2003 three
quarters of starting entrepreneurs were in services.
In 1975 there were 1.9 million employees. The number of employees peaked in 1989-90 at 2.1-2.2
million and was at its lowest in 1994 at 1.7 million. By 2003 the amount of employees rose back to
2.1 million persons. Total manufacturing’s share of the number of employees declined during our
observation period by 10 percentage points to 21.2 per cent in 2003. Other losers were construction,
trade (that ended up at 13.1 per cent with a decline of nearly two percentage points mostly due to retail trade but also wholesale trade), agriculture and the financial sector. The share of employees stayed
close to level in hotels & restaurants, transport & communication and household service activities.
The largest gainers were health & social work, real estate & business activities and education.
16
Table 7 Employees and self-employed by industry, %-share and amount in 100 persons
*=Preliminary estimate.
Source: Own calculations, data from Statistics Finland.
Table 8 Self-employed by industry, %-share and amount in 100 persons
*=Preliminary estimate.
Source: Own calculations, data from Statistics Finland.
17
Table 9 Employees by industry, %-share and amount in 100 persons
*=Preliminary estimate.
Source: Own calculations, data from Statistics Finland.
Table 10a Hours worked per employee and self-employed
*=Preliminary estimate.
Source: Own calculations, data from Statistics Finland.
18
Table 10b Hours worked per self-employed
*=Preliminary estimate.
Source: Own calculations, data from Statistics Finland.
Table 10c Hours worked per employee
*=Preliminary estimate.
Source: Own calculations, data from Statistics Finland.
19
The average amount of work done by employees and self-employed decreased from 1,900 to 1,700
hours per year during our observation period (table 10a). The longest annual hours were performed in
primary production and the shortest working time was in education: 1,400 hours per year in 2003.
Below average hours were worked also in health & social work, other community, social & personal
services and household services with 1,500 hours per year, respectively, and financial intermediation
& insurance and total manufacturing with 1,600 hours in 2003. The working time was average in
trade and real estate & business activities, administration, and more than average in construction, hotels & restaurants, transport & communications, and primary production. Self-employed persons
worked more than employees: 2,400 hours per year (table 10b). Entrepreneurs in trade managed to cut
their hours from 2,600 per year in 1975 to 2,300 per year in 2003. The amount of work performed by
employees annually declined from 1,800 to 1,600 hours during our observation period (table 10c).
Longer than average hours were worked in primary production, construction, sale of motor vehicles,
wholesale trade, transport & communication and administration.
3.3 Wages, average earnings and consumption
Employees’ nominal average earnings from wages and salaries grew from 4,400 Euro per year to
27,100 Euro per year, or 6.2 times, from 1975 to 2003 (table 11). During the same time the cost of
living index (1951=100) grew from 418 points in December 1975 to 1577 points in December 2003 or
by a factor of 3.8 meaning that real wages were 2.4 times higher at the end of our observation period
than at the beginning. The increased purchasing power of households resulted in a 7.7 fold increase in
the consumption expenditure of households in Finland from 1975 to 2003 (table 12). Households’
propensity to save declined as the savings ratio (savings per disposable income) changed from a prerecession arithmetic average of 3.2 per cent to a post-recession average of 0.8 per cent. The debt ratio
(disposable income per stock of credit) of households was 37.9 per cent in 1975 but as much as 74.6
per cent in 2003. The structure of consumption also changed as durable goods, semi-durable goods
and especially non-durable goods lost ground to services. The shares of more traditional consumption
groups such as food and beverages, alcohol and tobacco, clothing, furnishings and transport declined,
whereas housing, health, communications, recreation & culture, education and miscellaneous goods
and services increased their shares. In the 1990s housing expenditures increased to a full quarter of the
total.
In 1975 the average wage in the trade industry was 4,000 Euro per year (2,700 in retail trade, 3,700 in
sale of motor vehicles and 6,000 in wholesale trade) which was 90.9 (=4,000/4,400) per cent of the
national average. In 2003 the average wage in the trade industry was 24,000 Euro which was 88.9 per
cent of the national average. The highest annual wages and salaries were in financial intermediation &
insurance (36,500 Euro), wholesale trade (33,500 Euro), real estate & business services (31,300 Euro)
and total manufacturing (31,200 Euro). Eye-ball econometrics tells us that in 1975 the average earnings were average or more than average in eight of the shown industries, but in seven industries in
1990 and in 2003. To ascertain whether the relative variation of wages around the mean has increased
or decreased we calculated the coefficient of variation (CV) in these years. The coefficient of variation
was obtained by dividing the standard deviation s (which is equal to the square root of the arithmetic
mean of the squared deviations from the mean) with the mean X (see Feinstein and Thomas, 2002).
(2)
CV = s / X , where
20
(3)
s=
∑ (X
− X)
2
i
n
.
Using the data in table 13 (excluding sale of motor vehicles, wholesale trade and retail trade as they
are included in the aggregate trade industry) we found that the standard deviations in 1975, 1990 and
2003 were 1.0, 3.9 and 6.1 respectively. When dividing these standard deviations with the years’
means 4.4, 18.2 and 26.1 the coefficients of variation were 0.227, 0.214 and 0.223 which show a decrease in the relative variation of wages in 1990 compared with 1975 and an increase from 1990 to
2003.
Table 4 showed the interdependence between the value, price and quantity of value added. A similar
relationship exists between the average growth of wages and salaries, employees and average earnings
by industry as can be seen in table 13. For instance, the growth in the wages and salaries of wholesale
trade in the period from 1995 to 2003 was 5.9 p.p.a. (faster than the average 5.3 p.p.a. for the whole
economy). As the number of employees in wholesale trade increased during the same time by 3.2
p.p.a. therefore average earnings rose by 2.7 p.p.a. At the level of the whole economy the number of
employees increased moderately in 1975-90 (by 0.9 p.p.a.) and wages and earnings rapidly (10.3
p.p.a. and 9.4 p.p.a. respectively). During the early 1990s the wage sum decreased (-1.1 p.p.a.), however, as the number of employees diminished even more (-3.8 p.p.a.) average earnings increased at a
pace of 2.8 p.p.a. After 1995 earnings grew at a rate of 3.3 p.p.a. as employees increased by 2.0 and
the aggregate wage sum by 5.3 p.p.a. The only two industries that have consistently managed to maintain a faster-than-average growth in average earnings is total manufacturing and financial intermediation & insurance. Total manufacturing did the trick by having a slower than average growth in the
number of employees in 1975-90 and 1995-2003 and a higher than average growth in the wage sum
during the recession. In financial intermediation the wage sum rose faster than average in 1975-90
and the sectors’ employees decreased in 1990-2003. In retail trade earnings grew at a faster rate than
the national average in 1975-95, due to lower than average growth in the number of employees, and
after 1995 the growth was slower than the national average (2.9 p.p.a.). The 1990s recession was the
only time that wholesale trade could reach an average growth rate in earnings; whereas the sale of
motor vehicles did it from 1975-1995. Only during the post-1995 era was it slightly lagging behind
the nation’s average.
21
Table 11 Average earnings (wages and salaries) per employee, Euro
*=Preliminary estimate.
Source: Own calculations, data from Statistics Finland.
Table 12 Household consumption by purpose and durability, %-share and value in million Euro
*=Preliminary estimate.
Source: Own calculations, data from Statistics Finland.
22
Table 13 Average growth of wages and salaries, employees and average earnings by industry, ln-%
Wages and salaries
1975-1990
Employees
1990-1995
1995-2003*
1975-1990
1990-1995
Average earnings
1995-2003*
1975-1990
1990-1995
1995-2003*
A Agriculture, forestry & hunt.
6.9
-5.4
2.2
-1.1
-5.4
-1.3
8.0
0.1
3.5
B Fishing
10.7
15.8
0.0
3.4
6.7
-4.2
7.3
9.0
4.2
CDE Total manufacturing
8.7
0.4
4.4
-1.0
-4.0
0.6
9.7
4.4
3.8
F Construction
8.4
-11.1
7.2
-0.7
-12.5
3.5
9.1
1.4
3.7
G Trade
9.7
-2.7
5.8
0.3
-6.1
2.8
9.3
3.3
3.0
Sale of motor veh.; serv. stat.
11.4
-4.9
6.8
1.9
-7.7
3.7
9.5
2.8
3.1
Wholesale trade
8.8
-1.2
5.9
-0.2
-4.1
3.2
9.0
2.9
2.7
Retail trade
10.1
-3.8
5.1
0.3
-6.8
2.2
9.8
3.0
2.9
H Hotels & restaurants
10.9
-3.0
5.3
0.7
-5.7
2.5
10.1
2.7
2.8
I Transport, storage & comm.
10.0
-0.4
4.6
1.1
-3.5
1.0
8.9
3.2
3.7
J Financial interm. & insurance
11.8
-1.1
0.8
1.8
-6.3
-2.6
9.9
5.2
3.4
K Real estate & business act.
13.6
-0.6
10.1
4.5
-2.4
6.4
9.1
1.8
3.8
L Admin., comp. soc. serv.
11.1
0.5
4.4
1.8
-1.0
1.3
9.3
1.5
3.2
M Education
11.0
1.7
4.7
1.8
0.1
2.0
9.2
1.5
2.7
N Health & social work
13.4
1.4
5.0
4.5
-1.5
1.8
8.9
2.8
3.2
O Other comm., soc. & pers. s.
12.7
0.2
5.0
3.5
-1.5
2.7
9.1
1.8
2.3
P Household service activities
7.3
9.0
11.8
-4.9
8.7
8.5
12.2
0.3
3.3
10.3
-1.1
5.3
0.9
-3.8
2.0
9.4
2.8
3.3
FISIM
GDP at bp
*=Preliminary estimate.
Source: Own calculations, data from Statistics Finland.
23
4. … and Productivity
4.1 Labour productivity
Finnish economic growth switched into a faster gear as the earlier average growth rate of GDP at basic prices of 3.1 p.p.a. in 1975-90 changed to 3.6 p.p.a. in 1995-2003 (table 14). This more rapid
growth in aggregate value added was not matched by a corresponding step-up in the ratio of the volume of value added to hours worked, i.e. labour productivity (LP) growth. On the contrary, aggregate
LP increased by 3.0-3.1 p.p.a. 1975-95 and by 2.3 p.p.a. after the recession. Three industries managed
to keep the growth rate of value added higher than the mean throughout the observation period: total
manufacturing, transport & communication and real estate & business activities. In 1995-2003 they
were joined by the trade industries that all demonstrated robust growth. The sale of motor vehicles
even took the lead with 5.1 p.p.a. The 1990s were pro-cyclical for the trade industries as their value
added plummeted with the national average during the recession and picked-up with the post-1995
boom. The cyclicality has been more pronounced in trade than at the level of the aggregate economy,
which is understandable since trade is dependent both on the production and import of tradeable
goods and the demand for these goods. Also vis-à-vis hours worked the development in the trade industries was pro-cyclical in the 1990s. During the recession labour input in trade fell by 5.5 p.p.a. (3.7 p.p.a. in the whole economy) and increased in 1995-2003 by 1.9 p.p.a. (1.3 p.p.a. in the whole
economy). After 1995 retail trade increased its labour input only by 1.2 p.p.a., which resulted in the
strongest LP growth of all trade industries (2.6 p.p.a.). Alongside total manufacturing only primary
production kept its LP change above mean from 1975 to 2003. Manufacturing achieved this mainly by
strong value added growth and primary production by big cuts in labour input. LP in transport &
communication grew strongly in the 1990s and in the financial sector in 1975-90 and 1995-2003. The
trade industry’s LP grew at the same speed as the national average in 1975-1990 (3.1 p.p.a.), with
wholesale trade standing out to its advantage with 4.1 p.p.a. After the recession LP in trade grew at
the rate of 2.5 p.p.a. which is slower than prior to the recession but faster than the national mean.
Trade’s strong post-recession LP growth is thanks to retail trade’s 2.6 p.p.a. and the sale of motor
vehicles’ 2.4 p.p.a. Wholesaleing showed an increase in LP growth of 2.1 p.p.a.
In table 14 we observed the growth of LP. To see how the levels of labour productivity have evolved
we divide value added by hours worked. We use value added at current prices and normalize the total
economy to equal 100, which means that the overall improvement in LP from 1975 to 2003 is not
taken into account. We look at yearly cross-sections to ascertain the industries relative positions with
respect to the national average. In 1975 eight industries equaled or surpassed the nation’s average LP
level: total manufacturing, construction, wholesale trade, transport & communication, financial intermediation & insurance, real estate & business activities, education and other community, social and
personal services (table 15). By 1990 only one of these eight, construction, slipped below average.
But also the LP level of real estate & business activities, education and other community, social and
personal services worsened relative to the national mean. Of the eight original high productivity industries only five still maintained their stances as high productivity industries in 2003: total manufacturing, wholesale trade, transport & communication, financial intermediation & insurance and real
estate & business activities. Of these five the first four industries had in 2003 a level of LP that was
higher than it was in 1975 relative to the total economy. Of these four industries total manufacturing
and transport & communication both have a very dynamic ICT-producing sub-industry (radio, televi-
24
sion & communication equipment and telecommunications services) that performed double-digit LP
growth in 1995-2002 (Statistics Finland, 2004c). Wholesale trade and financial intermediation & insurance on the other hand are two major ICT-using industries (see van Ark, 2001; Jalava, 2003).
To find out what the effect of labour shifting to industries with either a higher level of or higher
growth rate of LP on LP growth is, we performed a shift-share analysis (see van Ark, 2001). The relative change in labour productivity can be expressed as:
n
LPt − LPt −1
=
LPt −1
∑ ( LP
i =1
i ,t
n
n
− LPi ,t −1 ) Si ,t −1 + ∑ ( Si ,t − Si ,t −1 ) LPi ,t −1 + ∑ ( Si ,t − Si ,t −1 )( LPi ,t − LPi ,t −1 )
i =1
i =1
LPt −1
(4)
where LP is the level of labour productivity, Si is industry i's share of all hours worked and t is time.
The first term on the right side of the equation is the industries' internal (within) productivity effect,
i.e., sub-industries impact on aggregate productivity change. The second term on the right is the static
shift effect of labour, that is, the contribution of a shift of labour to industries with a higher level of
LP. The third term on the right captures the dynamic shift effect of labour, i.e., the contribution of
labour shifting to industries with a higher than average LP growth rate. Thus the second and third
terms quantify the above mentioned Baumol’s effect.
The results of the shift-share analysis can be seen in table 16. The within effect was the most significant factor explaining labour productivity growth in the Finnish economy. The contribution of the
within effect increased in the 1990s compared with 1975-90. One quarter of LP growth was to be
attributed to labour shifting to industries with a higher productivity level prior to the recession but
only one fifth in the early 1990s and 13 per cent after 1995. The contribution of the dynamic shift was
negative the whole time, but increased from –0.9 via –1.6 to –2.6 per cent.
Table 17 reinforces the view of productivity growth being more concentrated after 1990 than before
the recession. When summing the three most influential industries (total manufacturing, real estate &
business activities and transport & communications) combined shares in within, dynamic and static
components in 1995-2003 the sum is 71.4 per cent. In contrast the three most influential industries
(total manufacturing, real estate & business activities and health & social work) in 1975-90 only
amounted to 54.1 per cent. Were we to add the fourth most important industry to LP growth in both
periods, trade, the sums would change to 84.3 per cent in the post-1995 period and 64.6 per cent prior
to 1990. So LP growth became very concentrated indeed. Trade’s share of the aggregate within component was 14.9 per cent in 1975-90 and 11.8 per cent in 1995-2003. Industries that significantly increased their share of the within component from pre-1990 to post-1995 were: total manufacturing
(from 45.4 to 52.8 per cent), transport & communication (from 9.1 to 18.7 per cent) and financial
intermediation & insurance (from 6.6 to 12.6 per cent).
25
Table 14 Average growth of value added, hours worked and labour productivity (output per hours worked) by industry, ln-%
Value added
1975-1990
1990-1995
Hours worked
1995-2003*
1975-1990
1990-1995
Labour productivity
1995-2003*
1975-1990
1990-1995
1995-2003*
A Agriculture, forestry & hunt.
0.4
-0.6
2.0
-3.5
-5.0
-4.0
3.9
4.4
5.9
B Fishing
1.8
6.5
-1.4
-1.4
-2.7
-4.6
3.2
9.1
3.3
CDE Total manufacturing
3.7
2.2
4.6
-1.3
-4.1
0.5
5.0
6.3
4.2
F Construction
1.5
-9.9
2.9
-0.1
-11.1
3.2
1.6
1.1
-0.2
G Trade
3.0
-4.4
4.4
-0.2
-5.5
1.9
3.1
1.1
2.5
Sale of motor veh.; serv. stat.
2.6
-2.9
5.1
1.2
-6.5
2.8
1.3
3.5
2.4
Wholesale trade
3.5
-5.9
4.5
-0.6
-3.5
2.4
4.1
-2.5
2.1
Retail trade
2.3
-2.2
3.8
-0.3
-6.4
1.2
2.6
4.3
2.6
H Hotels & restaurants
2.7
-2.1
2.8
1.1
-5.9
3.4
1.6
3.9
-0.6
I Transport, storage & comm.
3.4
1.6
4.9
0.7
-2.5
1.0
2.7
4.1
3.9
J Financial interm. & insurance
5.7
-7.0
4.2
1.8
-6.4
-2.9
3.9
-0.5
7.1
K Real estate & business act.
4.2
2.1
4.0
4.3
0.0
4.8
-0.1
2.0
-0.9
L Admin., comp. soc. serv.
2.4
-0.8
1.1
1.3
-0.7
1.1
1.2
-0.1
0.0
M Education
2.1
0.2
1.8
2.3
1.3
0.8
-0.2
-1.1
1.0
N Health & social work
4.0
-1.6
2.0
3.2
-1.3
2.4
0.8
-0.3
-0.4
O Other comm., soc. & pers. s.
4.0
-1.0
2.5
3.0
-1.0
2.9
1.0
0.0
-0.4
P Household service activities
-5.3
9.4
10.1
-5.1
8.8
8.6
-0.2
0.6
1.5
3.1
-0.7
3.6
0.0
-3.7
1.3
3.1
3.0
2.3
FISIM
GDP at bp
*=Preliminary estimate.
Source: Own calculations, data from Statistics Finland.
26
Table 15 Levels of labour productivity (current price value added per hours worked), total economy=100
1975 1980
1985
1990
1995
2000
2003*
A Agriculture, forestry & hunt.
52
54
49
56
42
41
48
B Fishing
32
28
26
22
22
20
19
CDE Total manufacturing
123
129
129
128
147
147
140
F Construction
100
83
80
85
66
68
67
G Trade
87
89
90
86
83
80
83
Sale of motor veh.; serv. stat.
91
91
86
79
72
65
70
Wholesale trade
126
133
144
139
125
126
127
Retail trade
61
62
59
56
59
51
54
H Hotels & restaurants
60
59
63
60
56
43
46
I Transport, storage & comm.
120
129
128
123
123
138
142
J Financial interm. & insurance
159
171
156
197
190
244
210
K Real estate & business act.
322
264
243
203
208
190
188
L Admin., comp. soc. serv.
86
79
83
84
73
69
69
M Education
143
121
122
113
92
89
92
N Health & social work
83
76
82
80
73
66
66
O Oth. comm., soc. & pers. s.
118
116
112
114
99
87
85
P Household service activities
32
40
45
48
36
29
34
100
100
100
100
100
100
100
FISIM
GDP at bp
*=Preliminary estimate.
Source: Own calculations, data from Statistics Finland.
27
Table 16 The impact of structural change on labour productivity growth, %
1975-1990
1990-1995
19952003*
Within
73.6
82.9
89.8
Static
27.3
18.8
12.8
Dynamic
-0.9
-1.6
-2.6
100.0
100.0
100.0
Total
*=Preliminary estimate.
28
Table 17 Shares of aggregate within component by industry and sum of within, static and dynamic components by industry, %
Within
Sum of within, static and dynamic shares
1975-1990
1990-1995
1995-2003*
1975-1990
1990-1995
1995-2003*
A Agriculture, forestry & hunt.
10.1
7.6
10.8
1.4
4.4
1.1
B Fishing
0.2
0.4
0.2
0.1
0.4
-0.1
CDE Total manufacturing
45.4
58.1
52.8
24.7
46.3
37.2
F Construction
6.5
5.1
-0.7
4.0
-14.9
4.2
G Trade
14.9
3.3
11.8
10.5
-3.5
12.9
H Hotels & restaurants
1.0
2.3
-0.4
1.3
0.8
0.9
I Transport, storage & comm.
9.1
15.1
18.7
8.5
16.5
15.4
J Financial interm. & insurance
6.6
-1.1
12.6
7.0
-4.7
4.5
K Real estate & business act.
-1.0
12.9
-6.6
17.9
31.0
18.8
L Admin., comp. soc. serv.
3.2
-0.2
0.2
4.9
6.0
-0.5
M Education
-0.5
-2.4
2.5
3.8
7.2
1.1
N Health & social work
3.1
-1.3
-1.4
11.5
6.8
2.3
O Other comm., soc. & pers. s.
1.5
0.0
-0.6
4.5
3.5
1.8
P Household service activities
0.0
0.0
0.1
-0.2
0.3
0.4
100.0
100.0
100.0
100.0
100.0
100.0
FISIM
TOTAL
May not sum to totals due to rounding.
*=Preliminary estimate.
Source: Own calculations, data from Statistics Finland.
29
4.2 Unit labor cost
The norm for maximum wage increases in the Finnish centralized wage bargaining system was during
the period we are analyzing aggregate LP growth corrected for inflation. However, the new postrecession state-of-play with fewer industries contributing more to aggregate LP than before is problematic for the old paradigm. How can low productivity industries afford the wage increases that high
productivity industries can? A useful way of looking at how a change in hourly compensation is financed is by decomposing it into the change in unit labour cost (ULC) and labour productivity. Thus
ULC equals hourly compensation less LP. Alternatively ULC can be calculated as the total compensation9 of employment divided by real value added, which means that ULC is total labour cost per unit
of output.
In the period 1975-90 the development in the trade industry was remarkably similar to that of the total
economy (table 18). Total compensation grew at an average rate of 10.2 per cent both in trade and
overall. The sale of motor vehicles increased its total compensation by 11.7 p.p.a., retail trade by 10.6
p.p.a. and wholesale trade by 9.4 p.p.a. Hours worked stayed level in the whole economy and diminished somewhat (-0.2 p.p.a.) in trade. The hourly compensation in trade was only growing a bit faster
than the national average (10.4 vs. 10.2 p.p.a.), with retail trade’s 10.9 p.p.a. and sale of motor vehicles’ 10.5 p.p.a. above average and wholesale trade at 10.1 p.p.a. Trade and the aggregate economy
both had a LP growth of 3.1 p.p.a. (the sale of motor vehicle’s LP grew only by 1.3 p.p.a., the corresponding figures for retail and wholesale trade were 2.6 and 4.1 p.p.a.). Trade’s real value added increased by 3.0 p.p.a. and the nation’s average by 3.1 p.p.a. Of the trade industries wholesale trade
demonstrated the strongest growth (3.5 p.p.a.) with the sale of motor vehicles and retailing performing
much worse (2.6 and 2.3 p.p.a., respectively). Therefore ULC in trade grew by 7.2 p.p.a. in comparison with 7.0 p.p.a. for the whole economy. In the trade industries wholesale trade showed the slowest
ULC growth (6.0 p.p.a.) as retail trade’s and the sale of motor vehicles’ ULC grew at rates of 8.3 and
9.2 p.p.a., respectively. The recession hit trade harder than the whole economy as its total compensation, hours worked and real value added all plummeted. The result was that ULC grew much faster in
trade than the national average. In terms of unit labour cost the previous best performer among the
trade industries, wholesale trade, did not manage to slow down its ULC growth during the recession.
After the recession ULC change in trade experienced a change for the better. Due to a strong 4.4 p.p.a.
growth in real value added in trade (3.6 p.p.a. in the whole economy) LP increased at a 2.5 p.p.a. pace
with 2.3 p.p.a. as the national mean. Trade’s ULC growth slowed down to only 0.8 p.p.a. which is
better than the 1.1 p.p.a. the whole economy performs. Trade’s low ULC growth stemmed from the
low 0.7 p.p.a. ULC change in retail trade. Motor vehicle sales and retailing were close to the national
mean. at 1.0 p.p.a., respectively. On the whole, ULC growth slowed down spectacularly both in the
whole economy and trade from what it was prior to the recession.
9
Wages, salaries and employers’ social contributions for employees plus the imputed wage share for the selfemployed. The imputation is performed by multiplying the hours worked by the self-employed with the employees’ average earnings per hour.
30
Table 18 Average growth of unit labour cost and related variables in trade, its sub-industries and the total economy,
ln-%
G Trade:
Total compensation
1975-
1990-
1995-
1990
1995
2003*
10.2
-2.6
5.2
50, 51, 52:
Total compensation
1975-1990
11.7, 9.4,
1990-1995
1995-2003*
-4.0, -1.2, -3.6
6.2, 5.5, 4.5
-6.5, -3.5, -6.4
2.8, 2.4, 1.2
2.5, 2.3, 2.8
3.4, 3.1, 3.3
10.6
Hours worked
-0.2
-5.5
1.9
Hours worked
1.2, -0.6, 0.3
Hourly compensation
10.4
2.9
3.3
Hourly compensation
10.5, 10.1,
10.9
Real value added
3.0
-4.4
4.4
Real value added
2.6, 3.5, 2.3
-2.9, -5.9, -2.2
5.1, 4.5, 3.8
Labour productivity
3.1
1.1
2.5
Labour productivity
1.3, 4.1, 2.6
3.5, -2.5, 4.3
2.4, 2.1, 2.6
Unit labour cost
7.2
1.8
0.8
Unit labour cost
9.2, 6.0, 8.3
-1.0, 4.7,-1.5
1.0, 1.0, 0.7
Total compensation
10.2
-0.6
4.7
Hours worked
0.0
-3.7
1.3
Hourly compensation
10.2
3.1
3.3
Real value added
3.1
-0.7
3.6
Labour productivity
3.1
3.0
2.3
Unit labour cost
7.0
0.0
1.1
Total economy:
*=Preliminary estimate.
Source: Own calculations, data from Statistics Finland.
4.3 Multi-factor productivity
The natural next step in our venture to account for the growth and productivity in trade and in the rest
of the economy is to look at which proximate factors determine LP growth. In a neoclassical growth
accounting framework labour productivity growth can be decomposed into the contributions of capital
deepening and multi-factor productivity (MFP):
(5)
Yˆ − Hˆ = vK ( Kˆ − Hˆ ) + Aˆ ,
where the ^-symbol indicates the rate of change, Y is real value added, H is hours worked, v is the
nominal income share, K is capital stock and A is MFP. It shows that there are two sources of labour
productivity growth. The first one is capital deepening, i.e. an increase in capital per hour worked
weighted by capital’s income share. Increases in capital deepening are usually sustained by a high
investment ratio that ensures that the stock of fixed capital grows faster than the labour input. Alternatively capital deepening can increase by decreases in the labour input realitive to capital. The second
31
source is a general advance in multi-factor productivity. MFP growth is calculated as the geometric
average of LP and capital productivity (CP) change. The weights used are the arithmetic averages of
capital’s and labour’s respective income shares in period t and t-1. Labour’s share has been constrained to a maximum of 1. The rental price of capital is calculated as the ratio of capital income to
the real capital stock. As a measure of capital we use the gross capital stock (GCS) which is not the
ideal measure but is in keeping with our effort to stay as closely as possible to official national accounts data.10 Aulin-Ahmavaara and Jalava (2003) showed for the total Finnish nonresidential economy that MFP measures calculated using the GCS did not differ much from the other capital
measures. The exception was the early 1990s recession when GCS based MFP measures were lower
than the alternative ones.
From 1975 to 1990 the contributions from capital deepening and MFP – as well as the income shares
of labour and capital – were virtually identical in the trade industry and the whole economy (tables 19
and 20, figures 2 and 3). During the 1990s recession the contribution from MFP vanished in trade thus
shrinking the LP change to a third from before. As can be seen in figure 3 trade’s low MFP growth
stemmed from a massive decrease in CP change. After 1995 MFP growth in trade rebounded to 3.5
p.p.a., thanks to a major step-up in CP growth, which offset the negative contribution from capital
deepening. In the total economy capital deepening’s contribution shrank to zero but MFP change
stayed near its pre-recession track record even after 1995. The overall productivity change is less cyclical in the total economy than in trade and its sub-industries (figures 4, 5 and 6). Primary production
and total manufacturing show above average MFP growth throughout the 1975 to 2003 period. The
low contribution from capital deepening post-1995 stems from lower investment ratios than before.
The investment ratio (current price gross fixed capital formation per current price gross value added)
in trade declined from an arithmetic average of 16.1 per cent in 1975-90 to 10.2 in 1995-2003. In the
same periods the aggregate investment ratio declined from 30.9 per cent to 21.7 per cent.11
10
See Statistics Finland (2004a) for definitions on how Gross and Net Capital Stocks are calculated in Finnish
national accounts.
11
Here the investment ratio for the total economy is gfcf per value added at basic prices. If the more commonly
used value added at market prices (which also takes into account the taxes on production and imports as well as
subsidies) is used the investment ratios are approximately 3 percentage points lower.
32
Table 19 Decomposition of compound annual average labour productivity growth by industry, ln-%
Labour productivity
1975-1990
1990-1995
Capital deepening
1995-2003*
1975-1990
1990-1995
MFP
1995-2003*
1975-1990
1990-1995
1995-2003*
A Agriculture, forestry & hunt.
3.9
4.4
5.9
0.5
0.6
0.9
3.4
3.8
5.1
B Fishing
3.2
9.1
3.3
0.0
0.0
0.0
3.2
9.1
3.3
CDE Total manufacturing
5.0
6.3
4.2
1.6
1.5
-0.1
3.4
4.8
4.2
F Construction
1.6
1.1
-0.2
0.2
0.4
-0.2
1.4
0.7
-0.1
G Trade
3.1
1.1
2.5
0.7
1.2
-0.8
2.4
-0.1
3.5
Sale of motor veh.; serv. stat.
1.3
3.5
2.4
0.5
0.9
-1.0
0.9
2.6
3.4
Wholesale trade
4.1
-2.5
2.1
1.1
1.1
-1.3
3.0
-3.6
3.3
Retail trade
2.6
4.3
2.6
0.6
0.8
-0.2
2.0
3.5
2.9
H Hotels & restaurants
1.6
3.9
-0.6
0.2
0.3
-0.1
1.3
3.6
-0.5
I Transport, storage & comm.
2.7
4.1
3.9
0.7
1.6
0.3
2.0
2.5
3.6
J Financial interm. & insurance
3.9
-0.5
7.1
0.9
2.0
-0.2
3.0
-2.6
7.3
K Real estate & business act.
-0.1
2.0
-0.9
0.1
1.3
-1.6
-0.2
0.8
0.7
L Admin., comp. soc. serv.
1.2
-0.1
0.0
0.3
0.3
0.1
0.9
-0.4
-0.1
M Education
-0.2
-1.1
1.0
0.1
0.1
0.1
-0.3
-1.2
0.9
N Health & social work
0.8
-0.3
-0.4
0.0
0.2
0.0
0.8
-0.5
-0.4
O Other comm., soc. & pers. s.
1.0
0.0
-0.4
0.4
0.9
-0.3
0.6
-0.9
-0.1
3.1
3.0
2.3
0.8
1.2
0.1
2.3
1.9
2.2
P Household service activities
FISIM
GDP at bp
*=Preliminary estimate.
Source: Own calculations, data from Statistics Finland [Table
19]
33
Table 20 Arithmetic average of income shares, investment ratios and profitability in trade and total economy, %
G Trade:
1975-1990
1990-1995
1995-2003*
Labour’s income share
76.0
77.2
67.7
Capital’s income share
24.0
22.8
32.3
Investment ratio
16.1
14.8
10.2
Profitability
16.7
13.5
28.8
Labour’s income share
76.3
74.3
66.5
Capital’s income share
23.7
25.7
33.5
Investment ratio
30.9
23.5
21.7
Profitability
6.5
6.7
10.3
Total economy:
*=Preliminary estimate.
Source: Own calculations, data from Statistics Finland
34
Figure 2 Productivity change in total economy, 1975-2003*, 1975=LN(100)
LP
CP
2001
1999
1997
1995
1993
1991
1989
1987
1985
1983
1981
1979
1977
1975
6,0
5,8
5,6
5,4
5,2
5,0
4,8
4,6
4,4
4,2
4,0
MFP
*=Preliminary estimate.
Source: Own calculations, data from Statistics Finland.
35
Figure 3 Productivity change in trade, 1975-2003*, 1975=LN(100)
1975=LN(100)
Figure 4 Productivity change in sale of mot. veh. etc., 1975-2003*,
LP
CP
MFP
LP
CP
2001
1999
1997
1995
1993
1991
1989
1987
1985
1983
1981
1979
1975
1977
6,0
5,8
5,6
5,4
5,2
5,0
4,8
4,6
4,4
4,2
4,0
2001
1999
1997
1995
1993
1991
1989
1987
1985
1983
1981
1979
1977
1975
6,0
5,8
5,6
5,4
5,2
5,0
4,8
4,6
4,4
4,2
4,0
MFP
*=Preliminary estimate.
Source: Own calculations, data from Statistics Finland.
*=Preliminary estimate.
Source: Own calculations, data from Statistics Finland.
Figure 5 Productivity change in wholesale trade, 1975-2003*, 1975=LN(100)
Figure 6 Productivity change in retail trade, 1975-2003*,
1975=LN(100)
6,0
5,8
5,6
5,4
5,2
5,0
4,8
4,6
4,4
4,2
4,0
LP
CP
MFP
LP
*=Preliminary estimate.
Source: Own calculations, data from Statistics Finland.
CP
*=Preliminary estimate.
Source: Own calculations, data from Statistics Finland.
36
MFP
2001
1999
1997
1995
1993
1991
1989
1987
1985
1983
1981
1979
1977
1975
2001
1999
1997
1995
1993
1991
1989
1987
1985
1983
1981
1979
1977
1975
6,0
5,8
5,6
5,4
5,2
5,0
4,8
4,6
4,4
4,2
4,0
The functional income distribution shifted by close to 10 percentage points in capital’s favour in both
trade and the total economy from 1975-90 to 1995-2003. Sauramo (2004) calculated so called equilibrium labour income shares and concluded that the functional income distribution was not in equilibrium at the turn of the millennium. As an explanation for this he offered the exceptionally high
profitability in Finnish firms in the 1990s. When looking at the non-financial corporations’ financial
status in the national accounts’ institutional sector accounts it is easy to concur with Sauramo’s conclusion. Throughout the 1975 to 1992 period (with the sole exception of the year 1978) non-financial
corporations were forced to borrow funds as their net lending was negative. After 1993 the net lending
of non-financial corporations was positive. One way of calculating profitability in the macroeconomic
framework is to divide the capital income, which equals nominal value added less total labour compensation, with the value of the net capital stock. We found that profitability indeed rose by 3.8 percentage points in the whole economy (from 6.5 per cent in 1975-90 to 10.3 per cent in 1995-2003).
Profitability in trade has also increased by double-digit figures thanks to favorable developments in
wholesale trade (from 16.7 per cent in 1975-90 to 28.8 per cent in 1995-2003).
5. Conclusions
In this paper we took a quantitative look at the growth and productivity of trade and the rest of the
economy in 1975-2003. During our observation period the share of primary and secondary production
in the total economy dwindled from half to a third. Overall economic growth shifted into a faster gear
after 1995 as it was 3.6 p.p.a. compared with the pre-recession 3.1 p.p.a. The trade sector’s value
added joined post-1995 the growth club of total manufacturing, transport & communication and real
estate & business services that all performed better than the national average. Average earnings differentials decreased from 1975 to 1990 but increased again from 1990 to 2003. In trade the average
earnings grew more slowly in the 1995 to 2003 period than the economy’s mean. Increases in hourly
compensation were post-1995 financed by lower unit labour costs than previously. The trade sector’s
ULC growth was – thanks to retailing – less than what it was in the rest of the economy.
Overall LP growth slowed from 3.1 p.p.a. in 1975-90 to 2.3 p.p.a. in 1995-2003. In the latter period
primary production, total manufacturing, trade, transport & communication and the financial sector
were strong performers. Primary production achieved LP growth mainly by strongly cutting back on
the labour input. Among the rest of the rapid growers were found either dynamic ICT-producing subindustries or use of ICT. High LP levels were achieved by fewer industries in 2003 than previously,
and wholesale trade was one of the few. When decomposing LP change into the contributions of capital deepening and multi-factor productivity, we found the post-recession slow aggregate LP growth to
stem from a nonexistent contribution from capital deepening. The trade industry, along with the
strong performers in LP, experienced a significant boost in MFP change that clearly surpassed the
national mean.
So what inferences if any can we draw on Baumol’s disease for Finland? At first sight the evidence
looks inconclusive. When comparing the LP growth in 1975-90 vs. 1995-2003 slightly more service
industries experienced a slowing down of LP growth than a speeding up. For MFP it was vice versa:
more service industries experience a speeding up than a slowing down. Were we to leave the public
sector out of the analysis (as in Statistics Finland, 2004b) the verdict concerning LP growth would
still be the same. However, for MFP growth the picture changes dramatically: all service industries
shift into a faster gear from the 1975-90 period to the 1995-2002 period. Furthermore, the results of
our shiftshare analysis clearly indicate that in the post-1995 era LP growth was much more a within
industry story than before. Based on the shiftshare analysis and the evidence on MFP growth in Finnish service industries our verdict on Baumol’s disease then becomes a definitive not guilty.
Be that as it may, for the trade industries the post-recession period looked good. Trade joined the
growth clubs in value added, LP and MFP. ULC growth was moderate and profits were high. However, vis-à-vis the level of LP only wholesale trade was above the national average whereas the sale of
motor vehicles and retailing slipped further behind the high productivity industries. Times were competitive as strong productivity growth was displayed by fewer industries post-1995 than in earlier
periods.
38
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Appendix
The Leontief inverse matrix is calculated in practice as shown in this fictitious example. The identity
matrix I is:
(A.1)
1 0 
0 1 


Assuming that the input coefficient matrix IC is:
(A.2)
 0.4 0.15
0.07 0.55 ,


then the (I-IC) matrix is:
(A.3)
− 0.15
 0.6
− 0.07 0.45  .


Its inverse L=(I-IC)-1 is:
(A.4)
1.734 0.578
0.270 2.312 .


As we know that the product of a matrix and its inverse is the identity matrix we can validate the results:
(A.5)
L11 = 0.6*1.734 + (-0.15)*0.270=1
(A.6)
L12 = 0.6*0.578 + (-0.15)*2.312=0
(A.7)
L21 = (-0.07)*1.734 + 0.45*0.270=0
(A.8)
L22 = (-0.07)*0.578 + 0.45*2.312=1.
41
Papers issued in the series of the EU KLEMS project
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Jalava, Jukka, Growth and Productivity in the Finnish Trade Industry, 1975-2003: A
National Comparative Perspective
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